MICROENTERPRISES AND MICROFINANCE IN ECUADOR€¦ · MICROENTERPRISES AND MICROFINANCE IN ECUADOR...

MICROENTERPRISES AND MICROFINANCE IN ECUADOR RESULTS OF THE 2004 BASELINE STUDY OF MICROENTERPRISES

MARCH 2005

This publication was produced for review by the United States Agency for International Development. It was prepared by John H. Magill, Development Alternatives Inc., and Richard L. Meyer, Ohio State University, for the USAID/Ecuador SALTO Project and Development Alternatives, Inc.

MICROENTERPRISES AND MICROFINANCE IN ECUADOR RESULTS OF THE 2004 BASELINE STUDY OF MICROENTERPRISES

The authors’ views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government.

TABLE OF CONTENTS I

TABLE OF CONTENTS

EXECUTIVE SUMMARY XVII

I. INTRODUCTION 1 BACKGROUND .....................................................................................................1

PURPOSE AND OBJECTIVES OF THE STUDY.................................................2 PURPOSE ......................................................................................................................................... 2 SPECIFIC OBJECTIVES ................................................................................................................. 2 STAKEHOLDERS............................................................................................................................ 3

A DEFINITION OF “MICROENTERPRISES” .....................................................4

UNDERSTANDING THE RESULTS ....................................................................5 SAMPLE DESIGN AND METHODOLOGY .................................................................................. 5 UNDERSTANDING THE NUMBERS............................................................................................ 6

II. UNDERLYING CHARACTERISTICS OF THE MICROENTERPRISE SECTOR 11

NUMBER AND DISTRIBUTION OF MICROENTERPRISES .........................11 SAMPLING FRAME.......................................................................................................................12 PROJECTING TO THE NATIONAL POPULATION....................................................................12 MICROENTREPRENEURS WITH MORE THAN ONE BUSINESS ...........................................13 GEOGRAPHIC DISTRIBUTION OF MICROENTERPRISES......................................................13

PERSONAL CHARACTERISTICS OF ECUADORIAN MICROENTREPRENEURS .................................................................................15

GENDER .........................................................................................................................................16 AGE .................................................................................................................................................16 EDUCATION ..................................................................................................................................18 CIVIL STATUS ...............................................................................................................................19 FAMILY SIZE .................................................................................................................................20 FAMILY POSITION .......................................................................................................................20

CHARACTERISTICS OF THE MICROENTERPRISES ....................................21 SECTOR ..........................................................................................................................................21 AGE OF BUSINESS........................................................................................................................24 BUSINESS START-UP...................................................................................................................25 ACTIVITIES PRIOR TO STARTING THE BUSINESS ................................................................25 BUSINESS EXPERIENCE..............................................................................................................26 REASONS FOR STARTING THE BUSINESS ..............................................................................26 LOCATION OF BUSINESSES AND SALES ................................................................................27 PRINCIPAL MARKETS FOR MICROENTERPRISE PRODUCTS..............................................29 FULL TIME VERSUS PART TIME ...............................................................................................30 IMPORTANCE OF THE BUSINESS..............................................................................................30 FORMALITY OF BUSINESSES ....................................................................................................31

SUMMARY AND CONCLUSIONS ....................................................................34

III. EMPLOYMENT 37 EMPLOYMENT HISTORY .................................................................................37

IMPACT OF AGE ON EMPLOYMENT HISTORY ......................................................................37

II MICROENTERPRISES AND MICROFINANCE IN ECUADOR

CURRENT EMPLOYMENT PATTERNS...........................................................39 GENDER AND EMPLOYMENT....................................................................................................40 SIZE OF FIRM BY SECTOR..........................................................................................................41 RELATIONSHIP BETWEEN FIRM SIZE, GENDER, AND EMPLOYMENT ............................41

GROWTH IN EMPLOYMENT............................................................................42

MACROECONOMIC IMPLICATIONS OF MICROENTERPRISE EMPLOYMENT....................................................................................................43


IV. SALES AND INCOME 47 SALES ...................................................................................................................47

AVERAGE MONTHLY SALES.....................................................................................................47 GROWTH IN SALES......................................................................................................................48

INCOME................................................................................................................49 PROFITABILITY ............................................................................................................................50 RETURN ON ASSETS....................................................................................................................51

PERCEPTIONS OF INCOME ..............................................................................52 ADEQUACY OF INCOME.............................................................................................................52 COMPARISON OF BUSINESS INCOME WITH SALARIED INCOME .....................................53

MACROECONOMIC CONTRIBUTION OF MICROENTERPRISES ..............53


V. PERCEPTION AND REALITY FOR MICROENTERPRISES IN ECUADOR 55

REASONS FOR STARTING THE BUSINESS ...................................................55

SATISFACTION WITH THE BUSINESS...........................................................56 OVERALL LEVEL OF SATISFACTION ......................................................................................56 ADEQUACY OF INCOME.............................................................................................................57 COMPARISON OF BUSINESS INCOME WITH SALARIED INCOME .....................................57 INDICATOR OF BUSINESS SATISFACTION .............................................................................57

PERCEPTIONS OF THE FUTURE......................................................................58 PERCEIVED FUTURE OF THE BUSINESS .................................................................................59 ATTITUDE TOWARD CONTINUING THE BUSINESS..............................................................59 INDICATOR OF OPTIMISM .........................................................................................................60

SUCCESS AND GROWTH..................................................................................61 ADDING EMPLOYEES..................................................................................................................61 ACQUIRING A BETTER LOCALE ...............................................................................................61 IMPROVING AN EXISTING LOCALE.........................................................................................62 PURCHASE OF NEW EQUIPMENT .............................................................................................62 OVERALL INDICATOR OF SUCCESS ........................................................................................62

CONCLUSIONS AND IMPLICATIONS.............................................................63

VI. MAJOR BUSINESS PROBLEMS AND NEEDS 65 MAJOR PERCEIVED PROBLEMS.....................................................................65

OVERVIEW ....................................................................................................................................65

TABLE OF CONTENTS III

MARKETS AND COMPETITION .................................................................................................66 FINANCIAL PROBLEMS ..............................................................................................................68

DEMAND AND COMPETITION ........................................................................69 PERCEPTIONS ABOUT DEMAND ..............................................................................................69 DIFFICULTIES IN SALES .............................................................................................................69 INTENSITY AND TRENDS IN COMPETITION ..........................................................................70 MAIN COMPETITORS...................................................................................................................70

MICROENTERPRISES AND THE FREE TRADE AGREEMENT ...................71 IMPACT ON INPUTS AND SUPPLIES.........................................................................................71 IMPACT ON SALES.......................................................................................................................71 IMPACT ON EXPORTS .................................................................................................................72

WHAT MICROENTERPRISES NEED TO GROW AND PROSPER ................72 PERCEPTION OF NEED................................................................................................................72


VII. FINANCING THE MICROENTERPRISE 77 GENERAL FINANCING PRACTICES ...............................................................77

SOURCES OF FUNDS FOR FAMILY NEEDS .............................................................................77 SOURCES OF FUNDS FOR IMMEDIATE BUSINESS FINANCE NEEDS ................................78

SOURCES OF FINANCE FOR BUSINESS START-UP ....................................79

FINANCING CURRENT BUSINESS OPERATIONS ........................................81

REASONS FOR BORROWING FROM SPECIFIC SOURCES .........................83

LEVELS OF INVESTMENT................................................................................84

IMPLICATIONS FOR MFIS ................................................................................85

VIII. ACCESS TO AND USE OF FINANCIAL SERVICES 87 KNOWLEDGE OF AND ATTITUDES TOWARD FINANCIAL INSTITUTIONS ....................................................................................................87

SPONTANEOUS RECOGNITION OF MFIs .................................................................................87 RECOGNITION OF SPECIFIC INSTITUTIONS...........................................................................88 GENERAL ATTITUDES TOWARD INSTITUTIONS ..................................................................89

CREDIT .................................................................................................................90 LOAN APPLICATIONS .................................................................................................................90 FACTORS INFLUENCING APPLICATION RATES....................................................................90 SUCCESS RATE IN OBTAINING LOANS...................................................................................92 FACTORS INFLUENCING SUCCESS RATES.............................................................................94 HYPOTHETICAL DEMAND FOR A 20 PERCENT INTEREST RATE LOAN ..........................95 MARKET SEGMENTS AND TYPES OF FINANCIAL INSTITUTIONS ....................................96

RELATIONSHIP BETWEEN CREDIT AND SUCCESS ...................................98

THE UNSERVED MICROENTERPRISE MARKET..........................................99 REASONS FOR NOT APPLYING FOR LOANS ..........................................................................99 MAJOR PROBLEMS WITH INSTITUTIONAL CREDIT...........................................................100 COLLATERAL..............................................................................................................................103

ESTIMATING THE POTENTIAL DEMAND FOR MICROENTERPRISE CREDIT ...............................................................................................................103

IV MICROENTERPRISES AND MICROFINANCE IN ECUADOR

THE SUPPLY OF MICROCREDIT ...................................................................105 A DEFINITION OF MICROCREDIT ...........................................................................................105 POINTS OF SERVICE ..................................................................................................................106 NUMBER OF MICROCREDIT CLIENTS ...................................................................................107 MICROCREDIT PORTFOLIO......................................................................................................108 PRODUCTS AND SERVICES......................................................................................................109

SAVINGS ............................................................................................................110 HOW MANY HAVE SAVINGS? .................................................................................................110 WHO SAVES AND WHO DOESN’T? .........................................................................................110 WHY DON’T MICROENTREPRENEURS SAVE?.....................................................................111 WHERE DO THEY HAVE SAVINGS? .......................................................................................112 PREFERRED INSTITUTIONS .....................................................................................................112 WHY DO THEY SAVE WHERE THEY DO?..............................................................................113 FEATURES CONSIDERED IMPORTANT IN CHOOSING A SAVINGS INSTITUTION .......114 INFORMAL SAVINGS.................................................................................................................115

USE OF OTHER SERVICES..............................................................................115

SUMMARY AND CONCLUSIONS ..................................................................117

IX. NONFINANCIAL SERVICES AND SUPPORT 121 MEMBERSHIP IN ASSOCIATIONS ................................................................121

TRAINING AND TECHNICAL ASSISTANCE................................................122

INTEREST IN TRAINING AND TECHNICAL ASSISTANCE.......................123 AREAS IN WHICH MICROENTREPRENEURS WOULD WELCOME ASSISTANCE...........124 WOULD MICROENTREPRENEURS BE WILLING TO PAY FOR TRAINING AND ASSISTANCE?..............................................................................................................................124

POTENTIAL MARKET FOR TRAINING AND TECHNICAL ASSISTANCE .....................................................................................................125

SUMMARY AND CONCLUSIONS ..................................................................126

X. CONCLUSIONS: OPPORTUNITIES FOR EXPANDING MICROFINANCE SERVICES IN ECUADOR 127

THE MAJOR CONCLUSIONS ..........................................................................127 ROLE OF MICROENTERPRISES................................................................................................127 PARTICIPATION IN MICROFINANCE .....................................................................................127

OTHER KEY FINDINGS ...................................................................................128 LACK OF AWARENESS OF MICROFINANCE INSTITUTIONS.............................................128 MICROENTERPRISES ARE NOT GROWING BUSINESSES...................................................128 MICROENTREPRENEURS ARE SATISFIED AND OPTIMISTIC ...........................................129 MANY FACTORS INFLUENCE BORROWING AND SAVINGS PATTERNS........................129

IMPLICATIONS FOR MICROFINANCE INSTITUTIONS.............................129 GROWTH STRATEGIES .............................................................................................................130 MATCHING LOANS TO CLIENT CAPACITY ..........................................................................131 PRODUCT MIX AND INTEREST RATES..................................................................................131

IMPLICATIONS FOR DONORS .......................................................................131 POVERTY IMPLICATIONS ........................................................................................................131 REACHING WOMEN...................................................................................................................132 EXTENDING FINANCIAL SERVICE TO RURAL AREAS ......................................................132 STIMULATING ECONOMIC GROWTH ....................................................................................132

TABLE OF CONTENTS V

OTHER OPPORTUNITIES...........................................................................................................133 FOLLOW-ON RESEARCH SUGGESTIONS....................................................133

BIBLIOGRAPHY 137

ANNEX A: HOUSEHOLD SURVEY 139

ANNEX B: MICROENTREPRENEUR SURVEY 143

ANNEX C: FINANCIAL INSTITUTION CODES 161

LIST OF TABLES AND FIGURES VII

LIST OF TABLES AND FIGURES Table

II-1 Geographic Distribution of Microenterprises ...................................................................... 14

II-2 Geographic Distribution of Microenterprises, by Size of City ............................................ 15

II-3 Employment Status of Economically Active Men and Women........................................... 16

II-4 Age of Population Surveyed and Microentrepreneurs in the Sample .................................. 17

II-5 Age Distribution of Microentrepreneurs, by Gender, Region, and Economic Sector.......... 18

II-6 Levels of Education of Microentrepreneurs, by Gender ...................................................... 19

II-7 Languages Spoken by EcuadorIan Microentrepreneurs, by Gender .................................... 19

II-8 Civil Status of EcuadorIan Microentrepreneurs, by Gender ................................................ 20

II-9 Family Position of Microentrepreneurs, by Gender............................................................. 20

II-10 Distribution of Enterprises by Economic Sector, by Gender and Region............................ 21

II-11 Subsector Breakdown of Major Enterprise Activities, by Gender and Region.................... 22

II-12 Principal Microenterprise Activities in the Services Sector, by Gender and Region........... 22

II-13 Principal Microenterprise Activities in the Production Sector, by Gender and Region....... 23

II-14 Principal Microenterprise Activities in the Commerce Sector, by Gender and Region....... 24

II-15 Distribution of Businesses by Age, by Gender, Region, and Economic Sector................... 25

II-16 Activities Prior to Starting the Business, by Gender, Region, and Economic Sector .......... 26

II-17 Principal Reasons for Starting the Business, by Gender, Region, and Economic Sector .... 27

II-18 Business Location, by Gender, Region, and Economic Sector ............................................ 28

II-19 Location of Sales, by Gender, Region, and Economic Sector ............................................. 28

II-20 Principal Clients ................................................................................................................... 29

II-21 Principal Client, by Gender, Region, and Economic Sector ................................................ 29

II-22 Importance of the Microenterprise, by Gender, Region, and Economic Sector................... 30

II-23 Proportion of Family Income Derived from the Business, by Gender, Region, and Economic Sector .................................................................................................................. 31

II-24 Percentage of Businesses Registered with the Tax Authorities, by Gender, Region, and Economic Sector .................................................................................................................. 31

II-25 Major Reasons for Not Registering with Tax Authorities ................................................... 32

II-26 Positive Benefits from Registering with Tax Authorities .................................................... 32

II-27 Percentage of Microenterprises Having Municipal Licenses or Permits, by Gender, Region, and Economic Sector............................................................................................................ 33

VIII MICROENTERPRISES AND MICROFINANCE IN ECUADOR

II-28 Percentage Maintaining Business Accounting Records, by Gender, Region, and Economic Sector ................................................................................................................................... 33

III-1 Historical Experience with Employees, by Gender, Region, and Economic Sector............ 37

III-2 Business Age and Employment Experience......................................................................... 38

III-3 Entrepreneur Age and Employment Experience.................................................................. 38

III-4 Number of Employees, by Gender, Region, and Economic Sector ..................................... 39

III-5 Average Number of Employees per Firm, by Gender, Region, and Economic Sector ........ 40

III-6 Average Employment per Firm, by Gender ......................................................................... 40

III-7 Average Employment per Firm, by Subsector ..................................................................... 41

III-8 Gender, Size of Firm, and Employment Patterns................................................................. 42

III-9 Patterns of Change in Employment, by Gender, Region, and Economic Sector ................. 42

III-10 Change in Number of Employees, by Subsector.................................................................. 43

III-11 Total Employment Generated by Microenterprises in Ecuador........................................... 44

IV-1 Average Monthly Sales, by Gender, Region, and Economic Sector.................................... 48

IV-2 Average Monthly Sales, by Subsector ................................................................................. 48

IV-3 Trends in Sales, by Gender, Region and Economic Sector.................................................. 49

IV-4 Average Net Monthly Income from Business, by Gender, Region, and Economic Sector .50

IV-5 Average Net Monthly Income, by Subsector ....................................................................... 50

IV-6 Average Profitability Rates, by Gender, Region, and Economic Sector.............................. 51

IV-7 Average Profitability Rates, by Subsector ........................................................................... 51

IV-8 Perception of Income, by Gender, Region, and Economic Sector ....................................... 52

IV-9 Comparison of Business Income with Wage-Earning Jobs, by Gender, Region, and Economic Sector .................................................................................................................. 53

V-1 Reasons for Starting the Business, by Gender, Region, and Economic Sector.................... 56

V-2 Level of Satisfaction with Business, by Gender, Region, and Economic Sector................. 57

V-3 Numeric Values for Constructing Satisfaction Indicator ..................................................... 58

V-4 Degree of Satisfaction with the Microenterprise, by Gender, Region, and Economic Sector ................................................................................................................................... 58

V-5 Perceived Future of the Business, by Gender, Region, and Economic Sector..................... 59

V-6 Job Preferences, by Gender, Region, and Economic Sector ................................................ 60

LIST OF TABLES AND FIGURES IX

V-7 Numeric Values for Constructing Optimism Indicator ........................................................ 60

V-8 Level of Optimism, by Gender, Region, and Economic Sector ........................................... 61

V-9 Businesses that Have Moved to an Improved Location, by Gender, Region, and Economic Sector .................................................................................................................. 61

V-10 Businesses that Have Improved Their Existing Location, by Gender, Region, and Economic Sector .................................................................................................................. 62

V-11 Businesses that Have Purchased New Equipment or Machinery, by Gender, Region, and Economic Sector .................................................................................................................. 62

V-12 Numeric Values for Constructing Growth Indicator............................................................ 63

V-13 Distribution of Microentrepreneurs by Growth Indicator, by Gender, Region, and Economic Sector .................................................................................................................. 63

VI-1 Two Most Important Problems Faced by Microentrepreneurs ............................................ 65

VI-2 Most Important Problem Faced, by Gender, Region, and Economic Sector ....................... 66

VI-3 Major Markets and Competition Problems, by Gender, Region, and Economic Sector...... 67

VI-4 Major Financing Problems Faced, by Gender, Region, and Economic Sector .................... 68

VI-5 Perception of Demand for Products, by Gender, Region, and Economic Sector ................. 69

VI-6 Whether or Not the Microentrepreneur Has Difficulty Selling, by Gender, Region, and Economic Sector .................................................................................................................. 69

VI-7 Perception of Competition, by Gender, Region, and Economic Sector ............................... 70

VI-8 Perception of Trends in Competition, by Gender, Region, and Economic Sector............... 70

VI-9 Principal Competitors........................................................................................................... 71

VI-10 What is Most Needed to Grow and Prosper......................................................................... 73

VI-11 Most Important Business Need, by Gender, Region, and Economic Sector........................ 74

VII-1 Main Sources of Personal Finance, by Gender, Region, and Economic Sector................... 77

VII-2 Main Sources of Finance for Urgent Business Needs, by Gender, Region, and Economic Sector .................................................................................................................. 79

VII-3 Financing Sources for Starting the Business........................................................................ 80

VII-4: Major Sources of Start-Up Financing, by Gender, Region, and Economic Sector .............. 81

VII-5 Major Sources for Financing Daily Business Operations .................................................... 82

VII-6 Major Sources for Financing Daily Business Operations, by Gender, Region, and Economic Sector .................................................................................................................. 83

VII-7 Reasons for Selecting Financing Source.............................................................................. 84

X MICROENTERPRISES AND MICROFINANCE IN ECUADOR

VII-8 Average Investment in Business, by Gender, Region, and Economic Sector...................... 84

VIII-1 Spontaneous Recognition of Institutions, by Gender, Region, and Economic Sector ......... 88

VIII-2 Institutions Mentioned ......................................................................................................... 89

VIII-3 General Opinion of Major Institutions ................................................................................. 89

VIII-4 Member and NonMember Attitudes toward Member-Based Institutions............................ 90

VIII-5 Distance to Lender ............................................................................................................... 91

VIII-6 Loan Application Rates, by gender, region, and economic sector ....................................... 91

VIII-7 Application Rates, by Economic Status and Gender............................................................ 92

VIII-8 Success Rates, by Economic Status and Gender.................................................................. 93

VIII-9 Percentages of loan Amounts Requested that were Received, by Type of Institution......... 94

VIII-10 Reasons for Not Obtaining Credit Requested, by Type of Institution ................................. 95

VIII-11 Interest in Loan if Interest Rate Were 20 Percent per Annum, by Gender, Region, and Economic Sector .................................................................................................................. 95

VIII-12 Reasons for Not Wanting Loan............................................................................................ 96

VIII-13 Market Segments Served by Major Microfinance Lenders.................................................. 97

VIII-14 Correlation Between Credit and Overall Satisfaction with the Business ............................. 98

VIII-15 Correlation Between Enterprise Growth and Credit ............................................................ 99

VIII-16 Reasons for Not Applying for a Loan During the Past 12 Months .................................... 100

VIII-17 Major Problems Associated with Credit from Formal Sector Microfinance Institutions .. 101

VIII-18 Assets Available to Guarantee a Loan, by Gender, Region, and Economic Sector ........... 103

VIII-19 Respondents Who Have Savings, by Gender, Region, and Economic Sector ................... 111

VIII-20 Reasons for Not Saving in Financial Institutions............................................................... 112

VIII-21 Preferred Savings Institution, by Gender and Region........................................................ 113

VIII-22 Main Reasons for Selecting a Particular Savings Institution ............................................. 114

VIII-23 Features that Attract Savers ............................................................................................... 115

VIII-24 Informal Savings Patterns .................................................................................................. 115

VIII-25 Other Services Used, by Gender, Region, and Economic Sector....................................... 116

VIII-26 Receipt and use of Remittances, by Gender, Region, and Economic Sector ..................... 117

IX-1 Membership in Chambers or Associations, by Gender, Region, and Economic Sector .... 121

IX-2 Training and Technical Assistance Received, by Gender, Region, and Economic Sector 122

LIST OF TABLES AND FIGURES XI

IX-3 Business Training and Technical Assistance Received, by Gender and Economic SubSector ........................................................................................................................... 123

IX-4 Interest in Receiving Training or Technical Assistance, by Gender, Region, and Economic Sector ................................................................................................................ 123

IX-5 Subject Areas Desired for Training and Technical Assistance .......................................... 124

IX-6 Percentage of Microentrepreneurs Willing to Pay for Training or Technical Assistance, by Gender, Region, and Economic Sector ......................................................................... 125

IX-7 Potential Market for Training and Technical Assistance, by Subject Area ....................... 125

Figure

I-1 Parroquias in which interviews were conducted .................................................................... 7

I-2 Cantones represented by interviews....................................................................................... 7

I-3 Relationship of sample to sample universe and population of Microentrepreneurs ............ 10

II-1 Distribution of Microenterprises, by Canton........................................................................ 15

VIII-1 Estimated demand for microcredit, by canton ................................................................... 106

VIII-2 Distribution of MFIs, by Canton........................................................................................ 107

VIII-3 Estimated coverage (penetration) rates, by canton............................................................. 108

VIII-4 Estimated saturation rates, by canton................................................................................. 109

ACRONYMS XIII

ACRONYMS BDS business development services

DAI Development Alternatives, Inc.

GDP gross domestic product

ICV Indicador de Condiciones de Vida (basic needs indicator)

IDB Inter-American Development Bank

INEC Instituto Nacional de Estadística y Censos (National Statistical and Census Institute)

MFI microfinance institution

NGO nongovernmental organization

SALTO Strengthening Access to Microfinance and Economic Liberalization (USAID/Ecuador project to support microfinance)

PREFACE XV

PREFACE This study of microenterprises in Ecuador (Estudio Nacional de Microempresas en Ecuador—ENAME) was financed by U.S. Agency for International Development (USAID)/Ecuador under the Strengthening Access to Microfinance and Economic Liberalization (SALTO) project to provide microfinance institutions, Ecuadorian government agencies and ministries, and donor organizations with information about the scope and characteristics of the microenterprise sector and its access to financial services.

The study embodies three basic approaches: a background analysis of existing data sources (primarily the 2001 Census of Population and Housing, and various household surveys conducted by the National Statistical and Census Institute, INEC), a series of focus groups with microentrepreneurs in Quito and Guayaquil, and a nationwide survey of microenterprises. This report includes information from all three sources, although the primary emphasis is on information obtained through the nationwide survey.

The study was conducted during a 15-month period from late October 2003 through January 2005 as follows:

October to November 2003 Background data analysis

December 2003 to January 2004 Focus group sessions

March 2004 to August 2004 Nationwide survey and database preparation

September 2004 to January 2005 Analysis, presentations, and report preparation

Results of the study have been presented at regular quarterly meetings of the SALTO microenterprise participant organizations, at the VII Foro de la Microempresa sponsored by the Inter-American Development Bank in Cartagena, Colombia, and at the III and IV Foros de la Microempresa sponsored by the Red Financiera Rural in Quito, Ecuador.

The greatest value of the study, however, lies in the continued use of the data by those who are planning and offering support to microenterprise development in Ecuador. The SALTO project staff hope that the data and results of this study will be widely used by researchers, donors, Ecuadorian government officials, practitioners, and others interested in microfinance and microenterprise development. Accordingly, study results—including databases, presentations, reports, and other information—can be accessed without charge via the SALTO website at:

www.salto-ecuador.com

The authors wish to acknowledge and thank those who have supported and provided input and comments on various stages of the study design, methodology, questionnaire, implementation, and analysis. In particular, we thank Rick Garland, Steve Smith, and Bernai Velarde of USAID/Ecuador for sponsoring the study and providing continued support and useful suggestions and comments throughout. We thank Alexander Shapleigh, Fernando Fernandez, Marina Mutchler, Carlos Palán, and Mercy Ochoa of the SALTO project for their constant support and guidance throughout the study. David J. Megill produced the sample design that guided the survey effort. Rodrigo Espinosa of the Superintendency of Banks and Insurance provided support and access to government officials and statistical information that was used to validate responses to the survey. We appreciated the thorough and professional collaboration of Carolina Reed, Francisco Carrion, Fernando Carrasco, and Eduardo Encalada of Habitus Investigaciones S.A., throughout the survey process. Alexandra Fiorillo assisted in assembling information on microfinance products. Ioana Bouvier of DAI produced our maps. We

XVI MICROENTERPRISES AND MICROFINANCE IN ECUADOR

also thank the microfinance institutions participating in the SALTO project for their continued review and comments on the findings and conclusions. And finally, we thank the microentrepreneurs who so willingly and patiently responded to the lengthy questionnaire—we hope the results of the study will lead to an expansion and improvement in services supporting their growth and prosperity.

As always, the conclusions presented here are those of the authors and do not necessarily reflect the opinions or positions of any of the institutions and individuals who have provided information or comments during the course of the study.

EXECUTIVE SUMMARY XVII

EXECUTIVE SUMMARY The Ecuador National Microenterprise Study was conducted between October 2003 and August 2004 and was sponsored by U.S. Agency for International Development (USAID)/Ecuador through the Strengthening Access to Microfinance and Economic Liberalization (SALTO) project, one of the cornerstones of USAID/Ecuador’s poverty reduction activities. The primary objectives of the study were to: 1) generate an understanding of the extent to which microentrepreneurs have access to and use financial services; 2) identify the constraints microentrepreneurs face in accessing formal sector financial services; and 3) provide a framework through which donors and microfinance institutions (MFIs) could plan more effective programs and expand outreach. The study consisted of a background analysis of existing studies and data, focus group sessions to explore tentative hypotheses about microenterprises, and a nationwide survey of 17,738 microentrepreneurs.

An executive summary cannot begin to cover the richness of information gathered during the course of study. As a result, this brief section covers only a few of the most significant findings and results. More detail is available in each of the chapters and in the materials posted to the SALTO project website.

DEFINITION OF A MICROENTERPRISE

There are many possible definitions of a microenterprise. For this study a very conservative definition—which restricts the microenterprise to lower-income strata and requires that it provide significant income to the family—was chosen:

A “microenterprise” is a personal or family business in commerce, production, or services that employs less than 10 persons, is owned and operated by an individual, family, or group of individuals of relatively low income, whose owner exercises independent judgment on products, markets, and prices, and that is an important (if not the most important) source of income for the household.

IMPORTANCE OF MICROENTERPRISES IN ECUADOR

Microenterprises provide jobs for a large percentage of the middle- to low-income urban workforce in Ecuador. More than one-third (33.5 percent) of households in middle- to low-income urban areas had one or more adult family members with a microenterprise. Projections to the overall population of microentrepreneurs indicate a total of 646,084 microentrepreneurs in Ecuador in urban areas (defined in this case as towns of 2,000 and greater)1 of Ecuador. These microentrepreneurs operate a total of 684,850 separate enterprises.

Ecuadorian microenterprises provided jobs for an estimated 1,018,135 persons, or nearly 25 percent of the urban workforce. Furthermore, the sales of these microenterprises represent approximately 25.7 percent of gross domestic product, and about 10 percent of the total net income earned in the country. Microenterprises, therefore, represent a significant component of the urban economy.

1 The sampling frame consisted of towns with a population of 5,000 and greater. The estimate of 646,084 as

the population of urban microentrepreneurs in Ecuador includes an extrapolation to towns of 2,000 to 5,000 inhabitants as well.

XVIII MICROENTERPRISES AND MICROFINANCE IN ECUADOR

INFORMALITY

Most microenterprises operate in the informal sector. About one-fourth of the enterprises had tax ID numbers and an equal number had municipal licenses. Less than 15 percent were enrolled in social security. Only 20 percent of the respondents kept formal financial records.

GENDER IMPACT OF MICROENTERPRISES

Perhaps the most noticeable characteristic of microentrepreneurs is the high percentage of women who depend on a microenterprise. Women comprise only 30.7 percent of the economically active population,2 but constitute 46.7 percent of the microentrepreneurs found in the survey. Of women who were economically active, 56.4 percent were microentrepreneurs. A substantial portion of women microentrepreneurs are single heads of household—single, separated, widowed, or divorced—demonstrating that microenterprises constitute a significant social safety net for this sector of the population.

When they hire employees, men tend to hire men and women tend to hire women. This is largely due to the nature of the businesses and the skills required. Male-owned businesses tend to require skills that men are most familiar with and that women have little opportunity to acquire. Women-owned businesses, apart from straight commerce and small restaurants, tend to specialize in products and services that cater to women, resulting in a greater demand for female employees.

MAJOR OCCUPATIONS

Microenterprises are heavily concentrated in the commerce sector; 55.2 percent of all microenterprises are in commerce, compared with 25.7 percent in services and 19.2 percent in production. Furthermore, within each economic sector there is a heavy concentration of enterprises in specific subsectors. Within the commerce sector, for example, 60.2 percent of the businesses are concentrated in foods, beverages, and clothing. In the services sector, 64.9 percent of all microenterprises are concentrated in four subsectors: small food and beverage subsector (bars, restaurants, and cafeterias), taxis, automotive repair shops, and beauty parlors. And 56.2 percent of microenterprises in the production sector are found in clothing, wood furniture and objects, and nonalcoholic beverages.

Women microentrepreneurs exhibit even greater clustering in specific types of businesses. In the service sector, 85.0 percent of women are in small foods and beverages and in beauty parlors. In the production sector, 74.7 percent of women entrepreneurs are found in clothing and nonalcoholic beverages. In the commerce sector, 67.9 percent of women entrepreneurs are engaged in the sale of foods, beverages, clothing, and miscellaneous small articles.

EMPLOYMENT IMPACT

Microenterprises are also an important source of employment. For the vast majority of microentrepreneurs, the microenterprise is a source of self-employment. Nearly 70 percent of Ecuadorian microenterprises employ no workers or assistants in addition to the microentrepreneur. Furthermore, microenterprises tend not to grow: in the vast majority of microenterprises, employment is generated as the enterprise is formed, and grows little after that. Only 10 percent of the microenterprises had increased employment during the life of the business.

2 INEC 2001.

EXECUTIVE SUMMARY XIX

Male-owned businesses tend to generate more employment than those owned by women. This is largely because woman-owned businesses are more likely to operate in the home, and bringing outside workers into the home is problematic. Moreover, male-owned businesses also tend to be larger, with more investment, capacity, and sales.

SALES AND INCOME

Most microentrepreneurs depend on the income they earn from their businesses. The vast majority (86.9 percent) operate their businesses as a full-time activity, and 94.3 percent say the enterprise is their sole source of income. For 67.7 percent of the families, the microenterprise constitutes the principal source of family income.

The average microenterprise had monthly sales of $778, which yielded an average net monthly family income of $308, or a net annual family income of $3,696. Woman-owned businesses have much lower sales and generate significantly less income than businesses owned by men. Businesses in the commerce sector generally have higher sales and generate more income than businesses in either services or production.

Sales and income form the basis for growing the business and for determining the amount of credit a client can reasonably absorb and service. MFIs targeting microentrepreneurs need to carefully consider the loan and payment limitations these two conditions indicate. Based on sales and income, for example, female microentrepreneurs have a lower borrowing capacity and a more limited ability to service loans than their male counterparts. Similarly, businesses on the coast do not appear to qualify for loans as large as those made to enterprises in the other two regions. The differences among businesses in the various subsectors in terms of their ability to generate income are also significant and consistent. Microfinance institutions need to take these differences into account in planning loan strategies and market expansion.

SATISFACTION AND OPTIMISM

Ecuadorian microentrepreneurs are generally satisfied with their businesses and are committed to continuing their microenterprises. There is little indication that they were forced to become microentrepreneurs because of a lack of other opportunities; the overwhelming majority of microentrepreneurs chose to start their own businesses because of a desire for greater independence or because they perceived an opportunity to earn more. There is also little indication they would abandon their enterprises to seek salaried employment. Furthermore, most entrepreneurs would like to see their businesses grow rather than change employment or remain as they are. As a result, microenterprises appear to represent a stable segment of the economy rather than a temporary or transitional one.

In general, microentrepreneurs are satisfied with the income they derive from their businesses. The overwhelming majority feel their income is at least “average”; more than half say it is good or very good. In addition, nearly 70 percent say their income is better than what they could receive in a wage-paying job.

This combination of commitment to working independently and desire to grow the business is important for MFIs contemplating loans to microentrepreneurs. Borrowers who have strongly positive feelings about their business, are optimistic about the future, and are committed to seeing the business grow are probably better credit risks than those who formed the business because of a lack of opportunities, are pessimistic about the future, and would prefer to have salaried employment. The large number of entrepreneurs who say they would like to see their businesses grow suggests that MFIs have a potentially large market in financing growing business activities.

XX MICROENTERPRISES AND MICROFINANCE IN ECUADOR

GROWTH AND SUCCESS

Even though the respondents expressed high levels of satisfaction and optimism, very few microenterprises demonstrated the kind of improvements or growth normally associated with a successful or growing business. Relatively few microentrepreneurs felt that sales were increasing; nearly 40 percent said that sales in 2004 were somewhat or much less than the previous year, compared with only 15 percent who said that sales had increased in 2004. Very few have added employees. And even fewer have made measurable improvements to their businesses. All of these factors suggest that most microentrepreneurs are operating in very limited and highly competitive niche markets, so their potential for growth in sales and income is limited.

This apparent contradiction needs to be carefully considered by MFIs seeking to expand their microfinance portfolios because the absence of growth indicators could signify a stagnant sector with little prospect for growth in the absence of other fundamental changes in the microenterprises and their markets.

MAJOR PROBLEMS AND NEEDS

The main problems mentioned by Ecuadorian microentrepreneurs suggest that many, if not most, operate in a highly competitive environment with relatively little growth potential. Most microentrepreneurs face an environment with numerous vendors and relatively slow growth in demand, and see those as the primary impediments to the success of their business. Financial problems—generally due to a lack of cash flow rather than access to credit—rank much lower in importance.

Given these conditions, donors need to be careful about focusing on credit as a solution to the problems facing microentrepreneurs. Credit can help producers (and vendors) produce and sell more. Credit can also help a producer manufacture something less expensively and a vendor to lower costs of goods sold by purchasing in larger quantities. However, increasing production and having a larger volume of goods to sell will not necessarily lead to higher sales, greater profit, or greater income in a saturated market. In highly competitive situations, improving product design, producing or selling in different market segments, and better marketing are often more appropriate measures for improving income than producing more or having more goods to sell. Credit alone, therefore, may not result in improving livelihoods for lower-income people.

The different needs and concerns of microenterprises in the different economic sectors also have implications for microfinance institutions. To the extent that the key needs are short-term in nature—primarily inventory and raw materials—MFI product offerings that focus on short-term, rapid turnover activities are relatively well-suited to the clients. This is particularly true with commerce sector businesses. Both service and production sector entrepreneurs expressed a need for improving their business premises, equipment, and facilities, which implies a need for larger, longer-term financing. Microfinance institutions need to be to respond to both of these needs.

SOURCES OF FUNDING

Microentrepreneurs rely almost exclusively on personal savings and assets and income generated from the businesses to finance both start-ups and ongoing operations. When they perceive a need for outside financing, they turn almost exclusively to informal sources—family, friends, and moneylenders. Institutions—such as banks, financieras, cooperatives, or nongovernmental organizations—are not viewed as reliable or positive sources of funding.

EXECUTIVE SUMMARY XXI

The problem is that relying only on internally generated funds limits a firm’s ability to grow. Ecuadorian microenterprises, in general, do not generate large cash flows, and profitability, especially in absolute terms, is relatively low. This shortage of cash leads to financial problems. Expanding the business often requires more capital than they can generate internally, yet the low levels of income and profitability limit their ability to service high-cost loans.

MFIs seeking to expand their market and attract additional clients from the microenterprise sector need to adapt their marketing strategies to this reality. Instead of maximizing loan volumes, they need to be careful to tailor loans to the capacity of the microentrepreneurs. Instead of promoting credit as a panacea for business problems, they need to better understand the conditions and dynamics of the individual firms they are working with in order to tailor loan products and amounts to yield a positive benefit for the client. And they need to develop the understanding among microentrepreneurs of how credit, properly used, can be an effective and profitable business tool. Microentrepreneurs, for their part, must understand the benefit of using external funds in practical terms, as well as the risk of borrowing.

ACCESS TO FINANCIAL SERVICES

In spite of the large expansion of the Ecuadorian microfinance industry in recent years, it has had little impact on most microenterprises. Only 29 percent reported holding savings in financial institutions. Credit from formal financial institutions is not part of the business strategy of most microentrepreneurs, and large numbers of respondents expressed a concern about becoming indebted. They also tend not to use many other formal financial services.

Only 15.7 percent of those interviewed reported that they applied for loans in the past 12 months. When they applied, it tended to be for only one loan and with only one financial institution. Except, perhaps, in a few local markets, it appears that excessive competition and borrowing from multiple institutions leading to overindebtedness, as occurred in Bolivia, is not a problem in Ecuador. Microentrepreneurs in Ecuador also tend to make little use of other, more modern, financial services. Only 6.1 percent have checking accounts, 7.7 percent use ATMs, and 3.9 percent use credit cards.

Why are so few microentrepreneurs using formal financial services? First, many are not aware that microenterprises can receive services. Only 34.7 percent could spontaneously identify an institution that lends to microentrepreneurs. Even the major microfinance institutions were recognized by only a small percentage of respondents.

Perhaps even more important, most microentrepreneurs do not view a relationship with a financial institution as a positive business strategy. They strive to avoid indebtedness and do not view debt as a positive tool in their business strategy. Credit is not seen as a positive tool to grow a business, but rather as a cost or penalty to be avoided at almost any cost. This is a very conservative approach to business. However, it is precisely this conservative position that protects the microentrepreneurs in an uncertain economic environment, and that prevents them from becoming overindebted.

Among the components of this resistance are the following:

1. The amount of credit many institutions offer is not worth the effort the clients have to put into obtaining the credit and the risks they have to take—forms, guarantees, cosigners, references, and multiple visits all imply a cost to the borrower, and if that cost is greater than the perceived benefit of the credit, the microentrepreneur will not take the risk of borrowing;

2. Most microentrepreneurs are not convinced that credit (becoming indebted) represents an opportunity to grow; and

XXII MICROENTERPRISES AND MICROFINANCE IN ECUADOR

3. Microentrepreneurs fear the consequences of not being able to pay back the loan or to meet repayment schedules.

As a result of these factors, many microentrepreneurs only borrow when they really need it—when circumstances force them to take on a debt obligation.

