Accounting for the Diversity of Rural Income Sources in Developing Countries:

The Experience of the RIGA Project

Katia Covarrubias, Ana Paula de la O & Alberto Zezza

ESA

Wye City Group Meeting on Statistics on Rural Development and Agriculture Household Income

Rome, June 11-12, 2009

The Rural Income Generating Activities Project

Database of 34 living standards surveys Outputs:

Income Aggregates Household Level Indicators

Access to capital Demographic indicators Additional analysis-specific indicators

Methodological Goal: Consistency and Comparability

RIGA Data: 34 Survey Countries Africa

Ghana GLSS (1992, 1998*) Kenya KIHBS (2005) Madagascar EPM (1993, 2001) Malawi IHS (2004*) Nigeria (2004*)

Asia Bangladesh IHS (2000*, 2005) Cambodia SES (2004) Indonesia FLS (1992, 2000*) Nepal LSS (1996, 2003*) Pakistan HIES (1991, 2001) Vietnam LSS (1992, 1998*,

2002*)

Eastern Europe/Central Asia Albania LSMS (2002, 2005*) Bulgaria IHS (1995, 2001*) Tajikistan LSMS (2003*, 2007)

Latin America Bolivia EH (2005) Ecuador ECV (1995*, 1998) Guatemala ENCOVI (2000*,

2006) Nicaragua EMNV (1998*,2001*) Panama ENV (1997, 2003*)

* Labor Data also Available at the Individual and Job Levels

Income Aggregates: Defining Income

Income must: Occur regularly Contribute to current economic well-being

(available for current consumption)

Income must not: Arise from a reduction in current net-worth Arise from an increase in household liabilities

Source: ILO, Resolution I “Resolution concerning household income and expenditure statistics” Available from: http://www.ilo.org/public/english/bureau/stat/download/res/hiestat.pdf

Income Aggregates: Basic Characteristics

Household-level Labor data also available at the Job and Individual levels

Annual Wage income data: also for daily and monthly time

frames Net of costs Purchases and sales of durables, investments and

windfall gains excluded Local currency units Rural (and urban) Outlier checks

RIGA

Issues and Lessons Learned

Income Estimation

Components of Total Household Income

Dependent Wage Income

agricultural non-agricultural

Independent Crop Livestock Self Employment Transfers

public private

Other Sources

Total Household Income ClassificationsTotal Income:

Agricultural: Agwge + Crop + LivestockNon-agricultural: Nonagwge + Selfemp + Transfers + Other

On-farm: Crop + LivestockOff-farm: Agwage + Nonagwge + Selfemp + Transfers + Other

Non-farm: Nonagwge + Selfemp

iii turalNonagriculalAgriculturY

iiiiiiii OtherTransferSelfempLivestockCropNonagwgeAgwgeY

iii OffarmOnfarmY

Total Household Income

Agwage

Nonagwage

Crop Livestock

Selfemp

Transfer

Other

On-farm

Agricultural

Off-farm Non-Agricultural

Non-farm

Dealing with CostsIssue: Dealing with investment/durables

expenditures Misclassification: bias total income Example: raw materials purchases (Albania;

Vietnam)

Recommendations: Clear classification of costs in survey instrument Appropriate choice of reference periods and

frequencies

Gross versus Net

Issue: Inconsistent reporting & estimation of gross/net income

Recommendations: In Qx: deductions and taxes should be asked about

and reported In income estimation:

Net: agricultural, self-employment and wage income

Gross: rental income and transfer income

RIGA

Issues and Lessons Learned

Questionnaire Design

Reference PeriodsIssue: Defining appropriate reference periods Choice of Short v. Long

seasonal fluctuations relevance to recall error link to survey timing phrasing of questions

Recommendations: Reference periods should reflect frequency of Inc/Exp Short: Regular or frequent sources (food exp, wages,

etc.) Long: Infrequent sources (business costs; ag inputs,

etc.)

Units & CodingIssue: Comparability and Standardization of Units and

Coding Variability of unit reporting Lack of equivalence scales in data and documentation Inconsistency in units and codification of items across

survey modules Agricultural Production and Food Expenditure modules

Recommendations: YES to local unit reporting but: Inclusion of equivalence scales Consistency in codification within/across survey modules

RIGA

Lessons Learned

From Key RIGA Results

RIGA Results: Main Components of Rural Household Income

020

4060

8010

0S

hare

s of

Inco

me

(%

)

MAL

04

MAD 9

3

BNG 00

NEP 03

GHA 98

TAJ 03

VNM 9

8

NIG 0

4

PAK 01

NIC 0

1

IND 0

0

GUA 00

ALB 0

5

ECU 95

BUL 01

PAN 03

Note: 1. Surveys sorted by increasing per capita GDP 2. Expenditure quintiles move from poorer to richer

by expenditure quintilesShare of total income from main income generating activities

On farm Activities Agricultural Wages

Transfers and Other Non-Labour Sources Non-farm Activities

On-farm income falls and Non-farm rises...

