Page 1 of 15 PROFILE OF THE POOR IN NCR: AN ANALYSIS by Lourdes V. Homecillo 1 Keywords: family, household, family size, poor families, total income, annual per capita income, housing, expenditures INTRODUCTION Poverty is a global concern as highlighted in goal no 1 of the MDG – to eradicate extreme poverty and hunger. Based on the new poverty estimates from the World Bank, the 2013 MDG Report of the United Nations underscores the fact that the world had reached the MDG target five years ahead of the 2015 deadline. The report further noted that In developing regions like Southeastern Asia and China, the proportion of people living on less than $1.25 a day fell from 47 percent to 22 percent in 2010. Government and non-government interventions to alleviate the status of the poor can then be effectively managed only if there is adequate information about the poor and their living conditions. The official poverty incidence released by the National Statistical Coordination Board (NSCB) for the entire country in 2009 was estimated at 20.9 percent, down by 0.95 percent in 2006. This poverty incidence revealed that poor families were living below the annual per capita poverty threshold of P16,841 in 2009. The picture is a bit encouraging in the National Capital Region (NCR) where only 2.6 percent of families were estimated to be living below the annual per capita poverty threshold of P19,802. This represents an improvement with poverty incidence down by 23.5 percent from the 2006 level. However, the poverty situation in District I Manila and District III of NCR was more pronounced as the incidence rates were comparatively higher than that of the entire region, at 3.8 percent each. Poverty generally thrives in areas that are densely populated. Most likely, the densely populated cities of Manila (in District I) and Navotas, Caloocan, and Malabon all (in District III) are the identified areas where there were relatively high incidence of poverty in 2009. OBJECTIVES This study has two main objectives. First, it aims to provide an analysis of the characteristics of poor families in the NCR and their housing conditions using a framework for poverty analysis. The consumption patterns based on the public use file of the 2009 FIES were likewise analyzed vis-à-vis the consumption of all-income households. The second objective is to identify those characteristics that are significantly related or associated to poor families. CONCEPTUAL FRAMEWORK The study adopts the framework postulated by Ward (1999) in measuring the characteristics of the poor, which consists of two fundamental dimensions: (1) flows of income, and (2) interrelated stock or status of poor people. The first dimension identifies the people who 1 National Statistics Office (NSO), National Capital Region (NCR)
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PROFILE OF THE POOR IN NCR: AN ANALYSIS
by
Lourdes V. Homecillo1
Keywords: family, household, family size, poor families, total income, annual per capita income, housing, expenditures
INTRODUCTION
Poverty is a global concern as highlighted in goal no 1 of the MDG – to eradicate extreme poverty and hunger. Based on the new poverty estimates from the World Bank, the 2013 MDG Report of the United Nations underscores the fact that the world had reached the MDG target five years ahead of the 2015 deadline. The report further noted that In developing regions like Southeastern Asia and China, the proportion of people living on less than $1.25 a day fell from 47 percent to 22 percent in 2010. Government and non-government interventions to alleviate the status of the poor can then be effectively managed only if there is adequate information about the poor and their living conditions.
The official poverty incidence released by the National Statistical Coordination Board
(NSCB) for the entire country in 2009 was estimated at 20.9 percent, down by 0.95 percent in 2006. This poverty incidence revealed that poor families were living below the annual per capita poverty threshold of P16,841 in 2009. The picture is a bit encouraging in the National Capital Region (NCR) where only 2.6 percent of families were estimated to be living below the annual per capita poverty threshold of P19,802. This represents an improvement with poverty incidence down by 23.5 percent from the 2006 level. However, the poverty situation in District I Manila and District III of NCR was more pronounced as the incidence rates were comparatively higher than that of the entire region, at 3.8 percent each. Poverty generally thrives in areas that are densely populated. Most likely, the densely populated cities of Manila (in District I) and Navotas, Caloocan, and Malabon all (in District III) are the identified areas where there were relatively high incidence of poverty in 2009.
OBJECTIVES
This study has two main objectives. First, it aims to provide an analysis of the characteristics of poor families in the NCR and their housing conditions using a framework for poverty analysis. The consumption patterns based on the public use file of the 2009 FIES were likewise analyzed vis-à-vis the consumption of all-income households.
The second objective is to identify those characteristics that are significantly related or
associated to poor families. CONCEPTUAL FRAMEWORK
The study adopts the framework postulated by Ward (1999) in measuring the characteristics of the poor, which consists of two fundamental dimensions: (1) flows of income, and (2) interrelated stock or status of poor people. The first dimension identifies the people who
1 National Statistics Office (NSO), National Capital Region (NCR)
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are poor, as measured by the poverty threshold, which is determined by countries based on accepted official methodology.
Ward (1999) specified two categories under the stock dimension, as follows: single stock
dimension and multi-dimensional. The single dimension is made used in this study and includes the demographic, economic, social, and intangible measures.
The table below presents details of these measures in the stock dimension.