Focus group participants were even more critical in their views of using the services of financial institutions. They complained of high interest rates for loans and the high associated costs of technical assistance, supervision, insurance, and other fees; deception in the way interest rates were quoted and imposed; heavy-handed pressure for timely payments and high penalty fees for late payments; and exaggerated requirements for small loans. If these views were widespread, they could have a depressing effect on demand for loans. However, such complaints may be more common among better-informed microentrepreneurs in larger cities than among all enterprises.

Location of the point of service and distance to the microenterprise undoubtedly play an important role in motivating microentrepreneurs to use financial services. Two-thirds of the loan applicants had businesses or homes within two kilometers of the financial institution. Convenience was an important reason given for choice of institution with which to save. Long distances drive up transaction costs for small loans and savings accounts and may cause potential clients to believe it is not worth the bother of dealing with financial institutions. Increasing points of service and increasing loan officer contact with clients and potential clients (that is, actively seeking clients in their homes and places of work) may be required to reach independent microentrepreneurs scattered across cities, towns, and neighborhoods. Moreover, this may be the easiest method of attracting more clients, especially in those geographic areas sparsely served by competitors. This factor is especially crucial for poor borrowers who borrow small amounts. Wealthier borrowers who borrow larger sums can afford to travel farther to obtain financial services.

The quality of service was also revealed as important in the survey—at least in the short run. Although microentrepreneurs felt that interest rates on savings were too low, and those on loans too high, these were not the most important factors they considered in making savings and borrowing decisions. Decisions to save were prompted more by a sense of stability, safety, and security than by interest rates. Complaints against credit institutions focused more on convenience, procedures, guarantees, courteous treatment, and time required to obtain a loan than on the interest rate that was charged. In the short run, institutions would be well advised to focus on improving these aspects of their business. As competition increases, and as interest rates and commissions become more transparent, attractive interest rates—on both savings and loans—may become a more important factor in competitive positioning.

SATURATION AND OVERINDEBTEDNESS

Data reported by the Superintendency of Banks and Insurance (Superintendencia de Bancos y Seguros) suggest a much higher level of microcredit than projected from the survey responses, in terms of both numbers of borrowers and loan volume. These data showed some 241,000 active loans, representing 37.6 percent of projected microentrepreneurs, in contrast to the 101,000 borrowers projected from the survey. Outstanding loan balances of $257 million represented close to 39 percent of projected demand.

These numbers could indicate that the microcredit market is approaching saturation. However, it is likely that a substantial portion of the loans reported through the Superintendency of Banks and Insurance are to “microentrepreneurs” that were excluded by definition from the domain of this study, and to individuals of higher socioeconomic status. This hypothesis is supported by the fact that borrowing patterns measured in the survey were directly related to socioeconomic status and by the

EXECUTIVE SUMMARY XXIII

fact that formal sector MFIs in Ecuador do not exclude those of a higher socioeconomic status from their microenterprise portfolios. However, this apparent contradiction in findings between the survey results and data from the Superintendency of Banks and Insurance suggests that this subject needs further study and analysis.

There is little indication that overindebtedness is a significant problem. Very few microentrepreneurs reported having applied to more than one institution and even fewer reported receiving loans from more than one institution.

IMPLICATIONS FOR MICROFINANCE INSTITUTIONS

What are the implications of these findings for the microfinance industry, and what does it need to do to tap this large market of microentrepreneurs, most of whom do not currently use its products and services? Perhaps the most important challenge to MFIs in Ecuador is to overcome the microentrepreneur’s resistance to using credit. Overcoming this resistance will require active marketing, because the microentrepreneurs will not likely be reached by mass marketing techniques or general publicity.

A second major issue—or opportunity—is to decrease the transaction costs for microentrepreneurs. Additional points of service in key locations, streamlined paper work, and convenient transaction systems for making payments or adjusting balances could prove attractive to potential clients.

Microfinance institutions also need to recognize that their current product mix may not fit client needs. There was little evidence of demand-driven product design, that is, institutions designing or modifying products based on surveys of clients and potential clients or consideration of the business cycle of different segments of the potential client market. Although this may not be important in an environment of limited competition, as competition increases among financial institutions, having products that match client needs will give institutions a competitive edge.

IMPLICATIONS FOR DONORS

Gender differences suggest strategic options for donors. Programs that seek to have the greatest overall employment impact should focus on male-owned businesses in the production and services sectors—particularly in chemicals and construction materials, construction, textiles and clothing, and metal or paper products. Programs seeking to have a direct impact on women should focus on female-owned businesses in the commerce sector, and programs that seek to increase employment opportunities for women should focus on female-owned businesses in the production and services sectors—especially in textiles and clothing and small restaurants or food service.

The findings on socioeconomic status also suggest strategic options for donors. Loan access—in terms of both applying for and receiving credit—is directly related to socioeconomic status. With only the exception of very poor women—suggesting the impact of targeted lending programs focusing on poor women—the less wealthy the entrepreneur, the less likely he or she was to either apply for or receive a loan. Microfinance seems to be reaching the upper levels of microenterprise population, but has not penetrated poor microentrepreneurs.

The survey results also suggest that it is important for donors to recognize the limits of finance. Many of the conditions described by the respondents in other chapters—increasing competition, lack of growth in sales, little demand—suggest that increasing the supply of credit may not benefit most microentrepreneurs. Donors need to recognize the importance of nonfinancial services—such as improving the understanding of markets, improving product quality, and increasing the efficiency of

XXIV MICROENTERPRISES AND MICROFINANCE IN ECUADOR

production and marketing—and how they may be crucial in breaking the constraints faced by microentrepreneurs.

Overcoming many of these problems requires knowledge and skills more than credit. Microentrepreneurs in Ecuador are not accessing—whether because of lack of availability and opportunity or for other reasons—nonfinancial support that can help them overcome these problems. Few belong to interest group or trade associations. Few have received training, and few have accessed technical assistance. Addressing the problem of access to nonfinancial support services should be an important donor priority even though focusing a program is challenging because of the heterogeneity of the microenterprise sector and its geographic dispersion.

I. INTRODUCTION 1

I. INTRODUCTION This report summarizes the findings and conclusions of a 2004 study of microenterprises and microfinance in Ecuador. The study was carried out by Development Alternatives, Inc. (DAI) under the Strengthening Access to Microfinance and Economic Liberalization (SALTO) project, which is sponsored and financed by U.S. Agency for International Development (USAID)/Ecuador to enhance the access of microentrepreneurs in Ecuador to financial services and to improve the macroeconomic environment for sustained development in Ecuador. The authors hope the results of this study will provide donors, Ecuadorian government agencies and ministries, microfinance institutions (MFIs), and others involved or interested in promoting the advancement of the microenterprise sector in Ecuador with a sound basis for strategic planning and actions.

BACKGROUND

The last extensive study of microenterprises and microenterprise support organizations in Ecuador was the 1990 sector assessment performed by DAI under the Growth and Equity through Microenterprise Initiatives and Investments (GEMINI) project.3 It provided descriptions and analysis of microenterprises and the impediments to their growth and development, the policy and legal framework for microenterprises, the demand and supply of credit to the sector, and the market potential for microenterprises, as well as a survey and analysis of the institutions that provided financial and nonfinancial support to the sector.

Much has changed in Ecuador since that study was completed. The number of institutions providing financial and nonfinancial services to microenterprises has declined, while the number of microenterprises active in the country has increased considerably. Attempts to establish national coordinating entities such as CONAUPE (Corporación Nacional de Apoyo a las Unidades Populares Económicas) and UNEPROM (Unidad Ejecutora del Programa de Microempresas) have been abandoned. Two major financial crises resulted in a major contraction and reorganization of the financial sector and a decision to “dollarize” the economy in order to stem runaway inflation. Standards of living declined and unemployment increased markedly in the aftermath of the crises. Many of the unemployed turned to microenterprise self-employment activities to earn a living, and microenterprises have become an even more important sector of the national economy. As a result of outmigration, remittances from abroad have become a major source of income for many in the poorer classes; in 2002 alone, remittances contributed $1.5 billion to the income of Ecuadorians.4

Major new financial intermediaries for microfinance have emerged, and the credit union movement has grown in size and importance as a provider of financial services to households and microenterprises, but there is a general feeling that large segments of the microenterprise sector are still unable to access the financial and other services that they need to grow and prosper. As a recent study of the potential for a second-story financing institution for microfinance in Ecuador pointed out:5

3 The GEMINI study covered a wide spectrum of issues related to the microenterprise sector, including

baseline characteristics of microentrepreneurs, the macroeconomic policy environment for microenterprise development, financial and nonfinancial support services available to microenterprises, and local and international marketing opportunities and constraints for microenterprise products. Relevant publications produced by that study are included in the bibliography.

4 Bendixen and Associates 2003, p. 5. 5 Dougherty, De Sousa, and Valenzuela 2003.

2 MICROENTERPRISES AND MICROFINANCE IN ECUADOR

[T]here has been no systematic, comprehensive study of the demand for microfinancial services in Ecuador at the national level…. [L]ittle solid data exist related to the structure of demand by region and by loan size, the amount of potential savings, the demand for non-credit products such as microinsurance and business development services…. [T]here appears to be a dearth of information regarding the level and characteristics of demand for microfinance by poverty level, geographic region, economic sector, household characteristics, etc. There is also a lack of data regarding the reach of alternative credit sources such as informal money lenders, consumer credit providers and equipment leasing…. [A study would] provide a more solid basis on which to plan and implement future donor interventions.

The absence of reliable information about the size, scope, characteristics, and distribution of microenterprises in Ecuador posed a serious constraint to the strategic planning efforts of MFIs and donors seeking to stimulate microenterprise development and reduce poverty.

PURPOSE AND OBJECTIVES OF THE STUDY

PURPOSE

The overall purpose of this microenterprise benchmark study is to help USAID/Ecuador, other international donors, the Government of Ecuador, MFIs, and other organizations that provide service to microenterprises to improve their efforts to reduce poverty in the country. It provides the baseline information needed to orient strategies, policies, and resources toward the development of financial and nonfinancial services for microenterprises so that they can expand their contribution to employment generation and stability and improve the income of the vulnerable poor in rural and urban areas.

The study will also provide USAID/Ecuador, other international donors, the government, and institutions that support providers of microfinance and other services to microenterprises with the baseline information needed to orient and plan assistance for expanding and improving this sector. The results of the study will help institutions that provide microfinance and nonfinancial support to microenterprises to identify geographic concentrations of microenterprises and potential demand for services and to understand better the characteristics, problems, and capacity of existing and potential clients. This information should help such institutions plan products and services, expand coverage and deepen outreach services to microenterprises, and target new clients and markets. The possibility of repeat surveys presents an opportunity to measure the impact of microenterprise development programs in the country.

SPECIFIC OBJECTIVES

The specific objectives of the study are:

1. To provide a statistically valid benchmark of the microenterprise population and providers of services to microenterprises in Ecuador to serve as a key tool for planning actions and interventions to strengthen the performance and growth of microenterprises in the national social and economic life and generate employment and income for the urban poor; and

2. To provide reliable descriptions of: 1) the major constraints and opportunities for microenterprise expansion and growth in the country; 2) microenterprise access to, use of, and demand for financial and nonfinancial services; and 3) the availability and characteristics of financial and nonfinancial services supporting microenterprise activities in Ecuador.

I. INTRODUCTION 3

STAKEHOLDERS

The study will benefit a wide variety of institutions that support microenterprises in Ecuador, including:

Providers

The study results will be valuable to the current providers of financial and nonfinancial services to microenterprises in Ecuador by:

• Identifying gaps in coverage that represent potential new or expanded markets;

• Identifying products and services that are currently used by microentrepreneurs and revealing the need to redesign existing products and services to appeal to microenterprise clients and potential clients; and

• Identifying aspects of existing services and products that clients and potential clients do not like—especially in terms of issues like group versus individual lending and village banking approaches versus solidarity group and individual approaches.

MFIs and business development services (BDS) providers should be able to use the study results to identify new market areas, products, and services.

Government of Ecuador

The study also produced results that will be useful to the government as it establishes policies and develops regulations and norms related to the microfinance industry in Ecuador. The data will enhance government’s understanding of the importance and role of microenterprises in the economy and in employment generation for the urban middle and lower classes and will provide a basis for making decisions on the proper role of the public sector in promoting the industry—for example, whether to use government funds to set up microfinance funds (if sufficient private sources of funds for capital expansion and other purposes are not available to MFIs). The data should also increase knowledge about the structure of the industry that will be of use to the Superintendency of Banks and Insurance as it refines its norms for microfinance operations and its supervision practices.

Donors

An immediate and primary audience for the study will be the international donor community. The study illuminated a number of factors that are critical to program design:

• The prevalence, distribution, and characteristics of microenterprises in Ecuador, especially in terms of characteristics of enterprises that are not accessing formal financial and nonfinancial services;

• The extent to which microenterprises have an identified or potential demand for financial and nonfinancial services;

• Geographic and other gaps (gender, sector, and so on) in the coverage of financial and nonfinancial services to microenterprises;

• The key problems faced by microenterprises and the role of finance in promoting micro and small enterprise growth and the types of programs and projects that are needed to help them overcome these key problems; and

• The attitudes and perceptions of microentrepreneurs toward existing financial and nonfinancial services and service providers so that new projects can better meet needs and expectations.


Armed with this knowledge, the donor community will be better able to plan and deliver projects that have a positive impact on the microenterprise community.

USAID/Ecuador

Finally, the information produced by the survey work and related studies in this exercise will provide additional valuable baseline data for USAID/Ecuador in measuring progress on poverty reduction. The possibility of conducting surveys of a similar nature in the future to measure changes in poverty indicators that may be attributable to greater access to microfinance and business development services will need be considered at a later date.

A DEFINITION OF “MICROENTERPRISES”

The definition used to define microenterprises has a profound impact on the findings of a study. Broad definitions will identify a large number of microenterprises; those that are more exclusive will identify fewer. The definition adopted will also have an impact on key distributions—gender, income level, geographic location, and others.

No single definition of microenterprise will ever satisfy everyone, as evidenced by the many different interpretations that abound. Attempts to define microenterprise have used maximum number of employees (less than five employees or less than 10 employees); assets (less than $5,000 in fixed assets or less than two times gross national product per capita in buildings and equipment); sales (less than $500 per month in total sales or monthly sales less than three times the minimum monthly salary); or level of formality (informal sector, nonlicensed, or nonregulated) or management structure. Some have resorted to esoteric formulae, such as a capital/labor ratio no greater than 10. And still others have combined indicators—assets less than $2,500 and sales no greater than five minimum monthly salary equivalents per month, for example.

Apart from the difficulty of measuring some of these indicators, there are many other inherent problems in attempting to arrive at a consensus definition. One problem is that any definition may lead to contradictory conclusions. A printing business, for example, may have only two employees but have tens if not hundreds of thousands of dollars in equipment. Is it a microenterprise because of its small number of employees, or a small enterprise because of the high value of its assets? Some businesses may have a large number of employees but relatively few assets. Still others may have a very high turnover, but very low profits.

Perhaps the major difficulty of trying to arrive at a universally accepted definition is that different organizations have different needs and objectives and tailor the definition to their specific requirements. Microfinance practitioners tend to define “microenterprise” in terms of their particular market niche. Institutions with a mission to alleviate poverty will limit the definition to the poorest of the poor. Rural-oriented institutions will include small farms in their definition of microenterprises; urban-oriented institutions will not consider small farming as a microenterprise activity. Microfinance institutions striving to achieve sustainability in a competitive commercial market will focus on clients who have viable businesses with a potential for growth, and will not attempt to reach the poorest of the poor. Yet each of these institutions considers its clients to be “microenterprises.”

Donors also need to define a microenterprise population in a manner consistent with their own program objectives and priorities and in terms that allow them to measure whether or not they have been successful in reaching that population. Donors that have a poverty alleviation focus are particularly interested in defining microenterprise in terms of poverty level; those that are more interested in growth and sustainability will place more emphasis on growth potential and financial performance than on income level or size of enterprise. Thus, definitions vary widely among the major donor organizations.

I. INTRODUCTION 5

Still, in the development community there are a number of characteristics associated with the term “microenterprise” that are generally understood and can be useful. Microenterprises tend to be personal or family businesses. They are small, in terms of assets, employees, and sales volumes, though it may be difficult to assign precise numbers to each of these characteristics. They are run by relatively poor and relatively low-educated people with limited professional training.6 They are characterized by low levels of technology. And they are likely to be informal, in the sense of not being licensed and regulated as are larger businesses.

Other characteristics may be less universally accepted but are useful nonetheless. For example, day laborers, or people who hire themselves out as contract personnel, are not generally considered to be microenterprises.7 It is generally accepted that a microenterprise involves “entrepreneurship” in the sense that the owner/operator of the business makes independent judgments and decisions about products, market strategies, and prices. For example, a seamstress who works in her own home but does nothing more than sew shirts on a contract basis for a large firm would not generally be considered a microentrepreneur because she makes no decisions on when or how much to produce, or on the designs, markets, pricing, or sale of the product. If, on the other hand, she creates her own designs, accepts orders from a variety of clients, and therefore attempts to present herself as someone to seek out, she would be considered a microentrepreneur. A street vendor may act as an independent microenterprise—making decisions on products, locations, and prices—or may actually be working for wages or on commission for an established company or wholesaler, functioning more as a paid employee than as a microenterprise. These many nuances make it difficult to arrive at a single definition that will satisfy everyone.

Although there will not be universal agreement on any definition of microenterprise, it is imperative to have a working definition to carry out a baseline study of the sector. The definition that underlies the findings and conclusions in this report is:

A “microenterprise” is a personal or family business in commerce, production, or services that employs fewer than 10 persons, is owned and operated by an individual, family, or group of individuals of relatively low income, whose owner exercises independent judgment on products, markets, and prices, and that is an important (if not the most important) source of income for the household.

UNDERSTANDING THE RESULTS

SAMPLE DESIGN AND METHODOLOGY

The survey of microenterprises was designed to be a representative survey of urban microenterprises. A consultant from the U.S. Bureau of Census who had previously worked with the Ecuadorian Instituto Nacional de Estadística y Censos (INEC) to design the master sample based on the 2001 national census, worked with INEC, SALTO, and the contracted survey firm to design a stratified

6 This characteristic is largely driven by the international donor community and socially oriented

nongovernmental organizations. Private sector “commercialized” microfinance institutions would tend to underplay the issue of poverty.

7 The Instituto Nacional de Estadística y Censos, in its Encuesta de Empleo y Desempleo, for example, determines whether or not a person has an enterprise by whether or not he has fixed assets and transforms or manages inventory and equipment in addition to merely selling his personal labor.


random sample for the survey.8 The design produced a weighted sample for microenterprises in middle- to low-income neighborhoods of towns and cities with 5,000 or more inhabitants. The distribution of the sample—which covered 750 census segments of approximately 120 households each in 143 separate towns and cities—is presented in Figures I-1 and I-2. Complete information on the sample and weighting procedures are available on the SALTO website.9

The survey was conducted between March and June 2004 by Habitus Investigaciones, S.A., an Ecuadorian firm specializing in marketing and opinion studies and socioeconomic research. The questionnaire was based on surveys used in other studies, including the numerous GEMINI baseline studies, and was submitted to extensive field-testing prior to the actual survey. The 112 interviewers were recruited, trained, and supervised by Habitus.

The actual survey involved a two-stage interview process. The survey team first canvassed each sample segment to enumerate every household. The first-stage interview was then conducted with every single household in the segment, and was designed to gather key background information on the households and to identify individuals who operated a microenterprise. A random sample of no more than 26 households with microenterprises was then selected for interviewing within the segment, with no substitutions. A complete description of the survey methodology10 is available on the SALTO website.

UNDERSTANDING THE NUMBERS

Because of the different analyses and projections performed on the survey data, the base number of observations (N) and the projected number of microenterprises may appear to vary from table to table. This is not an error, but the result of the different domains and universe of microenterprises referred to, structural characteristics of the survey instrument, and the way statistical analysis programs handle missing data and no responses. It is important to understand the underlying numbers and to keep the distinctions in mind while reading the report or using the data for independent analysis.

8 Megill 2004a and 2004b. 9 SALTO website: www.salto-ecuador.com. 10 Habitus Investigaciones 2004a.

I. INTRODUCTION 7

FIGURE I-1: PARROQUIAS IN WHICH INTERVIEWS WERE CONDUCTED

FIGURE I-2: CANTONES REPRESENTED BY INTERVIEWS


Numbers Related to the Survey Sample

This was a sample survey; therefore, a core set of numbers relate to the sample itself—the number of households and individuals interviewed. The survey identified a total of 91,352 households in the sample segments, of which 81,607 were enumerated. The households that were not enumerated included 7,372 in which no one was at home during the survey and 2,373 that refused to participate. Within the 81,607 households, the survey collected key socioeconomic data on all household members aged 12 and above.

91,352

81,607

240,802

households identified

households interviewed

persons age 12 and over in the interviewed households

Of the 240,802 adults in these households:

124,654

28,471

1,381

were economically active

had a microenterprise (as defined for the study) as their primary economic activity

had a primary economic activity that was not a microenterprise, but had a microenterprise as a secondary economic activity

Of those with a microenterprise as either a primary or secondary economic activity, the sampling procedure resulted in interviews with:

17,743 microentrepreneurs

of which five were eventually excluded because their microenterprise did not fit within the definition of microenterprise for the study, yielding:

17,738 interviews in the database

The number of enterprises represented by these respondents is greater than 17,738 because some microentrepreneurs operated multiple businesses.

The survey administered a full questionnaire only to microentrepreneurs whose enterprises were either the most important or the second most important enterprise in the household; 17,621 persons responded to the full questionnaire. A shorter questionnaire, consisting of only seven questions, was administered to those whose microenterprises were ranked as third, fourth, or fifth most important in the household; 117 respondents responded to this shorter questionnaire. Thus, in most cases the actual sample size (N) for the survey is 17,621, but for those few questions that were asked of the other household members as well, the N for the survey is 17,738.

Numbers Related to the Universe of Microentrepreneurs

A survey is designed to generate information about a broader population. Analyzing the data in terms of the actual survey responses is of only limited utility, because it does not provide a means for generalizing the results to the broader population.

In this case, the sample was not directly proportional to the overall microenterprise population. Guayaquil and other large cities were purposely undersampled in order to have enough cases in

I. INTRODUCTION 9

smaller towns to make valid inferences about those areas. Similarly, Amazonía was oversampled because the extremely low population densities would not yield sufficient cases to draw meaningful conclusions in a purely proportional sample.

The sampling procedures for the survey were designed to provide a means for projecting the actual sample to the broader universe of microentrepreneurs in the country. Expansion factors were created to adjust for the over and undersampling in the survey and to permit projections to the universe defined by the design. For this survey, the expansion factors (weights) were based on the known distribution of microenterprises as classified in the 2001 Census of Population and Housing and the selection of census segments for the survey.

These weights and expansion factors are rooted in the universe defined by the sampling design. In this case the universe of the sampling design was towns with more than 5,000 inhabitants (excluding the Galapagos and portions of Amazonía, the eastern lowland region of Ecuador) in neighborhoods that could be classified as middle-income and below. The weights used directly represent and reflect this universe of microenterprises. The projected total of microenterprises in this universe is:

464,548 urban microentrepreneurs in the sample universe

Most of the percentages presented in the tables of the report represent this universe of microenterprises.11

In addition to the microentrepreneurs in the sample, there are other microentrepreneurs in the country with businesses that fit the study’s definition of urban microenterprises. There are microentrepreneurs in smaller towns (2,000 to 5,000 inhabitants and even smaller) and microentrepreneurs who live in higher-income neighborhoods than those directly included in the sample design. Data from the 2001 Census permit us to also expand our estimates to this greater population of microentrepreneurs in the country, although not with the same degree of precision and confidence as the projections to the specific study universe. This expansion, projected from the survey sample, yields an estimate of 646,084 urban microentrepreneurs, as follows:

464,548

154,395

27,141

646,084

Universe of the study

Estimate of microenterprises in small towns

Estimate of microenterprises in higher-income neighborhoods

Total estimated urban microentrepreneurs in Ecuador

This projection of the total population of microentrepreneurs is only used in this report in a few instances when estimates of the total population of microentrepreneurs are required. Because of missing values for specific questions, the totals presented throughout the report may not be exactly equal to these numbers in the various tables.

The relationship of the sample to the sample universe and population of urban microentrepreneurs can be seen in Figure I-3.

11 Percentages are listed as percentages of non-missing responses, not of total respondents. In many cases

respondents were not asked a particular question because their answer to a previous question indicated that they had no information for the current question. Because of these missing responses, the “N” for specific questions is generally different than the total “N” for the sample.


FIGURE I-3: RELATIONSHIP OF SAMPLE TO SAMPLE UNIVERSE AND POPULATION OF MICROENTREPRENEURS

27,141

Total 646,084

Sample 17,738

Higher-income neighborhoods

Smaller towns

154,395

Urban microentre-preneurs in middle- and lower-income neighborhoods in towns and cities

Universe of Micro-

entrepreneurs Represented

by the Sample

464,548


II. UNDERLYING CHARACTERISTICS OF THE MICROENTERPRISE SECTOR

This chapter presents a basic description of the microenterprise sector, the socioeconomic characteristics of urban microentrepreneurs, and the characteristics of the enterprises themselves.

NUMBER AND DISTRIBUTION OF MICROENTERPRISES

One of the most important questions this study attempts to address is “How many microenterprises are there in Ecuador?” This is not a trivial question: the number of microenterprises defines the potential market for microfinance activities oriented toward business financing12 and serves as an important indicator of success and future growth potential and as a basis for planning business strategies.

Estimates of the microenterprise population have varied widely, from 950,000 to more than 1,700,000. In 2003, the Inter-American Development Bank placed the estimate for Ecuador at 1.7 million enterprises.13 The 2001 Censo de Población y Vivienda enumerated 1,457,877 adults who were economically active and were either owners of businesses or self-employed. Of these, 452,658 were engaged in farming and another 58,323 in activities that would normally be classified as day labor, leaving 946,896 who were engaged in urban-oriented enterprises.14 Similar estimates performed by Habitus Investigaciones, S.A. placed the estimated total at 974,310 microenterprises using the 1999 Encuesta de Condiciones de Vida, and 1,043,440 using data from the 2001 Encuesta de Empleo y Desempleo.15 It is important to note that agricultural enterprises—small farmers, in particular—were uniformly excluded from all of these estimates.

As mentioned in Chapter I, the number of microenterprises depends on the definition of a microenterprise. The projections in this report are based on a very specific definition of a microenterprise:

A “microenterprise” is a personal or family business that employs fewer than 10 persons, is owned and operated by an individual, family, or group of individuals of relatively low income, whose owner exercises independent judgment on products, markets, and prices, and that is an important (if not the most important) source of income for the household.

Using this definition of a microenterprise, the data from the 2001 Population Census were adjusted to arrive at an estimate of 657,887 urban microenterprises in the country.16 When correcting the data from the Census and surveys of condiciones de vida and empleo y desempleo, Habitus arrived at estimates of between 657,000 and 726,000 urban microenterprises in the country.17

12 In contrast to the earlier donor focus on targeted financing that was limited to financing only business

activities, microfinance institutions do not limit their loans to productive economic activities. Nevertheless, assisting microenterprises is still the underlying rationale and objective of most donors and MFIs.

13 Inter-American Development Bank 2003, p. 3. 14 Habitus Investigaciones, S.A. 2004b. 15 Habitus Investigaciones, S.A. 2004b. 16 Magill and Meyer 2004. 17 Unpublished statistics.


The consistency of these estimates, using different estimating procedures and different sources of official statistics, supports a conclusion that there are probably between 640,000 and 700,000 urban-based microentrepreneurs in Ecuador.

SAMPLING FRAME

Using the study’s more rigorous sample survey framework and definitions to adjust the data from the recent census and household surveys allows for a reasonable projection of the number of microentrepreneurs and microenterprises in the country.

The survey’s sampling frame determines the extent to which the results can be projected to the universe of microenterprises in the country. The sampling frame was an urban frame composed of towns with more than 5,000 inhabitants. Because the survey related to urban microenterprises, it excluded rural areas with dispersed populations and persons engaged in agriculture. For practical and financial reasons the study did not include urban populations with less than 5,000 inhabitants—the cost of including these communities in the survey was prohibitive. Certain geographic areas—the Galapagos (with a total population of 16,917) and remote areas of Amazonía—were also not included in the sampling frame for reasons of cost. Finally, wealthier neighborhoods were not included although it was recognized that they might contain some households with microenterprises; the ratio of such households to total households in these neighborhoods would have greatly increased the costs of interviewing the few cases that would have been found. Apart from the deliberate decision to exclude rural enterprises within the scope of the study, therefore, the exclusion of other population segments was based on financial considerations, not because of any belief that microenterprises in these areas were any different from those in other close proximity neighborhoods.

The survey’s framework, therefore, is directly representative of that portion of the microentrepreneurs in towns of 5,000 inhabitants and above who reside in middle- and lower-income neighborhoods, excluding the Galapagos and sparsely populated areas of Amazonía.

The first-stage survey of households found 28,471 persons with a microenterprise as their primary occupation and 1,381 people who are employed but who have a microenterprise as a secondary source of income. This projects to 439,611 persons with a microenterprise as their primary occupation and 22,187 persons with a microenterprise as a secondary occupation, for a total of 461,798 microentrepreneurs within the sample universe. Using the same expansion factors for the second-stage sample of 17,738 microentrepreneurs who were actually interviewed during the survey yields a projection of 464,548 microentrepreneurs in the sample universe. Thus, within the universe of the survey there were between 461,798 and 464,548 microentrepreneurs. Throughout this report, the second-stage sample projects a total of 464,548 microentrepreneurs in the sample universe.

PROJECTING TO THE NATIONAL POPULATION

Projections for the portion of the microentrepreneurs residing in towns of 2,000 to 5,000 inhabitants and for the portion residing in upper-middle-class and upper-class neighborhoods can be made under clearly defined assumptions. In the case of those residing in towns with 2,000 to 5,000 inhabitants, the assumption is that their distribution is similar to that of microentrepreneurs residing in towns of 5,000 to 9,000 inhabitants. Likewise, microentrepreneurs located in wealthier urban neighborhoods are assumed to be similar to those in middle-class neighborhoods.

With these assumptions, the adjustment of census data based on the survey results projects a total of 646,084 urban microentrepreneurs in Ecuador.


MICROENTREPRENEURS WITH MORE THAN ONE BUSINESS

The above numbers refer to individuals who own and operate at least one microenterprise as either a primary or secondary source of income. As a result, it represents the number of individuals, and not the number of businesses.

Most of the respondents to the survey (94.7 percent) operated only one microenterprise. Overall, there was an average of 1.06 enterprises per microentrepreneur, which would mean that the 646,084 urban microentrepreneurs in Ecuador operate a total of 684,850 enterprises.

GEOGRAPHIC DISTRIBUTION OF MICROENTERPRISES

The large majority of urban microenterprises (66.8 percent of the total18) are located on the coast, primarily in the Guayaquil metropolitan area. Another 31.5 percent are located in the highlands, with half of those in the metropolitan areas of the cities of Quito and Santo Domingo de los Colorados. A small number of microenterprises (1.7 percent of the total) are located in Amazonía. The distribution of microenterprises by province can be seen in Table II-1:

18 Totals in this section refer to the population of 646,084 urban microentrepreneurs.


TABLE II-1: GEOGRAPHIC DISTRIBUTION OF MICROENTERPRISES19

Region and Province %

Coast (66.8%) El Oro 5.5 Esmeraldas 2.0 Guayas 42.4 Los Rios 6.7 Manabi 9.8 Zonas No Delimitadas 0.4 Highlands (31.5%) Azuay 2.7 Bolivar 0.3 Cañar 1.1 Carchi 0.7 Cotopaxi 1.1 Chimborazo 1.9 Imbabura 2.3 Loja 1.5 Pichincha 17.6 Tungurahua 2.3 Amazonía (1.7%) Morona Santiago 0.3 Napo 0.2 Pastaza 0.4 Zamora Chinchipe 0.1

Sucumbios 0.5 Orellana 0.2 Total 100.0

As can be expected, the largest percentage of microenterprises is found in the large cities of Guayaquil, Quito, Machala, and Cuenca (Table II-2). However, there is a good representation of microenterprises in smaller cities and towns as well.20 In fact, the relative significance of microenterprises in the economies of these smaller cities and towns is undoubtedly greater than it is in the large cities, where larger businesses and government offices are concentrated.

19 In all tables in this report, percentages may not total to 100 percent due to rounding. 20 In this classification, “Large Cities” consist of Guayaquil, Quito, Cuenca, and Machala; “Large Towns”

consist of towns with populations ranging from 100,000 to 199,999; “Medium Towns” are those with populations of 20,000 to 99,999; and “Small Towns” are those with populations of 5,000 to 19,999.


TABLE II-2: GEOGRAPHIC DISTRIBUTION OF MICROENTERPRISES, BY SIZE OF CITY

Location by Size of City/Town %

Large cities 44.0 Large towns 23.9 Medium towns 18.8 Small towns 13.3 Total 100.0

The overall distribution of microenterprises in the country, by canton, can be seen in Figure II-1. Microenterprises tend to be clustered in highly urbanized cantones in the highlands and on the coast. In Amazonía and other largely rural cantones, the “urban” microenterprise population is concentrated in one or two towns.

PERSONAL CHARACTERISTICS OF ECUADORIAN MICROENTREPRENEURS

This section presents the basic demographic characteristics of Ecuadorian microentrepreneurs. The data came from two sources: the first stage of the survey provided the data for all adults 12 and over in the households, and the second-stage survey provided information on the microentrepreneurs themselves.

FIGURE II-1: DISTRIBUTION OF MICROENTERPRISES, BY CANTON


GENDER

In the general population of people identified in the first stage of the survey, men were more economically active than women; 69.5 percent of men aged 12 and older were engaged in a regular income-producing activity, compared with only 34.7 percent of the women. The difference was even larger for the population over 30 years of age—85.9 percent of the men were economically active compared with only 43.1 percent of the women. Non-economically active women were primarily engaged in housework (61.4 percent) or were students (26.7 percent). Within the urban microenterprise sector of microentrepreneurs interviewed in the second-stage survey, however, men and women were represented more equally, with men comprising 53.7 percent of the entrepreneurs in the sample and women 46.7 percent.

Economically active women (Table II-3) were much more likely to be microentrepreneurs (56.4 percent) than men (31.3 percent). Men have a much greater tendency to be employed (35.1 percent compared to 27.5 percent) or day laborers (29.4 percent compared to 7.7 percent), while women are more likely than men to work in a family-run business (5.1 percent compared to 1.6 percent). The high percentage of economically active women who are microentrepreneurs suggests that, for many women, this is their primary opportunity to enter the active workforce.

TABLE II-3: EMPLOYMENT STATUS OF ECONOMICALLY ACTIVE MEN AND WOMEN

Gender Employment Status Men Women

Total

Self-employed 31.3% 56.4% 39.2%

Owner/employer 2.6 3.4 2.8

Salaried worker 35.1 27.5 32.7

Daily laborer 29.4 7.7 22.5

Worker in family-owned business 1.6 5.1 2.7

Total 100.0% 100.0% 100.0%

AGE

The first-stage survey involved a census of adults in the sample households (Table II-4). The average age of the adult population21 covered in this stage was 34.6 years; 30.2 percent of the respondents were over 40 years of age. The average age of microentrepreneurs among this population was 41.9 years, and nearly half (49.2 percent) were over 40 years of age. Microentrepreneurs are generally older than the general adult population when persons 12 and older are considered adults.

21 The Instituto Nacional de Estadística y Censos uses age 12 and above in defining the adult population in

Ecuador.


TABLE II-4: AGE OF POPULATION SURVEYED AND MICROENTREPRENEURS IN THE SAMPLE

Age Groups Adults in Sample Microentrepreneurs

12 to 17 16.9% 1.1% 18 to 25 21.9 8.8 26 to 30 11.3 11.1 31 to 35 9.6 13.8 36 to 40 10.1 16.1 41 to 45 7.6 13.4 46 to 50 6.0 11.6 51 to 55 4.6 8.7 56 to 60 3.4 6.0 Over 60 8.6 9.5

Total 100.0% 100.0%

Young persons are relatively underrepresented in the microenterprise population, primarily because most people in the 12–17 age bracket are not economically active. Only 10.2 percent of the survey population in the 12–17 age group were economically active. Of the nonactive population in this age group, 85.7 percent were students and 6.6 percent performed household duties. Of those in the 12 to 17 age bracket who were economically active, only 13 percent could be classified as self-employed; the rest were either employed (42.2 percent), worked as day laborers (38.0 percent), or worked in family-run businesses (6.9 percent).

Female microentrepreneurs are somewhat younger than their male counterparts (Table II-5), with an average age of 41.0 compared to an average age of 42.7 for the men. Women were slightly more prevalent in the 18 to 45 age groups, and less prevalent in the age groups 46 and over. For both men and women, however, roughly two-thirds of the entrepreneurs fell between the ages of 26 and 50. The relatively large percentage of microentrepreneurs in the 60 and over age group suggests that, for many people, operating a microenterprise is a substitute for retirement.


TABLE II-5: AGE DISTRIBUTION OF MICROENTREPRENEURS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Age Groups

Men Women Coast Highlands Amazonía Services Production CommerceTotal

12 to 17 1.2% 0.9% 1.3% 0.7% 0.4% 1.0% 0.6% 1.3% 1.1%18 to 25 8.0 9.7 8.7 8.9 9.5 6.8 5.9 10.6 8.7 26 to 30 10.4 11.9 10.9 11.5 12.6 11.1 9.7 11.6 11.1 31 to 35 13.7 13.9 13.7 13.8 14.8 13.0 12.4 14.5 13.7 36 to 40 14.9 17.4 15.8 16.4 19.0 17.0 16.9 15.3 16.1 41 to 45 13.3 13.5 13.0 14.5 14.0 15.3 16.0 11.7 13.5 46 to 50 11.8 11.4 12.1 10.5 9.6 13.0 12.4 10.7 11.6 51 to 55 9.3 8.0 8.7 8.7 7.0 9.5 10.1 7.8 8.7 56 to 60 6.5 5.4 6.1 5.9 4.5 5.6 5.8 6.2 6.0 Over 60 10.8 8.0 9.8 9.1 8.6 7.6 10.1 10.2 9.5 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

There were only minor age differences among microentrepreneurs in these geographic regions.

Microentrepreneurs in the commerce sector were generally younger (average age of 41.5) than those in other sectors, although the age differences were not large. Younger microentrepreneurs were much more likely to be found in the commerce sector, suggesting that the low skill level required to engage in this activity allows easier access at a young age. Microentrepreneurs in the production sector had the highest average age at 43.2, with fewer in the age groups 35 and below. The skills required to operate a production business might require more time to acquire, resulting in a higher average age of microentrepreneurs in the production sector.

EDUCATION

Educational levels are relatively low among the microentrepreneurs; 46 percent have at most a primary level education. However, another 21.1 percent had some secondary education, 20.9 percent had completed a secondary education, and, rather surprisingly, 12 percent had education beyond the secondary level. This level of education is higher than among the general population, which includes the rural population with its significantly lower levels of education.

Women were slightly better educated than men, especially at the secondary level (Table II-6). Just over 10 percent of both the male and female entrepreneurs have some university education. Only 3 to 5 percent of the respondents reported that they are illiterate.


TABLE II-6: LEVELS OF EDUCATION OF MICROENTREPRENEURS, BY GENDER

Gender Highest Level of Education

Men Women Total

None 2.9% 4.1% 3.5% Literacy training 0.2 0.3 0.3 Some primary 8.3 9.0 8.6 Completed primary 36.5 31.3 34.1 Some secondary 20.4 21.8 21.1 Completed secondary 20.1 21.7 20.9 Some non-university superior 0.1 0.1 0.1 Completed non-university superior 0.3 0.4 0.3

Some university 8.0 8.7 8.3 Graduated from university 3.0 2.4 2.7 Postgraduate 0.2 0.2 0.2 Total 100.0% 100.0% 100.0%

Most microentrepreneurs (97.7 percent) are monolingual in Spanish (Table II-7). Less than 0.5 percent spoke only an indigenous language, which means that few people will be disadvantaged if microenterprise programs offer technical assistance, training, or credit services only in Spanish.