ALB 05

BNG 00

BUL 01

ECU 95

GHA 98

GUA 00

IND 00

MAD 93MAL 04

NEP 03

NIC 01

NIG 04

PAK 01

PAN 03

TAJ 03

VNM 98

10

20

30

40

50

60

Sh

are

of

Inco

me

fro

m N

on-

farm

Sou

rce

s

6.5 7 7.5 8 8.5 9Log Per Capita GDP (PPP, Constant 2005 $)

Note: On-farm income is comprised of income earned from crop and livestock activities. 2. Fitted curve fits the quadratic prediction of the income shares on per capita GDP.

Share of On-farm Income by Per Capita GDP

ALB 05BNG 00

BUL 01

ECU 95

GHA 98

GUA 00

IND 00

MAD 93MAL 04

NEP 03

NIC 01

NIG 04

PAK 01

PAN 03

TAJ 03

VNM 98

20

30

40

50

60

70

Sh

are

of

Inco

me

fro

m N

on-

farm

Sou

rce

s

6.5 7 7.5 8 8.5 9Log Per Capita GDP (PPP, Constant 2005 $)

Note: Non-farm income is comprised of income earned from non-agricultural wages and self employment.

Share of Non-farm Income by Per Capita GDP

...with increasing per capita GDP levels.

RIGA Results:Diversification of Rural Household Income

Defining Specialization and Diversification: Specialization >= 75% Diversification <75%

Influenced by survey timing and reference period: seasonal diversification individuals member diversification

Rural income diversification is the trend

On-farm specialization falls with PCGDP

ALB 05

BNG 00

BUL 01

ECU 95

GHA 98

GUA 00IND 00

MAD 93

MAL 04

NEP 03

NIC 01

NIG 04

PAK 01

PAN 03

TAJ 03

VNM 98

01

02

03

04

05

0S

har

e o

f F

arm

-Spe

cial

ize

d H

ouse

hold

s

6.5 7 7.5 8 8.5 9Log Per Capita GDP (PPP, Constant 2005 $)

On-Farm Specialization by Per Capita GDP

ALB 05

BNG 00

BUL 01

ECU 95

GHA 98

GUA 00IND 00

MAD 93MAL 04

NEP 03

NIC 01

NIG 04

PAK 01

PAN 03

TAJ 03

VNM 98

01

02

03

04

0S

har

e o

f H

ouse

hol

ds S

pec

ializ

ed

in N

on-

Agr

icu

ltura

l Wa

ges

(%

)

6.5 7 7.5 8 8.5 9Log Per Capita GDP (PPP, Constant 2005 $)

Specialization in Non-Agricultural Wage Labour by Per Capita GDP

...but Non-agricultural wage specialization rises.

RIGA Results: Defining the Agricultural Household

“Rural” as “Agricultural” lack of data to create comparable rural definition urban agriculture dwelling versus job location diversity of rural economy

Thresholds of income Non-zero (basic participation) Higher cut-offs

Occupation of the household head

RIGA Results: Sensitivity and Criteria in Agricultural Households Definition

Source: Aksoy, et al. (2009)

Survey

Percent Rural

Total Total Total

Peru (2003) 35.9 37.5 20.3 36.4Ecuador (1995) 37.4 43.9 19.9 26.4Bolivia (2002) 42 96 26.7 33.0Nicaragua (2001) 43.9 80.5 28.7 29.8Zambia (1998) 47.8 70.1 52.2 48.4Ethiopia (2000) 50.7 71.3 58.4 68.0Guatemala (2000) 56.7 70.2 31.4 38.7Cambodia (1999) 60 86.1 71.7 n.a.Ghana (1998) 63.3 65.5 52.3 49.7Pakistan (2001) 71 55.9 37.3 31.5Vietnam (1998) 71.2 92.7 62.3 60.8Madagascar (2001) 75.8 71.2 63.5 62.3Bangladesh (2000) 79.7 61.3 26.7 48.2

Nepal (2003) 87.4 90.6 59.8 49.5Malawi (2004) 88.1 89 77.5 66.3

Unweighted average 60.72 72.12 45.92 46.4

Shares of Households with Agricultural

Income > 30%

Share of Agricultural Households by

Occupation

Shares of Households with Positive

Agricultural Income

Summary and Conclusions Estimation of Income

Various approaches for characterizing household income Costs classification Reporting of deductions/taxes relevant

Questionnaire Design: Reference periods should reflect frequency of income

and expenditures Need for equivalence scales/conversion factors Unit and coding consistency within surveys.

Analysis: Different definitions of agricultural household exist;

generate differing characterization of results

Thank You!

Questions?