Demographic Household characteristics, eg. household size, sex and marital status of household head, members 15 years old and over, employed members
Economic Ownership of land, property, productive assets
Skills and job experience
Employment and occupation
Possession of other financial and liquid assets, e.g. jewelry
Social Housing quality and location
Services available
Access to supporting services and facilities, e.g. physical, economic, legal and institutional
Human capital, e.g. educational level, health status
Intangibles Independence, security, political freedom equality
REVIEW OF LITERATURE
Numerous literatures on poverty analysis present the household as the unit of observation rather than the individuals living in the household. Though many household surveys collect information about income of individual household members, Vos and Mejia (1999) argued that welfare measure must be based on income or consumption of the household, rather than on the individual. There are many household income sources not fully attributed to the individual household member, such as income from family business or property income on assets shared by the household. They further argued that this also holds true for consumption items as household members typically share many ‘public goods’ that cannot be assigned to specific members. Under these conditions, certain assumptions are made: (1) welfare is equally distributed within the household, (2) needs are the same for each household member, and (3) there are no economies of scale in household consumption.
A similar argument was presented by Atkinson (1990) on the choice of the household as
the unit of analysis in poverty. The household constitute an economic unit in which resources are shared on equal terms by all its members. The consequence of this is that the household acts as filter that tends to dampen the poverty and inequality in the distribution of income. Thus the information provided by the household gives a more accurate impression of the real level of welfare enjoyed by its members (Bellido, 1999).
Consumption
In the study of consumption patterns of poor families, the Engel’s Law apply particularly on food expenditures. The Engel’s Law is an economic theory introduced in 1857 by Ernst
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Engel, a German statistician, stating that the percentage of income allocated for food purchases decreases as income rises. As a household's income increases, the percentage of income spent on food decreases while the proportion spent on other goods, such as luxury goods, increases.
Engel's Law similarly states that lower income households spend a greater proportion of
their available income on food than middle- or higher-income households. As food costs increase, both for food at home (such as groceries) and food away from home (for example, at a restaurant), the percentage spent by lower income households is expected to increase.
Studies on consumption based on household surveys show that across many developing countries, expenditures for food accounts for the highest share. In developed countries like the US, the pattern is quite different. The US Bureau of Labor Statistics reported that in the 2009 to 2011 consumer expenditure survey the proportion of food expenditure ranked only third, after housing and transportation. SOURCES OF DATA
The study made use of secondary data which were obtained from the public use file (PUF) of the 2009 Family Income and Expenditure Survey (FIES) of the National Statistics Office. While the unit of enumeration refers to families, the data was collected at the level of the households in the FIES.
LIMITATIONS OF STUDY
Since the FIES primarily aims to collect information on income and consumption patterns of families, information for analyzing access to social services and presence of intangible measures are not available.
Except for data on income, expenditures, and house rental which are presented for the entire year of 2009, all other information about the household (sex, age, marital status, education, employment status and occupation of the household head; household type; household members; employed members; and housing characteristics including ownership of appliances) refer to data collected during the second visit of FIES, that is, for the second semester of 2009 only.
The FIES, being a household survey, excludes by design all population not living in households, which means that the homeless or those living in unstructured housing units were not included in the coverage. For analysis of poverty, this is a drawback as some of the very poor are not considered in the study (Bellido, et al.).
At the household level, the education of the household head, which was originally coded (in nominal term), was translated to estimated years in school attendance. For instance, college undergraduate was translated to 10 years, college graduate to 12 years, high school graduate to 8 years, high school undergraduate to 6 years, elementary undergraduate to 3 years, and elementary graduate 6 years. These values were however not validated. METHODOLOGY
Data of poor families were extracted from the 2009 FIES public use file (PUF) prepared by the NSO. Poor families, as defined in this study, are those whose annual per capita income
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falls below the official poverty threshold for NCR in 2009 which was estimated at P19,802. Descriptive analysis was used to present the state of the poor families in NCR, their housing characteristics and consumption pattern by major expenditure group. Correlation analysis was also used to identify the relationship of the characteristics of poor families.
Regression analysis was done to determine which of the predictor variables (household
characteristics) displayed significant effect on the predicted variable ( total income). VARIABLES
Selected variables used in the study are those available in the 2009 FIES PUF and classified according to the framework earlier presented.
FIES Variables
Flows of income Annual family income Average annual per capita income
(derived)
Stock Dimension
1. Demographic Age/ sex/ and marital status of
household head
Family size
Employed members of family
Family members 15 years old & over
Employed spouse of household head
2. Economic Employment Class of worker Ownership of property: TV, refrigerator
3. Social Education (years of shooling) of household head Housing type Tenure of housing unit Construction materials of roof Construction materials of outer walls Electricity supply Source of water Toilet facilities
RESULTS The summary of the characteristics of poor families in NCR for 2009 is presented below using Ward’s framework.