TABLE II-7: LANGUAGES SPOKEN BY ECUADORIAN MICROENTREPRENEURS, BY GENDER

Gender Language Normally Spoken

Men WomenTotal

Only Spanish 97.6% 97.8% 97.7% Only indigenous language 0.1 0.2 0.2 Only foreign language 0.0 0.1 0.0 Spanish and indigenous language 1.6 1.7 1.6

Spanish and foreign language 0.6 0.3 0.5 Other 0.0 0.0 0.0 Total 100.0% 100.0% 100.0%

CIVIL STATUS

Most microentrepreneurs are involved in long-term family unions (Table II-8); 76 percent are either married or in common-law relationships. Here, however, there is an important difference between male and female entrepreneurs. Women microentrepreneurs are more likely to be single (unmarried, widowed, divorced, or separated) than their male counterparts. Only 68 percent of the women microentrepreneurs were involved in long-term relationships, compared with 82 percent of the men. Operating a microenterprise is an important business opportunity for single women.


TABLE II-8: CIVIL STATUS OF ECUADORIAN MICROENTREPRENEURS, BY GENDER

Gender Civil Status

Men WomenTotal

Single 10.8% 13.0% 11.8% Married 54.4 47.3 51.1 Common Law 28.0 21.0 24.8 Widowed 1.7 6.4 3.9 Divorced 1.2 3.1 2.1 Separated 2.9 8.4 5.5 Don't Know, NR 0.8 0.7 0.8 Total 100.0% 100.0% 100.0%

FAMILY SIZE

The average family in the sample population consists of 4.26 members, of which 2.99 are age 12 or over. Sixty percent of the households consist of four or fewer members, with 6.7 percent of the households consisting of a single person. Households with a microentrepreneur tended to have larger families than those with no microentrepreneur. The average family size for microentrepreneurs in the sample was 4.62 family members, with 3.34 persons age 12 and over.

FAMILY POSITION

Strong gender differences emerged in the family position of the microentrepreneurs (Table II-9). On the one hand, more than 86 percent of the male microentrepreneurs were heads of households, compared with only 29 percent for the women. On the other hand, 59 percent of the women were spouses or partners, compared with less than 2 percent of the men. Sons and daughters comprise another 8.1 percent of the microentrepreneurs. Relatively few of the microentrepreneurs were other relatives or nonrelatives.

TABLE II-9: FAMILY POSITION OF MICROENTREPRENEURS, BY GENDER

Gender Relationship to Head of Household Men Women

Total

Head of household 86.4% 29.2% 59.9% Spouse/partner 1.6 59.3 28.3 Son/daughter 8.0 8.2 8.1 Nephew/niece 1.3 0.7 1.0 Grandson/daughter 0.2 0.1 0.2 Parents/in-laws 0.2 1.0 0.6 Other relatives 1.7 1.3 1.5 Nonrelative 0.5 0.3 0.4 Total 100.0% 100.0% 100.0%


Most single respondents were heads of household (47.1 percent) or the sons and daughters of the head of household (38.2 percent).

Microentrepreneurs who are widowed, separated, or divorced are overwhelmingly heads of household (80 to 90 percent). A smaller percentage of respondents in these categories (widowed 3.5 percent, divorced 9.2 percent, and separated 10.7 percent) were living in their parents‘ homes as sons or daughters of the head of household. Most of these (67 to 88 percent) were women.

CHARACTERISTICS OF THE MICROENTERPRISES

The microenterprises—the businesses operated by the microentrepreneurs—encountered during the survey were as diverse as the entrepreneurs themselves. This section describes the basic characteristics of the enterprises.22

SECTOR

More than half (55.2 percent) of all microenterprises in Ecuador are in the commerce sector, 25.7 percent are in services, and 19.2 percent are in production (Table II-10).23 This pattern is to be expected, because commerce presents the fewest barriers to entry—requiring little in the way of education, skills, or capital. Service sector activities generally require a basic skill, and production activities often require more substantial skills and greater capital. The large percentage of microentrepreneurs in the commerce sector is also reflected, as will be seen later, in the heavy concentration of microfinance clients in the commerce sector.

TABLE II-10: DISTRIBUTION OF ENTERPRISES BY ECONOMIC SECTOR, BY GENDER AND REGION

Gender Region Economic Sector Men Women Coast Highlands Amazonía

Total

Services 31.1% 19.4% 24.6% 27.6% 30.7% 25.7% Production 22.4 15.3 18.0 21.7 17.3 19.2 Commerce 46.4 65.3 57.4 50.7 52.1 55.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Although both men and women are concentrated in commerce, a higher percentage of women (65.3 percent) than men (46.4 percent) are engaged in commerce. Higher percentages of men than women are found in production and services.

Regional differences are not particularly striking, though production constitutes a higher percentage of the businesses in the highlands than in other regions and services constitute a higher percentage of businesses in Amazonía.

A finer breakdown by economic sector shows a stronger gender distribution of occupations and less dramatic, though important, regional influences on occupations (Table II-11). In the services sector, women are more likely to be found in “personal services” (particularly beauty parlors) and small

22 Throughout this report, tables reporting gender are reporting the gender of the microentrepreneur. 23 The classification of occupations into services, production, and commerce sectors can be seen in the code

sheets for the questionnaire.


restaurants, while men are more involved in vehicle repairs, construction, and transportation. In production, women are concentrated almost exclusively in textiles and clothing and in food preparation, while men are more involved in wood and metal products.

Regional differences are not readily apparent in the data, although Amazonía has a higher concentration of microenterprises in hotels, bars, and restaurants than the other two regions. Businesses in transportation, textiles and clothing, and wood products are slightly more prevalent in the highlands.

TABLE II-11: SUBSECTOR BREAKDOWN OF MAJOR ENTERPRISE ACTIVITIES, BY GENDER AND REGION

Gender Region Economic Sector

Men Women Coast Highland Amazonía Total

Services

Personal services 3.2% 4.8% 4.2% 3.5% 4.2% 3.9% Hotels, bars, and restaurants 6.3 13.6 9.3 10.1 14.4 9.6

Vehicle repairs 8.9 0.4 4.6 5.9 5.2 5.0 Construction 2.3 0.1 1.2 1.4 0.8 1.3 Transportation 12.7 0.6 6.6 8.1 6.9 7.1 Production Textiles and clothing 3.5 9.2 5.8 6.9 3.4 6.1 Wood products 5.9 0.4 2.3 5.4 4.2 3.4 Paper Products 0.7 0.2 0.5 0.5 0.7 0.5 Metal Products 4.2 0.1 1.9 3.2 2.3 2.3 Chemicals and construction 1.0 0.5 0.6 1.2 1.1 0.8 Food Products 4.8 4.9 5.7 3.2 4.6 4.9 Commerce Commerce 46.4 65.3 57.4 50.7 52.1 55.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Even these categories disguise key trends in the pattern of microenterprises—particularly the heavy clustering of enterprises in only a few subsectors. In the services sector, for example, microenterprises are clustered in four basic areas: 1) hotels, bars, and restaurants; 2) transportation; 3) vehicle repairs; and 4) beauty parlors and barbershops. These four occupations account for 76.1 percent of all of the microenterprises in the services sector (Table II-12).

TABLE II-12: PRINCIPAL MICROENTERPRISE ACTIVITIES IN THE SERVICES SECTOR, BY GENDER AND REGION

Gender Region Service Sector Microenterprises Men Women Coast Highlands Amazonía

Total

Beauty parlors and barbershops 2.3% 17.2% 8.7% 5.4% 5.5% 7.5% Bars, restaurants, and cafes 16.5 67.8 34.8 33.5 40.2 34.5 Automotive and tire repair shops 16.6 0.9 10.0 13.3 11.8 11.2 Transportation (buses, taxis, and trucks) 33.6 2.9 20.8 26.7 20.6 22.9 Percentage of Total Service Sector Microenterprises 69.0% 88.8% 74.3% 78.9% 78.1% 76.1%


Of most significance in the services sector is the extreme differentiation of activities by gender. Female entrepreneurs in the service sector are overwhelmingly concentrated in small food and beverage outlets and beauty shops, while men are more dispersed among transportation and vehicle maintenance (virtually no women are engaged in these activities) and in small food and beverage outlets. There is little differentiation in terms of geographic region, although Amazonía has a higher concentration of small food and beverage outlets.

Production firms also tend to be clustered in a few occupations. Five activities—tailoring, furniture and other wood products, nonalcoholic beverages, metal products, and bread and pastries—account for nearly 75 percent of the enterprises in the production sector (Table II-13).

TABLE II-13: PRINCIPAL MICROENTERPRISE ACTIVITIES IN THE PRODUCTION SECTOR, BY GENDER AND REGION

Gender Region Production Sector Microenterprises

Men Women Coast Highlands Amazonía Total

Clothing (tailors and dressmakers) 9.8% 52.3% 27.4% 22.8% 17.8% 25.6% Wood furniture, windows, and doors 24.3 1.8 12.2 21.7 22.9 15.7 Metal products (furniture, gates, fences) 15.0 0.4 8.3 11.8 10.5 9.6

Nonalcoholic beverages and juices 10.7 22.4 20.7 5.1 13.5 15.0 Bread and pastry 8.8 5.2 7.6 7.1 9.5 7.5 Percentage of Total Production Sector Microenterprises 68.6% 82.1% 76.2% 68.5% 74.2% 73.4%

Again, there are strong gender differences in production sector businesses. Tailoring and nonalcoholic beverages account for 74.7 percent of the woman-owned businesses in the production sector. Male-owned businesses are more heterogeneous.

Although there is not a great regional differentiation in these five occupations, businesses involved in tailoring and beverages constitute a greater percentage of production sector businesses on the coast, while manufacture of wood objects and metal working are slightly more prevalent in the highlands and Amazonía. Production of nonalcoholic beverages is much higher in the warmer regions of the coast and Amazonía.

Businesses in the commerce sector were concentrated in five categories (although other articles for commerce could have been combined within this listing); these accounted for 88.1 percent of businesses in the commerce sector (Table II-14). Gender played less of a role in differentiating enterprises in this sector, although woman-owned businesses were somewhat more likely to be found in the clothing, personal articles, and general goods markets than men’s businesses.


TABLE II-14: PRINCIPAL MICROENTERPRISE ACTIVITIES IN THE COMMERCE SECTOR, BY GENDER AND REGION

Gender Region Commerce Sector Microenterprises

Men Women Coast Highlands Amazonía Total

Sales of food, beverages, and other items 52.0% 49.2% 48.4% 55.0% 57.9% 50.5%Sales of clothing and shoes 10.0 14.5 12.3 12.9 11.9 12.5 Sales of products for personal use and cleaning 1.8 9.6 7.3 3.3 2.3 6.1

Sales of other small items (knick-knacks) 2.3 7.5 6.0 3.1 3.3 5.1 Other articles for commerce 21.0 8.0 14.1 13.2 13.7 13.9 Percentage of Total Commerce Sector Microenterprises 87.1% 88.8% 88.1% 87.5% 89.1% 88.1%

AGE OF BUSINESS

Most microenterprises were relatively young businesses—50 percent of the enterprises were started during the past 5 years (since 1999) and 20 percent during 2003 and the first half of 2004 (Table II-15).

This recent creation of businesses may be the result of many different factors and influences. Ecuador suffered a severe financial and economic crisis in 1999 and 2000, with many bank and business failures and downsizing in the public sector. The hypothesis that this would be reflected in new business start-ups as people who had lost their jobs or were unable to find jobs because of the crisis would turn to microenterprises to survive is at least consistent with the data. The young age of businesses may also reflect the rising number of people entering the workforce relative to the number of formal sector salaried jobs being created. Finally, the young age of Ecuadorian microenterprises is consistent with patterns of small business start-ups in the rest of the world; many, if not most, small businesses fail during the first year of operation. Microentrepreneurs, especially those in the commerce sector, tend to drift in and out of the market, with many new start-ups.

Woman-owned enterprises tend to be younger than those owned by men, with an average of 6.7 years in business compared with an average of 10.2 years in business for men. Sixty-two percent of female-owned businesses were less than five years old, and 28.4 percent had been created during the previous year and a half. In contrast, only 43 percent of the male-owned businesses were less than five years old, and only 15 percent had been created during the previous year and a half. Similarly, while 35.6 percent of the male-owned businesses were over 11 years old, only 20.2 percent of female-owned businesses had been in existence more than 11 years.

The young age of businesses is also noticeable in Amazonía, where 60 percent are five or fewer years old. The average age of businesses in Amazonía is 6.5 years, compared with 8.49 years in the highlands and 8.66 years on the coast. This pattern is consistent with the characteristic of Amazonía as an area of new settlements and recent in-migration.

There is also a pattern in the age of business by sector. As could be expected, businesses in the commerce sector were younger than those in either the production or services sectors, with an average business age of 7.3 years in the commerce sector compared with an average age of 9.0 years in the service sector and 11.7 years in the production sector. There are fewer barriers to entering the commerce sector and people with limited skills and resources tend to start businesses in this sector. Businesses in the production sector tended to be the oldest—only 36.8 percent of the enterprises in this sector were less than five years of age, compared with 47.1 percent for those in the services sector and 56.7 percent for those in commerce.


TABLE II-15: DISTRIBUTION OF BUSINESSES BY AGE, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Years in

Operation Men Women Coast Highlands Amazonía Services Production Commerce Total

Less than 1 year 6.5% 14.1% 9.7% 10.4% 15.8% 9.6% 6.7% 11.4% 10.0%1 Year 8.5 14.3 10.9 11.6 12.4 11.0 7.3 12.6 11.2 2–5 years 27.6 34.7 30.9 30.9 34.4 27.7 24.3 34.8 30.9 6–10 Years 21.6 16.6 19.4 19.2 16.7 20.3 20.1 18.5 19.3 11–15 Years 11.9 7.5 10.0 9.7 8.2 11.4 11.7 8.5 9.9 Over 15 Years 23.9 12.8 19.1 18.3 12.4 20.0 29.8 14.3 18.7 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

The age of the businesses is important because entrepreneurs with newly established businesses often face a disadvantage in getting access to formal finance. Most lenders, including most nongovernmental organizations (NGOs), want to see that potential borrowers have successfully operated a business for some time before taking the risk of lending to them.

BUSINESS START-UP

Most microentrepreneurs (92.9 percent of the total) started their own businesses. Only small percentages had inherited their business from a relative (3.1 percent) or purchased the business from a previous owner (3.3 percent). Gender differences were insignificant, although women were slightly more likely to have started their own business and less likely to have inherited or purchased it than men. About 6 percent of the respondents in the highlands and in Amazonía reported purchasing their businesses, compared with only 2 percent on the coast. People in commerce were much more likely to have started the business themselves than those in other sectors.

ACTIVITIES PRIOR TO STARTING THE BUSINESS

Most microentrepreneurs had been economically active prior to starting their businesses; nearly three-fourths of all microentrepreneurs had salaried jobs, were day laborers, assisted in a family business, or were employed as domestic servants prior to starting the business (Table II-16). About 20 percent of the respondents had owned other businesses prior to starting their current one. A small percentage (6.9) had been students and an even smaller percentage (1.9) had been unemployed. The relatively small percentage of students entering directly into a microenterprise indicates that operating a microenterprise is not the first choice occupation of persons entering the workforce for the first time. However, the small percentage of persons who had been unemployed appears to contradict the hypothesis that starting microenterprises was a direct response to loss of jobs during the economic crisis of 1999–2000.

There are significant differences between men and women in what they did prior to initiating their businesses. Thirty-one percent of the men had held salaried jobs in a private company and 27 percent had worked as laborers—more than double the percentage of women. A large percentage of women had been housewives (30.7 percent)—caring for the household and family—or employed as domestic servants (4.8 percent); virtually no men had been engaged in these activities.

By sector, 28 to 29 percent of those in services and production had held salaried jobs in a private company, while less than 20 percent of those in the commerce sector had done so. Likewise, 21 to 22 percent in the production and services sectors had worked as laborers, compared with only 16 percent


of those engaged in commerce. Only 12 percent of those in the production sector reported to have had a different business prior to starting their current one, compared with 21 to 23 percent of those in the other two sectors. Over 18 percent in commerce had previously done housework, compared with 12 percent in production and 9 percent in services, mirroring the gender distribution by sector.

TABLE II-16: ACTIVITIES PRIOR TO STARTING THE BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Activity Prior to Starting Business Men Women Coast Highlands Amazonía Services Production Commerce

Total

Student 6.0% 8.0% 6.6% 7.4% 10.0% 6.1% 8.1% 6.8% 6.9%

Unemployed 1.6 2.3 1.8 2.2 1.9 1.4 1.8 2.2 1.9

Housework 1.0 30.7 14.8 14.8 16.0 9.2 12.4 18.2 14.8

Assisted in family business 4.0 3.7 3.3 5.0 2.0 3.4 4.6 3.8 3.8

Had a different business 20.2 20.8 22.5 16.1 21.8 20.7 12.1 23.3 20.5

Worked as laborer 26.8 8.3 19.5 16.0 11.6 20.7 22.2 15.7 18.2 Salaried job in private company 30.6 15.8 22.8 25.9 21.1 28.4 29.5 19.6 23.7

Salaried job in government 4.0 2.5 3.0 4.0 6.6 3.6 2.7 3.4 3.3

Domestic employee 0.3 4.8 2.4 2.4 1.8 2.2 1.7 2.7 2.4

Other 4.9 2.7 3.0 5.5 6.7 3.9 4.3 3.7 3.9

Don't know, NR 0.6 0.4 0.4 0.7 0.5 0.5 0.6 0.5 0.5

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

BUSINESS EXPERIENCE

There is a certain amount of business churning—some entrepreneurs close one business and start another, so the business experience of some is greater than it seems. About 20 percent of both men and women reported having had a different business before starting the current one.

In terms of how many years of experience microentrepreneurs had working in the field of their business—whether as family assistants, as employees, or as entrepreneurs—the results were consistent with expectations. Women were less experienced than men, with an average of 8.0 years of experience, compared with 12.3 years for men. Entrepreneurs in Amazonía had less related work experience (8.2 years) than entrepreneurs on the coast (10.2 years) or in the highlands (10.6 years).

Entrepreneurs in commerce had much less work-related experience (8.5 years) than entrepreneurs in either the service sector (11.1 years) or the production sector (14.5 years). These differences are consistent with the differences in skills required for being successful in the various sectors.

REASONS FOR STARTING THE BUSINESS

The reasons given for starting a business—as opposed to choosing another occupation—largely reflect attraction or pull, rather than being pushed into a second-class alternative, as is often assumed in studies of microenterprises (Table II-17). A desire to be independent and a perceived opportunity to earn more than in a salaried position were the two primary motivations for starting a microenterprise rather than seeking a wage-earning job. Only 9.2 percent of the respondents reported they could not find a salaried job or that this business was the only available alternative.

However, there were strong gender differences underlying the decision to start a microenterprise. Men were much more likely to view it as an opportunity to gain independence—while women were


primarily interested in a microenterprise as a better chance to earn a decent income. A large percentage of women (17.5 percent) saw a microenterprise as an opportunity to combine household and income-earning activities, while few men started a business for this reason. A larger percentage of men (10.2 percent) than women (8.0 percent) said they could not find other employment.

The desire to become independent as a motivation for starting a microenterprise was found more in the highlands, while the desire to earn a higher income was the main motivating factor in Amazonía.

The desire to be independent was more pronounced in persons who started microenterprises in the production and services sectors and much less pronounced in those engaged in commerce. The desire to combine home and work was a greater motivating factor for persons who started businesses in production or commerce than for those in the service sector.

TABLE II-17: PRINCIPAL REASONS FOR STARTING THE BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Reason for Starting Own

Business Men Women Coast Highlands Amazonía Services Production Commerce

Total

To be independent 46.9% 27.8% 37.0% 40.7% 29.0% 43.0% 43.6% 33.8% 38.0%Opportunity to earn more 31.6 36.9 34.0 33.8 44.7 33.3 30.7 35.7 34.1

To continue a family business 3.2 3.1 3.0 3.5 2.3 2.5 4.0 3.2 3.2

Couldn't find a salaried job 6.0 3.7 5.5 3.7 3.1 4.7 4.5 5.2 4.9

Only thing available 4.2 4.3 4.2 4.5 5.1 4.9 3.8 4.2 4.3 Because of age 1.6 1.9 2.0 1.2 0.8 1.3 1.1 2.1 1.7 To combine home and work 1.9 17.5 10.1 7.1 8.2 5.7 7.9 11.1 9.1

Other 4.2 4.7 4.0 5.3 6.5 4.4 4.4 4.5 4.4 Don't know, NR 0.2 0.2 0.2 0.2 0.3 0.2 0.0 0.2 0.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

LOCATION OF BUSINESSES AND SALES

Almost 46 percent of all microenterprises are located at home, and this contributes to the efficient use of home-based capital (Table II-18).

A larger proportion of women’s than men’s enterprises are located at home: 58.7 versus 34.7 percent. Women often choose home-based enterprises because they can combine these businesses more easily with the greater responsibility they usually assume compared with men for maintaining the home and raising young children in the home. A larger proportion of men, on the other hand, work outside the home—as street vendors, at jobs that have no fixed location (such as a carpenter or a mason on a construction project or as a taxi driver), or in a permanent store, shop, or workshop.

There are also significant differences in location by economic sector. On the one hand, only 16 percent of businesses in the production sector are operated as street vendors, have transitory or permanent market stalls, or have no fixed location; 83 percent—far more than any other sector—are located at home or in a permanent shop, store, or workshop. This probably reflects the need for machinery, tools, and special facilities that cannot be easily obtained as an itinerant worker. On the


other hand, 47.4 percent of those in the services sector and 43.1 percent in the commerce sector operate in non-fixed locations.

TABLE II-18: BUSINESS LOCATION, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector

Business Location Men Women Coast Highlands Amazonía Services Production Commerce

Total

At home 15.8% 34.7% 27.6% 18.6% 12.0% 16.2% 45.2% 21.3% 24.5% At home, in dedicated location 18.9 24.0 18.0 27.2 40.4 16.1 24.6 22.5 21.3

Street vendor 13.0 6.5 11.1 8.0 3.2 6.3 4.1 13.8 10.0 Transitory stall on street/market 7.9 7.5 8.0 7.2 5.7 10.1 3.0 8.3 7.7

Permanent market stall 3.3 3.8 2.8 5.0 4.1 2.7 0.9 4.8 3.5 Permanent store, shop, workshop 14.4 8.5 9.8 15.3 19.1 17.5 13.2 8.4 11.7

No fixed location 25.6 14.2 21.7 17.8 14.4 30.0 8.1 20.1 20.3 Other 0.8 0.5 0.7 0.6 0.6 0.8 0.7 0.6 0.7 Don't know, NR 0.3 0.2 0.2 0.4 0.4 0.2 0.2 0.3 0.3 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

The location of sales is consistent with the location of the business (Table II-19). About 63 percent of the sales of women’s firms are located in the same neighborhood and another 20 percent are located in another neighborhood in the same town; only 36.4 percent of the men reported that their sales are located in the neighborhood. A third of the men reported that their sales occurred in different places, including in other towns and cities. Likewise, 82 percent of the enterprises in the production sector reported that their sales were located in the neighborhood or in another neighborhood in the same town. Those percentages were 72.8 percent for commerce and 69.3 for services.

TABLE II-19: LOCATION OF SALES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Geographic Focus of

Sales Men Women Coast Highlands Amazonía Services Production Commerce Total

In this neighborhood 36.4% 62.8% 49.2% 46.9% 59.7% 41.2% 59.1% 48.5% 48.7% In another neighborhood 29.0 20.4 23.6 28.2 22.0 28.1 22.9 24.3 25.0 In different places 27.6 13.5 22.2 19.2 14.5 26.2 12.9 21.5 21.1 In another town/city 5.7 2.3 4.2 4.1 1.6 2.9 4.2 4.7 4.1 Don't know, NR 1.3 0.9 0.8 1.7 2.2 1.5 0.8 1.0 1.1 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

This information on location and sales reflects both the strengths and the weaknesses of many microenterprises. On the one hand, they are based and sell locally, use capital carefully to keep costs low, exploit local niche markets, and cater to local tastes and demands. On the other hand, they usually find it challenging to expand out of these niche markets and successfully penetrate larger, more distant markets. It also means that if more firms are created for selling in the local market, saturation may occur when supplies exceed local demand, and prices and profits may decline for all.


PRINCIPAL MARKETS FOR MICROENTERPRISE PRODUCTS

Most microenterprises (95.7 percent) sell to individual final consumers (Table II-20). Only 11.3 percent sell to retailers; sales to intermediaries, other businesses, government, and institutions are virtually nonexistent. Less than 0.2 percent sell for export.

TABLE II-20: PRINCIPAL CLIENTS Order of Importance Totals

Most Important Clients First Second Third Responses %

Individuals, general public 419,343 15,468 3,592 438,403 95.7 Small retailers 20,020 30,138 1,553 51,711 11.3 Wholesalers 7,966 3,836 2,888 14,690 3.2 Other businesses 4,450 5,716 1,735 11,901 2.6 Government 311 865 557 1,733 0.4 Institutions 5,333 8,361 1,749 15,443 3.4 Exporters 708 264 155 1,127 0.2 Total 458,131 64,648 12,229 535,008

Note: Percentages total to more than 100 due to multiple responses.

A study of just the most important client reveals some important nuances (Table II-21). Women’s sales are more limited to individuals than are men’s; although the percentages are small, men have developed more sales relationships with small retailers, wholesalers, other businesses and institutions than women.

Microenterprises on the coast and in Amazonía are more restricted to selling to individuals than are their counterparts in the highlands, which have slightly more developed markets with small retailers wholesalers, other businesses and institutions.

Although the general public continues to constitute the principal client base for microenterprises in the production sector, these microentrepreneurs are less dependent on sales to individuals. Microenterprises in the production sector are much more likely to sell to intermediaries, institutions and other businesses than those in other sectors.

TABLE II-21: PRINCIPAL CLIENT, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector

Most Important Client Men Women Coast Highlands Amazonía Services Production Commerce

Total

Individuals, general public 88.4% 95.1% 92.4% 89.5% 94.7% 94.5% 85.3% 92.3% 91.5%

Small retailers 5.7 2.9 4.0 5.2 1.8 1.5 6.8 4.8 4.4 Wholesalers 2.5 0.9 1.6 2.0 1.2 0.4 3.8 1.6 1.7 Other businesses 1.5 0.3 0.9 1.1 0.2 1.4 1.8 0.5 1.0 Government 0.1 0.0 0.0 0.1 0.2 0.1 0.1 0.0 0.1 Institutions 1.5 0.8 0.8 1.8 1.9 1.9 2.0 0.5 1.2 Exporters 0.3 0.0 0.2 0.2 0.0 0.2 0.2 0.1 0.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


In general, Ecuadorian microenterprises sell to individuals and are not involved as suppliers to larger businesses or institutions—markets that tend to be very important for microenterprises in other countries. Being limited to sales to the general public constrains the growth potential of the microenterprises and limits potential for expansion into exports. Technical assistance, especially in developing market linkages, would be a more effective service than credit for expanding market opportunities.

FULL TIME VERSUS PART TIME

Most of the microentrepreneurs (86.9 percent) operate their businesses as full-time activities. Only 2.7 percent said they operated the business only part of the year. The rest (10.4 percent) said they had just recently started the business and it was too early to tell if they were going to operate it full time or only part time.

IMPORTANCE OF THE BUSINESS

For the vast majority of microentrepreneurs, the microenterprise is their primary occupation; 94.3 percent reported that the business was their primary economic activity and only 5.7 percent described their business as a secondary income-generating activity.

Consistent with these responses, most microentrepreneurs reported that the income from their business was an important, if not the most important, source of income for the family. Two-thirds of the respondents said the business was the principal source of income, and another 21.9 percent reported that it was the second most important source of family income (Table II-22).

Men were much more likely to say their business was the principal source of income. Women non-heads of households were more likely to say their business was a secondary source of income. Significantly, respondents in the commerce sector were more likely to see their business as providing a secondary source of income to the family.

TABLE II-22: IMPORTANCE OF THE MICROENTERPRISE, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Importance of This

Business for Family Income Men Women Coast Highlands Amazonía Services Production Commerce

Total

Principal source 84.7% 48.1% 67.8% 67.7% 68.7% 77.0% 70.7% 62.4% 67.7% Second most important 10.3 35.3 22.0 21.7 21.3 16.9 17.8 25.6 21.9

Helps, but not indispensable 3.9 14.9 9.0 9.0 7.7 5.3 10.3 10.3 9.0

Negligible 0.6 1.3 0.8 1.2 2.3 0.6 0.8 1.1 0.9 Don't know, NR 0.5 0.5 0.5 0.5 0.1 0.3 0.4 0.6 0.5 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Finally, and consistent with the responses above, nearly three-fourths of the microentrepreneurs reported that the business provided half or more of the family’s income, with 41.7 percent saying that it provided all of the family’s income (Table II-23).

Again, women were more likely to report their income as supplementing other family income, and those in the commerce sector indicated that the income from the business supplemented other sources.


TABLE II-23: PROPORTION OF FAMILY INCOME DERIVED FROM THE BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Contribution of this Business to Family

Income Men Women Coast Highlands Amazonía Services Production Commerce Total

All, 100% 56.3% 24.9% 42.0% 41.2% 43.6% 48.5% 46.3% 37.0% 41.7%More than half 19.4 17.5 18.5 18.6 21.1 20.8 16.7 18.1 18.5 About half 11.8 20.7 16.4 15.0 12.8 13.1 14.7 17.6 15.9 Less than half 8.0 24.2 15.5 15.8 13.8 11.8 13.5 18.0 15.5

Very little, almost nothing 3.3 11.1 6.6 7.6 6.5 4.2 7.8 7.8 6.9

Don't know, NR 1.3 1.6 1.2 1.9 2.2 1.5 1.0 1.6 1.4 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

FORMALITY OF BUSINESSES

Most microenterprises operate in the informal sector, as measured by registration in various official sanctioning and service agencies. Among these are tax registration, municipal licenses and permits, and enrollment of self and employees in social security.

There is also a behavioral dimension to formality; as businesses begin to operate as entities independent from the family, accounting records in particular become more formal and separated from household records. In short, the entrepreneur begins to view the business as an independent entity. These behavioral changes are often evidenced before other actions to formalize the business.

Tax Registration

Businesses in Ecuador are required to have a tax identification (RUC) number. However, relatively few microenterprises (25.1 percent) have registered with the tax authorities (Table II-24).

Businesses owned by men are somewhat more likely to be registered with the tax authorities than those operated by women.

There were strong regional differences in tax registration. Only 17 percent of microenterprises on the coast had tax identification numbers; at the other extreme, nearly 60 percent of businesses in Amazonía reportedly were registered.

Economic sector also influenced tax registration—only 21.8 percent of businesses in commerce were registered with the tax authorities, while 32.9 percent of those in services were registered.

TABLE II-24: PERCENTAGE OF BUSINESSES REGISTERED WITH THE TAX AUTHORITIES, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Has Tax ID Number (RUC) Men Women Coast Highlands Amazonía Services Production Commerce

Total

Yes 29.9% 19.5% 17.0% 40.3% 58.6% 32.9% 24.0% 21.8% 25.1%No 68.7 78.7 81.1 58.6 40.3 66.0 74.4 76.3 73.3 Don't know, NR 1.4 1.8 1.9 1.1 1.1 1.1 1.6 1.8 1.6 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


The primary reasons entrepreneurs gave for not registering their business with tax authorities were that they did not perceive a benefit in registering, their business was too small, and they were not required to register (Table II-25). Direct disincentives to registering—such as having to pay higher taxes, complicated registration procedures, and compliance requirements—were mentioned by relatively few respondents.

TABLE II-25: MAJOR REASONS FOR NOT REGISTERING WITH TAX AUTHORITIES Principal Reason for Not Having Tax ID

Number First

Response Second

Response Third

Response Total %

No need, no benefit 129,595 0 0 129,595 37.4 Business is too small 73,729 27,643 4,075 105,447 30.4 Not required to 39,162 6,926 620 46,708 13.5 Hasn't occurred to him/her 31,124 4,597 0 35,721 10.3 Would have to pay (higher) tax 9,027 4,178 400 13,605 3.9 Procedures are difficult 10,308 2,542 206 13,056 3.8 Doesn't know how 8,074 2,192 466 10,732 3.1 Cost to register is high 1,814 602 101 2,517 0.7 Would have to comply with labor laws 1,103 983 67 2,153 0.6 Other 18,643 3,828 234 22,705 6.5 Don't know 24,136 0 0 24,136 7.0 Total24 346,715 53,491 6,169 406,375


Similarly, when asked what benefits they could see in registering their business, most respondents (53.4 percent) said that there was no benefit to be obtained from registering the business. Of those who did perceive a benefit, most cited fewer problems with authorities and the ability to obtain formal sector credit as the primary benefits (Table II-26).

TABLE II-26: POSITIVE BENEFITS FROM REGISTERING WITH TAX AUTHORITIES Perceived Benefit from Registering

Business First

Response Second

Response Third

Response Total %

Can obtain formal credit 44,368 1,770 0 46,138 21.5 Fewer problems with authorities 77,408 18,574 291 96,273 44.8 Could increase clients 7,906 4,826 1,233 13,965 6.5 Can't operate without it 10,849 11,482 2,052 24,383 11.4 Could buy inputs in quantity 2,495 2,730 1,916 7,141 3.3 Other 11,598 3,326 118 15,042 7.0 Don't know 60,100 0 0 60,100 28.0 Total25 214,724 42,708 5,610 263,042


24 Totals do not add to total number of respondents because of non-responses. 25 Totals do not add to total number of respondents because of non-responses.


Municipal Licenses

Approximately the same percentage of Ecuadorian microentrepreneurs (25.2 percent) have municipal licenses to operate their businesses as are registered with tax authorities (Table II-27).

Men are slightly more likely to have licenses. Enterprises in Amazonía are more likely to be licensed. Enterprises in services and commerce are more likely to have municipal licenses than those engaged in production.

TABLE II-27: PERCENTAGE OF MICROENTERPRISES HAVING MUNICIPAL LICENSES OR PERMITS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Has Municipal License or Registration Men Women Coast Highlands Amazonía Services Production Commerce

Total

Yes 26.7% 23.5% 19.2% 36.0% 59.1% 28.0% 18.4% 26.3% 25.2% No 58.9 61.9 64.1 53.5 33.0 56.5 67.8 59.4 60.2 Not Applicable 13.6 13.9 16.0 9.4 6.8 14.6 12.9 13.6 13.7 Don't know, NR 0.8 0.8 0.6 1.2 1.1 0.9 0.9 0.7 0.8 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Social Security

Ecuadorian microenterprises are generally not involved in the country’s social security system. Only 14.7 percent of the microentrepreneurs were themselves enrolled in social security, and less than one-third of those were actively paying social security contributions. Men were significantly more likely than women to be enrolled in social security and to be making contributions.

Workers in microenterprises are also unlikely to be covered by social security. Less than 4 percent of employers with workers reported that their employees were enrolled in social security.

Accounting Records

Only 20 percent of the microentrepreneurs keep written accounting records for their businesses (Table II-28). Because accounting records are generally required for formal sector credit, the absence of records restricts a microentrepreneur’s access to credit.

Gender and region had no effect on whether or not accounting records were kept. Those engaged in commerce were the most inclined to keep formal records, while those in services were least likely to keep records.

TABLE II-28: PERCENTAGE MAINTAINING BUSINESS ACCOUNTING RECORDS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Keeps Written Business Accounts Men Women Coast Highlands Amazonía Services Production Commerce

Total

Yes 20.0% 19.7% 19.7% 20.0% 23.6% 15.9% 16.2% 23.1% 19.9%No 79.5 79.8 79.9 79.3 75.8 83.7 83.3 76.5 79.7 Don't know, NR 0.4 0.4 0.4 0.6 0.6 0.5 0.4 0.4 0.4 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


Separation of Accounts

Even fewer microentrepreneurs separate their business accounts from household income and expenses: only 11.5 percent reported keeping separate accounts. Those engaged in commerce were slightly more likely to keep separate records.

Summary

Microenterprises in Ecuador operate primarily in the informal sector. Only one-fourth are registered with tax authorities and about the same number have municipal licenses to operate. Very few belong or contribute to social security, and few workers in microenterprises are covered by social security.

Only about one-fifth of the microenterprises keep accounting records, which, because financial institutions typically require financial records in making credit decisions, limits their access to formal credit. MFIs wishing to serve informal sector businesses must generate their own version of the business accounts (an expensive undertaking) or adopt other mechanisms—such as group loans, group or solidarity guarantees, or others—to ensure repayment.

SUMMARY AND CONCLUSIONS

There are approximately 646,084 microentrepreneurs who operate a total of 684,850 enterprises in urban areas (defined in this case as towns of 2,000 and greater)26 of Ecuador. Most of these (66.8 percent) reside on the coast, and most (44 percent) live in the large cities of Guayaquil, Quito, Cuenca, and Machala.

Microenterprises provide an income-earning opportunity for a wide spectrum of the Ecuadorian population—male and female, young and old, married and single, with all levels of education.

Perhaps the most noticeable characteristics of microentrepreneurs is the high percentage of women who depend on a microenterprise. Women comprise only 30.7 percent of the economically active population,27 but constitute 46.7 percent of the population of microentrepreneurs. Of women who were economically active, 56.4 percent were microentrepreneurs, compared with only 31.3 percent of the economically active men. A substantial portion of female microentrepreneurs are single heads of household—single, separated, widowed, or divorced—demonstrating that microenterprises constitute a significant social safety net for this sector of the population.

Microenterprises are heavily concentrated in the commerce sector; 55.2 percent of all microenterprises are in commerce. Even within the economic sectors there is a heavy concentration of enterprises in specific subsectors. In the services sector, microenterprises are concentrated in the small food and beverage subsector (bars, restaurants, and cafeterias), taxis, automotive repair shops, and beauty parlors—64.9 percent of the businesses are in these occupational categories. In the production sector, 56.2 percent of the microenterprises are concentrated in clothing, wood furniture and objects, and nonalcoholic beverages. And in commerce, the majority of businesses (60.2 percent) are concentrated in foods and beverages and clothing.

Female microentrepreneurs exhibit even greater clustering in specific types of businesses. In the service sector, 67.8 percent of women are in small foods and beverages and 17.2 percent are in beauty parlors. In production, 74.7 percent of women entrepreneurs are found in clothing and nonalcoholic

26 The sampling frame consisted of towns with a population of 5,000 and greater. The estimate of 646,084

microentrepreneurs includes an extrapolation to towns of 2,000 to 5,000 inhabitants as well. 27 INEC 2001.


beverages. In commerce, 67.9 percent of female entrepreneurs are engaged in foods and beverages, clothing, and miscellaneous small articles.

Most microentrepreneurs depend on the income they earn from the business. The vast majority (86.9 percent) operate their business as a full-time activity, and 94.3 percent say the enterprise is their sole source of income. For 67.7 percent of the families, the microenterprise constituted the principal source of family income.

Most of the microenterprises are relatively young; half of them have been started within the past five years. In particular, 28.4 percent of woman-owned businesses have been started within the past year, and 62 percent within the past five years.

Most microentrepreneurs had been economically active prior to starting their businesses, though there are significant differences between men and women. Fully 60 percent of the men had worked as laborers or salaried employees prior to initiating their businesses, compared with only 26.5 percent of the women. A large percentage of women (35.5 percent) had been engaged in housework or employed as a domestic servant prior to initiating the business. The implication is that, for women at least, a microenterprise is an opportunity for someone with only limited skills and capital to earn an income.

Most microentrepreneurs have started their businesses to be independent or earn a better income. Relatively few (9.2 percent) said they were forced into a microenterprise because they could not find other employment.

Microenterprises tend to be located in the home, and to sell products and services in the local neighborhood. Another large segment of the microenterprise population is composed of people whose businesses have no fixed location—they are street vendors or persons who move from place to place (for example, construction workers).

And finally, most microenterprises operate in the informal sector. About one-fourth of the enterprises had tax ID numbers and an equal number had municipal licenses. Less than 15 percent were enrolled in social security, and only 20 percent of the respondents kept formal financial records.

III. EMPLOYMENT 37

III. EMPLOYMENT Microenterprises in Ecuador are primarily single-person activities—almost two-thirds (64.4 percent) report that they have never had an employee or the assistance of paid or unpaid family workers, and, at the time of the survey, 69.1 percent of the surveyed respondents had no employees other than themselves. Of those who have, at one time, employed workers or family members, 12.7 percent currently have no employees and another 12.7 percent have only a part-time assistant. This chapter explores the employment impact and characteristics of the microenterprise sector in Ecuador.

EMPLOYMENT HISTORY

Male entrepreneurs (43.1 percent) were much more likely than women (26.9 percent) to have ever employed workers or assistants. In part, this is due to the difference in size of firms. Male-owned businesses tended to be larger than female-owned businesses in terms of assets and sales, and larger firms tended to hire more employees than smaller ones.

There was virtually no difference among the regions in patterns of employment history, with around 35 percent in each of the regions having employed workers or assistants at some point during the life of the business.

Microenterprises engaged in production activities were the most likely to have had employees (46.9 percent), followed by service sector enterprises (39.7 percent). Microenterprises engaged in commerce were the least likely (29.7 percent) to have employed or utilized workers. This finding is closely correlated with both the gender of the entrepreneur and the size of the business.

TABLE III-1: HISTORICAL EXPERIENCE WITH EMPLOYEES, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Has Business Ever Had Workers or

Assistants Men Women Coast Highlands Amazonia Services Production Commerce Total

Yes 43.1% 26.9% 35.6% 35.6% 35.0% 39.7% 46.9% 29.7% 35.6%No 56.9 73.1 64.4 64.4 65.0 60.3 53.1 70.3 64.4 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

IMPACT OF AGE ON EMPLOYMENT HISTORY

Business age plays a very significant role in employment. Uniformly, younger firms are less likely to have had employees, and older firms more likely to have employed workers at some stage in the life of the business. This suggests that overall employment levels in at least some businesses will rise as they mature.


TABLE III-2: BUSINESS AGE AND EMPLOYMENT EXPERIENCE

Has Business Ever Had Workers or Assistants Years in Operation Yes No Total

Less than 1 year 22.0% 78.0% 100.0% 1 year 26.6 73.4 100.0 2–5 years 34.4 65.6 100.0 6–10 years 38.4 61.6 100.0 11–15 years 42.6 57.4 100.0 Over 15 years 44.9 55.1 100.0 Total 35.9% 64.1% 100.0%

Personal age also influenced the tendency to have had employees: younger microentrepreneurs were less likely than older ones to have had employees. Very young microentrepreneurs were the least likely to have ever hired employees. Having employees increased with age through the 41–45 age group, and declined somewhat thereafter.

TABLE III-3: ENTREPRENEUR AGE AND EMPLOYMENT EXPERIENCE

Has Business Ever Had Workers or Assistants Age Group Yes No Total

12 to 17 14.2% 85.8% 100.0% 18 to 25 26.3 73.7 100.0 26 to 30 30.0 70.0 100.0 31 to 35 35.6 64.4 100.0 36 to 40 39.2 60.8 100.0 41 to 45 39.3 60.7 100.0 46 to 50 39.2 60.8 100.0 51 to 55 36.2 63.8 100.0 56 to 60 35.1 64.9 100.0 Over 60 35.8 64.2 100.0 Total 35.5% 64.5% 100.0%

These findings are consistent with expectations. Businesses tend to add employees as they succeed and grow over time, and older microentrepreneurs have generally had their businesses longer than younger ones.

III. EMPLOYMENT 39

CURRENT EMPLOYMENT PATTERNS

At the time of the survey, microenterprises were predominantly single-person firms—providing employment only for the owner.28 As can be seen in the following table (Table III-4), 69.1 percent of the firms had no employees other than the owner, while 17.6 percent provided employment for the owner plus one additional worker. Less than 1 percent of the enterprises hired more than five workers in addition to the owner.

TABLE III-4: NUMBER OF EMPLOYEES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Current

Number of Employees Men Women Coast Highlands Amazonía Services Production Commerce

Total

Only the owner 62.8% 76.4% 69.2% 68.8% 67.7% 64.5% 61.5% 73.8% 69.1% 1 19.3 15.6 17.8 17.2 16.9 18.8 17.4 17.1 17.6 2 9.7 5.2 7.6 7.5 8.7 9.6 10.2 5.7 7.6 3 4.0 1.5 2.6 3.2 3.4 3.7 4.5 1.8 2.8 4 1.9 0.8 1.3 1.4 1.8 1.9 2.8 0.6 1.4 5 1.1 0.2 0.6 0.9 0.7 0.5 1.6 0.5 0.7 6 0.5 0.1 0.2 0.4 0.5 0.3 0.8 0.1 0.3 7 0.4 0.1 0.3 0.3 0.2 0.3 0.5 0.1 0.3 8 0.2 0.1 0.2 0.1 0.1 0.2 0.2 0.2 0.2 9 0.1 0.1 0.1 0.1 0.0 0.1 0.3 0.1 0.1

10 or more 0.1 0.0 0.0 0.1 0.1 0.1 0.2 0.0 0.1 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Again, women were clearly less likely to have employees, and firms in the commerce sector were less likely to hire employees than those in the other two sectors.

The results of this pattern of employment can be seen more clearly in the following table (Table III-5). Of the businesses that do hire at least one worker or assistant in addition to the owner, male-owned businesses hire an average of 1.85 workers or assistants per firm, while those owned by women hire an average of 1.44 workers or assistants per firm.

Businesses on the coast tend to be smaller—have fewer workers—than those in the highlands or Amazonía. This could be because of the younger age of firms on the coast, or because more women are engaged in microenterprises on the coast.

As can be expected, of the businesses with employees, those in the production sector have the highest average number of workers per firm; those in commerce have the lowest average number of employees. Production activities frequently require assistance, while commerce and many services can more easily be performed alone.

28 These numbers may understate the involvement of nonpaid family labor—especially children—in the

businesses, because the respondents may have considered only paid assistants in spite of instructions to include nonpaid family members in their reporting of workers.


TABLE III-5: AVERAGE NUMBER OF EMPLOYEES PER FIRM, BY GENDER, REGION, AND ECONOMIC SECTOR


Men Women Coast Highlands Amazonía Services Production Commerce Overall

Average number of employees per firm 1.85 1.44 1.65 1.81 1.81 1.75 2.08 1.48 1.70

GENDER AND EMPLOYMENT

Gender has a strong influence on employment patterns in microenterprises. As mentioned earlier, female microentrepreneurs were less likely to have ever had workers or assistants than male microentrepreneurs, and women have fewer average employees per firm. But there are other gender patterns as well.

As can be seen in Table III-6, female entrepreneurs who have employees are less likely to hire full-time employees than men, averaging 1.11 full-time employees per firm, compared with an average of 1.6 full-time employees in male-owned businesses.

TABLE III-6: AVERAGE EMPLOYMENT PER FIRM, BY GENDER

Averages per Firm That Has Employees or Assistants

Male-Owned Businesses

Female-Owned

Businesses Total number of employees 1.85 1.44

Number of full-time employees 1.60 1.11 Number of part-time employees 0.25 0.32

Number of male employees 1.27 0.64 Number of female employees 0.59 0.80

Number of relatives employed 1.01 1.04 Number of nonrelatives employed 0.85 0.40

Number of male relatives employed 0.55 0.48 Number of male nonrelatives employed 0.72 0.15

Number of female relatives employed 0.46 0.55

Number of female nonrelatives employed 0.13 0.25

Men have a tendency to hire men, while women have a tendency to hire women. Men, on average, hired twice as many men as they did women. The ratio was not as extreme in the case of woman-owned businesses, but women tended to hire more women than men.

Both men and women have a tendency to hire relatives, but men are more likely to hire nonrelatives that are women.

Perhaps most notable in the data is that women tend not to hire male workers who are not relatives, and men are unlikely to hire female workers who are not relatives.

III. EMPLOYMENT 41

SIZE OF FIRM BY SECTOR

It must be remembered that 64.4 percent of all microenterprises in Ecuador have never had employees. Of those that do have employees, firms in the commerce and transportation sector have the smallest average number of employees per firm (Table III-7). Firms in the production sector are generally the largest.

TABLE III-7: AVERAGE EMPLOYMENT PER FIRM, BY SUBSECTOR 95% Confidence Interval

Economic Subsector Average per Firm Lower Upper

Personal services 1.82 1.56 2.07 Hotels, bars, and restaurants 1.80 1.70 1.90 Vehicle repairs 1.78 1.66 1.91 Construction 2.37 2.02 2.71 Transportation 1.38 1.24 1.52 Textiles and clothing 2.13 1.89 2.37 Wood products 1.95 1.76 2.13 Paper products 2.11 1.62 2.60 Metal products 2.16 1.90 2.41 Chemicals and construction materials 2.64 2.11 3.17

Food products 1.76 1.58 1.94 Commerce 1.48 1.43 1.54

The confidence intervals indicate that, according to the distribution of firms in the survey sample, 95 percent of all Ecuadorian businesses that have employees in those subsectors will have a number of employees (not including the owners) between the lower and upper bounds of the confidence interval.

RELATIONSHIP BETWEEN FIRM SIZE, GENDER, AND EMPLOYMENT

Recognizing that larger firms tend to hire more employees than smaller ones, and that gender influences employment patterns, it is not surprising to find that size of firm and gender strongly influence the tendency of microentrepreneurs to provide employment to women.

To gauge the size of the firms, they are divided into quintiles based on invested assets. Other measures could have been used, but assets provided a good discrimination among the firms. The study divided the firms by the gender of the owner, and then calculated the number and percentage of firms in each quintile that had employees, the number of employees in those firms, and the percentage of employees who were women.

The results were strong and consistent (see Table III-8). Larger firms, whether owned by men or women, were more likely to have employees and had more employees than smaller firms. In all but the smallest 20 percent of the firms, female-owned businesses hired fewer employees than male-owned businesses. As can be seen in this table, 61.1 percent of large male-owned businesses had employees, compared with only 17.3 percent of the smallest male-owned firms. Male-owned businesses were clustered in the fourth and fifth quintiles, while female-owned businesses were clustered in the third and fourth quintiles.


The strongest relationship was between gender and size of firm and the tendency to hire female employees. In all firm-size categories, woman-owned businesses employed approximately the same percentage of women—between 53 and 60 percent of their total workforce. With male-owned businesses, women as a percentage of total employees decline significantly as the firms get larger, from 41.4 percent of the workforce in the smallest firms to 25.5 percent in the largest businesses.

TABLE III-8: GENDER, SIZE OF FIRM, AND EMPLOYMENT PATTERNS Male-Owned Businesses Female-Owned Businesses

Size of Firms (Quintiles) No. of Firms with

Employees

Percent of All Male-Owned

Firms in Quintile

Number of Employees

Percent of Employees

Who Are Women

No. of Firms with

Employees

Percent of All Female-

Owned Firms in Quintile

Number of Employees

Percent of Employees

Who Are Women

Smallest firms 7,453 17.3 8,024 41.4 7,058 15.6 7,854 56.6 Second quintile 10,807 29.4 12,881 41.5 8,054 18.4 8,219 60.8 Third quintile 15,841 42.4 20,876 37.2 11,666 24.4 12,973 56.6 Fourth quintile 23,891 51.7 35,246 33.9 11,584 36.8 14,814 54.3 Largest firms 34,177 61.1 70,030 25.5 9,329 50.8 15,700 53.5 Total 92,169 42.0 147,057 31.4 47,691 25.6 59,560 55.8

GROWTH IN EMPLOYMENT

Most of the microenterprises in Ecuador have neither added nor lost employees during their lifetime—83.6 percent had neither lost nor added employees, while 5.6 percent indicated that they had fewer employees now than when they started and 10.8 percent indicated that they now had more employees than when they started (Table III-9). This corresponds very closely to the fact that most businesses (69.1 percent) are single person firms.

Male-owned businesses displayed more volatility: more had added employees and more had lost employees compared with woman-owned businesses.

Fewer firms in Amazonía reported a decrease in employees than in the other two regions, and fewer firms on the coast reported positive increases in employment.

Commerce sector firms showed the least amount of change—fewer had either increased or lost employees since their founding. Production sector firms were the most likely to have added employees, but also the most likely to have lost them.

TABLE III-9: PATTERNS OF CHANGE IN EMPLOYMENT, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Change in

Number of Employees Men Women Coast Highlands Amazonia Services Production Commerce

Total

Negative change 7.6% 3.2% 5.5% 5.9% 3.3% 5.9% 12.0% 3.3% 5.6%No change 78.8 89.0 84.6 81.4 84.2 80.8 72.2 88.8 83.6 Positive change 13.5 7.7 9.9 12.7 12.5 13.3 15.8 8.0 10.8 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

There was no obvious pattern of employment growth at the subsector level (Table III-10). The largest percentages of firms that had added employees were found in the chemicals and construction materials, construction, metal products, paper products, and vehicle repair subsectors, while the largest percentages of firms that had lost employees were found in metal products, construction, wood

III. EMPLOYMENT 43

products, and vehicle repairs. Transportation and commerce subsectors had the smallest percentage of firms with either positive employee growth or reduction in employees.

TABLE III-10: CHANGE IN NUMBER OF EMPLOYEES, BY SUBSECTOR Change in Number of

Employees Economic Subsector Negative Change No Change Positive

Change

Total

Personal services 5.0% 83.6% 11.3% 100.0% Hotels, bars, and restaurants 4.9 78.7 16.4 100.0 Vehicle repairs 13.8 66.5 19.8 100.0 Construction 20.1 50.2 29.7 100.0 Transportation 2.2 92.1 5.8 100.0 Textiles and clothing 8.6 81.1 10.3 100.0 Wood products 18.7 63.2 18.1 100.0 Paper products 6.8 70.9 22.3 100.0 Metal products 20.5 57.0 22.5 100.0 Chemicals and construction materials 5.3 57.2 37.6 100.0

Food products 6.9 82.7 10.3 100.0

Commerce 3.3 88.8 8.0 100.0

Total 5.6% 83.6% 10.8% 100.0%

Of the 10.8 percent of the firms that had increased employment, the average number of employees added since the firm was established was only 1.74. Of those firms that had added staff:

• Male-owned firms added an average of 1.85 employees, while female-owned firms added fewer—an average of 1.52 employees.

• Firms in the highlands added an average of 1.85 employees, while those in Amazonía added an average of 1.72 and those on the coast an average of 1.68.

• Firms in production tended to add more employees than those in the other two sectors, with an average of 1.97 additional employees compared with 1.67 in the service sector and 1.64 in commerce.

MACROECONOMIC IMPLICATIONS OF MICROENTERPRISE EMPLOYMENT

Although most microenterprises are single-person firms, the urban microenterprise sector provides a significant number of jobs in Ecuador. The 646,048 enterprises represented directly by the survey provide full-time employment for an estimated 1,018,135 persons,29 including the owners.

29 The survey estimates employment in terms of full-time employment equivalents (FTEs), with part-time jobs

equal to 0.5 FTEs and full-time jobs equal to 1.0 FTEs. Since the survey did not ask questions about second or third businesses operated by the respondents, the actual number of employees may be slightly higher.


TABLE III-11: TOTAL EMPLOYMENT GENERATED BY MICROENTERPRISES IN ECUADOR

Employees per Firm (including owners) Number of Firms Estimated

Workforce

1 445,553 445,553

2 113,484 226,968

3 49,004 147,012

4 18,055 72,220

5 9,027 45,135

6 4,513 27,078

7 1,935 13,545

8 1,935 15,480

9 1,290 11,610

10 645 6,450

11 644 7,084

Totals 646,084 1,018,135

With a total estimated adult “urban” workforce of 4,166,192 as enumerated in the 2001 Census, it appears that 24.4 percent of the urban Ecuadorian workforce is engaged in microenterprise activities—either as owners or employees.


Microenterprises provide jobs for a large percentage of the urban workforce in Ecuador. The survey found that 33.5 percent of households in middle- to low-income urban areas had one or more adult family members with a microenterprise. These microenterprises provided jobs for an estimated 1,018,135 persons, or nearly 25 percent of the urban workforce. Microenterprises, therefore, represent a significant component of the urban economy.

For the vast majority of microentrepreneurs, the microenterprise is a source of self-employment. Few have ever employed additional workers or helpers, and even fewer have workers at the present time. As a result, the growth in employment that occurs in the microenterprise sector occurs with the formation of the firm. Very few microenterprises report growth in number of employees after the founding of the business.

Male-owned businesses tend to generate more employment than those owned by women. This is largely due to the fact that woman-owned businesses are more likely to operate in the home, and bringing outside workers into the home is problematic.

When they hire employees, men tend to hire men and women tend to hire women. This is largely due to the nature of the businesses and the skills required. Male-owned businesses tend to require skills that men are most familiar with and that women have little opportunity to acquire. Woman-owned businesses, apart from straight commerce and small restaurants, tend to specialize in products and services that cater to women, resulting in a greater demand for female employees.

III. EMPLOYMENT 45

Cultural factors also play a strong role in gender relationships between employers and employees. Both male and female microentrepreneurs are most likely to hire relatives, when they hire employees. This is especially true when hiring persons of the opposite sex. Male entrepreneurs are very unlikely to hire women who are not relatives, and female entrepreneurs are very unlikely to hire men who are not relatives.

These gender differences suggest strategic options for donors and microfinance institutions. Programs seeking to have a direct impact on women should focus on woman-owned businesses in the commerce sector, and programs that seek to increase employment opportunities for women should focus on woman-owned businesses in the production and services sectors—especially in textiles and clothing and small restaurants or food service. Programs that seek to have the greatest overall employment impact should focus on male-owned businesses in the production and services sectors—particularly in chemicals and construction materials, construction, textiles and clothing, and metal or paper products.

IV. SALES AND INCOME 47

IV. SALES AND INCOME There are several significant limitations on the data presented in this chapter. The most important is that there was no way to independently verify the responses to the questionnaire; therefore, this report relies solely on the responses of the microentrepreneurs. Reported sales and income suffer from many possible distortions. In most cases—lacking formal accounting records and the habit of analyzing business sales, trends, and profitability—the microentrepreneur has no basis for making an estimate.30 In other cases, the responses may also be distorted by the respondent’s perception of what the interview wants to hear, or by a desire to present himself/herself in a particular way. Some may wish to appear more successful than they really are, while others may want to appear poorer in anticipation of receiving assistance.

With a large sample, however, such as exists in this survey, extreme responses tend to be cancelled out and the overall tendencies tend to be valid. Thus, although individual responses may not be highly accurate, the general pattern of responses will be.

Also, most of the tables in this chapter deal with averages, or means, rather than distributions. Because individual responses may vary widely, measures of central tendencies (such as means) tend to provide a more valid estimate of the population.

An important consideration to keep in mind is that there are really three different kinds of businesses in the universe of microenterprises—those that are operated on a full-time basis, those that are operated on a part-time basis, and those that are recently established and whose owner is not certain if the business will be operated on a full-time or part-time basis. These businesses have different patterns of sales and income and need to be treated separately. Estimates from newly established businesses may be particularly unreliable.

SALES

AVERAGE MONTHLY SALES

Average monthly sales were calculated on the basis of the months the business is operated. Sales in part-time businesses were adjusted to reflect the months actually worked.

Businesses can either have a steady income stream or have sales that are seasonal. Respondents with seasonal businesses were asked to identify the months of average sales, high sales, and low sales, and to estimate a monthly sales figure for each type of month. These responses were then used to calculate total annual sales for the business, which were divided by 12 to obtain the average monthly sales.

As can be seen in Table IV-1, full-time businesses generally have higher average monthly sales than either part-time or recently established businesses. Full-time businesses averaged $831 per month in sales, compared with $490 per month for the businesses that were operated part-time and $420 per month for recently established businesses.

30 Surveys conducted under the GEMINI project, in which individual respondents kept detailed records of

income and expenses and were then asked their sales, income, and profitability, revealed little correlation between the values reported in response to the survey questions and the actual records kept by the entrepreneurs, although, in aggregate, the tendencies revealed by the responses correlated with overall survey results.


Male-owned businesses had, on average, significantly higher sales than woman-owned businesses. Businesses in Amazonía had higher average monthly sales than businesses in the other regions, and businesses on the coast had the lowest average monthly sales. Somewhat surprisingly, businesses in the commerce sector had significantly higher average monthly sales than those in services or production.

TABLE IV-1: AVERAGE MONTHLY SALES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector

Type of Business Men Women Coast Highlands Amazonía Services Production Commerce

Total

Full-time businesses $1,032 $568 $802 $880 $1,060 $644 $702 $966 $831 Part-time businesses 689 296 453 562 358 455 290 645 490 Recently established businesses 617 311 433 378 515 437 336 429 420

Average $995 $522 $753 $823 $979 $618 $661 $894 $778

Disaggregating the economic sectors further (Table IV-2) reveals that firms in the production subsectors of metal products (metal mecánica) and chemicals and construction materials had the highest average monthly sales, followed by those in commerce; personal services and textiles and clothing averaged the lowest.

TABLE IV-2: AVERAGE MONTHLY SALES, BY SUBSECTOR

Economic Subsector Full-Time Businesses

Part-Time Businesses New Businesses Average

Personal services $420 $1,225 $196 $406 Hotels, bars, and restaurants 711 432 476 664 Vehicle repairs 655 613 446 645 Construction 868 311 189 793 Transportation 673 313 481 651 Textiles and clothing 473 270 274 458 Wood products 766 173 469 736 Paper products 818 402 154 733 Metal products 1,169 529 1,144 1,138 Chemicals and construction materials 1,226 400 504 1,155 Food products 587 99 227 527 Commerce 966 645 429 894

GROWTH IN SALES

Ecuadorian microenterprises do not perceive sales to be improving (Table IV-3). When asked to compare current sales with last year’s sales, only 15.0 percent said their sales were greater or much greater this year, compared with 39.5 percent who said sales had decreased since the year before. This is in spite of the general recovery in the economy experienced in 2003 and 2004.

There was little difference between men and women in their perception of changes in sales, although more women than men had newly formed businesses and could not compare sales with the year before.


Microentrepreneurs on the coast were slightly more inclined to say that sales had increased, and less likely to say they had decreased than microentrepreneurs in the other two regions. Businesses in Amazonía were the most likely to say that sales had fallen significantly during the past year.

There was little sectoral difference in responses, although entrepreneurs in the production sector were more likely to say that sales had declined.

TABLE IV-3: TRENDS IN SALES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Trend in Business

Sales (2003-2004) Men Women Coast Highlands Amazonía Services Production Commerce Total

Much greater this year 2.0% 1.6% 2.1% 1.4% 1.1% 1.8% 1.6% 2.0% 1.8% Somewhat greater this year 13.2 13.1 14.5 10.5 10.3 13.5 13.6 12.9 13.2

About the same 34.1 30.2 34.3 28.5 23.8 31.8 32.8 32.4 32.3

Somewhat less this year 30.4 27.0 27.4 32.0 27.3 29.6 29.8 28.1 28.8

Much less this year 11.2 10.2 8.8 14.4 19.8 10.4 13.4 10.0 10.7 NA, started this year 7.7 16.1 11.5 11.6 16.3 11.5 7.4 13.1 11.6 Don't know, NR 1.3 1.7 1.5 1.5 1.4 1.3 1.4 1.6 1.5 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

INCOME

Average monthly income from the microenterprises averaged 39.6 percent of sales according to responses to a question on net monthly income from all sources. The average microenterprise provided about $308 in net monthly family income, or $3,696 per year (Table IV-4).31

As could be anticipated from monthly sales, net income from male-owned businesses was nearly two times that of female-owned businesses. This pattern occurred in all geographic regions. Income disparity between men and women was greatest on the coast and lowest in Amazonía, although even in Amazonía men had, on average, income from their microenterprises 1.7 times higher than that of women. This pattern was also consistent among the economic sectors, with the greatest disparity in the production sector, where men earned, on average, 2.68 times more than women from their businesses. Income disparity was lowest in the services sector, with men earning 1.6 times the average income of women in the sector.

Businesses in Amazonía averaged higher monthly net income than businesses in the other regions; businesses on the coast had the lowest average monthly net income.

Although businesses in the commerce sector had significantly higher average monthly sales than those in services or production, as could be seen in the previous section, businesses in the services sector had higher average net incomes. This is perhaps due to the fact that commerce-oriented businesses are limited to the margins between buying and selling goods, and in highly competitive

31 Estimates of per capita income for Ecuador vary widely. The United Nations Development Programme and

U.S. Central Intelligence Agency report an estimated per capita income of $3,300 to $3,400, while the World Bank estimated per capita income in 2003 at $1,790. According to the World Bank, average monthly labor income in the informal sector was $147.80 for independent workers and $122.80 for employees in 2001. Source: Fretes-Cibils, Giugale, and López-Cálix 2003, pp. 450–1.


markets these margins are limited. Service sector businesses, on the other hand, have lower materials costs, so returns are higher.

TABLE IV-4: AVERAGE NET MONTHLY INCOME FROM BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Type of Business

Men Women Coast Highlands Amazonía Services Production Commerce

OverallAverage

Full-time businesses $397 $223 $306 $357 $396 $337 $301 $324 $323 Part-time businesses 402 133 232 351 193 321 197 291 271 Recently established businesses 303 111 194 151 196 210 141 180 183

Average $391 $205 $292 $340 $372 $325 $287 $307 $308

There are substantial differences at the subsector level (Table IV-5). Businesses in textiles and clothing, personal services, and food products produced the lowest average net incomes. Businesses in metal products, chemicals and construction materials, construction, and transportation yielded the highest average monthly net incomes.

TABLE IV-5: AVERAGE NET MONTHLY INCOME, BY SUBSECTOR

Economic Subsector Full-Time Businesses

Part-Time Businesses New Businesses Overall Average

Personal services $245 $200 $131 $237 Hotels, bars, and restaurants 298 225 194 281 Vehicle repairs 353 1,049 218 356 Construction 435 262 196 413 Transportation 421 275 297 409 Textiles and clothing 218 143 100 211 Wood products 343 125 262 332 Paper products 440 337 91 403 Metal products 440 448 370 438

Chemicals and construction materials 446 334 181 423

Food products 235 94 90 213 Commerce $324 $291 $180 $307

PROFITABILITY

Profitability, calculated as net monthly income from the business divided by total monthly sales and expressed as a percentage, was directly measured from a set of questions that first asked the microentrepreneurs for their average weekly sales, and then asked what they were able to keep each week after meeting all expenses.

As can be seen in Table IV-6, there was little difference between male- and female-owned businesses in terms of profitability. There was also little difference among the respondents by region, although businesses in Amazonía were less profitable than businesses on the coast or in the highlands.


Commerce sector businesses were substantially less profitable than service sector or production sector businesses. This could be due to the fact that service and production sector businesses are based more on labor, and labor in single-person informal firms carries no explicit cost, while commerce is based on buying and selling, and profit is limited to the margin between the two.

TABLE IV-6: AVERAGE PROFITABILITY RATES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector

Type of Business Men Women Coast Highlands Amazonía Services Production Commerce

Average Profitability

Full-time businesses 48.2% 46.6% 46.9% 49.2% 45.6% 55.7% 53.6% 41.5% 47.6% Part-time businesses 60.0 53.6 56.7 57.4 45.2 56.7 60.5 55.1 56.8

Recently established businesses 48.0 43.1 45.4 43.6 40.0 52.6 50.2 40.8 44.9

Average 48.4% 46.2% 46.9% 48.8% 44.9% 55.4% 53.5% 41.6% 47.4%

What is significant about the preceding table is that part-time businesses (those that only operate during certain months) were generally more profitable than either the full-time or new businesses. This could mean that entrepreneurs operating businesses on a part-time basis are better able to control costs during slow periods and take advantage of peak seasons.

The businesses with the highest average profitability were found in the transportation, personal services, repairs, and textiles and clothing subsectors (Table IV-7). These are all businesses that primarily provide labor and have relatively low inventory and operational costs.

TABLE IV-7: AVERAGE PROFITABILITY RATES, BY SUBSECTOR

Average Profitability Full-Time Businesses

Part-Time Businesses

New Businesses Average


Food products 48.9 69.2 47.6 48.9 Commerce 41.5% 55.1% 40.8% 41.6%

RETURN ON ASSETS

When a rough measure of return on assets is calculated, taking either an annualized weekly net income or annualized monthly income from the business as a percentage of investments in assets (land, vehicles and machinery, and tools and equipment—but not inventories or improvements), the results are very different from what would be found in most situations. The results, which appear impossibly high, reflect the very low level of investment in most Ecuadorian businesses.


The overall average return on assets was 1,180.5 percent. Male-owned businesses averaged 1,237.2 percent and female-owned businesses averaged 1,082.3 percent. Businesses in Amazonía had the lowest average return on assets, with 406.8 percent, while businesses on the coast averaged a return of 1,328.8 percent. Businesses in the highlands had an average return on assets of 886.1 percent.

Commerce sector businesses averaged the highest return on assets (1,568.1 percent), service sector businesses averaged 1,032.1 percent, and production sector businesses averaged 920.8 percent. These differences are clearly highlighted at the subsector level. Transportation sector businesses had the lowest overall return on assets with 361.9 percent, reflecting the relatively high investment in vehicles required for this activity. Construction businesses and commerce oriented businesses had the highest average returns of assets, with 2,602.5 percent and 1,568.1 percent, respectively.

These figures do not indicate high income, but rather the extremely low level of investment in Ecuadorian microenterprises. Those firms with the highest average returns on assets were precisely those businesses that required little in the way of fixed asset investment—almost all investment lies in materials and inventory in the case of commerce sector businesses and in personnel in the construction businesses.

PERCEPTIONS OF INCOME

ADEQUACY OF INCOME

Ecuadorian microentrepreneurs generally feel that their businesses provide them with a decent income (Table IV-8): 47.5 percent said their income from the business was good or very good, while another 45.3 percent said it was at least average. Only 5.2 percent said the income from their business was bad.

Women expressed slightly more dissatisfaction with income than men. Fewer women said their income was good or very good, and slightly more said their income was bad. The differences were small and insignificant.

Again, regional differences were strong—microentrepreneurs on the coast are more likely to perceive the income from their business as good to very good (51.0 percent) than microentrepreneurs in either the highlands (40.9 percent) or Amazonía (37.4 percent). Microentrepreneurs in Amazonía are most likely to say they are dissatisfied with their level of income.

The economic sector apparently has little impact on perceptions of the adequacy of income; there were only minor differences in the responses from entrepreneurs in the different sectors.

TABLE IV-8: PERCEPTION OF INCOME, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Total Perception of

Adequacy of Income from the Business Men Women Coast Highlands Amazonía Services Production Commerce

Very good 6.2% 5.4% 6.2% 5.2% 5.6% 5.7% 6.1% 5.8% 5.8% Good 42.4 40.9 44.8 35.7 31.8 42.3 39.0 42.4 41.7 Average 44.7 45.9 42.8 50.2 50.4 46.0 46.3 44.5 45.3 Bad 4.7 5.8 4.2 7.1 10.2 4.0 6.6 5.3 5.2 None, or other 0.1 0.1 0.1 0.1 0.3 0.0 0.1 0.1 0.1 Don't know, NR 1.9 1.9 2.0 1.7 1.6 1.9 1.8 1.9 1.9 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


COMPARISON OF BUSINESS INCOME WITH SALARIED INCOME

Surprisingly, the microentrepreneurs feel that their businesses provide them with a better income than they could earn as salaried employees (Table IV-9): 68.7 percent said their businesses provided a better income, and only 13.9 percent said the income they earned from their businesses was less than they could earn as a paid worker.

Gender helped shape the perception of income—men were more likely than women to see the income from a microenterprise as better than they could earn from wage-earning employment. Women were slightly more inclined to say their income was about the same or worse than they could receive from wage-earning employment.

Regional patterns continued, as respondents on the coast were more likely to see income from their businesses as better than they could earn in a wage-earning position than were respondents in either of the other two regions.

TABLE IV-9: COMPARISON OF BUSINESS INCOME WITH WAGE-EARNING JOBS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Perception of Business Income Versus Salaries Men Women Coast Highlands Amazonía Services Production Commerce

Total

Better 73.4% 63.2% 70.5% 65.0% 64.5% 72.0% 68.3% 67.3% 68.7%The same 8.1 9.0 8.1 9.4 9.7 8.2 7.9 8.9 8.5 Worse 12.1 16.1 12.3 17.2 15.7 12.4 14.9 14.3 13.9 Don't know, NR 6.5 11.7 9.1 8.5 10.1 7.4 8.9 9.6 8.9 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Overall, microentrepreneurs appear satisfied with their businesses and the income they generate. Although income levels appear low, the microentrepreneurs consider their income to be adequate and better than what they could make as employees. These responses indicate, perhaps, the most important reason that microentrepreneurs choose to maintain their independent businesses.

MACROECONOMIC CONTRIBUTION OF MICROENTERPRISES

Based on responses to questions about sales and income, urban microenterprises in Ecuador have annual sales of approximately $6.03 billion and earn about $2.36 billion in net income. With a total estimated GDP of $23.5 billion,32 sales of microenterprises are approximately 25.7 percent of GDP, and net income is about 10 percent of gross domestic product (GDP). Because income levels are low, the microenterprise share of GDP is less than its share of total employment, which is estimated at 25 percent.

Another factor to consider, however, is that this survey does not cover agricultural enterprises, the rural sector in general, and microenterprises operated by professionals (doctors, lawyers, and others). If these activities were included, the total contribution of microenterprises to the national economy would be considerably larger.

32 UNICEF data for 2003.



In general, microentrepreneurs are satisfied with the income they derive from their businesses. The overwhelming majority feel their income is at least “average,” with more than half saying it is good or very good. Nearly 70 percent say their income is better than what they could receive in a wage-paying job.

At the same time, relatively few microentrepreneurs felt that sales were increasing: nearly 40 percent said that sales in 2004 were somewhat or much less than the previous year, compared with only 15 percent who said that sales had increased in 2004.

These responses suggest that most microentrepreneurs are operating in very limited and highly competitive markets. The potential for growth in sales and income in this kind of market is limited.

The average microenterprise had monthly sales of $778, which yielded an average net monthly family income of $308, or a net annual family income of $3,696. Woman-owned businesses had much lower sales and generated significantly less income than businesses owned by men. Businesses in the commerce sector generally had higher sales and generated more income than businesses in either services or production. And businesses in Amazonía generally had higher sales and produced higher income than those in the other two regions.

The information presented in this chapter has important implications for microfinance institutions. Sales and income form the basis for growing the business and for determining the amount of credit a client can reasonably absorb and service. MFIs targeting microentrepreneurs need to carefully consider the loan and payment limitations these two conditions indicate.

Based on sales and income, for example, female microentrepreneurs have a lower borrowing capacity and a more limited ability to service loans than their male counterparts. Similarly, businesses on the coast would not appear to qualify for loans as large as those in the other two regions. The differences among businesses in the various subsectors are also significant and consistent. MFIs need to take these differences into account in planning loan strategies and market expansion.

MFIs can use the data presented in this chapter as initial parameters for judging the income and profit potential of loan applicants and clients based on their gender, region, and subsector. A fuller listing of means and confidence intervals for sales, income, and profitability by occupation is available on the SALTO website.


V. PERCEPTION AND REALITY FOR MICROENTERPRISES IN ECUADOR

Microenterprises are well entrenched in Ecuador and will continue to play an important, if not vital, role in the microeconomy of lower-income sectors of the population. What happens to particular businesses, however, often depends more on intangible factors than on empirical data or trends, and the two key intangible variables are satisfaction with the business and perceptions of what the future will bring. Having a framework for understanding these less tangible attitudes can be important for a microfinance institution to better judge the success prospects of its loan clients.

REASONS FOR STARTING THE BUSINESS

Opponents of microenterprise development and microfinance have long argued that microenterprises are temporary businesses that people undertake because they lack the education or skills to find meaningful employment. This position argues that microentrepreneurs will tend to abandon their businesses when paid employment becomes available.

Why people start businesses should reveal their long-term interest in the businesses. For the overwhelming majority of microentrepreneurs in this survey, the decision to start their own businesses rather than seek salaried employment was a conscious choice (Table V-1)—rather than being forced into a self-employed business by a lack of other opportunities, the respondents deliberately chose to be self-employed. Most of the respondents chose to have a microenterprise because it allowed them to be independent or because they perceived that it offered them an opportunity to earn more than they could as a salaried employee or wage earner. Seventy-two percent of the respondents cited these as the most important reasons for choosing to start their own business. Only 10.9 percent of the survey population said they had started their businesses because they could not find a salaried job, had no other opportunity, or age limited their choices. In this sense, a decision to start a microenterprise rather than seek paid employment is an entrepreneurial decision that demonstrates a willingness to take risks to improve one’s situation.

There were strong gender differences in the reasons for starting a business. Men were much more likely to view self-employment as an opportunity to be independent than were women; 46.9 percent of the men chose to open a small business because it afforded them the opportunity to be independent, compared with 27.8 percent of the women. Slightly more women than men (36.9 percent compared with 31.6 percent) opened a business because they believed it afforded them an opportunity to earn more.

An important consideration for many women was that having their own business allowed them to combine home care with their economic activity—17.5 percent of women cited this as the main reason for starting their own business rather than seeking paid employment. Only 1.9 percent of the men cited the ability to combine home and business responsibilities as a deciding factor in choosing to start a business.

Regional differences were not strong, although women on the coast were more likely to cite the need to combine home and work than women in other parts of the country, and men on the coast were somewhat more likely to say they could not find alternative employment.


TABLE V-1: REASONS FOR STARTING THE BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Reason for Starting

Own Business Men Women Coast Highlands Amazonía Services Production CommerceTotal

To be independent 46.9% 27.8% 37.0% 40.7% 29.0% 43.0% 43.6% 33.8% 38.0% Opportunity to earn more 31.6 36.9 34.0 33.8 44.7 33.3 30.7 35.7 34.1

To combine home and work 1.9 17.5 10.1 7.1 8.2 5.7 7.9 11.1 9.1

Couldn't find a salaried job 6.0 3.7 5.5 3.7 3.1 4.7 4.5 5.2 4.9

Only thing available 4.2 4.3 4.2 4.5 5.1 4.9 3.8 4.2 4.3 To continue a family business 3.2 3.1 3.0 3.5 2.3 2.5 4.0 3.2 3.2

Because of age 1.6 1.9 2.0 1.2 0.8 1.3 1.1 2.1 1.7 Other 4.2 4.7 4.0 5.3 6.5 4.4 4.4 4.5 4.4 Don't know, NR 0.2 0.2 0.2 0.2 0.3 0.2 0.0 0.2 0.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

SATISFACTION WITH THE BUSINESS

How satisfied a person is with his or her business plays an important role in determining whether or not that person will continue with it. The survey included several questions to probe for attitudes about business satisfaction

OVERALL LEVEL OF SATISFACTION

The microentrepreneurs expressed a high level of overall satisfaction with their businesses (Table V-2). Nearly 60 percent said they were satisfied or very satisfied with their businesses, and only 6.9 percent said they were dissatisfied or very dissatisfied. The remaining 34.2 percent said they were neutral—neither satisfied nor dissatisfied.

Gender did not play a significant role in determining satisfaction; men and women were equally satisfied with their businesses.

There are major differences in business satisfaction by region, however. Microentrepreneurs on the coast are much more likely to say they are satisfied or very satisfied with their businesses than microentrepreneurs in either the highlands or Amazonía; far fewer respondents on the coast say they are unsatisfied or very unsatisfied compared with those in the highlands or Amazonía.


TABLE V-2: LEVEL OF SATISFACTION WITH BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Overall

Satisfaction with Business Men Women Coast Highlands Amazonía Services Production Commerce

Total

Very satisfied 11.6% 10.9% 12.3% 9.4% 8.0% 11.8% 10.9% 11.3% 11.3% Satisfied 48.6 46.0 51.5 39.2 38.3 47.5 46.9 47.5 47.4 More or less satisfied 32.7 35.9 30.8 40.8 42.3 34.6 34.1 34.0 34.2

Unsatisfied 6.3 6.2 4.8 9.2 9.7 5.3 7.2 6.3 6.2 Very unsatisfied 0.6 0.8 0.4 1.2 1.4 0.6 0.7 0.7 0.7 Doesn't know/NR 0.2 0.2 0.2 0.2 0.3 0.2 0.2 0.2 0.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

ADEQUACY OF INCOME

As reported in Chapter IV, Ecuadorian microentrepreneurs generally feel that their businesses provide them with a decent income: 47.5 percent said their income from the business was good or very good, while another 45.3 percent said it was at least average. Only 5.2 percent said the income from their businesses was bad.33

Women expressed slightly more dissatisfaction with income than men, but the difference was small. Regional differences, however, were strong—microentrepreneurs on the coast were more likely to perceive the income from their business as good to very good (51.0 percent) than microentrepreneurs in either the highlands (40.9 percent) or Amazonía (37.4 percent). Microentrepreneurs in Amazonía were most likely to say they were dissatisfied with their level of income. The economic sector apparently had little impact on perceptions of the adequacy of income.

COMPARISON OF BUSINESS INCOME WITH SALARIED INCOME

Consistent with perceptions of the adequacy of their income, the microentrepreneurs overwhelmingly felt that their businesses provide them with a better income than they could earn as salaried employees; fully two-thirds (68.7 percent) said their businesses provided a better income, and only 13.9 percent said the income they earned from their businesses was less than they could earn as a paid worker.34 Gender helped shape the perception of income; men were more likely than women to see the income from a microenterprise as better than they could earn from wage-earning employment. Regional patterns continued, as respondents on the coast were more likely than respondents in either of the other two regions to see income from their businesses as better than they could earn in a wage-earning position.

INDICATOR OF BUSINESS SATISFACTION

Combining and scoring the responses on satisfaction—comparison of income from the business to what they could earn as a wage-earning employee, perceived adequacy of income, and overall

33 See tables in Chapter IV. 34 See tables in Chapter IV.


satisfaction—creates an indicator of overall satisfaction. One way of doing this can be seen in Table V-3.35

Adding a respondent’s scores produces a single index of satisfaction, with the score ranging from 0 (least satisfied) to 45 (most satisfied). These scores were grouped, and then classified as very satisfied, satisfied, dissatisfied, and very dissatisfied.

TABLE V-3: NUMERIC VALUES FOR CONSTRUCTING SATISFACTION INDICATOR

How would you compare your business income with income from salaried employment?

How good is the income you earn from your business?

How satisfied are you with your business?

Score Response Score Response Score Response

10 Better 15 Very good 20 Very satisfied

5 Same 10 Good 15 Satisfied

5 Uncertain 5 Not very good 10 Neither satisfied nor dissatisfied

0 Worse 5 Uncertain 5 Dissatisfied

0 Bad 0 Very dissatisfied

As shown in Table V-4, the overwhelming majority of microentrepreneurs appear to be satisfied with their businesses—only 18.5 percent were classified as dissatisfied, and 4.9 percent were very dissatisfied. Men were somewhat more satisfied with their businesses than women. Microentrepreneurs on the coast expressed substantially greater satisfaction with their businesses than those in the other two regions. Microentrepreneurs in the production sector were somewhat less satisfied with their businesses than those in the other two sectors.

TABLE V-4: DEGREE OF SATISFACTION WITH THE MICROENTERPRISE, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Indicator of Satisfaction Men Women Coast Highlands Amazonía Services Production Commerce

Total

Very satisfied 37.4% 34.5% 39.6% 29.2% 24.9% 37.0% 33.5% 36.6% 36.1%Satisfied 41.8 39.1 40.1 41.2 44.9 41.7 42.4 39.3 40.5 Dissatisfied 16.4 20.9 16.6 22.1 22.8 17.6 18.3 18.9 18.5 Very dissatisfied 4.4 5.5 3.6 7.5 7.4 3.7 5.9 5.1 4.9 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

PERCEPTIONS OF THE FUTURE

Naturally, one would expect the positive responses reported above to also be reflected in attitudes about the businesses’ future.

35 An analyst wishing to use different scores and weights can do so with the database that is available on the

SALTO website (www.salto-ecuador.com) using questions 51, 52, and 123.


PERCEIVED FUTURE OF THE BUSINESS

The majority of microentrepreneurs are optimistic about their businesses’ future: 69.1 percent said they thought the future was good or very good (Table V-5). Another 19.9 percent said the business would stay about the same, and only 5.7 percent said things would get worse.

Gender plays little role in perception of the future of the business, although women were more likely to say the future prospects for their businesses were good to very good, and a larger percentage of men expected their future to be bad.

Regional differences continued. Respondents on the coast were more likely than respondents in the other two regions to say the future will be good or very good. Respondents in the highlands and Amazonía were much more likely to perceive the future prospects for their business as “bad.”

The sector of the economy in which the business operated appeared to have no impact on perceptions of the its future.

TABLE V-5: PERCEIVED FUTURE OF THE BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Perceived

Future of Business Men Women Coast Highlands Amazonía Services Production Commerce

Total

Very good 18.4% 19.5% 20.6% 15.3% 18.1% 18.7% 18.6% 19.1% 18.9%Good 49.4 51.2 52.5 45.6 43.1 49.1 48.1 51.4 50.2 Same as now 20.4 19.1 18.5 22.8 18.7 20.8 21.0 19.0 19.9 Bad 6.5 4.8 3.8 9.5 11.6 6.4 6.6 5.1 5.7 Uncertain, NR 5.2 5.4 4.6 6.7 8.5 5.0 5.7 5.3 5.3 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

ATTITUDE TOWARD CONTINUING THE BUSINESS

Perhaps even more illuminating are the entrepreneurs’ feelings about what they would like to do with their businesses in the future. More than 70 percent of the microentrepreneurs would like to expand their businesses and another 12.2 percent would be content to continue them as they are (Table V-6). Only 13.9 percent said they would like to abandon their current business; most of these, however, would choose to start another business rather than seek salaried employment.

Women were slightly more likely to want to expand their businesses than men. Women were also less likely to want to quit their businesses, either for a salaried position or to start a new business. This may reflect fewer economic opportunities for women.

Regional differences were not as pronounced; there were only slight differences among respondents in terms of their attitudes toward maintaining their businesses. Likewise, there were minor differences among the major economic sectors in willingness to continue a microenterprise.


TABLE V-6: JOB PREFERENCES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Preference for the

Future Men Women Coast Highlands Amazonía Services Production CommerceTotal

Quit business for employed job 3.2% 2.6% 2.3% 4.1% 3.8% 2.8% 3.3% 2.8% 2.9%

Quit business to start another 12.5 9.2 11.0 10.9 13.2 13.7 10.9 9.7 11.0

Continue business as it is 12.5 11.8 10.9 14.9 13.0 14.3 11.1 11.6 12.2 Expand this business 68.5 72.8 72.8 65.8 65.7 65.6 71.0 72.6 70.5 Don't know, NR 3.3 3.6 3.0 4.3 4.4 3.6 3.7 3.3 3.4 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

INDICATOR OF OPTIMISM

Combining and scoring the responses on optimism about the future—expectations about the business and the respondents’ commitment to continuing the business—creates an indicator of overall optimism. One way of doing this can be seen in Table V-7.36

TABLE V-7: NUMERIC VALUES FOR CONSTRUCTING OPTIMISM INDICATOR

Expectations of Business Future Personal Interest in Future

Score Response Score Response

15 Very good 15 Expand business

10 Good 10 Continue business as is

5 Same as now 5 Start different business

5 Uncertain 5 Uncertain

0 Bad 0 Seek salaried employment

Adding a respondent’s scores produces a single index of optimism, with the score ranging from 0 (least optimistic) to 30 (most satisfied). These scores were grouped, and then classified as very optimistic, optimistic, and pessimistic. As shown in Table V-8, the overwhelming majority of microentrepreneurs appear to be optimistic about the future of their businesses—nearly 60 percent were very optimistic about their businesses’ future, and only 11 percent were classified as pessimistic.

36 An analyst wishing to use different scores and weights can do so with the database that is available on the



TABLE V-8: LEVEL OF OPTIMISM, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Indicator of

Optimism Men Women Coast Highlands Amazonía Services Production Commerce Total

Very optimistic 57.3% 61.6% 63.1% 51.6% 51.3% 55.1% 59.5% 61.2% 59.3%Optimistic 30.2 29.0 27.2 34.6 34.3 31.9 28.2 29.0 29.6 Pessimistic 12.5 9.4 9.7 13.9 14.4 13.0 12.3 9.8 11.1 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

SUCCESS AND GROWTH

To test whether or not the microenterprises were successful and growing, the questionnaire included several questions that could provide an empirical (as opposed to merely perceptual) indicator of success and growth. These questions asked if the microentrepreneur had increased the number of workers or employees, moved into a better locale, improved his or her existing locale, or purchased new or improved equipment and machinery. The hypothesis was that businesses that were successful would tend to display visible signs of increased employment or improvement in either the locale or the equipment they used.

ADDING EMPLOYEES

As pointed out in Chapter III, Ecuadorian microenterprises are almost entirely single-person businesses: nearly 70 percent of the businesses provided employment only for the owner. Furthermore, only 10.8 percent had added employees since their founding, and those that had added employees had increased by an average of only 1.74 new workers. Taking employment growth as an empirical indicator of success, Ecuadorian microenterprises have not been very successful.

ACQUIRING A BETTER LOCALE

Very few (2.7 percent) of the microenterprises had moved into a new or improved locale (Table V-9). For a substantial number of microenterprises (29.6 percent of the total), acquiring improved space was not applicable given the nature of the business—moving from job site to job site, location on the street, or other.

Men showed a slightly greater tendency than women to have moved to an improved locale, but the difference was very slight. Businesses on the coast and in the commerce sector were the least likely to have moved to better locations.

TABLE V-9: BUSINESSES THAT HAVE MOVED TO AN IMPROVED LOCATION, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Has Moved to New and Better

Locale Men Women Coast Highlands Amazonía Services Production Commerce Total

Yes 2.9% 2.5% 2.2% 3.7% 3.7% 3.5% 3.1% 2.1% 2.7%No 64.0 72.1 65.7 71.8 76.3 62.3 79.4 66.3 67.8 Not applicable 33.1 25.4 32.2 24.5 20.0 34.2 17.5 31.6 29.6 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


IMPROVING AN EXISTING LOCALE

A slightly higher percentage of businesses had made improvements to their existing locales, but the total number of microentrepreneurs reporting that they had done so was still very small (Table V-10).

Women showed a slightly greater tendency than men to have made improvements in their work locations. Again, businesses on the coast were the least likely to have made such improvements. Businesses in the production sector were less likely than those in either services or commerce to have made improvements in their locales.

TABLE V-10: BUSINESSES THAT HAVE IMPROVED THEIR EXISTING LOCATION, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Has Improved Existing Locale Men Women Coast Highlands Amazonía Services Production Commerce

Total


PURCHASE OF NEW EQUIPMENT

A slightly greater number of microentrepreneurs had purchased new or better equipment during the past year (Table V-11). Nearly one-fourth of the enterprises—primarily in the services and commerce sectors—reported that they did not use equipment or machinery in their businesses.

Men showed a greater tendency to have purchased equipment or machinery. Businesses in the commerce sector were far less likely to have purchased equipment or machinery than those in either services or production. Somewhat surprisingly, businesses in the services sector were the most likely to have invested in new equipment. There were virtually no regional differences.

TABLE V-11: BUSINESSES THAT HAVE PURCHASED NEW EQUIPMENT OR MACHINERY, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Has Purchased New Equipment or

Machinery Men Women Coast Highlands Amazonía Services Production CommerceTotal


OVERALL INDICATOR OF SUCCESS

Combining and scoring the responses on the various empirical measures of growth37 creates an overall indicator of success. One way of doing this can be seen in Table V-12.38

37 Respondents were scored on the basis of number of jobs added, acquiring an improved location, improving

their existing location, and acquiring tools and equipment. 38 An analyst wishing to use different scores and weights can do so with the database that is available on the



TABLE V-12: NUMERIC VALUES FOR CONSTRUCTING GROWTH INDICATOR

Change in Number of Employees Physical Investment to Improve Business (new locale, improved locale, purchase of equipment or

machinery)

Score Employees Added Score Response

20 More than 7.5

15 5.1 to 7.5

10 2.6 to 5.0

10 Yes

5 .6 to 2.5

0 0 to .5

-5 Reduced employment

0 No

Adding a respondent’s scores produces a single index of growth, with the score ranging from -5 (negative growth) to 40 (highest growth). These scores were grouped, and then classified as high growth, moderate growth, low growth, no growth, and negative growth.

As can be seen in Table V-13, the vast majority of microenterprises (82.3 percent) exhibited no growth. Only 12.8 percent of the microenterprises showed any growth at all, and most of these exhibited low growth.

TABLE V-13: DISTRIBUTION OF MICROENTREPRENEURS BY GROWTH INDICATOR, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Indicator of Growth Men Women Coast Highlands Amazonía Services Production Commerce

Total

High growth 0.8% 0.6% 0.5% 1.0% 0.6% 1.1% 0.7% 0.4% 0.7%Moderate growth 2.3 2.0 2.0 2.4 2.7 2.5 2.4 1.9 2.1 Low growth 10.8 9.1 9.1 11.6 13.1 12.4 11.7 8.2 10.0 No growth 79.7 85.3 83.4 80.0 80.5 79.2 74.9 86.3 82.3 Negative growth 6.5 3.1 4.9 5.1 3.1 4.8 10.2 3.2 4.9 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

There were minor differences in growth by gender, region, and sector. Male-owned businesses showed slightly more growth than those owned by women (though also more cases of negative growth). Businesses on the coast displayed slightly less growth than those in the other two regions. Businesses in the production sector were more likely to exhibit negative growth than those in either services or commerce.

CONCLUSIONS AND IMPLICATIONS

Ecuadorian microentrepreneurs are generally satisfied with their businesses and are committed to being microentrepreneurs. There is little indication that they were forced to become


microentrepreneurs because of a lack of other opportunities; the overwhelming majority of microentrepreneurs chose to start their own businesses because of a desire for greater independence or because they perceived an opportunity to earn more. There is also little indication that they would abandon their enterprises to seek salaried employment. Furthermore, most entrepreneurs would like to see their businesses grow rather than change employment or remain as they are. As a result, microenterprises appear to represent a stable segment of the economy rather than a temporary or transitional one.

This combination of commitment to working independently and desire to grow the business is important for MFIs contemplating loans to microentrepreneurs. Borrowers who have strongly positive feelings about their businesses, are optimistic about the future, and are committed to seeing their businesses grow are probably better credit risks than those who formed a business because of a lack of opportunities, are pessimistic about the future, and would prefer to have salaried employment. The large number of entrepreneurs who say they would like to see their businesses grow suggests that MFIs have a potentially large market in financing growing business activities.

However, even though the respondents expressed high levels of satisfaction and optimism, very few microenterprises demonstrated the kind of improvements or growth that one would associate with a successful or growing business. This apparent contradiction needs to be carefully considered by MFIs seeking to expand their microfinance portfolios—the absence of growth indications could signify a stagnant sector with few prospects for growth in the absence of other fundamental changes in the microenterprises and their markets. The apparent lack of growth makes it important for the government and donors to learn more about the constraints that microenterprises face and to develop more effective strategies to deal with these constraints. Understanding these issues requires more in-depth analysis than can be provided by this broad survey; it would probably require a subsector-by-subsector approach.

VI. MAJOR BUSINESS PROBLEMS AND NEEDS 65

VI. MAJOR BUSINESS PROBLEMS AND NEEDS Credit, training, and technical assistance are tools to address problems; however, not all problems can be addressed by any one of these tools. The extent to which a microentrepreneur will respond to offers of credit, training, or technical assistance will depend on his or her perception of the problems he or she faces and the appropriateness of the tool to resolving that problem. It is therefore important for donors, the Government of Ecuador, and MFIs to understand the problems microentrepreneurs face, their perceptions of those problems, and the “goodness of fit” between the services offered and the problems as perceived by the microentrepreneur.

MAJOR PERCEIVED PROBLEMS

OVERVIEW

Survey respondents were asked what they considered to be the two major problems they faced in trying to operate their businesses. A substantial number—22.5 percent—said they faced no major problems at all (Table VI-1). Of those who did respond, most of the problems mentioned fell into two general categories—market conditions and financial problems. Market problems and competition were mentioned by 63.8 percent of those who mentioned at least one problem as either the most important problem or as the second most important problem. Financial problems were much less significant to the respondents; only 36.7 percent of those respondents who mentioned at least one problem gave a response that could be classified as indicating a problem with finances—either as the most important or as the second most important problem they faced.

TABLE VI-1: TWO MOST IMPORTANT PROBLEMS FACED BY MICROENTREPRENEURS

Types of Problems Most Important

Second Most Important Total %

Markets and competition 174,221 53,575 227,796 63.8 Financial 94,869 36,094 130,963 36.7 Location and facilities 20,624 13,535 34,159 9.6 Inputs and supplies 13,410 12,091 25,501 7.1 Machinery and tools 8,579 6,499 15,078 4.2 Authorities and rules 8,680 4,469 13,149 3.7 Transportation 4,338 2,751 7,089 2.0 Urban infrastructure 1,936 1,405 3,341 0.9 Personnel 1,143 1,444 2,587 0.7 Technical and management 966 535 1,501 0.4 Other 28,510 14,940 43,450 12.2 Total 357,276 147,338 504,614


An analysis of the number of respondents who say they faced no major problems and the first, or most important, problem cited by those who do have a problem reveals significant gender, regional, and sectoral differences in the perceptions of problems faced by microentrepreneurs in the country.


Men perceived greater problems with markets and competition than did women; female entrepreneurs perceived more financial problems than did men (Table VI-2). At first, the high level of “finance-related” problems would appear counterintuitive because many, if not most, of the MFIs operating in Ecuador target female entrepreneurs with financial services. However, a problem with finance does not mean “absence of credit.” Anecdotal information gathered during the interviews suggests that woman-owned businesses tended to occupy specialized or narrow market niches in which there was little or no competition—even in activities that overall experience a great deal of competition. One woman, who prepared lunches for sale, reported having no competition. The reason was that she only sold those lunches to work crews from her neighborhood who were engaged on construction projects: it was a pre-arranged commitment, and no one else competed for that business.

Microentrepreneurs on the coast were much more likely than their counterparts in either the highlands or Amazonía to say that they did not face any major problems. Coastal microentrepreneurs were also much less likely to see markets and competition as a major problem than microentrepreneurs in either the highlands or Amazonía, and were more likely to say they faced problems with financing. Microentrepreneurs in the highlands perceived a much greater problem with markets and competition than microentrepreneurs in either of the other two regions.

Microentrepreneurs in the services sector perceived greater problems with markets and competition than those in production or commerce. Somewhat surprisingly, those in commerce were the least likely to mention markets and competition as their main problem, and perceived a much greater problem with finances than their counterparts in the other sectors. Again, this high level of “finance-related” problems appears counterintuitive because many, if not most, of the MFIs operating in Ecuador target the commerce sector for financial services, but finance does not necessarily mean credit.

TABLE VI-2: MOST IMPORTANT PROBLEM FACED, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector

Most Important Problem Men Women Coast Highlands Amazonía Services Production Commerce

Total

None 21.8% 23.4% 26.7% 14.1% 16.0% 24.3% 20.0% 22.6% 22.5%Markets and competition 39.8 35.4 30.7 52.4 44.5 40.8 39.2 35.9 37.8 Financial 18.3 23.2 24.0 13.8 11.8 12.7 18.9 24.8 20.6 Location and facilities 4.0 5.0 4.3 4.9 4.3 6.4 4.6 3.5 4.5 Inputs and supplies 3.0 2.8 2.4 3.9 4.8 1.8 3.6 3.2 2.9 Machinery and tools 2.3 1.3 2.0 1.6 1.6 3.0 4.3 0.5 1.9 Authorities and rules 2.5 1.1 2.1 1.4 1.4 2.4 1.0 1.9 1.9 Transportation 1.3 0.5 1.0 0.8 0.6 1.4 0.7 0.8 0.9 Urban infrastructure 0.5 0.4 0.5 0.3 1.7 0.5 0.6 0.3 0.4 Technical and management 0.2 0.2 0.2 0.3 0.5 0.3 0.3 0.1 0.2 Personnel 0.2 0.3 0.1 0.5 0.5 0.3 0.7 0.1 0.2 Other 6.1 6.3 6.1 6.0 12.4 6.0 6.2 6.3 6.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

MARKETS AND COMPETITION

Disaggregate the individual responses to the broad question on key problems provides a better idea of the specific types of problems the respondents encountered. Of those who mentioned markets and competition as their main problem, most (75 percent) said that they faced too much competition—that


there were too many vendors of similar products in the market (Table VI-3). The second problem they perceived was little demand—there were too few buyers in the crowded marketplace.

The perceptions were similar for men and women and for entrepreneurs in all three regions, with very little variation.

There were some differences among entrepreneurs in the different economic sectors. Entrepreneurs in the production sector perceived a greater problem with limited demand and a greater problem with the availability of cheaper competing products than entrepreneurs in the other two sectors. The inflow of manufactured goods—especially housewares and toys—from countries like China has increased competition for enterprises that produce low-quality competing goods domestically. As one entrepreneur who made traditional dolls put it, “How can I compete with Chinese-made dolls that only cost a dollar in the local markets, and they even talk?” Production sector enterprises faced more problems of competing imports and less of a problem with too many competitors than did entrepreneurs in the other two sectors.

Entrepreneurs in the commerce sector perceived the greatest amount of competition from having too many competing vendors. This is to be expected, since the low barriers to entry in petty commerce (low initial investment and minimal skills requirements) mean that this is usually the first economic activity of people entering the informal economy.

TABLE VI-3: MAJOR MARKETS AND COMPETITION PROBLEMS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Main Problem for the Business, First Reply Men Women Coast Highlands Amazonía Services Production Commerce

Total

Too much competition, many competing vendors and products

75.1% 74.8% 74.0% 76.1% 74.4% 75.7% 61.8% 79.6% 75.0%

Little demand, few clients 18.9 21.9 21.8 18.0 22.3 19.9 28.7 17.0 20.2 Cheaper competing products 3.5 1.9 2.2 3.5 1.6 2.8 5.9 1.6 2.8

Local manufactured products 0.2 0.1 0.2 0.1 0.0 0.0 0.0 0.2 0.1

Other marketing problems 2.4 1.4 1.8 2.2 1.8 1.6 3.5 1.6 2.0 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

It must be noted that neither of the major market-related problems—too much competition or too few customers—can be addressed effectively through increased use of credit. In fact, increasing the supply of credit in a market that is highly competitive or saturated could have negative consequences in terms of prices and the ability to sell goods.

The dollarization of the economy39 has affected both the production and commerce sectors. Producers experience greater competition as foreign-made goods become more price-competitive. Commerce vendors are affected in that goods they sell are not as attractive in cross-border trade. Vendors on both the northern and southern borders of Ecuador (with Colombia and Peru) experienced significant declines in sales as Ecuadorian products became more costly. A substantial number of stalls in major markets in the border towns closed because of the reduction in cross-border trade.

39 Ecuador dollarized its economy in 2000 in response to the banking and financial crisis of 1999–2000.


FINANCIAL PROBLEMS

Lack of funds to finance investment or ongoing business operations was overwhelmingly the main financial problem reported by microentrepreneurs (Table VI-4). This could indicate either that the businesses are not capable of generating sufficient income and profits to finance growth and expansion, or that the lack of financing (specifically credit) is a major constraint. There are several indicators, however, that the financial problem faced by microentrepreneurs lies more with sales and profits and less with a lack of access to credit.

First, difficulty in obtaining credit was mentioned as a first or second major problem by only 23.7 percent of the respondents (12.3 percent said that lack of access to credit was the main problem and 11.4 percent said that lack of access to credit was the second major problem they faced). Second, for those who cited a lack of funds for investment or operations as the main problem, the second problem most frequently cited related to competition and markets, not to a lack of credit—48.6 percent cited excessive competition with many similar competing products or little demand and too few clients as the second principal problem they faced. Lack of credit was mentioned as the second problem by only 1.5 percent of the respondents who reported lack of funds for investment and operations as the primary problem.

Inability to access credit was mentioned as a problem more by men than women,40 and was perceived to be a greater problem on the coast than in the highlands or Amazonía. Entrepreneurs in the commerce sector perceived less of a problem obtaining credit than those in either services or production, perhaps because many microfinance programs target the commerce sector.

The problem of having to extend credit to clients affects female entrepreneurs more than men. This seems to be more of a problem in Amazonía and the highlands than on the coast and it affects those in commerce much more than those in either production or services.

TABLE VI-4: MAJOR FINANCING PROBLEMS FACED, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Main Problem for the

Business Men Women Coast Highlands Amazonía Services Production CommerceTotal

Lack of funds for investment or operations

80.1% 81.9% 81.0% 81.5% 75.9% 81.2% 81.7% 80.8% 81.0%

Can't obtain credit 13.8 9.2 12.9 6.1 7.8 13.0 13.7 10.4 11.4 Has to extend credit to client 3.3 6.9 4.8 6.5 12.1 1.6 2.0 6.9 5.2

Profits or profit margin is low 0.8 0.9 0.5 2.2 1.3 0.7 1.2 0.8 0.8

Interest rates are very high 0.1 0.0 0.1 0.1 0.6 0.0 0.1 0.1 0.1

Other financial problems 2.0 1.1 0.9 3.7 2.4 3.6 1.3 1.0 1.5 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Lack of funds may be a serious constraint to business success for Ecuador’s microentrepreneurs, but answers to the questions about their major problems suggest that the problem lies more with the

40 These responses do not reveal if the inability to access credit is a perception on the part of the entrepreneurs

or actually the result of being denied credit. One hypothesis might be that, with the focus of many donors and MFIs on providing credit to women, women do not face the same problems in accessing credit that men do.


inability to generate sufficient revenues and profitability from the business than with a lack of access to credit.

DEMAND AND COMPETITION

PERCEPTIONS ABOUT DEMAND

The interviewees were asked about their perception of demand for their products and services (Table VI-5). Overall they tended to be surprisingly positive in their responses. Women tended to be a bit more optimistic about their ability to sell more: 67.7 compared with 63.7 percent for men. Microentrepreneurs in the coastal region were markedly more optimistic regarding their ability to sell more: 72.3 percent compared to 52.3 percent in the highlands and only 47.8 in Amazonía.

TABLE VI-5: PERCEPTION OF DEMAND FOR PRODUCTS, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector

Perception of Demand Men Women Coast Highlands Amazonía Services Production

Commerce Commerce Total

Could sell a lot more 46.3% 49.7% 53.2% 37.4% 33.2% 41.9% 50.0% 49.9% 47.9% Could sell a little more 17.4 18.0 19.1 14.9 14.6 16.4 16.4 18.7 17.7 Could not sell more, market is small 30.6 29.4 23.6 42.8 46.0 32.4 29.6 29.1 30.0

Other 1.1 0.5 0.7 1.0 1.2 1.6 0.9 0.4 0.8 Don't know, NR 4.6 2.5 3.4 3.9 5.1 7.7 3.2 1.9 3.6 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Microentrepreneurs in commerce tended to be most optimistic (68.6 percent) compared with those in production (66.4 percent) and services (58.3 percent). This result was somewhat unexpected. Generally, it would be expected that ease of entry would be greatest in commerce, so that firms might be more easily started and/or expanded. Therefore, it would be logical to expect that supplies might exceed local demand more quickly for commerce than for the other two sectors.

DIFFICULTIES IN SALES

Given the results reported above, the expected opposite responses were obtained to the question about difficulties in selling (Table VI-6). Just over 30 percent of both men and women reported having difficulty in selling their products. The results varied by region: 27.6 percent on the coast, 39.5 percent in the highlands, and 44.7 percent in Amazonía reported difficulty. Enterprises in the production sector tended to report more difficulty than those in commerce or services.

TABLE VI-6: WHETHER OR NOT THE MICROENTREPRENEUR HAS DIFFICULTY SELLING, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Has Difficulty Selling Product Men Women Coast Highlands Amazonía Services Production

Commerce Commerce Total

Yes 32.8% 30.4% 27.6% 39.5% 44.7% 32.4% 36.2% 29.8% 31.7% No 66.0 68.2 71.3 58.6 54.5 66.5 62.5 68.8 67.0 Don't know, NR 1.2 1.4 1.1 1.9 0.9 1.1 1.3 1.5 1.3 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


INTENSITY AND TRENDS IN COMPETITION

In spite of their optimism about sales, most microentrepreneurs report high levels of competition (Table VI-7). Fifty-nine percent of the women reported a lot of competition, compared with 66 percent of the men. The perception of competition is highest in the highlands and in Amazonía— about 70 percent reported a lot, compared with less than 60 percent on the coast. There is not a great deal of difference in reported levels of competition by sector.

TABLE VI-7: PERCEPTION OF COMPETITION, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Intensity of

Competition Men Women Coast Highlands Amazonía Services Production CommerceTotal

A lot 66.1% 59.2% 58.7% 71.5% 68.8% 63.2% 60.0% 63.8% 62.9% A little 31.6 37.9 38.8 26.0 27.4 34.3 37.3 33.7 34.6 Don’t know, NR 2.3 2.8 2.5 2.5 3.8 2.5 2.7 2.5 2.5 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

The interviewees were also asked for their views about the trends in competition and the results followed the same pattern as the responses to the question above (Table VI-8). Men were more likely than women to believe that competition had increased. Microentrepreneurs on the coast were less likely (35 percent) to think that competition had increased than those in the highlands and in Amazonía (51 percent). There were not large differences by economic sector.

TABLE VI-8: PERCEPTION OF TRENDS IN COMPETITION, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Trend in

Competition During the Past 12 Months Men Women Coast Highlands Amazonía Services Production Commerce

Total

Has increased 43.7% 37.3% 35.4% 51.4% 51.2% 41.9% 39.3% 40.7% 40.7%Stayed the same 37.5 38.7 42.6 29.2 27.8 36.7 40.6 37.9 38.1 Has decreased 12.1 10.5 12.1 10.1 7.9 11.6 12.8 10.8 11.4 NA, Business less than 1 year old 5.3 11.7 8.5 7.6 10.7 8.1 5.6 9.3 8.3

Don't know, NR 1.3 1.7 1.4 1.7 2.5 1.6 1.8 1.4 1.5 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

MAIN COMPETITORS

The main competitors for microentrepreneurs in Ecuador are other microentrepreneurs—microenterprises and street vendors (Table VI-9). Medium and large businesses do not appear to compete in the same markets as microentrepreneurs.

Somewhat surprisingly, especially considering complaints about cheap foreign goods, legal and contraband imports were not seen as major competition. The majority of microenterprises, however, tend to occupy specialized niche markets that may be insulated from excessive competition from imports. Vendors in the commerce sector are perhaps the most insulated because they can shift goods easily to respond to changing demands—the source of goods is not particularly important. Services are also insulated from foreign competition because they operate almost exclusively within the local economy. Producers, on the other hand, do face competition from competing imported goods.


TABLE VI-9: PRINCIPAL COMPETITORS

Main Competitors First Response

Second Response

Third Response

Total Responses %

Other microenterprises 381,905 0 0 381,905 82.8 Street sellers 32,511 51,448 6,868 90,827 19.7 Medium or large businesses 22,477 25,563 0 48,040 10.4 Contraband 4,976 6,434 1,738 13,148 2.9 Other 7,564 3,021 281 10,866 2.4 Legitimate importers 3,983 5,092 1,637 10,712 2.3 Cachineros 363 1,158 791 2,312 0.5 Don't know, NR 7,402 118 41 7,561 1.6 Total 461,181 92,834 11,356 565,371 122.6

MICROENTERPRISES AND THE FREE TRADE AGREEMENT41

Most microenterprises will not be directly affected by the new free trade agreement. For the most part, microenterprises operate in the local economy, with few imported inputs and few exports.

IMPACT ON INPUTS AND SUPPLIES

Microenterprises in the commerce sector—which accounts for 55 percent of all urban microenterprises—are quick to adopt new products and may actually benefit from the greater availability of goods for sale and reduced cost of merchandise if freer trade provides a more abundant supply of less expensive imported goods.

Microenterprises in the services sector could also benefit from a wider range of products available for use in their businesses. They also may benefit from lower prices on imported inputs.

Production sector businesses may benefit from greater access to higher-quality inputs at lower cost as the result of reduced trade barriers to imports.

IMPACT ON SALES

Cheaper imported goods could well have a negative impact on the sales businesses in the production sector; consumers and microenterprises in the commerce and services sectors are able to purchase imported goods at lower cost. Particularly vulnerable are traditional handicraft industries and lower-end household goods and products. The low-quality goods produced by many Ecuadorian microenterprises may face significantly increased competition as a result of free trade liberalization.

Microenterprises in the service sector should feel few negative effects from the free trade agreement because services cannot be easily imported. The increase in imported goods that is likely to result from the liberalized trade regime will not constitute competition to this sector.

The commerce sector will not experience an increase in competition as a direct impact of trade liberalization—vendors will merely have a wider range of products to sell. However, the wider range of consumer products available through import houses may exacerbate the current tendency toward

41 Tratado de Libre Comercio, or TLC.


expansion of malls and large outlets at the expense of small specialized vendors in the larger cities and towns. Microentrepreneurs in businesses that trade in fresh fruits and vegetables and other products that tend to not enter foreign trade will be less affected by trade liberalization.

IMPACT ON EXPORTS

Microenterprises do not participate to any significant degree in the export market. Only 0.2 percent of microenterprises sell to exporters or have goods that are exported. Although the free trade agreements will not help them, the microenterprises should also feel little negative impact in the area of exports. Expanding into export markets offers a prospect for expanding markets, but also carries increased risks and greater competition. Ecuadorian microenterprises may not have the resources and skills to enter these markets successfully.

WHAT MICROENTERPRISES NEED TO GROW AND PROSPER

PERCEPTION OF NEED

Only 82 percent of the respondents were able to identify a most important need for their businesses to grow and prosper (Table VI-10). Among those who did respond, credit for raw materials and inventory was seen as the most important need. Better space and better equipment are similar responses and, if considered together, were the second most important need. More inventory and product ranked third, followed by credit for machinery, tools, and equipment. Needs for improved management and production skills and technology were mentioned only infrequently.

Most of the responses indicate a problem with financing: the need for better equipment or space, for example, or the need for more product and inventory can be interpreted as a need for financial resources to acquire those things. Whether or not this indicates low demand and sales and a failure of the business to generate sufficient income, or the constraint of inadequate access to financial resources to take advantage of growth opportunities, is difficult to determine.


TABLE VI-10: WHAT IS MOST NEEDED TO GROW AND PROSPER Total Most Important Needs for

the Business Most

Important Second Most

Important Third Most Important Responses %

More or better equipment 31,384 10,875 3,469 45,728 12.0 More or better space 44,144 27,216 7,498 78,858 20.7 Better access to raw materials 12,757 8,785 2,554 24,096 6.3

More inventory/products 65,633 41,029 6,842 113,504 29.8 Better production technology 1,348 2,631 926 4,905 1.3

Better labor 868 1,670 676 3,214 0.8 Better packaging/ presentation 3,602 5,563 1,807 10,972 2.9

Credit for inventory, raw materials 151,388 48,056 9,513 208,957 54.9

Credit for machinery, tools, and equipment 46,591 27,386 6,447 80,424 21.1

Training 2,874 4,923 4,261 12,058 3.2 Technical assistance or advice 1,187 2,076 2,191 5,454 1.4

Pay off debt 4,224 2,252 1,513 7,989 2.1 Better promotion, increase sales force, more outlets 5,420 4,258 2,997 12,675 3.3

Transportation 9,297 5,325 1,873 16,495 4.3 Total 380,717 192,045 52,567 625,329 164.3

There are major differences in the perceived single most important need between men and women and among the economic sectors (Table VI-11). Differences among the regions are less pronounced.

Men are more likely to see a need for better equipment and for credit to improve equipment, tools and machinery than women. Women, on the other hand, are more inclined than men to see a need for more inventory or products, credit to purchase inventory and products, and more or better space.

Differences among the economic sectors are truly significant. Microentrepreneurs in commerce are much more likely to see a need for more inventory and product and to express a need for credit to purchase inventory and product than are microentrepreneurs in the other two sectors. They are also much less likely to see a need for better equipment or for credit to purchase machinery, tools, and equipment. This could partially explain why so many clients of MFIs are traders—they have a large need for relative small amounts of short-term credit that does not require significant analysis of the business.

Enterprises in the services sector are most interested in improving equipment and in obtaining credit to purchase machinery, tools, and equipment.42 Enterprises in the production sector have a more general set of needs, with particular emphasis on raw materials, space, and equipment, and credit to improve these.

42 This may be due to the high number of transportation enterprises in the services sector.


TABLE VI-11: MOST IMPORTANT BUSINESS NEED, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Most Important Need for

the Business Men Women Coast Highlands Amazonía Services Production CommerceTotal

More or better equipment 12.3% 6.0% 9.0% 10.1% 9.4% 18.3% 16.9% 2.5% 9.5% More or better space 9.3 14.1 11.2 11.9 11.7 14.1 11.3 10.3 11.5 Better access to raw materials 4.7 3.5 3.3 5.4 2.0 2.8 5.6 4.2 4.2

More inventory/products 14.0 23.1 20.1 15.1 21.3 5.7 6.7 28.2 18.1 Better production technology 0.5 0.3 0.2 0.7 0.6 0.4 1.3 0.1 0.4

Better labor 0.5 0.3 0.3 0.5 0.7 0.4 1.2 0.1 0.4 Better packaging/presentation 1.1 1.2 1.1 1.2 0.9 1.9 0.8 0.9 1.1

Credit for inventory and raw materials 32.9 39.4 36.8 34.6 34.4 19.9 31.3 45.1 35.8

Credit for machinery, tools, and equipment 14.3 6.5 11.5 9.8 10.7 21.3 16.5 3.7 10.8

Training 1.5 0.9 0.9 1.6 2.1 2.0 1.9 0.6 1.2 Technical assistance or advice 0.6 0.5 0.3 0.9 0.7 0.6 0.7 0.5 0.6

Pay off debt 1.8 1.4 0.8 2.7 2.2 3.6 1.0 0.9 1.6 Better promotion, increase sales force, more outlets 2.3 2.0 1.6 2.9 2.5 2.1 3.9 1.5 2.2

Transportation 4.2 0.9 2.8 2.6 0.8 6.9 0.8 1.4 2.7 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

In spite of the recognition that competition and demand are major constraints to growing their businesses, few microentrepreneurs expressed a need for training, technical assistance, improved technology, or better marketing—all areas for improvement that could directly address the issues of low demand and high competition.


The main problems mentioned by Ecuadorian microentrepreneurs suggest that many, if not most, operate in a highly competitive environment with relatively little growth potential. Most microentrepreneurs face an environment with numerous vendors and relatively low demand.

Donors and MFIs need to be careful about focusing on credit as a solution to these problems. Credit can help producers (and vendors) produce and sell more. Credit can also help a producer manufacture something less expensively and a vendor to lower costs of goods sold by purchasing in larger quantities. But increasing production and having a larger volume of goods to sell will not necessarily lead to higher sales, greater profit, or greater income in a saturated market. In highly competitive situations, improving product design, producing or selling in different market segments, and better marketing are often more appropriate measures for improving income than producing more or having more goods to sell. Credit in and of itself may not result in improved livelihoods for lower-income people.

The different needs and concerns of microenterprises in the different economic sectors also have implications for microfinance institutions. To the extent that the key needs are short-term in nature—


primarily inventory and raw materials—MFI product offerings that focus on short-term, rapid-turnover activities are relatively well-suited to the clients. This is particularly true with commerce sector businesses. Both services and production sector business owners expressed a need for improving the business premises, equipment, and facilities, which implies a need for larger, longer-term financing. MFIs need to be able to respond to both of these needs.

The perceptions reported about problems in obtaining credit also must be tested against the reported success rate in obtaining loans. That issue is addressed in Chapter VII.

VII. FINANCING THE MICROENTERPRISE 77

VII. FINANCING THE MICROENTERPRISE

GENERAL FINANCING PRACTICES

Two questions in the survey sought to ascertain the extent to which microentrepreneurs use credit for family and business needs. The results showed that microentrepreneurs do not customarily borrow from formal sector institutions to finance either personal or business needs, but rather rely on personal assets and the informal sector.

SOURCES OF FUNDS FOR FAMILY NEEDS

Respondents were asked how they would obtain funds to cover an urgent family need, such as a medical or other type of major emergency (Table VII-1).

Approximately 15 percent of the respondents felt they could cover such emergencies from personal sources—savings or sale of a personal asset. Most indicated they would turn to informal sources of credit—loans from family, friends, and moneylenders, or advances from clients and suppliers. Very few—only 11 percent—said they would borrow from a formal sector institution.

Women indicated that they could rely less on personal savings and sale of personal assets than men, which may indicate that women have fewer assets or savings than men. Women were also more likely to depend on family and friends as sources for financing in the case of urgent family necessities, and were less likely to borrow from moneylenders or formal credit sources.

TABLE VII-1: MAIN SOURCES OF PERSONAL FINANCE, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Source of Funds for

Urgent Family Needs Men Women Coast Highlands Amazonía Services Production CommerceTotal

Personal Sources Personal savings 11.9% 10.0% 11.5% 10.0% 10.5% 10.4% 10.1% 11.6% 11.0% Sale of animal 0.6 0.6 0.6 0.6 1.0 0.5 0.6 0.6 0.6 Sale of other asset 4.4 3.5 4.6 2.7 2.5 3.6 3.7 4.3 4.0

Informal Credit Loan from family or friends 52.0 56.0 55.9 49.8 51.7 50.6 54.6 55.2 53.9

Advance from supplier or client 0.8 0.4 0.7 0.4 0.2 0.6 1.3 0.4 0.6

Loan from moneylender 11.3 10.4 12.2 8.3 6.0 13.7 10.2 9.8 10.9

Formal Sector Credit Loan from bank/finance company 6.2 5.4 3.1 11.4 9.7 6.9 5.8 5.3 5.8

Loan from credit union 4.7 4.5 2.3 9.2 10.3 5.8 5.5 3.7 4.6 Loan from NGO, foundation 0.6 0.7 0.6 0.7 0.2 0.6 0.6 0.7 0.6

Other Other sources 2.6 3.0 2.7 2.8 4.1 3.2 2.4 2.8 2.8 Don't know, NR 4.8 5.6 5.7 4.1 3.8 4.2 5.3 5.6 5.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


Perhaps the most striking feature of these responses was the low percentage of respondents on the coast who indicated that they would access formal sector credit—only 6 percent of respondents on the coast indicated that they would obtain a loan from a formal sector institution for personal needs, compared with 21.3 percent in the highlands and 20.2 percent in Amazonía.

SOURCES OF FUNDS FOR IMMEDIATE BUSINESS FINANCE NEEDS

Respondents were then asked how they would obtain funding for an urgent business need that required immediate funds (Table VII-2). Recognizing that this would require funds from an outside source, most respondents indicated that they would secure the funds from informal credit sources: 43.0 percent said they would borrow from family or friends, and another 10.4 percent said they would get the funds from a moneylender. Only one-fourth of the respondents indicated they would get funds from formal sector microfinance institutions: 12.4 percent from banks or financieras, 8.7 percent from credit unions, and 1.4 percent from NGOs or foundations.

As in the case of funding for family needs, women were slightly less likely to secure the funds from personal sources than men. Women also were somewhat less likely to turn to external credit sources—more women than men said they would borrow from family or friends, and fewer indicated they would borrow from suppliers, moneylenders, or banks. Women were slightly more inclined to say they could obtain the funds from a credit union or NGO, suggesting that, perhaps, women perceive a greater ability or willingness to borrow from those sources.

Microentrepreneurs on the coast were less likely to obtain funds from either banks or credit unions than microentrepreneurs in either the highlands or Amazonía—probably reflecting the lower prevalence of microfinance in the coastal region. Only 11.9 percent of coastal microentrepreneurs said they would get funds from a bank or credit union, compared with 39.9 percent of those in the highlands and 36.6 percent in Amazonía.


TABLE VII-2: MAIN SOURCES OF FINANCE FOR URGENT BUSINESS NEEDS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Principal Source of Funding for Urgent

Business Need Men Women Coast Highlands Amazonía Services Production CommerceTotal

Personal Sources Personal savings 7.1% 6.3% 7.4% 5.4% 5.3% 6.6% 5.8% 7.1% 6.7% Sale of animal 0.4 0.6 0.4 0.6 0.6 0.2 0.5 0.6 0.5 Sale of other asset 2.5 1.8 2.6 1.4 1.5 2.1 2.1 2.3 2.2

Informal Credit Loan from family or friends 41.6 44.1 48.5 30.9 38.4 41.3 40.5 44.2 42.8 Advance from supplier or client 5.5 3.9 5.7 3.0 2.3 3.5 8.3 4.1 4.8

Loan from moneylender 11.0 9.7 12.2 6.7 5.2 12.5 8.7 10.0 10.4

Formal Sector Credit Loan from bank/finance company 13.3 11.4 6.9 23.7 20.2 13.6 13.1 11.6 12.4

Loan from credit union 8.5 9.0 5.0 16.2 16.4 10.1 9.7 7.7 8.7 Loan from NGO 1.0 1.9 1.2 1.8 0.1 0.9 1.6 1.6 1.4

Other Other 3.1 3.4 2.8 4.1 4.1 3.4 2.8 3.3 3.2 Don't know, NR 6.2 7.9 7.3 6.3 5.9 5.9 7.0 7.5 7.0 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

SOURCES OF FINANCE FOR BUSINESS START-UP

As can be expected, most microentrepreneurs self-finance the start of their businesses (Table VII-3). Personal resources were a principal source of start-up financing for 72.1 percent of the respondents, 10.2 percent of the respondents had received gifts from relatives and friends, 5.0 percent had used payouts from a previous salaried job, and 2.8 percent used inheritances to finance the start of their businesses. Only 0.3 percent reported that they had used money received through remittances to finance the start of their business.

A small percentage of respondents reported that they had received a loan to start the business, and most of these (18.0 percent of the respondents) had received the loan from other family members or friends. Loans from other sources were used by very few respondents to start their businesses—2.4 percent had received a loan from a moneylender, 3.4 percent from banks, 2.3 percent from credit unions, and 1.1 percent from other institutions.


TABLE VII-3: FINANCING SOURCES FOR STARTING THE BUSINESS Total Most Important Source of

Funds for Starting the Business

Most Important

Second Most

Important

Third Most Important Responses %

Personal Sources Personal savings 292,310 20,439 909 313,658 72.1 Gifts from family or friends 30,892 12,865 521 44,278 10.2 Inheritance 10,242 1,856 285 12,383 2.8 Remittances 633 389 244 1,266 0.3 Payout from salaried position 16,369 5,384 161 21,914 5.0

Lottery, other prize 359 168 7 534 0.1

Informal Credit Loans from family or friends 54,996 21,708 1,847 78,551 18.0 Moneylender 6,983 2,879 427 10,289 2.4

Formal Sector Credit Bank or finance company 11,088 3,335 452 14,875 3.4 Credit union 7,907 2,097 100 10,104 2.3 Other cooperative 455 283 88 826 0.2 NGO, foundation, etc. 3,084 703 67 3,854 0.9 Total 435,318 72,106 5,108 512,532 117.7

In terms of the most important source of funds to start the business (column 1 in Table VII-3), there are several important differences in funding sources used by microentrepreneurs. Although personal savings was the single most important source of funding for starting a business, more women than men had received money—either loans or gifts—from family and friends, and they were more likely to have received a loan from an NGO (Table VII-4). Men, on the other hand, were more likely than women to have received loans from banks or credit unions to start their businesses, or to rely on payouts from previous employment as a source of funds.

There are some differences in the financial patterns reported by region. From 5 to 6 percent of the microentrepreneurs in the highlands and Amazonía reported using loans from banks or finance companies, compared with only 1 percent of the microentrepreneurs on the coast. However, more than 4 percent on the coast reported payouts from salaried jobs, compared with less than 3 percent in the highlands and Amazonía.

These results are consistent with the pattern of financing business start-ups in other—even developed—economies: overwhelmingly, small business start-ups are self-financed. The results are also consistent with the standard lending policies of Ecuadorian microfinance institutions. Only a few MFIs will finance business start-ups; most require the business to have been in operation for at least a year before they will lend to it. This policy helps ensure that the microentrepreneurs have demonstrated the capacity to effectively manage their businesses and, therefore, manage their loan payments.


TABLE VII-4: MAJOR SOURCES OF START-UP FINANCING, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector Most Important

Source of Start-up Capital Men Women Coast Highlands Amazonía Services Production Commerce

Total

Personal savings 68.5% 65.6% 67.1% 67.4% 66.0% 65.4% 70.3% 66.8% 67.1% Gifts from family or friends 4.2 10.5 8.2 5.0 4.8 5.6 8.5 7.3 7.1

Loans from family or friends 12.3 13.0 13.2 11.5 10.2 13.1 9.3 13.6 12.6

Inheritance 2.6 2.1 2.5 2.2 1.0 2.3 3.1 2.1 2.4 Moneylender 1.6 1.6 1.6 1.5 2.2 1.8 0.9 1.8 1.6 Bank or finance company 3.0 2.0 1.3 5.0 6.4 3.8 2.3 2.0 2.5

Credit union 2.1 1.5 0.7 3.9 5.7 2.8 1.4 1.5 1.8 Other cooperative 0.0 0.2 0.1 0.1 0.2 0.1 0.1 0.1 0.1 NGO, foundation, etc. 0.2 1.3 0.7 0.7 0.6 0.4 0.2 1.0 0.7 Remittances 0.1 0.2 0.2 0.0 0.2 0.2 0.0 0.2 0.1 Payout from salaried position 5.3 2.0 4.3 2.7 2.9 4.3 3.8 3.5 3.8

Lottery, other prize 0.1 0.1 0.1 0.0 0.0 0.1 0.1 0.1 0.1 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

FINANCING CURRENT BUSINESS OPERATIONS

The microentrepreneurs were also asked about their principal sources of financing for ongoing business operations (Table VII-5). Most reported that internally generated resources from two sources —sales and savings—were the most important sources of financing for ongoing business operations. Sales were clearly the major source of funds (89.7 percent of the respondents indicated that this was the single most important source of funding for the business, and it accounted for 92.6 percent of all responses); personal resources accounted for 11.1 percent of total responses. Suppliers’ credits (5.7 percent) and advances from clients (5.1 percent) were the other two primary sources of funding. Loans from informal sources were mentioned as a principal source of funding by only 4.1 percent of the respondents, and formal sector financial resources from banks, finance companies, credit unions, cooperatives, and NGOs together were reported as being a principal source of funds by only 2.6 percent of the microentrepreneurs.


TABLE VII-5: MAJOR SOURCES FOR FINANCING DAILY BUSINESS OPERATIONS Totals Most Important Sources of

Business Funding Most

ImportantSecond

Most Important

Third Most

Important Responses %

Sales 403,159 12,311 600 416,070 92.6 Own resources, savings 18,259 30,869 957 50,085 11.1 Remittances 466 1,964 339 2,769 0.6 Family or friends 2,268 8,598 1,807 12,673 2.8 Moneylenders 1,212 3,974 814 6,000 1.3 Credit union 1,154 2,211 250 3,615 0.8 Other kind of cooperative 127 115 168 410 0.1 NGO, foundation, etc. 539 723 229 1,491 0.3 Bank or finance company 1,751 3,949 674 6,374 1.4 Suppliers’ credits 7,898 16,444 1,143 25,485 5.7 Advances from clients 12,452 9,690 873 23,015 5.1 Total 449,285 90,848 7,854 547,987 122.0

These answers do not mean that the respondents do not use credit, but rather that they do not consider credit as a primary tool for financing their businesses. The responses do suggest that business growth is largely constrained to what the businesses can generate through sales.

The responses regarding the most important source of financing—the first column in Table VII-5—indicate some important differences in financing sources (Table VII-6).

Women generally relied more on sales than men, and reported less ability to mobilize other personal resources (such as savings) to finance their businesses. Women also reported less use of credit from banks, credit unions, other cooperatives, and moneylenders than men, but a slightly greater use of funds from NGOs and foundations.

Microenterprises in the production sector were unusual in that only 84 percent reported sales as most important, while 8.1 percent reported that advances from clients were the most important source of business financing. Some production sector enterprises—such as wood and metal manufacturers and tailors—produce custom-made products for which there are few alternative uses, so they often require the customer to pay all or part of the cost in advance.

Enterprises in the services sector also reported advances as being an important source of financing.

Businesses in the commerce sector were more dependent on sales than firms in either production or services, probably because individuals with fewer resources were generally involved in commerce and had fewer personal resources to invest. More microenterprises in the commerce sector than in the other sectors made use of supplier credits to obtain merchandise for sale.


TABLE VII-6: MAJOR SOURCES FOR FINANCING DAILY BUSINESS OPERATIONS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Most Important Source of Funding

for Ongoing Business Operations


Sales 87.2% 92.6% 89.3% 90.6% 91.9% 84.6% 84.1% 93.9% 89.7%Own resources, savings 5.3 2.7 4.3 3.8 0.4 8.4 5.2 1.7 4.1

Remittances 0.0 0.2 0.1 0.1 0.0 0.1 0.0 0.1 0.1 Family or friends 0.4 0.6 0.5 0.5 0.4 0.6 0.5 0.5 0.5 Moneylenders 0.3 0.2 0.3 0.2 0.1 0.3 0.2 0.3 0.3 Credit union 0.3 0.2 0.1 0.5 0.9 0.6 0.2 0.1 0.3 Other kind of cooperative 0.1 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0

NGO, foundation, etc. 0.1 0.2 0.1 0.1 0.0 0.1 0.0 0.2 0.1 Bank or finance company 0.5 0.3 0.2 0.8 0.9 0.4 0.4 0.4 0.4

Suppliers’ credits 1.8 1.8 1.9 1.5 2.1 0.7 1.3 2.4 1.8 Advances from clients 4.1 1.2 3.1 2.0 3.4 4.1 8.1 0.4 2.8 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

REASONS FOR BORROWING FROM SPECIFIC SOURCES

The main reason for selecting a particular source for funding was that the respondent perceived that source to be the only option available to him or her (Table VII-7). This was certainly the case for drawing from personal assets—between 66 and 73 percent of the respondents who selected this response did not see any other alternative. The other principal reason for drawing from personal assets was that it was quicker.

Respondents borrowed from friends because they were perceived as the only source that would lend money, because they could respond quickly, and because the respondents had borrowed from them before. Moneylenders were chosen primarily because they were perceived as agile and rapid sources of funds, and because they were often the only sources of funds with whom the respondents had had a previous history of borrowing.

Banks were largely selected for the same reasons. Credit unions and NGOs, on the other hand, were selected because they could respond quickly, the respondents had a prior relationship with them, and they were perceived as charging lower interest rates.

Interest rates did not appear to be a particularly important consideration in selecting a loan source. Only 12.7 percent of the respondents mention interest rates as an important reason for selecting the person or institution they borrowed from.43

43 Responses to other questions about interest rates did indicate that rates are important in making decisions.


TABLE VII-7: REASONS FOR SELECTING FINANCING SOURCE Total Reason for Selecting this

Source First

Response Second

ResponseThird

Response Responses %

Only available source 191,502 0 0 191,502 45.3 More agile, rapid 133,171 38,291 0 171,462 40.6 Knows/has used source before 50,023 27,307 3,788 81,118 19.2 They're honest, trustworthy 12,197 11,990 2,411 26,598 6.3 They have a good reputation 4,812 3,734 1,775 10,321 2.4 Don't want to be indebted 8,665 4,020 635 13,320 3.2 Don't want to be indebted to family 2,791 4,178 1,576 8,545 2.0

They don't charge interest 7,289 13,602 5,959 26,850 6.4 Interest rate is low 13,803 9,661 3,204 26,668 6.3 Other 7,525 3,241 573 11,339 2.7 Don't know, NR 29,403 728 24 30,155 7.1 Total 461,181 116,752 19,944 597,878 141.4

LEVELS OF INVESTMENT

As could be expected, levels of investment in the microenterprises varied widely by gender, region, and sector (Table VII-8).

Women, in general, had much less invested in their businesses than men did—only about one-third the average investment in male-owned businesses. Average investments in businesses was much higher in Amazonía than in the other two regions. Average levels of investment were lowest on the coast.

Businesses in the services sector tended to have much higher average investment than those in thee other sectors, and commerce sector businesses had the lowest levels of investment. The low average investment in commerce was expected because of the large number of microenterprises that operate in markets or on the streets. Production sector businesses tended to invest more in tools and equipment, and businesses in the services sector had the highest average investments in vehicles and machinery—probably because of the presence of transportation businesses in the services sector. As expected, commerce sector businesses had the highest average investments in inventory, but very low levels of investment in land, vehicles, machinery, and tools.

TABLE VII-8: AVERAGE INVESTMENT IN BUSINESS, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector


Overall Average

Land $708.35 $202.81 $340.01 $735.72 $874.07 $531.03 $645.24 $386.43 $472.97Vehicles and machinery 1,886.26 262.06 743.98 1,895.11 2,230.74 2,418.67 1,225.38 501.50 1,129.50

Equipment and tools 868.41 335.50 470.11 914.65 1,182.22 904.72 1,166.00 308.49 621.21

Inventory and materials 1,237.51 862.28 842.81 1,464.32 2,732.80 332.66 615.33 1,560.98 1,065.18Improvements and furnishings 123.16 28.28 33.77 169.88 182.43 132.08 55.83 62.26 78.92

Average total Investment $4,823.70 $1,690.94 $2,430.68 $5,179.68 $7,202.28 $4,319.16 $3,707.78 $2,819.66 $3,367.78


Total investments also varied greatly by economic subsector. Some subsectors reported fairly low average levels of investment per enterprise, such as bars and restaurants ($1,280), barber shops and beauty parlors ($1,403), food and nonalcoholic beverages vendors ($1,853), shoe repair ($2,156), and tire repair ($2,976). Others reported quite high levels, such as printers ($9,513), automobile body shops ($14,893), and hotels and pensions ($40,944). Moreover, there are differences between men and women within the same subsector. For example, men reported $2,672 for investments in barbershops and beauty parlors, while women reported $1,095.

These differences comprise one of the factors that explain the entrepreneur’s choice of enterprise. Logically, there are a comparatively higher number of microenterprises in subsectors that require lower investments, and relatively fewer in those that require more capital, as shown in Chapter II. These differences in level of investment would also be expected to be reflected in the differences in the net income and profits reported by microentrepreneurs.

IMPLICATIONS FOR MFIs

One of the most important findings in the responses on business financing is that, for most microentrepreneurs, relationships with a financial institution are not viewed as a positive business strategy. Microentrepreneurs rely almost exclusively on personal savings and assets and income generated from the businesses to finance both start-ups and ongoing operations. When they perceive a need for outside financing, they turn almost exclusively to informal sources—family, friends, and money lenders. Institutions—such as banks, financieras, cooperatives, or NGOs—are not viewed as reliable or positive sources of funding.

Related to this, microentrepreneurs are conservative. They strive to avoid indebtedness, as will be shown in Chapter VIII, and do not view debt as a positive tool in their business strategy. They do not perceive a positive benefit from being in debt and do not understand how to incorporate debt into a positive business strategy. However, it is precisely this conservative position that protects microentrepreneurs in an uncertain economic environment and that prevents them from becoming overindebted.

The problem is that, by relying only on internally generated funds, a firm’s ability to grow is limited. Ecuadorian microenterprises, in general, do not generate large cash flows. Profits, in absolute terms, are relatively low. This shortage of cash leads to the financial problems reported in Chapter VI. Expanding a business often requires more capital than it can generate internally, yet the low levels of income and profitability limit its ability to service high-cost loans.

Microfinance institutions seeking to expand their market and attract clients from the microenterprise sector need to adapt their marketing strategies to this reality. Instead of maximizing loan volumes, they need to be careful to tailor loans to the capacity of the microentrepreneurs. Instead of promoting credit as a panacea for business problems, MFIs need to better understand the conditions and dynamics of the individual firms they are working with to be able to tailor loan products and amounts to yield a positive benefit for the clients. And they need to develop the understanding among microentrepreneurs of how credit, properly used, is an effective and profitable business tool. Microentrepreneurs must understand the benefit of using external funds in practical terms in order to become successful microfinance clients.

VIII. ACCESS TO AND USE OF FINANCIAL SERVICES 87

VIII. ACCESS TO AND USE OF FINANCIAL SERVICES The microfinance system in Ecuador is composed of public sector development banks,44 private sector banks with a microfinance program, financieras (regulated financial intermediaries that have lower capital requirements and lack some of the powers of commercial banks), credit unions (regulated and unregulated), nongovernmental organizations, and a variety of informal sector arrangements. This chapter examines the use of formal sector financial services—primarily loans—by microentrepreneurs and explores the underlying factors that influence whether or not a microentrepreneur accesses such services. In particular, the chapter examines attitudes toward financial institutions, borrowing patterns, and patterns of use of other financial services. It also examines the supply of microcredit and the possibility of market saturation.

KNOWLEDGE OF AND ATTITUDES TOWARD FINANCIAL INSTITUTIONS

Knowledge and attitudes are precursors to action. Becoming a client of a financial institution is a process involving knowledge, attitudes, and action. People generally know about an institution or product, then develop attitudes about it as they learn more, and only when they have developed strong positive attitudes will they adopt the product or service. The survey included various questions to test for knowledge of financial institutions and attitudes toward them.

SPONTANEOUS RECOGNITION OF MFIs

The first step in any process of becoming a client of a financial institution is to be aware of the institution and the services that it offers.

The survey respondents were asked first if they were aware of any institution that lends money to finance microenterprises. Only about one-third (34.5 percent) of the respondents indicated that they were aware of such an institution, and nearly two-thirds (63.7 percent) said they were not. There were no significant differences between male and female respondents or among respondents from the different economic sectors. Respondents on the coast, however, were less able to identify an institution that lends money to microenterprises than were respondents in the other two regions.

Respondents who said they knew of such an institution were asked to name that institution.45 Credit unions were the most frequently named, followed by NGOs and then private banks (Table VIII-1). The large number of credit unions in Ecuador—more than 300 credit unions are registered with the Ministerio de Bienestar Social—probably accounts for the high level of awareness of credit unions.

Responses varied significantly by gender, region, and sector. Men were more likely to mention a public bank (such as the BNF or CFN), a private bank, or a credit union as institutions that lend to microenterprises, while women were much more likely than men to mention NGOs.

Microentrepreneurs in the highlands were much more likely than those in the other two regions to mention private banks and finance companies as sources of credit for microenterprises, reflecting the strong presence of institutions such as Banco Pichincha, Banco Solidario, and Sociedad Financiera

44 Institutions such as the Banco Nacional de Fomento (BNF) and Corporación Financiera Nacional (CFN)

have declined in importance due to delinquency and other financial problems and have ceased to function as retail credit outlets, though there has been a proposal to resurrect one or more of these institutions as a first-story lending facility.

45 A full list of institutions mentioned appears in Annex C.


Ecuatorial46 in this region. Credit unions are well known throughout the country as lenders to microenterprises, though particularly so on the coast and in Amazonía. NGOs are virtually unknown in Amazonía, but are well recognized as lenders to microenterprises on the coast.

Firms in the production sector were much more likely than others to mention public banks, perhaps reflecting the greater average age of firms in this sector and historical programs of subsidized credit for production that were channeled through public banks. NGOs, on the other hand, were mentioned much more frequently by those in the commerce sector, reflecting the strong orientation of most NGOs toward working with small enterprises in the commerce sector.

These responses reflect, to a great extent, the different market niches carved out by the financial institutions in Ecuador. NGOs have largely concentrated on providing services to female entrepreneurs in the commerce sector, and this is reflected in the responses.

TABLE VIII-1: SPONTANEOUS RECOGNITION OF INSTITUTIONS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Type of Institution Mentioned Men Women Coast Highlands Amazonía Services Production Commerce

Total

Public banks 14.7% 9.2% 12.7% 10.4% 27.4% 10.5% 19.6% 10.3% 12.2%Private banks 21.9 18.3 15.5 29.2 13.5 21.1 19.3 20.2 20.2 Finance companies 4.0 3.9 1.0 9.5 1.8 3.9 4.7 3.7 3.9 Mutuals 0.1 0.3 0.1 0.4 0.0 0.3 0.1 0.2 0.2 Credit unions 35.4 30.1 36.5 25.8 44.6 40.7 30.7 30.2 32.9 NGOs and foundations 16.1 29.6 26.1 16.2 5.6 15.8 18.0 26.9 22.3 Government programs 0.1 0.1 0.1 0.1 0.3 0.1 0.0 0.2 0.1 Other cooperatives 0.1 0.0 0.1 0.0 0.0 0.1 0.1 0.0 0.1 Don't know, NR 7.5 8.5 7.9 8.2 6.7 7.5 7.6 8.3 8.0 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

RECOGNITION OF SPECIFIC INSTITUTIONS

The respondents were then asked specifically if they were familiar with different types of institutions—public banks, private banks, financieras, credit unions, and NGOs. Recognition rates were higher with the direct question than with the open-ended question asked earlier (Table VIII-2); responses to the open-ended question may indicate that the respondents did not associate the institutions with microcredit.

46 Sociedad Financiera Ecuatorial has now been converted to a private bank named Banco Procrédito.


TABLE VIII-2: INSTITUTIONS MENTIONED

Type of Institution Percentage Having

Knowledge of Such an Institution

Private banks Banco de Fomento Credit unions NGOs Financieras Government program

76.9 73.4 61.6 10.2 9.4 3.1

The Banco de Fomento, private banks, and credit unions enjoyed widespread name recognition among microentrepreneurs in the country: between 60 and 77 percent of microentrepreneurs are familiar with the institutions. Financieras, NGOs, and government programs in support of microenterprises are much less visible to the microenterprise population and few respondents expressed knowledge of these institutions.

GENERAL ATTITUDES TOWARD INSTITUTIONS

Those respondents who said they were familiar with an institution were asked their opinion of the institution (Table VIII-3). A substantial percentage of the respondents expressed no opinion about the institutions.

Credit unions and NGOs enjoyed very favorable opinions among those respondents who were familiar with them.47 Banks, financieras, and the BNF received similar ratings by the respondents, and were rated significantly lower than credit unions or NGOs. Government programs received the largest negative vote.

TABLE VIII-3: GENERAL OPINION OF MAJOR INSTITUTIONS Opinion of Institution BNF Banks Financieras Credit

Unions NGOs Government Programs

Good 24.2% 29.7% 28.5% 54.4% 58.5% 34.5% Average 19.8 26.2 23.2 18.3 18.2 11.9 Bad 11.6 11.9 11.0 3.7 4.0 15.8 Don't know, NR 44.5 32.2 37.2 23.6 19.3 37.8 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

A number of institutions—credit unions, village banks, and solidarity groups—involve membership relations with the program. Members and nonmembers of these programs were asked their opinions of the institutions (Table VIII-4).

Members of all three types of institutions were equally positive about their experiences; differences in opinion emerged among the nonmembers. Credit unions received favorable opinions from a

47 Very few respondents expressed knowledge of NGOs, financieras, and government programs, so the number

of responses for these categories is small.


substantial percentage of nonmembers. Nonmembers of village banking programs indicated a general lack of knowledge about the institutions or programs involved. Nonmembers of solidarity groups were much less positive in their evaluations of such groups than were members and a large percentage gave them a bad rating; in this case it appears that nonmembers have chosen not to participate in such programs because of some negative perceptions of the programs or the methodology employed by them.

TABLE VIII-4: MEMBER AND NONMEMBER ATTITUDES TOWARD MEMBER-BASED INSTITUTIONS

Credit Union Village Banking Program Solidarity Group

Opinion of Institution Members Nonmembers Members Nonmembers Members Nonmembers

Good 76.8% 59.1% 74.8% 43.5% 74.2% 25.9%

Average 17.5 20.2 20.4 0 19.3 13.5

Bad 2.4 3.4 1.4 0 2.6 25.6

Don't know, NR 3.3 17.3 3.4 56.5 3.9 35.0 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

CREDIT

It is often assumed that there is a large unsatisfied demand for credit by microentrepreneurs, but several findings in the survey—especially regarding the low frequency of loan applications and the high success rate in getting loans—cast doubt on this assumption.

LOAN APPLICATIONS

Most microentrepreneurs reported that they had not applied for a loan during the past 12 months. This was the case for about 85 percent of both men and women. Only 15.7 percent reported applying for loans. Thirteen percent applied for one loan, 2 percent applied for two loans during the year, and less than 1 percent applied for three or more loans.

For those who applied, almost 90 percent applied to only one institution. Almost 9 percent applied to two different institutions, and 1.5 percent applied to three. Once again, the coast stands out with a larger percentage of applicants applying to only one institution. The absence of significant multiple applications suggests that Ecuador does not yet face the problems of excessive competition and overindebtedness that has plagued some countries, such as Bolivia, with extensive microfinance activities.

FACTORS INFLUENCING APPLICATION RATES

Many factors appear to be related to the patterns of loan applications encountered in the survey, including the distance the borrower had to travel to apply for a loan, gender, region, sector, and economic status.

Distance to Lender

Transaction costs can have considerable influence on a microentrepreneur’s decision to apply for a loan. Borrower transaction costs are significantly affected by the location of financial institutions. Potential borrowers cannot be expected to incur the costs and time involved in traveling multiple times to distant institutions to apply for loans, obtain and provide required documents, and make loan payments, especially when the loans are small and short-term. Transaction costs can easily approach


or even exceed the magnitude of the interest charges in these circumstances. Borrowers of larger, longer-term loans, however, accept the need to travel longer distances if necessary.

TABLE VIII-5: DISTANCE TO LENDER Kilometers from MFI Office %

0–2 66.0

2.1–5 17.0

5.1–10 9.0

No data 8.0 Total 100.0

The data in Table VIII-5 represent the distances reported between the loan applicants’ businesses or homes and the lenders’ offices. Two-thirds of the applicants were located within only two kilometers of the lender. Another 17 percent were within 2 to 5 kilometers, and only 9 percent were located as far as 5 to 10 kilometers away. These relatively short distances mean that borrowers can control their transaction costs at least as far as location of the lender is concerned.

Gender, Region, and Sector

One of the surprising results was the little difference found between men and women in the rate of application for loans (Table VIII-6). Overall, a slightly larger percentage of male microentrepreneurs applied for loans than women (16.7 percent compared with 15.0 percent). There was a significant difference in the rate of application for loans by region. Roughly a quarter of the microentrepreneurs interviewed in the highlands (25.2 percent) and Amazonía (26.0 percent) said they had applied for a loan during the past year, compared with only 11.2 percent of the microentrepreneurs on the coast. There was virtually no difference, however, in application rates among the three sectors: between 15.0 percent and 16.0 percent of the respondents in each of the sectors indicated they had applied for a loan during the past year.

TABLE VIII-6: LOAN APPLICATION RATES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector


Total

Percentage who have applied for at least one loan during the past 12 months

16.7% 15.0% 11.2% 25.2% 26.0% 16.0% 15.0% 15.9% 15.7%

Economic Status

The poverty level of the potential applicants could be expected to have an impact on application rates. On the one hand, poorer people may be more likely to apply for loans than wealthier ones because they are desperate to find ways to raise their income levels. On the other hand, many poor people live so close to subsistence levels that they are too risk-averse to borrow, which creates the risk of losing the few assets they have if their projects fail and they have difficulty in repaying.


For the analysis, the respondents were ranked into deciles by their households’ score on a basic needs indicator.48 The wealthiest 10 percent appear in the first decile and the poorest 10 percent in the tenth decile. There is a clear trend for wealthier households to apply for at least one loan compared with poorer ones (Table VIII-7). For example, almost one-quarter of the households included in the wealthiest decile applied for loans, compared with less than 10 percent for those in the poorest two deciles. It appears, therefore, that wealthier households have a greater propensity for borrowing. This may be because they have more information about financial institutions, have more experience in borrowing, and are more confident in being able to get a loan and repaying it than are poorer people.

Of particular note is the fact that poorer women were much more likely to apply for loans than poorer men. For example, 13.1 percent of the women in the poorest decile applied compared with only 6.0 percent of the men. One explanation for this sharp difference may be that the strategy of some microfinance institutions, especially NGOs, to specifically target poor women is having some success in inducing them to use credit compared with men in the same lower-income groups.

TABLE VIII-7: APPLICATION RATES, BY ECONOMIC STATUS AND GENDER

ICV Decile Men Women Total

1 (Wealthiest) 23.8% 24.5% 24.2%

2 23.4 20.9 22.2

3 22.4 20.6 21.5

4 17.2 18.9 18.0

5 16.6 16.2 16.4

6 15.7 16.8 16.2

7 10.0 12.1 11.0

8 10.9 11.7 11.3

9 7.7 11.3 9.2

10 (Poorest) 6.0 13.1 9.0 Total 15.0% 16.7% 15.8%

SUCCESS RATE IN OBTAINING LOANS

It is logical to expect that not all loan applicants will actually receive loans when they apply. Lenders reject applications when they consider the applicants to be uncreditworthy, to have insufficient collateral, or to fail in some other way to meet the lender’s loan criteria. It is often expected that the poor and women will be less likely to meet these criteria than other groups.

Another surprising result of the survey, however, was that the success rate in actually getting a loan was extremely high for those who applied (Table VIII-8). The overall success rate for those applying for loans was 97.4 percent: for those applying for one loan, it was 97.6 percent, while it was 96.1 percent for those applying for two loans and 98.4 percent for three loans. Moreover, there were essentially no differences in the success rates between men and women, across the three regions, or across the three economic sectors. Overall, 15.0 percent of the men applied and 14.8 percent were successful, implying a 98 percent success rate, and 16.7 percent of the women applied and 16.3 percent were successful, for a 97 percent success rate. Moreover, there was no evidence that the

48 This basic needs indicator, or ICV (Indicador de Condiciones de Vida), was developed initially to rank

households in the census and household surveys by their basic standard of living.


success rate was lower for entrepreneurs in poorer households compared with wealthier ones. Although poorer men were less likely to apply than women, they were just as likely to be successful when they did apply. Lack of success in borrowing, therefore, would not seem to be a significant factor in discouraging entrepreneurs from applying for loans.

TABLE VIII-8: SUCCESS RATES, BY ECONOMIC STATUS AND GENDER

Men Women ICV Decile

Applied Received Applied Received

1 (Wealthiest) 23.8% 23.4% 24.5% 24.1%

2 23.4 22.8 20.9 20.1

3 22.4 21.8 20.6 20.4

4 17.2 16.8 18.9 17.7

5 16.6 16.5 16.2 16.1

6 15.7 15.3 16.8 16.5

7 10.0 10.2 12.1 11.9

8 10.9 10.7 11.7 11.6

9 7.7 7.6 11.3 10.9

10 (Poorest) 6.0 6.0 13.0 12.9 Total 15.0% 14.8% 16.7% 16.3%

It is also expected that some successful loan applicants will obtain smaller loans than they apply for (referred to as loan-size rationing) because the lenders will not consider them qualified to borrow as much as they would like. Lenders sometimes reduce loan sizes to amounts they think that borrowers can successfully manage with the income earned from their enterprises, or because their own funds are limited. Once again, the survey results were surprising. The data in the Table VIII-9 show the absolute number of loans applied for by the respondents divided into the type of institutions to which they applied. The success rate reports the percentage of the loan amount they actually received. At one extreme, the first category of 0 to 5 percent includes all those applicants who were either completely rejected or who received only a small fraction of the amount requested. At the other extreme, the 96–105 percent category includes those who essentially received what they requested, and there is even a category over 105 percent for those who obtained more than they applied for. The latter category includes applicants who may have changed their minds after applying and opted for larger amounts when they became available.

Generally, 80 percent or more of the applicants were successful in obtaining the amounts applied for. This percentage exceeded 85 percent for credit unions and NGOs. Approximately 10–12 percent received 60–95 percent of the amounts applied for. The clear exception is public banks. Only 65 percent of the applicants to these institutions obtained the amounts applied for, and over 20 percent received only 60 to 95 percent. Moreover, almost 6 percent received nothing or only a small fraction of their applications. The implication seems to be that although public banks may offer better loan terms, such as lower interest rates, the probability of being an unsatisfied applicant is higher than with other institutions. This may be one of the reasons that public banks received only 15–20 percent as many of the loan applications as private banks or regulated cooperatives.


TABLE VIII-9: PERCENTAGES OF LOAN AMOUNTS REQUESTED THAT WERE RECEIVED, BY TYPE OF INSTITUTION

Type of Institution Amount Received as Percentage of Amount

Requested Public Banks Private Banks Financieras Regulated Credit Unions

Local Credit Unions

NGOs & Foundations

0–5% 5.6% 1.6% 0.3% 1.0% 0.3% 0.6% 6–59% 6.1 4.1 4.7 2.3 1.7 2.6

60–95% 20.7 12.8 12.7 12.9 9.6 10.6 96–105% 65.4 80.4 80.7 82.4 86.7 85.8 >105% 2.2 1.1 1.7 1.4 1.7 0.4

Total Number of Applications 179 1,094 363 917 301 697

It is possible, of course, that lenders engage in discussions with potential applicants as part of a process of pre-application screening. In this process, they may effectively discourage entrepreneurs from applying if they believe they are not creditworthy and their application will be denied. It is also possible that many entrepreneurs develop the perception that financial institutions are generally unfriendly to people like them and/or to their type of economic activities, so they never even explore the possibility of borrowing. However, if the high success rates reported by borrowers are generally known in the local communities, there should be positive perceptions among entrepreneurs about the possibility of being successful in getting a loan.

FACTORS INFLUENCING SUCCESS RATES

Those whose applications were rejected or who received a smaller loan than applied for were asked to identify the reason (Table VIII-10). The results show that almost half did not know or could not recall the reason they were denied credit or received less than anticipated. This may imply a lack of clear communication by the financial institutions about the reasons for the decisions they make. The two most important reasons given were that the applicants did not meet requirements or did not have enough collateral. These two reasons were of lesser importance for NGOs and foundations compared with other types of lenders; insufficient collateral was of great importance for public banks. A large number of undefined “other” reasons were important for all categories of lenders.


TABLE VIII-10: REASONS FOR NOT OBTAINING CREDIT REQUESTED, BY TYPE OF INSTITUTION Reason for Not Receiving All

Funds Requested Public Banks

Private Banks Financieras Mutuals Credit

Unions NGOs &

Foundations Other Total

Did not meet requirements 7.2% 10.5% 6.4% 0.0% 7.1% 4.2% 0.0% 7.7%

Did not have needed documents 5.3 0.6 0.0 0.0 3.1 3.5 0.0 2.1

Did not have sufficient collateral 18.1 6.0 10.3 0.0 8.4 1.9 0.0 7.2

Did not have a guarantor 1.3 3.2 0.7 0.0 0.7 0.0 0.0 1.2

Bad credit history 0.0 1.6 1.1 0.0 0.9 1.0 0.0 1.1

Did not have enough income 0.8 5.3 5.2 0.0 4.2 2.5 0.0 4.1 Institution did not have enough funds 8.6 0.3 0.0 0.0 0.5 2.2 0.0 1.3

Institution did not lend for this purpose 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Other 12.7 24.6 25.8 100.0 27.3 35.6 100.0 26.5

Did not know, NR 45.9 49.2 50.5 0.0 48.3 49.2 0.0 48.7

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

HYPOTHETICAL DEMAND FOR A 20 PERCENT INTEREST RATE LOAN

To further test the potential demand for loans, the entrepreneurs were asked if they were interested in borrowing at a 20 percent annual interest rate (Table VIII-11). Nearly half (47.5 percent) responded that they were not interested.

TABLE VIII-11: INTEREST IN LOAN IF INTEREST RATE WERE 20 PERCENT PER ANNUM, BY GENDER, REGION, AND ECONOMIC SECTOR



Percentage who would be interested in having a loan at 20% interest rate

53.4% 51.3% 60.8% 35.8% 36.0% 51.9% 51.4% 53.1% 52.5%

They were then asked to give up to three reasons for not being interested in obtaining such a loan (Table VIII-12). Half of the responses were that the 20 percent interest rate is too high. Roughly a third said they did not want to be indebted, and another 8.9 percent of the respondents said that they did not need a loan. This suggests that a large segment of the sample is not interested in credit on any terms.


TABLE VIII-12: REASONS FOR NOT WANTING LOAN Order of Importance Total Reasons for Not Wanting a

Loan at 20% Interest First Second Third Responses %

Interest rate is too high 85,983 14,481 830 101,294 50.1 Don't want to be indebted 64,688 4,635 0 69,323 34.3 Don't need a loan 17,954 0 0 17,954 8.9 Procedures are too complicated 2,471 5,190 1,669 9,330 4.6

Don't meet requirements 1,862 3,355 984 6,201 3.1 Don't know where to apply 1,512 1,112 476 3,100 1.5 Other 9,127 4,469 490 14,086 7.0 Don't know, NR 18,616 0 0 18,616 9.2

Total 202,213 33,242 4,449 239,904


This result is somewhat of a puzzle to interpret. On the one hand, it suggests that the respondents are very sensitive to rates of interest. On the other hand, 20 percent is actually a low interest rate among MFIs in Ecuador because of the need to cover high operating costs, the cost of funds, risks, and inflation. Therefore, some borrowers must already be paying interest rates for microfinance loans that are much higher than 20 percent. Moreover, borrowers in the informal financial markets must be paying rates at least that high, if not higher. This response may suggest a problem of perception and lack of sophistication among some microentrepreneurs. They may already be paying or be willing to pay interest stated at, say, 2 percent per month, because that sounds low compared with 20 percent annually.

These results suggest two issues that the microfinance industry needs to consider. One is the need to educate the public more fully about interest rates and how they are determined. The other is that some potential borrowers may indeed be sensitive to high rates so lenders must find ways to drive down costs and rates in order to attract more clients.

MARKET SEGMENTS AND TYPES OF FINANCIAL INSTITUTIONS

The data for the successful loan applicants were examined to see if it was possible to detect patterns of market segmentation, that is, do different types of institutions tend to serve different segments of the market. A complete answer to this question would require a study of a representative sample of the loans made by different institutions, but some insights can be obtained by analyzing the survey data.

A few specific institutions with a reasonably large number of borrowers in the survey were specifically selected for this analysis. As shown in Table VIII-13, the private banks tended to serve wealthier clients as measured by their lower average ICV values49 and higher reported average monthly income earned from their businesses. As expected, the banks also made the largest loans

49 The ICV scale, as constructed, measures unmet household needs. The more unmet needs, the higher the ICV

value and the poorer the household is. Thus, lower ICV values indicate wealthier respondents, and higher ICV values indicate poorer respondents.


reported in the survey, and they tended to make larger loans on average as measured by either mean or median loan sizes. Surprisingly, at least one borrower reported receiving a very small loan from three of the four banks, as reflected in the small minimum loan size values. Therefore, it seems that these banks are willing to serve a wide range of clients.

TABLE VIII-13: MARKET SEGMENTS SERVED BY MAJOR MICROFINANCE LENDERS Loan Sizes

Institutions Mean Median Minimum Maximum

Average ICV Level

of Borrowers

Average Monthly

Business Income of Borrowers

Private Banks

A $4,763 $3,000 $88 $55,000 20 $708 B 3,836 3,000 500 15,000 17 761 C 1,695 1,000 40 50,000 24 440 D 1,189 800 70 40,000 20 482

Credit Unions A 3,348 3,000 80 20,000 23 602 B 2,073 1,400 100 10,000 19 543 C 1,292 860 64 12,000 22 424

Financieras A 1,552 1,000 150 6,000 22 450 B 3,259 1,300 200 38,000 23 402

NGOs and Foundations A 612 500 80 2,000 31 277 B 446 300 100 2,000 26 341 C 887 700 150 3,000 23 355 D 373 300 150 1,500 24 176 E 121 114 60 400 43 81

The three credit unions selected appear to serve roughly the same types of clients as banks, except that one of the three makes smaller size loans. Likewise, the two financieras appear to serve roughly the same market, but one makes much larger loans than does the other. Not surprisingly, the NGOs tend to serve poorer clients and make smaller loans. NGO “E” is clearly distinct—it serves an especially poor clientele and makes loans that only ranged between $60 to $400 in size.

These results suggest that, on the one hand, NGOs have a strong social mission that leads them to serve poorer clients and make many small loans. The advantage is that in doing so they may develop special expertise in serving the poor. However, the disadvantage is that if they are limited to making small loans, as a matter of policy or resource constraints, they will not be able to serve that segment of the poor that succeeds and demands larger loans. On the other hand, it appears that the banks, credit unions, and financieras are serving a wider segment of the market, and some of these institutions are making some surprisingly small loans. Their ability to also make larger loans, mainly because they are able to mobilize savings, means they have a better chance than NGOs of retaining those clients whose businesses and incomes grow and of helping them graduate to larger loans. The banks clearly stand out as having the largest range of loan sizes reported in the survey.


These loan size patterns were confirmed in interviews with a sample of microfinance institutions—NGOs, credit cooperatives, and banks—concerning their business models.50 The three NGOs interviewed explicitly targeted poorer segments of the population with loans as small as $80 to $150 and restrictions on maximum loan sizes. The commercial banks, on the other hand, designed their services and products for more developed microenterprises with loans as large as $10,000 to $20,000. The credit cooperatives and “financieras” generally offered products for a range of clients, from relatively poor clients to wealthy microentrepreneurs, with average loan sizes between those of the NGOs and commercial banks.

RELATIONSHIP BETWEEN CREDIT AND SUCCESS

There is always a question of whether or not microenterprises benefit from credit—does credit have a significant positive impact on the business? Unfortunately, because this study was not designed to test impact, it cannot provide a direct answer to that question. There is a strong positive correlation between credit, overall level of satisfaction, and a general measure of business success, but it is impossible to determine whether the success and satisfaction are the result of having access to credit, or whether access to credit is the result of being successful and having a strong sense of satisfaction and optimism.

Table VIII-14 shows the correlation between overall satisfaction and optimism51 about the future prospects for the business and receiving a loan. As can be seen, there is a strong positive correlation between the two. Entrepreneurs who expressed satisfaction and optimism about their businesses were nearly three times as likely to have loans as those who were very dissatisfied and pessimistic. Furthermore, the average size of loan obtained by those who were very satisfied and optimistic was much larger than that obtained by those who were less satisfied or optimistic.

TABLE VIII-14: CORRELATION BETWEEN CREDIT AND OVERALL SATISFACTION WITH THE BUSINESS

Level of Satisfaction and

Optimism

Received Loan During Previous 12

Months

Average Loan Size

Very positive 21.4% $3,000 Positive 17.2 2,337 Negative 12.1 2,199 Very negative 7.8 2,159

Overall average 15.7% $2,443

Similarly, Table VIII-15 demonstrates a strong positive correlation between empirical indicators of success and having access to credit. A much higher percentage of microenterprises that scored high on the success indicator52 (41.7 percent) had received a loan during the past 12 months, compared with only 13.7 percent of those in the no growth category and 17.4 percent of those with negative growth. The pattern is strong and consistent. Furthermore, there was also a corresponding relationship

50 Meyer and Fiorillo undated. 51 Using the indicator for optimism and pessimism developed in Chapter V. 52 Using the success indicator developed in Chapter V.


between success and the size of loan received, with those showing no growth or negative growth receiving much smaller loans on average that those with higher success scores.53

TABLE VIII-15: CORRELATION BETWEEN ENTERPRISE GROWTH AND CREDIT

Growth Category Received Loan

During Previous 12 Months

Average Loan Size

High growth 41.7% $3,459

Moderate growth 27.6 2,609

Low growth 25.7 3,500

No growth 13.7 2,202

Negative growth 17.4 2,036

Overall average 15.6% $2,443

As stated in the introduction to this section, the research design of the study does not permit it to state whether having credit contributed to success and positive feelings or whether being successful and having positive feelings led to greater success in obtaining loans. What is clear is that there is a strong, positive correlation between using credit and success and business satisfaction.

One characteristic of these findings that merits further analysis and consideration is the relatively large percentage of entrepreneurs who have received loans but whose businesses showed negative growth or who held decidedly negative attitudes toward their businesses. The average size of their loans was also surprisingly large. It appears that microfinance institutions needs to be a little more careful in assessing the dynamics of the businesses they are lending to as well as the attitudes and future commitment of their microentrepreneur clients. Entrepreneurs who experience slow growth and little business success often attempt to borrow out of desperation, with the hope that a loan will improve their business. However, lenders should prefer to lend to businesses that are enjoying success (so that the loans might be repaid out of an expansion in business income) rather than to microentrepreneurs who are only marginally successful and may be at greater risk of defaulting on their loans.

THE UNSERVED MICROENTERPRISE MARKET

One of the most notable findings of the survey was the low incidence of borrowing by microenterprises in Ecuador. It was clear that microenterprises do not view credit as a positive business tool (see Chapter VI), and few report having applied for loans during the past 12 months. The responses suggest a rejection of credit and financial institutions rather than lack of access to credit as might be assumed.

REASONS FOR NOT APPLYING FOR LOANS

Persons who had not applied for loans were asked about their reasons for not applying. These results were revealing about their attitudes towards debt, because more than a third (36.6 percent) of the first or second reasons given were that they did not want to be indebted (Table VIII-16). Another 14.2

53 The low average loan size for those in the moderate growth category is an irregular pattern in the data that

cannot be explained.


percent of the responses were that they were not interested or had no need for a loan. Therefore, in total, about 51 percent of the responses suggest that the entrepreneurs did not want loans under any terms.

Almost 60 percent of the remaining responses related to characteristics of loans or lending procedures, including interest rates, procedures, requirements, and collateral. This finding suggests that by redesigning their products and procedures, some financial institutions may be able to attract applicants from among those who were reluctant to apply during the last year. It is also possible, of course, that some of these responses may conceal the fact that the entrepreneurs are actually highly risk-averse with respect to borrowing, at least at the current terms offered for loans.

TABLE VIII-16: REASONS FOR NOT APPLYING FOR A LOAN DURING THE PAST 12 MONTHS Multiple Responses, Not in Order of

Importance Total Reasons for Not Requesting a Loan

First Second Third Fourth Fifth Responses %

Not interested, no need 50,887 0 0 0 0 50,887 14.2 Don't want to be indebted 123,121 8,036 0 0 0 131,157 36.6 Interest rates too high 37,089 16,896 553 0 0 54,538 15.2 Procedures are difficult 47,897 24,427 4,692 151 0 77,167 21.5 Don't meet requirements 22,961 16,299 3,789 565 0 43,614 12.2 Don't know where to apply 8,385 4,131 1,162 96 0 13,774 3.8 Lack of collateral 8,914 16,842 6,969 982 174 33,881 9.4 Fear of losing Bono Solidario* 2,957 2,375 633 66 71 6,102 1.7

Other 18,245 7,201 1,326 35 19 26,826 7.5 Don't know, NR 38,357 0 0 0 0 38,357 10.7 Total 358,813 96,207 19,124 1895 264 476,303 132.7

* A special subsidy granted by the Government of Ecuador to families in extreme poverty to help them meet basic needs.

MAJOR PROBLEMS WITH INSTITUTIONAL CREDIT

The entrepreneurs were asked to identify up to three major problems with institutional credit (Table VIII-17). Of all the reasons cited, three far surpassed the others: procedures are too difficult, too much collateral is required, and interest rates are too high. These reasons were followed by the views that the procedures were too time-consuming, the maturities were too short, and the loan amounts were too small.


TABLE VIII-17: MAJOR PROBLEMS ASSOCIATED WITH CREDIT FROM FORMAL SECTOR MICROFINANCE INSTITUTIONS

Order of Importance Total Major Problems with Institutional Credit First Second Third Responses %

Procedures are too difficult 130,094 59,612 16,301 206,007 61.4 Requires too much collateral 84,823 73,793 22,055 180,671 53.9 Interest rates are too high 76,592 39,060 21,893 137,545 41.0 Takes too much time 9,603 27,909 8,693 46,205 13.8 Maturities are too short 13,113 10,055 5,733 28,901 8.6 Amounts are too small 11,592 4,584 3,466 19,642 5.9 Requires a savings balance 4,780 4,772 3,852 13,404 4.0 Payments are too frequent 4,861 3,370 2,551 10,782 3.2 Total 335,458 223,155 84,544 643,157 191.7

These responses indicate areas where financial institutions might try to redesign their products and procedures with some hope of attracting more clients. However, it is also possible that the large number of nonapplicants is indicative of the fact that the microentrepreneurs have limited experience with borrowing and, therefore, hold naive views about the necessary steps and procedures that any lender must use to make and recover loans. The interest rate response is particularly suspect because it is unlikely that anyone would respond that rates are too low regardless of their level. Only through actually redesigning their products and testing them in the marketplace will lenders ever learn which of these reasons is really significant in attracting more clients.

Focus group sessions revealed other dimensions of attitudes toward MFI credit programs.54

Participants in the sessions noted that the two key positive factors that they considered in selecting a credit institution were the quickness with which they could obtain a loan, and the way they were treated by the institution. Particularly important in terms of the quickness with which they could obtain a loan was the complexity of the procedures for obtaining it. Additional positive factors cited by the participants were the variety of loan products and how well they were suited to their needs, pleasant facilities, larger loan maximums and longer maturities, and the cost structure for the loan.

The key negative factors reported in the focus groups that discouraged the participants from taking loans from an institution included:

• The high cost of the loans—particularly the way interest rates are added up to produce a total (5 percent for this, plus 6 percent for that, and so on) and the high associated costs of technical assistance, supervision, insurance, and other fees.

• The inconsistency between the stated rate and the actual effective rate. The participants had a feeling they were being deceived or cheated by the way interest rates were quoted and imposed.

• The constant and often heavy-handed pressure for them to make timely payments, including threats if payment deadlines were not met and threats to report them to the credit bureau.

54 A total of 18 focus group sessions were held in Quito and Guayaquil to probe the relationships between

microentrepreneurs and financial institutions.


• High penalty fees for late payments.

• Excessive procedures and exaggerated requirements for small loan amounts.

Other negative factors mentioned by the focus group participants included poor treatment by MFI personnel, forced compensating balances, large guarantees, small loan amounts, and overly frequent payments.

In many cases the solution is to increase and improve the information given to the clients. Perceived high costs and the feeling that they are being misled by loan officers should be a major concern for MFIs. Anything MFIs can do to increase the transparency of interest rates so that the client does not feel that he or she is being cheated will greatly reduce the negative perceptions many clients feel toward MFIs. Similarly, the feeling that they are being threatened by heavy-handed pressure to make payments on time can be mitigated to a great extent by the MFIs. Clients need to be counseled more carefully on the reasons for insisting on meeting rigorous payment schedules. At the same time, the pressure to meet payment schedules can signal the need to modify products to better meet client needs, and to take greater care in matching loan amounts to the repayment capacity of the client.

Interviews with a sample of microfinance institutions55 showed that few of the institutions were aware of desertion rates and had not made attempts to determine why large percentages of their client base were either inactive or had deserted the institution. Only one of the institutions had information on whether their clients were also clients of other institutions. In a noncompetitive market, an MFI would not need to worry about client satisfaction, but the microfinance market in Ecuador is becoming more and more competitive and the MFIs need to be concerned about client perceptions to maintain client loyalty.

In general, then, Ecuadorian MFIs increasingly need to be aware of client attitudes, develop effective responses to capitalize on positive aspects of their client relationships, and mitigate the negative impact of client dissatisfaction. Positive steps can include:

• Expanding the range of services and products to better correspond with client needs;

• Making every effort to reduce the procedures and steps involved in processing a loan;

• Treating the client with respect; and

• Minimizing the time required of the client in any loan process.

To offset the negative perception clients and potential clients may have, MFIs should:

• Be more forthcoming about their interest rates and the various charges involved, reducing the explanation to single, easily understandable numbers so the client does not feel he or she is being cheated or deceived;

• More effectively communicate their need for rigorous adherence to payment schedules and credit reporting, and demonstrate how the client benefits from complying through building a solid credit history and reputation; and

• Be very clear about the rules, but show clearly how following those rules benefits the client.

55 Meyer and Fiorillo undated.


COLLATERAL

Collateral—especially the amount of collateral required and the lack of sufficient collateral to meet requirements—was frequently mentioned as a problem with obtaining credit and a reason for not applying for a loan. When respondents were asked if they owned any assets that they could pledge as collateral for a loan, only 28 percent said they possessed no assets that they could use as collateral.

Slightly more than half of the microentrepreneurs owned their own home (Table VIII-18). Approximately one-fourth owned land and another fourth owned equipment or machinery. No attempt was made to value the assets or assess their value as collateral, and some microentrepreneurs may not be willing to pledge assets such as a house to secure a loan.

Men were more likely than women to own a vehicle and to own equipment or machinery. Vehicle ownership was very low on the coast. Microentrepreneurs in the production sector were most likely to own equipment or machinery that they could use as collateral, while entrepreneurs in the services sector were most likely to own vehicles (probably due to the fairly large number of enterprises in the transportation sector).

TABLE VIII-18: ASSETS AVAILABLE TO GUARANTEE A LOAN, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Assets to Use as Collateral Men Women Coast Highlands Amazonía Services Production Commerce

Total

Owns home 49.9% 51.3% 51.7% 47.7% 57.6% 50.1% 49.4% 51.1% 50.5%Owns land 28.8 26.1 25.8 30.3 45.8 27.0 27.6 27.8 27.5 Owns a vehicle 24.6 11.1 14.6 25.9 23.4 30.0 13.0 14.8 18.3 Owns equipment or machinery 28.6 20.4 23.4 27.7 25.1 27.0 50.3 14.9 24.8

Owns other asset 17.4 17.5 17.6 17.1 19.3 16.7 16.7 18.1 17.5

Of those who did own some form of asset that could be used to guarantee a loan, 43.3 percent owned only one such asset, 31.5 percent owned two different forms of assets, 17.2 percent owned three different assets, and 8.0 percent owned four or more.

ESTIMATING THE POTENTIAL DEMAND FOR MICROENTERPRISE CREDIT

Estimating demand for credit is a very imprecise exercise. Nevertheless, microfinance institutions—especially those seeking to expand—need to be able to estimate the potential market for their loans. There are sufficient data to at least describe the general boundaries of the microenterprise demand for credit. Institutions planning new branches or significant expansion activities would need to engage in detailed local market analysis to make informed decisions.

Data to estimate the potential market for microenterprise credit come from two major sources: data collected and maintained by the Superintendency of Banks and Insurance on all regulated financial institutions (including banks, financieras, and regulated credit unions), and data generated by this survey of microenterprises. Data from the Superintendency include information on “microcredit,” which is defined as small loans that are not backed by regular income such as a salary. All regulated institutions are required to report on microcredit each month. Specific information on microcredit compiled in the Superintendency database includes number of loans made, current end-of-month


outstanding balances, and the delinquency pattern of the portfolios of the regulated institutions.56 Data generated by the survey provide estimates of the number of microenterprises in the country and information on the number and amount of loans applied for and disbursed to microenterprises from both regulated and nonregulated institutions during the past 12 months. Although most of the loans are for business purposes, microentrepreneurs also borrow for personal reasons from these same institutions.

According to the Superintendency of Banks and Insurance’s monthly statistics, in August 200457 there were 175,826 active credits with a total outstanding balance of $241.6 million. The average loan outstanding was $1,462. Assuming that every single microentrepreneur would, if given the opportunity, want a loan equal to this average loan amount, the total potential demand for credit would be approximately $888.1 million. If each active credit were a single loan to a microenterprise, these numbers would suggest that approximately 27.3 percent of microentrepreneurs currently have loans and that the amount outstanding represents about 27.2 percent of the potential demand.

This calculation obviously overestimates the potential demand for credit, however. Not all microentrepreneurs would want a loan at the same time and, in fact, not all microentrepreneurs even want credit. The survey data show that only 15.7 percent of microentrepreneurs have requested a loan during the past 12 months, 36.6 percent said they did want to be indebted, and 14.2 percent indicated that they did not need a loan. When asked if they would be interested in obtaining a loan at an interest rate of 20 percent,58 only 52.5 percent said they would be interested; 35.8 percent said they would not, and 11.8 percent were uncertain. The average loan obtained by the microentrepreneurs was for $2,042, or 39 percent greater than the average loan size outstanding as reported by the Superintendency.59

The 15.7 percent of the microentrepreneurs who received loans in the past 12 months obtained loans for a total of $206.2 million. This amount is slightly below the total outstanding microcredit reported by the Superintendency. If only 15.7 percent of the microenterprises would want credit at any time, these numbers suggest that the total market for microenterprise credit may be approaching saturation. However, much of the reported “microcredit” is not loans to microenterprises.

With better information, more familiarity with MFIs and products, more points of service to lower client transaction costs, improved credit products that more adequately meet the needs of the clients, and interest rates that reflect efficient operations, a larger percentage of microenterprises could be projected as potential microfinance clients. If 25 percent of the microenterprises requested credit at any one time, and the average loan size was $2,042, the total projected loan demand would be about

56 Limitations on the use of data from the Superintendency include the fact that it only contains information

from regulated institutions, it reports “operations” rather than “number of clients,” the loans are not necessarily to microenterprises but can be to any individual, and the loans include some loans that are not for microenterprise business purposes. Still, the data are very useful for gaining a broad perspective on microfinance in the country and, with the caveats mentioned, provide a good overview of the size and trends of the microcredit market.

57 The study uses data from August 2004 because it roughly corresponds to the period of the survey. More recent updates are available from the Superintendency.

58 Twenty percent is a very low interest rate for MFIs in Ecuador 59 The difference in average loan sizes reported by the Superintendency of Banks and Insurance and the survey

may reflect the difference between amounts disbursed (the figure reported in the survey) and average balances outstanding (the statistic reported by the Superintendency of Banks and Insurance). Amounts disbursed tend to be larger than average balance outstanding.


$328.3 million. With an even more optimistic scenario of 50 percent as borrowers, the total projected loan demand would be about $656.7 million. Furthermore, average loan sizes can be expected to increase over time.

In summary, there appears to be significant growth potential for the microfinance industry, provided that it continues to actively expand financial services to those who are currently nonborrowers. Total loan demand from microentrepreneurs can be estimated at between $206.2 million and $656.7 million annually, depending on the assumptions made about the percentage of microentrepreneurs who would be willing to borrow and average loan sizes. This potential demand is heavily concentrated in a relatively few highly urbanized markets with large concentrations of microenterprises, however, as can be seen in Figure VIII-1. Understanding these markets is important for MFIs planning to expand into new areas.

THE SUPPLY OF MICROCREDIT

Ecuador has witnessed an explosive growth in microcredit during the past few years. The number of regulated institutions offering microcredit has increased, outstanding microcredit portfolios have grown dramatically, and the number of loans outstanding has soared.60 This raises questions about market saturation and future growth potential that need to be addressed.

A DEFINITION OF MICROCREDIT

The Superintendency of Banks and Insurance has adopted the following as an official definition of microcredit for the regulated financial industry:

Microcredit is all credit granted to a borrower—natural or legal person or group of persons with a solidarity guaranty—destined to finance small-scale activities in production, commerce or services whose principal source of repayment is the product of the sales or income generated by such activities, as verified by the lending institution.… [B]alance sheets and profit and loss statements are not required of microentrepreneurs … [unless] the original amount of the loan exceeds $US 20,000.

60 The data cited in this section are from August 2004 to correspond with the period of the survey.


FIGURE VIII-1: ESTIMATED DEMAND FOR MICROCREDIT, BY CANTON

This definition is under review and may be changed in the future. However, the important conditions are that the credit support an income-generating activity and that the amount is typically less than $20,000.

All regulated financial institutions are required to classify their loan portfolios according to purpose as consumer, commercial, microcredit, or housing. The introduction of microcredit as a category in recent years has resulted in a large-scale effort on the part of the institutions to reclassify their portfolios.

POINTS OF SERVICE

Official data, which exist only for institutions regulated by the Superintendency of Banks and Insurance, show that the approximately 36 regulated institutions had microcredit portfolios in August 2004.61

61 In addition to regulated financial institutions, there are many nonregulated institutions that have microcredit

portfolios. There are more than 300 nonregulated cooperatives (credit unions), and numerous NGOs that are not included in the official statistics. However, most of the nonregulated institutions are small. The tendency is for the larger NGOs and credit unions to become regulated.


These institutions are highly clustered, with numerous institutions providing microfinance services in the large metropolitan and high-population density areas, and a general absence of financial services in other areas, as can be seen in Figure VIII-2. In general, the highlands are well covered by microfinance services, but there is sparse service in much of the coast and Amazonía. This pattern is even more obvious when nonregulated institutions are considered because they tend to be more numerous in the highlands.

FIGURE VIII-2: DISTRIBUTION OF MFIs, BY CANTON

NUMBER OF MICROCREDIT CLIENTS

Data from the Superintendency of Banks and Insurance report the number of active “operations” as of any specific date. Because a microentrepreneur may have multiple loans, the number of operations may be larger than the number of microcredit clients. Data from the survey, however, suggest that the difference is not significant; very few microentrepreneurs reported applying to more than one institution or for more than one loan.

As of August 2004, the regulated MFIs had 241,640 active “operations.”62 Projections from the survey estimated that there are 646,084 microentrepreneurs. If each “operation” represents a single microentrepreneur client, an estimated 37.4 percent of all microentrepreneurs in the country have loans outstanding from formal sector financial institutions.

62 This number is significantly larger than the projected total of microentrepreneurs who obtained loans during

the 12 months preceding the survey.


Comparing the distribution of “operations” with the projected number of microentrepreneurs at the canton level shows that penetration rates (number of operations divided by estimated number of microentrepreneurs) vary widely from canton to canton (Figure VIII-3). Penetration rates are highest in the highlands, which is consistent with the general distribution of MFIs. In several cantones these penetration rates exceed 100 percent. Penetration rates in the rest of the country are relatively low. This pattern of penetration rates is consistent with the findings of the survey.

Areas of lowest penetration offer the best prospects for expansion by microfinance institutions. The marketing strategy to pursue initially in these areas may simply be to increase the points of service so that financial services are physically more accessible to entrepreneurs FIGURE VIII-3: ESTIMATED COVERAGE (PENETRATION) RATES, BY CANTON

MICROCREDIT PORTFOLIO

The outstanding microcredit portfolio of regulated financial institutions, as reported by the Superintendency of Banks and Insurance in August 2004, was $257.1 million, compared to a total estimated potential demand of between $206.2 million and $656.7 million. At the lower end of the estimated demand, the market for microcredit would be supersaturated; at the upper end, approximately 39.1 percent of demand for microcredit is being met by the regulated financial institutions.

As in the case of numbers of clients, the microcredit portfolios of the regulated financial intermediaries is concentrated in the highlands, and specifically in metropolitan and high-population density areas. This can be seen in Figure VIII-4, which compares the outstanding microcredit


portfolios of the regulated financial institutions with total demand estimates projected from the survey (saturation rate equals outstanding portfolio balances divided by total estimated demand for microcredit).

FIGURE VIII-4: ESTIMATED SATURATION RATES, BY CANTON

As can be seen in Figure VIII-4, microcredit is heavily concentrated in a relatively few cantones of the highlands. Other cantones have a very low volume of microcredit compared to estimated demand.

The total volume of microcredit has increased from $73.7 million in December 2002 to more than $327.3 million in December 2004. Much of this growth is the result of portfolio reclassification—“microcredit” was added as a portfolio classification and financial institutions were required to reclassify their outstanding loans to report on microcredit—but a substantial amount of growth has occurred because of a growing focus on microcredit in regulated institutions. With nonregulated institutions, the overall level of microcredit outstanding would be even higher.

PRODUCTS AND SERVICES

Interviews with a sample of MFIs63 revealed that there are relatively few products being offered by the various institutions. Microcredit for individuals, group loans, housing, savings (especially fixed-time deposits), and processing of remittances represent the general mix of products available.

63 Meyer and Fiorillo undated.


Individual microcredit loans are almost universally small, short-term loans with standard repayment schedules based on an amortization table. These types of loans are generally for inventory and raw materials. Larger and longer-term loans more appropriate for equipment or facilities are generally not available. Most institutions offer “seasonal” credit—short-term loans designed to meet specific seasonal business needs, such as the need to increase inventory for periods of increased sales.

Group lending is not widely offered in Ecuador. A few NGOs follow the traditional village banking model, but as a lending methodology it is losing favor. Even the pioneer of this approach is shifting to an individual lending methodology, a pattern that is found throughout the developing world as the microfinance industry matures. At least one bank and several cooperatives have attempted group solidarity lending, or have attempted to partner with NGOs offering either village banking or solidarity group approaches, but without incorporating these technologies in their own programs.

Housing loans can be used for construction, improvements, or expansion—of either homes or business establishments. These are generally for a longer term, but following a standard repayment schedule.

Regulated financial institutions offer both sight and fixed-term savings instruments. The village banking and group methodologies encourage “internal” savings that are managed by the local village banks or groups, but which the NGOs themselves are unable to capture or manage.

In general, then, the range of products offered by the microfinance institutions is limited. Only a couple of institutions have experimented with truly innovative products—smart cards or credit cards, lines of credit (rotating credit), or other flexible instruments designed to minimize transaction costs and staff time. Developing and offering such products will become increasingly important as competition among the MFIs increases. A trend toward increasingly sophisticated microfinance products is a sign of a maturing microfinance market that has been observed in such widely divergent countries as Bolivia, Bangladesh, and Uganda as MFIs compete for client loyalty.

SAVINGS

HOW MANY HAVE SAVINGS?

Although more microentrepreneurs report that they have savings in a financial institution than regularly use credit or have solicited credit during the past 12 months, the number with savings is still relatively small—only 29 percent of microentrepreneurs said they have savings in a financial institution.

WHO SAVES AND WHO DOESN’T?

Men are a little more likely to have savings than women, but the differences are not great—30.6 percent compared with 27.1 percent (Table VIII-19).

People on the coast were least likely to have savings; only 22.5 percent of the microentrepreneurs on the coast reported that they kept savings in a financial institution. A much higher percentage of respondents in the highlands (41.6 percent) and Amazonía (51.3 percent) maintained savings in financial institutions.

The economic sector of the respondents had little impact on savings patterns, although slightly fewer respondents in the commerce sector reported keeping savings in a financial institution.


TABLE VIII-19: RESPONDENTS WHO HAVE SAVINGS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Have Savings


No 69.4% 72.9% 77.5% 58.4% 48.7% 69.0% 70.9% 72.0% 71.0%

Yes 30.6 27.1 22.5 41.6 51.3 31.0 29.1 28.0 29.0

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Age also appeared to play a role in determining savings patterns. Middle age groups, from 31 to 55, were the most likely to have savings, while younger and older age groups were less likely to keep savings in institutions.

WHY DON’T MICROENTREPRENEURS SAVE?

Overwhelmingly, the microentrepreneurs say they do not have the resources to permit them to save (Table VIII-20). Coupled with responses like “need to spend on children’s education” and “prefer to spend,” the image left is one of a rather precarious income level that does not have discretionary funds that they would choose to put into savings in an institution. This conclusion is consistent with the fact that the income levels reported for many of the businesses are quite low.

At the same time, the responses suggest a lingering mistrust of the financial system: a large percentage of respondents (24.9 percent) said they lack confidence in financial institutions and either preferred to keep their savings at home (7.4 percent) or invested in other assets (4.6 percent). A small but important group of respondents mentioned the difficulties of working with the financial institutions—complicated procedures (4.7 percent), high initial deposit requirements (2.9 percent), low interest rates (3.0 percent), difficulty in withdrawing savings (1.0 percent), and the fact that taxes are withheld on savings by the institutions (3.1 percent)—as reasons for not holding savings in financial institutions.


TABLE VIII-20: REASONS FOR NOT SAVING IN FINANCIAL INSTITUTIONS

Total Why Don't

Microentrepreneurs Save? Most

Important Reason

Second Most

Important Reason

Third Most Important Reason Responses %

Has no money to save 200,900 12,207 1,541 214,648 70.6

Prefers to invest in property 7,749 5,416 981 14,146 4.6Invests in education of children 14,486 21,399 2,231 38,116 12.5

Prefers to keep at home 11,820 8,344 2,263 22,427 7.4

Prefers to spend 7,255 15,199 3,920 26,374 8.7

Doesn't trust banks 48,353 22,254 5,329 75,936 24.9

Too many steps 4,836 7,026 2,390 14,252 4.7Require very high initial deposit 2,429 4,184 2,086 8,699 2.9

No financial institution nearby 390 484 203 1,077 0.4

Interest rate is too low 2,574 3,957 2,528 9,059 3.0

They collect a lot of taxes 2,885 4,227 2,393 9,505 3.1

Too hard to withdraw savings 577 1,624 865 3,066 1.0

Total 304,254 106,321 26,730 437,305 143.8

WHERE DO THEY HAVE SAVINGS?

Most of those who have institutional savings hold those savings in only one institution: of the 29 percent of microentrepreneurs with institutional savings, the vast majority (86.8 percent) have those savings in only one institution, while 12.6 percent have savings in two institutions, and only 0.6 percent have savings in three or more institutions. Although the use of multiple institutions for savings is higher than it is for loans, there appears to be a good deal of customer loyalty: most borrowers and savers patronize only one institution. Nonetheless, the higher proportion of savers patronizing more than one institution indicates that financial institutions need to better understand client preferences and attitudes in order to more completely serve their needs and maintain loyalty.

Banks and credit unions were the institutions of choice for savings deposits. Of the microentrepreneurs who do hold savings in a financial institution, 51.4 percent have them in banks, 53.8 percent in credit unions, 4.3 percent in mutuals, 3.3 percent in NGOs, and 0.3 percent in financieras.64

PREFERRED INSTITUTIONS

Regardless of where they held their savings, men generally preferred to have their savings in a commercial bank, while women indicated a preference for credit unions (Table VIII-21). Women were also more likely than men to prefer holding their savings in an NGO (village bank or other), probably reflecting the specific focus of these institutions on women.

64 Percentages total to more than 100 due to multiple responses.


TABLE VIII-21: PREFERRED SAVINGS INSTITUTION, BY GENDER AND REGION Gender Region Preferred Savings

Institution Men Women Coast Highlands Amazonía Total

Credit union 43.1% 52.2% 50.0% 44.8% 44.3% 47.0% Bank 49.1 35.3 40.7 44.2 53.7 43.2 Mutual 4.8 7.5 4.4 7.7 0.6 6.0 NGO/foundation 1.1 3.7 3.3 1.6 0.0 2.2 Other 0.9 0.5 1.1 0.4 1.3 0.7 Don't know 0.5 0.5 0.6 0.6 0.0 0.5 Financiera 0.5 0.3 0.0 0.7 0.0 0.4 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Savers on the coast tended to prefer credit unions, while those in the highlands equally preferred credit unions and banks and those in Amazonía indicated a strong preference for banks. NGOs and mutuals have little apparent presence in Amazonía.

WHY DO THEY SAVE WHERE THEY DO?

Security and safety of funds was the most important criterion that microentrepreneurs used to select an institution for their savings (Table VIII-22). This is reflected in the high percentage of responses (49.8 percent) that cited security, stability, and reputation as the single most important reason for selecting the institution they preferred to save in. This emphasis on safety and security probably reflects a continued wariness of the financial sector in the wake of the 1999–2000 crisis, and is consistent with reasons given for not placing savings in a financial institution. Respondents who considered these to be the most important requirements generally chose to hold their savings in banks or financieras.

Convenience is the second most important reason—27.6 percent of the respondents cited convenience, location, and ease of withdrawing savings as the main reason for choosing their particular institution, followed closely by the fact that savings are required to obtain a loan. Convenience was a particularly important criterion for those who held savings in an NGO. This probably reflects the practice of many NGOs to mobilize savings during local group meetings. Financieras were generally not considered to be very convenient.

Choosing an institution because savings were required for obtaining credit was the main reason given by 15.3 percent of the microentrepreneurs, particularly those who held savings in credit unions and NGOs.65

Interest rates appear to be of relatively low priority in selection of a savings institution, possibly because the institutions do not openly compete for savings through interest rate incentives. This suggests that as long as interest rate competition does not become prevalent among financial institutions, MFIs currently do not need to compete on the basis of interest rates.

65 Although NGOs are not legally authorized to hold savings or deposits, many clients of NGO programs view

the “internal savings accounts” or other mandatory savings balances required by these institutions as savings held in the institution.


Credit unions should notice that, although they promote the concept that members are owners of the credit union, that reason does not appear to be a significant factor in choosing to place savings in an institution. Credit unions should reexamine the psychological attraction of being a member, especially in light of the growth of “open” credit unions that downplay the significance of being a member.

TABLE VIII-22: MAIN REASONS FOR SELECTING A PARTICULAR SAVINGS INSTITUTION

Institution Chosen Main Reasons for Having Chosen a Particular

Institution Bank Financiera Credit Union Mutual NGO

Overall

Security 39.3% 33.5% 26.9% 32.4% 16.7% 32.2%

Reputation 11.8 27.1 11.0 8.3 4.0 10.9

Stability 7.8 0.0 6.1 4.6 1.3 6.7

Convenience 16.3 7.4 13.3 15.2 34.0 15.7

Ability to withdraw funds 8.8 10.4 10.0 13.6 8.7 9.5

Location 2.5 0.0 2.4 1.3 0.0 2.4

Needed to obtain a loan 8.5 13.4 21.0 12.9 32.3 15.3

Good interest rates 2.2 8.1 7.1 8.1 1.5 4.7

Good facilities 1.6 0.0 1.3 2.5 1.4 1.5

Friendliness of staff 1.1 0.0 0.8 1.1 0.0 0.9 I'm an owner of the cooperative 0.0 0.0 0.3 0.0 0.0 0.2

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

FEATURES CONSIDERED IMPORTANT IN CHOOSING A SAVINGS INSTITUTION

When asked a more hypothetical question about what features they would consider in choosing an institution to place future savings in, the respondents again stressed the importance of safety and security (Table VIII-23). The vast majority of respondents felt that this was the most important factor—nearly half of all respondents said this was the single most important consideration. Overall, 69.3 percent of all respondents mentioned security as one of the most important considerations.

The second most important reason for choosing a future institution was whether or not the microentrepreneurs would be able to obtain a loan from that institution. There is a demand for credit, and microentrepreneurs recognize the need to have savings in order to leverage credit. The responses indicate that they tend to favor institutions that offer them the possibility of obtaining a loan should they choose to borrow.

Unlike in previous responses, attractive interest rates were cited as the third most important factor in choosing a future savings institution. In contrast to answers to the previous question, these answers suggest that microentrepreneurs might respond to interest rate competition among the institutions.

Finally, a significant number of responses stressed quality of service as a feature they would look for in selecting an institution; 43.8 percent of the respondents mentioned simple procedures, lower fees, ability to withdraw savings when needed, ease of opening accounts, and friendly service as factors that would influence their decision to place funds in an institution. MFIs competing for savings need to be sensitive to this dimension in planning their marketing strategies.

Access to other services, such as checking accounts or automated teller machine (ATM) services, were not viewed as important by the respondents.


TABLE VIII-23: FEATURES THAT ATTRACT SAVERS Total Reason for Selecting an

Institution to Deposit Savings In

Most Important

Second Most

Important

Third Most Important Responses %

Security 200,882 61,997 17,643 280,522 69.3Opportunity to obtain credit 92,998 40,038 18,250 151,286 37.4High interest rate 54,986 55,533 13,240 123,759 30.6Simple procedures 14,152 20,393 8,075 42,620 10.5To be able to withdraw savings 10,215 20,165 10,211 40,591 10.0

Low fees and other costs 9,998 17,417 12,482 39,897 9.9Ease of opening account 8,635 12,201 8,081 28,917 7.1Friendly service 6,144 11,698 7,603 25,445 6.3Health and life insurance 2,329 5,986 3,530 11,845 2.9Location near business or home 3,161 4,026 1,977 9,164 2.3

To have a checking account 688 1,207 1,006 2,901 0.7Convenient hours 215 544 1,602 2,361 0.6Availability of ATM 228 552 1,002 1,782 0.4Total 404,631 251,757 104,702 761,090 188.0

INFORMAL SAVINGS

Surprisingly, very few respondents indicated that they had informal savings, such as with relatives, village banks, or moneylenders (Table VIII-24).

TABLE VIII-24: INFORMAL SAVINGS PATTERNS

Informal Savings Yes No Don't know Total

Has savings with a relative 3.6% 96.2% 0.2% 100.0%

Has savings with an acquaintance 1.5 98.2 0.3 100.0

Has savings with a savings club 2.3 97.5 0.3 100.0

Has savings with a village bank 1.0 98.7 0.3 100.0

Has savings with a moneylender 0.2 99.0 0.8 100.0

USE OF OTHER SERVICES

In general, microentrepreneurs exhibited a low level of usage of modern financial and other services (Table VIII-25). The survey specifically asked about use of checking accounts, ATMs, credit cards, and money transfer services. It also asked about their use of the Internet to communicate with friends and relatives who have emigrated. Communicating with relatives overseas using the Internet was the most commonly used modern service. With the large number of Ecuadorians who have migrated, the desire to communicate with persons living abroad has increased significantly in the last few years.


The rapid growth of “Internet cafes,” even in poor neighborhoods, has placed this technology within reach of even very poor people.

Checking accounts and automated teller machines are the financial services that are used the most, but even these were used by less than 10 percent of the microenterprise population.

Men tend to use financial services more than women. A larger percentage of men than women have checking accounts and credit cards and use ATMs, but a larger percentage of women receive remittances, send or receive funds through an agency, and use the Internet to communicate with relatives overseas.

For unknown reasons, respondents in Amazonía reported a greater use of checking accounts, automated teller machines, and credit cards than respondents in the other regions.

Also somewhat unexpectedly, microentrepreneurs in the commerce sector reported a higher use of checking accounts and automated teller machines than those in other sectors.

TABLE VIII-25: OTHER SERVICES USED, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector

Financial Services Used Men Women Coast Highlands Amazonía Services Production Commerce

Total

Checking account 7.3% 4.8% 4.6% 9.0% 14.0% 5.7% 4.9% 6.8% 6.1%

Automated teller machines 8.9 6.3 6.3 10.4 13.6 7.7 6.9 8.0 7.7

Credit cards 4.5 3.2 3.0 5.8 6.4 4.2 3.8 3.8 3.9

Sends/receives funds through an agency 3.6 4.6 3.9 4.3 4.2 4.0 3.1 4.4 4.0

Has used Internet to communicate 9.6 9.9 10.2 8.9 7.2 10.8 9.2 9.5 9.8

Receives remittances 3.9 6.4 5.1 5.1 4.3 4.8 4.5 5.4 5.1

Table VIII-26 shows the patterns of receiving remittances and using those remittances in business. As can be seen, relatively few microentrepreneurs (5.1 percent) receive remittances from relatives living abroad. The Bendixon study of remittances found that, overall, about 15 percent of Ecuadorian households receive remittances from relatives living abroad.66 It appears that microentrepreneurs are less likely than others in the general population to have family members who have emigrated to seek employment abroad.

Women are more likely to receive remittances than men. Fewer microentrepreneurs in Amazonía reported receiving remittances. Microentrepreneurs in the commerce sector are more likely to have received remittances than those in the other two sectors, and those in the production sector reported the lowest tendency to receive remittances.

Of those who do receive remittances, a little over one-third (37.6 percent) say they use those remittances in their businesses—a finding that suggests that credit obtained from financial institutions might not be used for business as well. The use of remittances in business is highest among women, those on the coast, and those in the commerce sector.

66 Bendixon and Associates 2003, p. 5.


TABLE VIII-26: RECEIPT AND USE OF REMITTANCES, BY GENDER, REGION, AND ECONOMIC SECTOR Gender Region Economic Sector


Total

Receives remittances 3.9% 6.4% 5.1% 5.1% 4.3% 4.8% 4.5% 5.4% 5.1%Uses remittances in business 35.0 39.4 39.5 34.3 23.3 35.9 30.7 40.3 37.6


The key finding of this chapter is that in spite of the large expansion in recent years in the microfinance industry, it has had little impact on most microenterprises. Only 29 percent reported holding savings in financial institutions. Credit from formal financial institutions is not part of the business strategy of most microentrepreneurs, and large numbers do not want to become indebted. They also tend to not use many other formal financial services.

Only 15.7 percent of those interviewed reported that they applied for loans in the past 12 months. When they applied, it tended to be for only one loan and with only one financial institution. Except, perhaps, for a few local markets, it appears that excessive competition and borrowing from multiple institutions— leading to overindebtedness, as occurred in Bolivia—is not a problem in Ecuador.

Microentrepreneurs in Ecuador also tend to make little use of other, more modern, financial services. Only 6.1 percent have checking accounts, 7.7 percent use ATMs, and 3.9 percent use credit cards.

Why are so few microentrepreneurs using formal financial services? First, many are not aware that microenterprises can receive services. Only 34.7 percent could spontaneously identify an institution that lends to microentrepreneurs. Even the major microfinance institutions were recognized by only a small percentage of respondents. Credit unions were most widely recognized, perhaps because they are numerous and widespread and respondents can recall a local institution more readily than a distant one.

Location of the point of service and distance to the microenterprise may play an important role. Two-thirds of the loan applicants had businesses or homes within two kilometers of the financial institution. Convenience was an important reason given for choice of institution with which to save. Long distances drive up transaction costs for small loans and savings accounts and may cause some to believe it is not worth the bother of dealing with financial institutions. Increasing the number of points of service and increasing loan officer contact with clients and potential clients (that is, actively seeking clients in their homes and places of work) may be required to reach disperse, independent microentrepreneurs scattered across cities, towns, and neighborhoods.

Attitudes and opinions held by microentrepreneurs about financial institutions and their products and services, whether well-informed or not, undoubtedly are important. Of those respondents who did not apply for loans, over a third (36.6 percent) did not want to be indebted, and another 14.2 percent were not interested in or did not need a loan. Many said the procedures were too difficult, too much collateral was required, and interest rates were too high. A quarter of those who did not report savings said they lacked confidence in financial institutions. This opinion may be a legacy of the financial crisis of 1999–2000.

Participants in the focus groups were even more critical in their views. They complained of high interest rates and the associated costs of technical assistance, supervision, insurance, and other fees; deception in the way interest rates were quoted and imposed; heavy-handed pressure for timely payments and high penalty fees for late payments; and exaggerated requirements for small loans. If these views were widespread, they could have a depressing effect on demand for loans. However,


such complaints may be more common among better-informed microentrepreneurs in larger cities than they are of all enterprises.

If the users of financial services have positive experiences, there should be positive spillover effects on the attitudes of nonusers. Here the survey results were somewhat unexpected and encouraging. Most who applied for loans received them and most obtained loan amounts close to the amounts for which they applied. The biggest exception seemed to be for applicants in public banks. Men and women tended to apply for loans in roughly equal proportions and were equally successful. There was even evidence that a higher proportion of poorer women applied compared with men. Importantly, both men and women in the higher deciles of wealth ranking (ICV values) applied at a rate almost double those in the lower deciles.

The high loan approval success rates clearly suggest that loan demand shapes borrowing patterns more than loan supplies, and wealth is an important factor in shaping loan demand. More in-depth analysis is needed to explore the differences between borrowers and nonborrowers, and how those differences affect the demand for loans and other financial services.

What are the implications of these findings for the microfinance industry, and what does it need to do to tap this large market of microentrepreneurs, most of whom do not currently use its products and services? Perhaps the most important challenge to MFIs in Ecuador is to overcome the microentrepreneur’s resistance to using credit. Credit is not seen as a positive tool to grow a business, but rather as a cost or penalty to be avoided at almost any cost. Among the components of this resistance:

• The amount of credit many institutions offer is not worth the effort the clients have to put into obtaining the credit and the risks they have to take—forms, guarantees, cosigners, references, and multiple visits all imply a cost to the borrower, and if that cost is greater than the perceived benefit of the credit, the microentrepreneur will not take the risk of borrowing.

• Most microentrepreneurs are not convinced that credit (becoming indebted) represents an opportunity to grow.

• Fear of the consequences of not being able to pay back the loan or to meet repayment schedules keeps many microentrepreneurs from borrowing.

As a result of these factors, many microentrepreneurs only borrow when they really need it—when circumstances force them to take on a debt obligation. Overcoming this resistance will require active marketing because the microentrepreneurs will not likely be reached by mass marketing techniques or general publicity.

Microfinance institutions also need to recognize that their current product mix may not fit client needs. There was little evidence of demand-driven product design, that is, institutions designing or modifying products based on surveys of clients and potential clients or consideration of the business cycle of different segments of the potential client market. While this may not be important in an environment of limited competition, as competition increases among financial institutions, having products that match client needs will give institutions a competitive edge.

The quality of service was also revealed as important in the survey, at least in the short run. Although microentrepreneurs felt that interest rates on savings were too low, and those on loans too high, these were not the most important factors they considered in making savings and borrowing decisions. Decisions to save were prompted more by a sense of stability, safety, and security than by interest rates. Complaints against credit institutions focused more on convenience, procedures, guarantees, courteous treatment, and time required to obtain a loan than on the interest rate that was charged. In the short run, institutions would be well advised to focus on improving these aspects of their business.


As competition increases, and as interest rates and commissions become more transparent, interest rates—on both savings and loans—may become a more important factor in competitive positioning.

The survey results also suggest that it is important for donors and MFIs alike to recognize the limits of finance. Many of the conditions described by the respondents in other chapters—increasing competition, lack of growth in sales, little demand—suggest that increasing the supply of credit may not benefit most microentrepreneurs. Donors need to recognize the importance of nonfinancial services and how they may be crucial in breaking the constraints faced by microentrepreneurs, such as a need for a better understanding of markets, improved product quality, and increased efficiency of production and marketing.

IX. NONFINANCIAL SERVICES AND SUPPORT 121

IX. NONFINANCIAL SERVICES AND SUPPORT Competing successfully in the highly competitive environment that most microenterprises find themselves in requires knowledge and skill in management, marketing, and technology. This knowledge and skill can be acquired in many ways, from simple trial and error in operating the business to more formal schooling, apprenticeships, membership in associations, training, and technical assistance. Success is more likely to occur when microenterprises have access to helpful instruction and information.

MEMBERSHIP IN ASSOCIATIONS

Entrepreneurs frequently benefit from memberships in associations that afford them the opportunity to exchange experiences and ideas and that provide training and other member support services. According to the responses to the survey, very few Ecuadorian microentrepreneurs belong to organizations that provide support to or represent the interests of businesses: only 8.5 percent reported membership in a business association, chamber, guild (gremio), or other interest group organization (Table IX-1). Of those entrepreneurs who do belong to some form of association, more than half (62.4 percent) belong to either artisans’ associations, artisans’ gremios, or vendors’ associations. About 20 percent said they belonged to one of the chambers of industry and commerce.67 The rest belonged to assorted artisan, producer, and vendor cooperatives.

Although membership rates were low for both male and female entrepreneurs, male microentrepreneurs were nearly three times more likely to belong to such organizations than women. This could be because female entrepreneurs are less mobile and more locally focused than male entrepreneurs, with household responsibilities, production in the home, and sales in local neighborhoods. The lack of mobility undoubtedly limits the possibility for affiliation with associations.

Entrepreneurs in Amazonía report a higher incidence of membership in chambers, business associations, or gremios than those in the other two regions. Membership was lowest on the coast.

Entrepreneurs in the services sector are much more likely to belong to an association than those in the other two sectors; entrepreneurs in commerce are the least likely. The low level of memberships among production sector entrepreneurs was somewhat surprising because there tend to be small industry chambers and other associations in most towns and cities.

TABLE IX-1: MEMBERSHIP IN CHAMBERS OR ASSOCIATIONS, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Belongs to a Chamber, Gremio,

or Association Men Women Coast Highlands Amazonía Services Production CommerceTotal

Yes 11.8% 4.7% 7.3% 10.6% 15.1% 14.8% 8.9% 5.4% 8.5% No 87.0 94.1 91.3 88.4 84.4 84.2 89.6 93.3 90.3 Don't know, NR 1.2 1.2 1.3 1.0 0.5 1.0 1.5 1.2 1.2 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

67 Chamber of Industry, Chamber of Commerce, Small or Medium Industry Chamber, Artisan’s Chamber,

Chamber of Construction, Chamber of Tourism, and Agriculture or Livestock Chamber.


The low level of membership in business-related associations is at least partly due to the small size of the microenterprises: it is difficult for an owner of a single-person firm to leave the business to attend meetings, receive training, or seek out information. But it is also probably due to the relative scarcity of such institutions oriented toward smaller businesses. Ecuador has chambers of commerce and industry, but these are essentially exclusive clubs of wealthy owners and executives of large companies and industries. Chambers of small enterprises and industry are relatively abundant in Ecuador, but the members of these organizations also tend to come from larger businesses that operate in the formal sector. Specialized artisan chambers and associations of market vendors are virtually the only institutions in Ecuador that involve low-income informal sector businesses.

TRAINING AND TECHNICAL ASSISTANCE

Ecuadorian microentrepreneurs have also received relatively little assistance in the form of training or technical assistance. Less than one-fourth (22.2 percent) of the microentrepreneurs reported that they had received some form of training. An even smaller percentage (13.2 percent) of microentrepreneurs had received technical assistance for their business.

Men were more likely to have received both training and technical assistance (24.1 percent and 14.9 percent, respectively) than women (19.9 percent and 11.3 percent, respectively).

Enterprises in the highlands were more likely to have received both training and technical assistance than those on the coast or in Amazonía. The concentration of donor-supported NGOs and other entities in the highlands may account for the greater access to nonfinancial services in this region.

Entrepreneurs in the production sector were the most likely to have received both training and technical assistance, and those in the commerce sector were the least likely to have received either. The greater skill level required in production activities may account for the higher percentage of respondents reporting that they had undergone training or received assistance. In contrast, the low skill levels and technical experience required to enter the commerce sector undoubtedly results in the lower percentage of entrepreneurs in that sector who have received training or technical assistance. Of course, government- and donor-sponsored training, technical assistance, and technical programs also tend to focus on production activities rather than commerce, so there is likely to be more available related to production than commerce.

TABLE IX-2: TRAINING AND TECHNICAL ASSISTANCE RECEIVED, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Exposure to Business-Oriented

Support Men Women Coast Highlands Amazonía Services Production Commerce Total

Received training to operate the business 24.1% 19.9% 19.8% 27.1% 22.5% 26.7% 32.1% 16.6% 22.2%

Received technical assistance for the business

14.9 11.3 11.0 17.7 16.4 16.4 17.2 10.3 13.2

The differences between male and female entrepreneurs in receiving training and technical assistance are not particularly large, but there are some notable exceptions when access to nonfinancial technical support is analyzed by economic sector (Table IX-3).68 Women in the wood products and commerce

68 The small number of female entrepreneurs in the construction sector accounts for the wide disparity in the

statistics for this sector.


sector have generally received more training and technical assistance than the men. Male entrepreneurs in the food products sector, on the other hand, have received significantly more training and technical assistance than their female counterparts. One explanation for this might be that male-owned businesses in this sector tend to be more industrialized than woman-owned businesses, which are more artisan or home-based.

TABLE IX-3: BUSINESS TRAINING AND TECHNICAL ASSISTANCE RECEIVED, BY GENDER AND ECONOMIC SUBSECTOR

Training Technical Assistance Subsector

Men Women Men Women


Food products 28.1 10.8 17.6 5.4 Commerce 14.8 18.1 9.4 11.2 Total 24.1% 19.9% 14.9% 11.3%

INTEREST IN TRAINING AND TECHNICAL ASSISTANCE

When asked if they were interested in receiving training or technical assistance to help with their businesses, 60.1 percent said they would be interested in training, and 49.6 percent said they would be interested in technical assistance (Table IX-4).

There was little difference in the responses between men and women. Neither were there major differences in the responses of microentrepreneurs in the three regions.

By sector, those in production were more interested in receiving both training and technical assistance (65.8 percent and 57.6 percent, respectively) than entrepreneurs in either services (59.5 percent and 49.3 percent) or commerce (58.4 percent and 46.9 percent).

TABLE IX-4: INTEREST IN RECEIVING TRAINING OR TECHNICAL ASSISTANCE, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Interested in Receiving Training or Technical

Assistance Men Women Coast Highlands Amazonia Services Production CommerceTotal

Training 60.0% 60.3% 59.4% 61.5% 61.1% 59.5% 65.8% 58.4% 60.1% Technical Assistance 50.7 48.3 48.4 52.1 52.0 49.3 57.6 46.9 49.6


AREAS IN WHICH MICROENTREPRENEURS WOULD WELCOME ASSISTANCE

When asked to identify areas in which they would like to receive training or technical assistance, 40.4 percent of microentrepreneurs could not identify any training that they would be interested in, and 50.7 percent could not identify any area of technical assistance they would like to receive.

Of those who expressed an interest in training or technical assistance, most expressed interest in assistance that would improve their ability to manage the business (planning, accounting, analysis of costs and prices, and general management and administration) or competitiveness (suppliers and markets or market studies and marketing). The third general area of interest was in improving products (designs, production techniques, and new technologies).

TABLE IX-5: SUBJECT AREAS DESIRED FOR TRAINING AND TECHNICAL ASSISTANCE

Training Technical Assistance Subject Areas

Total % Total % Management and administration 50,210 18.1 37,461 16.2

Planning 35,490 12.8 31,888 13.8 Accounting 40,608 14.7 35,286 15.2 Analysis of costs and prices 30,585 11.0 30,813 13.3 Suppliers and markets 30,774 11.1 22,166 9.6 Market studies and marketing 43,163 15.6 40,212 17.4

Designs 24,606 8.9 20,962 9.1 Production techniques 20,986 7.6 19,089 8.2 New technology and machinery 32,451 11.7 33,625 14.5

Personnel management 17,056 6.2 12,574 5.4 Other 49,691 18.0 25,834 11.2 Total 375,620 309,910


Given the widespread perception of problems with marketing and competition, it is a little surprising that more entrepreneurs did not identify marketing and market studies as the priority training and technical assistance need.

WOULD MICROENTREPRENEURS BE WILLING TO PAY FOR TRAINING AND ASSISTANCE?

Although the responses to any question about willingness to pay must be treated with caution, about half (49.5 percent) of the respondents indicated they would be willing to pay for training, and slightly more than half (51.1 percent) indicated they would be willing to pay for technical assistance (Table IX-6). Men were slightly more willing to pay for technical assistance and training than women. Respondents in Amazonía were the most willing to pay, while entrepreneurs on the coast were the least likely to say they would be willing to pay for technical assistance or training. Microentrepreneurs in the production and services sectors were more willing to pay than those in commerce, but the differences were not particularly large.


TABLE IX-6: PERCENTAGE OF MICROENTREPRENEURS WILLING TO PAY FOR TRAINING OR TECHNICAL ASSISTANCE, BY GENDER, REGION, AND ECONOMIC SECTOR

Gender Region Economic Sector Willing to Pay

Men Women Coast Highlands Amazonia Services Production Commerce Total

Training 52.4% 46.3% 47.6% 53.0% 61.1% 52.2% 52.8% 47.0% 49.5%Technical assistance 53.3 48.5 49.5 53.6 62.3 54.2 52.9 48.9 51.1

POTENTIAL MARKET FOR TRAINING AND TECHNICAL ASSISTANCE

Considering the subject areas that the respondents indicated they would like to receive training in, controlling for those who said they would be willing to pay, and then projecting the numbers to the total population of microenterprises in the country (rather than just the survey universe) enables the derivation of a preliminary estimate of the potential demand for marketable training and technical assistance services in the country. Using this estimation procedure, it appears that there are about 193,000 microentrepreneurs in the country that say they are both interested in and willing to pay for training, and 166,000 interested in and willing to pay for technical assistance. These preliminary estimates are intended only as a rough guide to donors and potential suppliers of nonfinancial assistance; individual market studies would be needed to confirm the demand for business planning purposes.

Because some microentrepreneurs indicated an interest in multiple training and technical assistance subjects, the potential total involvement in specific training courses and technical assistance sums to more than the number mentioned above. The potential market for specific training courses and technical assistance can be seen in Table IV-7. The percentages are percentages of those indicating an interest in and willingness to pay for the specific assistance and training, not the population of microentrepreneurs.

TABLE IX-7: POTENTIAL MARKET FOR TRAINING AND TECHNICAL ASSISTANCE, BY SUBJECT AREA

Training Technical Assistance Subject Matter

Number % Number % Management and administration 35,083 18.2 27,518 16.5

Planning 22,872 11.9 21,353 12.8 Accounting 29,870 15.5 26,608 16.0 Analysis of costs and prices 23,328 12.1 22,907 13.8

Suppliers and markets 21,921 11.4 16,190 9.7 Market studies and marketing 30,712 15.9 30,182 18.1

Designs 18,281 9.5 15,778 9.5 Production techniques 15,506 8.0 15,205 9.1 New technology and machinery 25,841 13.4 25,886 15.6

Personnel management 11,230 5.8 8,319 5.0 Other 34,508 17.9 19,322 11.6 Total 269,152 139.6 229,268 137.7



Overcoming many of the problems that microenterprises identified in Chapter VI requires knowledge and skills rather than credit. Microentrepreneurs in Ecuador are not accessing—whether because of lack of availability and opportunity or for other reasons—nonfinancial support that can help them overcome these problems. Few belong to interest groups or trade associations. Few have received training and few have accessed technical assistance. Addressing the problem of access to nonfinancial support services should be an important donor priority, even though focusing a program is challenging because of the heterogeneity of the microenterprise sector and its geographic dispersion.

X. CONCLUSIONS 127

X. CONCLUSIONS: OPPORTUNITIES FOR EXPANDING MICROFINANCE SERVICES IN ECUADOR

THE MAJOR CONCLUSIONS

Two major findings stand out as the most important conclusions of this study. First, microenterprises play an important role in Ecuador: approximately 24 percent of the urban workforce is engaged in a microenterprise activity—primarily as the microentrepreneur and to a lesser extent as an employee. Second, although microfinance has grown rapidly in Ecuador during the past few years, most microenterprises are not accessing financial services from the formal or semiformal (NGO) sector.

ROLE OF MICROENTERPRISES

Almost one-third of urban low- to middle-income households in Ecuador include at least one person who is a microentrepreneur, and a little more than 1 million people, about 24.3 percent of the urban workforce, are engaged in a microenterprise activity—either as the entrepreneur or as an employee/worker. The definition of microenterprise for the purposes of this study was very restrictive—enterprises employing fewer than 10 persons (including the owner), that are owned and operated by lower- to middle-income families. If the definition is expanded to include professionals (lawyers, accountants, and consultants, for example), agricultural enterprises (especially small farms), and day laborers (especially persons in the construction subsector who perform labor on diverse job sites), the numbers would be much larger. Regardless of the definition, microenterprises provide income-earning employment for a very large segment of the adult national population.

On the economic side, urban microenterprises in Ecuador have annual sales of approximately $6.03 billion and earn about $2.36 billion in net income. Microenterprise sales are approximately 25.7 percent of Ecuador’s GDP,69 and net income is about 10 percent of GDP. Microenterprises are, therefore, an important economic activity for the country and for a large segment of the Ecuadorian population.

Microenterprises are especially important for women because women are disproportionately active as microentrepreneurs compared with their participation in the economy as a whole. Microenterprises provide important income-earning opportunities for single women (single, divorced, separated, or widowed) and for women who need to combine household and business activities. It is through a microenterprise that a substantial percentage of women enter the workforce and earn income for themselves and their families.

Moreover, the microenterprise sector will continue to play an important role in the country’s social and economic life. Although the microenterprises are not particularly dynamic and employ relatively few nonfamily employees, most microentrepreneurs are satisfied with their businesses and the income they provide, and do not plan to seek salaried employment.

PARTICIPATION IN MICROFINANCE

The second major finding is that, for the most part, microentrepreneurs do not participate in the formal financial sector. Only 29 percent have savings accounts in financial institutions and only 15.7 percent had applied for a loan during the past 12 months. Very few said they regularly use financial

69 Ecuador’s GDP is estimated at $23.5 billion (UNICEF data for 2003).


institutions and almost none considered borrowing to be a regular source of financing for their businesses.

Ecuadorian microentrepreneurs expressed considerable caution about using credit. More than half of those who had not applied for a loan during the previous 12 months said they either were not interested and had no need for a loan (14.2 percent) or did not want to become indebted (36.6 percent). For many this obviously reflected a fear of becoming indebted. But for others, including many of those who said they did not want to become indebted, this seems to be the result of not being convinced that external financing will help their businesses grow. They rely on sales and their own resources for financing. Although credit is not a panacea for the problems facing microenterprises, properly used, credit can permit an enterprise to grow beyond what would be possible if only personal resources and business income are used to finance the business. Currently, most microentrepreneurs seem to view credit as a costly, high-risk proposition that should be avoided if at all possible. Misunderstandings about microfinance institution procedures and requirements also appeared to discourage credit applications.

Two conclusions result from the pattern of credit access observed in the survey responses. First, there is a potential for growth in microfinance services to microentrepreneurs. The fact that only 15.7 percent of microentrepreneurs have applied for a loan during the past year suggests that there is a potentially large unserved market for microfinance services. Second, programs that seek to encourage poorer households to use credit need to provide extra, nonfinancial, support and counseling to help potential clients understand the possible benefits and limitations of using credit in their businesses, and to assist them to apply for and manage loans.

OTHER KEY FINDINGS

In addition to the two major findings, there are others that have specific implications for MFIs.

LACK OF AWARENESS OF MICROFINANCE INSTITUTIONS

First, microentrepreneurs are generally not aware of microfinance programs. Only 34.7 percent could spontaneously identify an institution that lends to microentrepreneurs. Even major actors in the microfinance field were recognized by only a small percentage of microentrepreneurs. The lack of recognition that such programs even exist may be a major cause for the low incidence of loan applications among microentrepreneurs, especially those in poorer households.

MICROENTERPRISES ARE NOT GROWING BUSINESSES

Second, microenterprises are relatively stagnant. There is little indication that microenterprises are growing or expanding, that income levels are rising, or that they will become larger businesses. Relatively few microentrepreneurs (15 percent) said their sales were growing year-to-year. Even fewer (only about 10 percent) have added employees since they were started; employment generation occurs at the moment of starting the business, with very little employment growth after that. Also, few microenterprises exhibited the kinds of investment or improvements that normally accompany successful businesses—moving to better workplaces, making improvements to existing spaces, or investing in equipment and machinery. Microenterprises are, by and large, permanent and stable enterprises providing income for single families, and most are likely to remain so.

At the same time, there are microenterprises that are both capable of and interested in growing. Identifying them is a major challenge for microfinance institutions because these businesses represent the best opportunity for developing a growing financial partnership for the MFIs.

X. CONCLUSIONS 129

MICROENTREPRENEURS ARE SATISFIED AND OPTIMISTIC

Although the microenterprises showed little signs of growth, their owners had surprisingly positive attitudes about the businesses. A sizeable majority (58.7 percent) said they were satisfied or very satisfied with their businesses. An even larger majority (68.7 percent) said their businesses provided a better income than they could earn as employed workers. And 37.6 percent scored as Satisfied or Very Satisfied on a composite index of satisfaction.

Microentrepreneurs were also optimistic about their business future: 69.1 percent said their business prospects were good or very good and 70.5 percent said they wanted to expand their businesses rather than seek other employment.

The high level of satisfaction with the business and optimism for the future suggests that these are stable, permanent businesses. As such, they would probably be good credit clients.

MANY FACTORS INFLUENCE BORROWING AND SAVINGS PATTERNS

Patterns of financial service use vary by gender, region, sector of the economy, and economic status. The role of gender in patterns of microfinance activity is particularly complicated and complex. Woman-owned businesses were much smaller than those owned by men: female entrepreneurs reported fewer business assets than men; the amount of investment in woman-owned businesses is less; and average business income is less than half that of their male counterparts, even within the same economic sectors. Perhaps related to this, the average loan received by women was about half (52.9 percent) the amount received by men. Far fewer women than men were using microcredit, but that is because there were far fewer female microentrepreneurs. On a relative basis, however, women entrepreneurs were just as likely to apply for and receive loans as men—there appeared to be no inherent bias against women entrepreneurs by the established MFIs.

Region plays a very important role in patterns of credit use. Microentrepreneurs on the coast were the most likely to report that they had difficulty accessing credit, and were the least likely to apply for and obtain loans. Sales and income earned from businesses also tend to be lower on the coast, which may account for at least some of the difference in accessing credit. However, the fact that fewer microfinance institutions operate on the coast is also an important factor.

There is a strong relationship between level of wealth and loan access. Wealthier microentrepreneurs—as measured by the wealth index created by Habitus Investigaciones, S.A.—were consistently more likely to apply for and receive loans than their poorer counterparts. However, extremely poor women apparently have greater access to credit than expected, possibly because of NGO programs that specifically target poor female entrepreneurs.

The economic sector also had an influence on the purpose of borrowing. According to survey responses, those in the commerce sector borrowed primarily for inventory, while those in production and services had a greater tendency to borrow for equipment, machinery, and vehicles (especially among the transportation sector). The different characteristics of these loan purposes would suggest that substantially different products are required to serve the different economic sectors.

IMPLICATIONS FOR MICROFINANCE INSTITUTIONS

There are certainly opportunities for MFIs to grow and expand services. The low rate of usage of financial products and services by microenterprises suggests that the potential market for aggressive MFIs is substantial.


GROWTH STRATEGIES

There are two basic growth strategies that a microfinance institution could adopt: expanding the breadth of its market by geographic expansion to serve new clients, or expand locally by gaining a larger share of the market. Of course, a rational strategy might include elements of both, but they are conceptually different enough to demand separate consideration.

Expanding Market Breadth

It is immediately apparent from a map of microfinance coverage (see Figure VIII-3) that in most cantones in Ecuador the percentage of clients served is very low. Expansion into market areas of low coverage offers an opportunity for a microfinance institution to grow and expand its client base. Market potential varies by geographic region, size of town, local economic conditions, and the presence of competitors. This study provides a general background for understanding the broad characteristics of the potential market for credit and other microfinance services, and can be used to select geographic areas for further study.

Projections of potential demand for credit for business purposes by microentrepreneurs range from $206.2 to $656.7 million. Most of this potential demand is concentrated in the large and medium-sized urban centers and in other very specific locations (see Figure VIII-4).

But potential demand is also influenced by current lending patterns. As data from the Superintendency of Banks and Insurance show, there is already some $241.0 million outstanding in “microcredit”—much of which has ostensibly been lent to microenterprises. Calculating the degree of saturation based on numbers of potential borrowers and projected average loan sizes indicates that there is still a substantial unfulfilled potential demand for credit among microentrepreneurs in Ecuador.

Potential demand can also be affected by competition. There are a fair number of MFIs in Ecuador, though they tend to be concentrated in a few urban locations. The distribution of MFIs, which an institution seeking to broaden its market should be acutely aware of, can be seen in Figure VIII-2. Additional analysis of data from the survey and from the Superintendency of Banks and Insurance could examine population per branch outlet in a given area, a measure that is frequently used to estimate market saturation.

Data from the survey suggest that there is a potentially large market for microfinance in the country, but more in-depth market analyses by the institutions involved are required to enter those new markets successfully.

Increasing Penetration of Existing Markets

The second major strategy that a microfinance institution can pursue is to increase its penetration of an existing market, increasing the numbers of clients served by existing branches and intensifying the use of services by existing clients. The fact that only 15 percent of microenterprises received loans during the past year, even in areas served by existing MFIs, suggests that this would be an appropriate strategy for most institutions. There appears to be a large number of microenterprises in currently served markets that are not clients of any microfinance institution; marketing to these clients would be a less expensive alternative for expansion than opening new branches or initiating services in previously unserved areas. Also, the fact that so few microentrepreneurs use other financial services suggests that cross-selling products could result in more profitable operations.

It appears from responses to this survey that MFIs seeking to expand their client base should be primarily concerned with improving the quality of service they provide—at least in the short run. Although microentrepreneurs felt that interest rates on savings were too low, and those on loans too high, these were not the most important factors they considered in making savings and borrowing

X. CONCLUSIONS 131

decisions. Decisions to save were prompted more by a sense of stability, safety, and security than by interest rates. Complaints against credit institutions focused more on convenience, procedures, guarantees, courteous treatment, and time required to obtain a loan—complaints related to the noninterest borrowing costs involved in obtaining and repaying loans—than on the interest rate that was charged.

In the short run, therefore, institutions would be well advised to focus on improving these aspects of their business. As competition increases, as interest rates and commissions become more transparent, and as transactions costs are reduced for clients, interest rates—both on savings and loans—may become a more important factor in competitive positioning.

MATCHING LOANS TO CLIENT CAPACITY

A second issue that MFIs need to focus on is that absorptive capacity varies greatly among microentrepreneurs. The various economic sectors and subsectors exhibit marked differences in sales, income levels, and profitability. These vary also by gender and region. Limits on absorptive capacity affect potential loan size, overall demand, repayment capacity, and risk (both to the borrower and to the lender). Some sectors and clients also have highly seasonal activities.

Tailoring loans to fit the capacity of borrowers—in terms of payment frequency and schedule as well as amount and terms of loan—is important for maintaining portfolio quality and avoiding delinquency problems. Institutions that have a fixed approach to loan products or that are not sensitive to the particular needs of individual clients may generate problems of overindebtedness or cause microentrepreneurs to seek services elsewhere; those with flexible products tailored to the specific needs of individual clients will attract clients and develop loyalty and repeat business. In particular, MFIs need to understand the business dynamics of the microenterprise, and match products to the capabilities and characteristics of the enterprise.

PRODUCT MIX AND INTEREST RATES

Finally, MFIs need to recognize that their current product mix may not fit client needs. There was little evidence of demand-driven product design, that is, institutions designing or modifying products based on surveys of clients and potential clients or consideration of the business cycle of different segments of the potential client market. Although this may not be important in an environment of limited competition, as competition increases among financial institutions for the microenterprise market, having products that match client needs will give institutions a competitive edge.

Similarly, at present, interest rate competition does not exist among MFIs in Ecuador. As markets become more competitive, however, and rate structures more transparent, institutions can expect microentrepreneurs to become more sensitive to differences in interest rates.

IMPLICATIONS FOR DONORS

Donors generally have their own internal priorities and objectives, though these tend to overlap in the areas of poverty alleviation, improving the status of women, reaching rural populations, and stimulating economic growth. The microenterprise field encompasses all of these diverse objectives.

POVERTY IMPLICATIONS

There is certainly a poverty dimension to the subject of microenterprise development and microfinance. The data collected for this study show that poorer segments of the microenterprise


population have less access to formal and semiformal (NGO) sector financial services. They were less likely to have savings, less likely to apply for or obtain loans, and less likely to use other financial services such as ATMs, credit cards, checking accounts, or money transfers.

Donors interested in addressing the poverty issue will find that there is still a large opportunity to expand microfinance services downward to reach and benefit poorer segments of the population.

However, an unresolved question is whether the poor really have less access to financial services, or whether they simply demand less. If they demand less, the real issue is to understand why they demand less, and address those constraints. Providing improved access to financial services is of little value if the intended beneficiaries do not want those services. Additional analysis of the relationship between wealth (as measured by the ICV) and other questions in the survey might provide additional insights into whether the poor really do not have access to financial services, or simply demand less.

REACHING WOMEN

Although the survey indicates that women are not discriminated against in access to financial services, there are large numbers of female microentrepreneurs who do not use external financing for their businesses, do not have savings in financial institutions, and are not served by either formal or semiformal financial institutions. The main exception to this is that women in the lowest socioeconomic status actually access credit to a greater degree than men in this socioeconomic group, probably due to the emphasis placed on reaching poor women by many NGOs.

Donors seeking to target this market need to recognize, however, that merely increasing access to credit—at any cost—may not represent a positive benefit to female entrepreneurs in the absence of complementary programs to reduce other constraints and problems that they face. In particular, women microentrepreneurs generally lack mobility (both their work and markets are limited to their home markets) and are concentrated in such a limited number of economic subsectors (occupations) that they face severe constraints in markets and product competition. Addressing these constraints may be more important than increasing the volume of credit available to women entrepreneurs.

EXTENDING FINANCIAL SERVICE TO RURAL AREAS

This study, for practical and cost considerations, did not include the rural sector. Although the rural sector has been declining in relative importance in recent years, there is still a sizeable rural population of self-employed, economically active persons. Because poverty is so closely related to “ruralness,” donors are well advised to take a strong interest in this area and to continue support for expanding financial and nonfinancial services deeper into rural areas.

STIMULATING ECONOMIC GROWTH

The focus of some donors has shifted from poverty alleviation and microenterprise development to an economic growth focus on financial institution sustainability and larger enterprises that are capable of generating employment. There is nothing inherently wrong or incorrect with this change in focus. Formal sector financial institutions are well suited to providing financial services to those sectors of the microenterprise sector that are interested in growing and expanding. The natural tendency of microfinance institutions is to go upmarket—to increasingly serve larger enterprises, more successful enterprises, and growing enterprises rather than continue a social or poverty alleviation focus.

X. CONCLUSIONS 133

OTHER OPPORTUNITIES

The problems faced by the respondents to the survey suggest that, in many if not most cases, providing increased access to credit may not be effective in stimulating the growth and success of microenterprises.

Using formal sector credit can help a business produce more, or produce what it does at lower cost—both of which can be positive benefits. However, if the problem is one of too many competitors in a limited market, or too little purchasing power in the client population, producing more may not help. Producing something at lower cost may improve margins, but only if there is demand for the goods or services in a competitive market.

Many of the conditions described by the respondents—increasing competition, lack of growth in sales, little demand—suggest that increasing the supply of credit may not benefit many microentrepreneurs. Donors need to consider the types of nonfinancial services that can make a difference in market segmentation, improved quality of product, more efficient production, marketing, and understanding client tastes.

FOLLOW-ON RESEARCH SUGGESTIONS

The comprehensive database assembled for this study offers great opportunities to conduct more detailed analysis on a nationally representative sample concerning some of the issues that were touched on briefly in this report but were not analyzed in great detail because they fell outside the immediate objectives of the study. Additional data collection and research would be needed to explore a number of other important topics that were raised or hinted at by responses to the survey, but were not analyzed in depth because the broad nature of the survey prevented detailed follow-up questions.

One such issue is the apparent discrepancy between the relatively small number of microentrepreneurs who said they had applied for and been granted loans during the preceding year (projected to a total of 101,091 microentrepreneurs, or 15.7 percent of the population of microentrepreneurs), and the reported totals of microcredit clients and loans in the regulated microfinance institutions (some 242,000 active “operations” in August 2004). The difference may be due to a combination of factors—that the MFIs are providing loans to a different (wealthier) group of microentrepreneurs than those covered by the study, that a large percentage of so-called “microcredit” loans are really consumer loans, and that the “operations” recorded in the data of the Superintendency of Banks and Insurance include multiple loans to single clients. Knowing the answer to this apparent contradiction should be important to MFIs, donors, and the Government of Ecuador.

Individual institutions should expend more effort studying their clients and nonclients to determine what appeals—what will attract borrowers.

Another potential research topic centers on exploring the attitudes and perceptions that clients and nonclients hold of specific microfinance institutions and how they would respond to different initiatives to attract their business. The broad questions suggest a lack of awareness of financial institutions offering loans to microentrepreneurs, a fear of becoming indebted, and a feeling that the procedures for obtaining financial services are too cumbersome and time-consuming. Individual institutions should undertake their own smaller research activities to explore these general findings in greater detail among their own clients and potential clients, in order to plan better and more effective marketing strategies.


A third general area of investigation should center on testing whether microentrepreneurs are really as insensitive to interest rates as they appear to be. Would they respond positively to interest rate incentives?

The wealth index generated by Habitus Investigaciones, S.A. provides a fourth and unique opportunity to test a number of important issues concerning potential differences in the poverty or wealth levels of microentrepreneurs, and how these might affect business potential and performance and income generation. For example:

• Do the entrepreneurs in poorer households have different types of enterprises than wealthier ones?

• Do they perform as well?

• Are their markets different?

• Do they sell to different types of customers?

• Do the entrepreneurs have different patterns of opinions and perceptions?

• Do they exhibit as much dynamism?

• Are their capital structures and investment patterns different?

Fifth, the survey results revealed that only about 15 percent of those interviewed had applied for loans during the past 12 months. It would be useful to compare borrowers and nonborrowers to determine if they vary systematically by characteristics of households and entrepreneurs, types of enterprises, enterprise performance, income level, perceptions and opinions, and access to training and technical assistance. Information about such differences would help clarify why so many chose to not apply for credit. This information would also be useful in developing models and strategies for efficiently targeting potential new clients. Detailed analysis of these data might also help identify if different types of entrepreneurs hold different opinions about financial products and services, and would be the first step in determining how to redesign products to fit different types of clientele.

A sixth general area of research that might yield valuable insights into microenterprise dynamics would be to examine slightly larger enterprises to see if (1) they have evolved from microenterprises, and (2) what factors account for successful growth. This survey found little indication that firms were growing or evolving into larger businesses, but a study of larger businesses may reveal that, in fact, such growth has taken place. The results could help MFIs better target businesses with a high potential for growth, or to at least define specific products to serve those businesses.

And finally, if a subset of the sample could be reinterviewed in a few years and the results compared with this survey,70 some insights could be obtained into dynamic enterprise questions, with important implications for microenterprise and microfinance policies:

• How many of these firms will still be operating?

• Will many have been closed and new ones started?

• Will many of them have modernized or expanded in important ways?

• Will many firms have made significant breakthroughs to access larger, more dynamic markets?

70 Note that this would require saving the physical copies of the present, completed questionnaires in order to

identify and locate respondents to be reinterviewed.

X. CONCLUSIONS 135

• Will the enterprises of the poor have grown and modernized as quickly as those of wealthier microentrepreneurs?

• Will the income gap between the poorer and wealthier microentrepreneurs have widened or narrowed?

• Will a significant number of the poor have shifted from lower- to higher-income enterprises?

• Will there have been a discernable impact on enterprise performance through improved access to training, technical assistance, and credit?

• Will such improvements have been as important for the poor as for the wealthier microentrepreneurs?

Data contained in the databases and reports for this study can be used to explore many of these questions in greater depth and to suggest further topics for reach and analysis that will improve services to Ecuadorian microentrepreneurs.

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