Flows of income Average annual family income = P114,189 Average annual per capita income = P 16,100
Demographic Average family size = 7.2 Household with at least one employed member = 97.2%
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Economic Household head with job = 87.2% Household with TV = 70.6%
Social Household heads who were high school graduates and below = 96.3% Average annual rental of house = P13,892 (including imputed value of owned house) Household with own use water supply = 32.1% Household with electricity supply = 90.8% Households with water-sealed toilets = 80.7%
The detailed characteristics of poor families in NCR are shown in Annex 1. Family size. Poor families tend to have bigger family size. In 2009, the average family size among poor families in NCR was quite high at 7.2 persons with majority of poor families (93.6%) having at least 6 family members. This figure is nearly twice higher than the average family size for all income households of 4.6 persons. The 2010 CPH results further revealed that in NCR the average household size was 4.3 persons. Comparative figures for 2009 show that female-headed families have slightly lower family size (7.2) than their male counterpart (7.3), though the difference is not statistically significant. Employment Status. Majority of the household heads (91.7%) were below 60 years of age in 2009 and thus were expected to be working. Yet only 87.2% reported to have a job. Female-headed families may likely face higher risk of becoming poorer as only 71.0 percent of household heads were with jobs in 2009, compared to their counterpart with about 91.0 percent. Generally, female workers tend to concentrate in jobs that require less on-the-job training, resulting to low earnings. Education and Occupation. The findings of the BLS report (2011) revealed that achieving higher levels of education reduces the incidence of living in poverty. Individuals who completed more years of education usually have greater access to higher paying jobs than those with fewer years of education. Among poor families in NCR, a very high proportion of household heads (96.3%) were high graduates and below. This explains why majority of them were employed in occupations that are characterized by relatively low earnings such as labourers and unskilled workers, construction workers, and service workers. Number of family members employed. Despite majority of the poor families (97.2%) had at least one employed member in 2009, these families were considered poor as the combined income of members resulted to a per capita income still below the poverty threshold. Reasons may be due partly to low earnings, period of unemployment during the year, and/or part-time employment, which were coupled with large family size. Note that the number of employed family members refer only to data for the second semester of 2009. Ownership of Property. Not all poor families are really impoverished. Ownership of major household appliances is an indicator of some comfort living. In NCR, 70 percent of poor families reported to have owned a TV while only less than 10 percent reported to own a refrigerator. Data on ownership of other household properties were also available in the FIES but are not shown in this report due to low ownership rates.
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Annual per capita income. The average annual per capita of poor families in NCR was estimated at P16,100. While the per capita income of female-headed households was lower than their male counterpart, both having about the same family size, this does not suggest that female-headed households face higher risk of becoming poorer. Under the assumption of unequal variance, results of t test shows that computed t = -1.672 (less than 1.96) and p value is .107 (greater than .05). We can therefore conclude that there is evidence at 5% level of significance that the difference in the per capita incomes of male and female headed households is not statistically significant. Housing Unit. The characteristics of housing units, electricity supply, access to safe water supply, and toilet facilities are also indicators that are useful in analyzing the state of the poor. Nearly 80 percent of poor families in NCR lived in single-type houses while about 50 percent owned their own homes. Two-thirds of poor families lived in housing units made of strong roofing materials while only 50 percent have strong materials for the outer walls. Compared to other housing characteristics such as the type and tenure of housing unit, the rental value of house, including imputed value of owned houses, gives a better indication of the quality of the living quarters occupied by a household. Nearly 50 percent and 25 percent of poor families lived in owned or owner-like housing units and rented housing units, respectively. The annual average rental value, including imputed value of house, was P13,892 or P1,158 per month in 2009. In the 2009 monthly retail price survey of NSO, the average monthly rental value of a one-bedroom apartment in NCR, having a toilet and bathroom, was pegged at P4,929, which was more than four times the average rent paid by poor families. About 90 percent of poor families in NCR have electricity supply in their homes, while the rest have none. Nearly one-third have running water in their homes, sourced from Maynilad or Manila Water. While another one-third of these families sourced their water supply from shared water system. Still nearly another third of these families did not enjoy the benefits of piped water in their homes. Instead, they get their water from open sources like buying from peddlers. In terms of sanitation facilities, 80 percent of poor families in NCR reported the presence of water-sealed toilets. Yet a big number of poor families have inadequate, or entirely, lack sanitation facilities in their homes. This poses serious health and environmental risks to themselves and the communities.
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Consumption Pattern The comparative illustrations of the consumption expenditure of all income households and poor families in NCR show wide disparity particularly in the proportions of expenditure for food, beverage, and tobacco in 2009. The consumption expenditures of poor families as observed from the 2009 FIES results clearly satisfy Engel’s Law. In NCR, nearly 60 percent of total expenses were spent on food, beverage and tobacco by poor families. This is in contrast to the proportion spent by all-income households for the same expenditure group which was less than 40 percent.
All Income Households, NCR:2009 Poor families, NCR: 2009
Source: 2009 FIES Final Results, NSO
Correlation Analysis
Total income of poor families has high positive correlation with family size; also has moderate positive correlation with the number of family members employed, education of household head, household type, total expenditures, proportion of food expenditure, rental value of house; and low positive correlation with age, marital status and class of worker of household head, house tenure, and electricity and water supply. Total income has, however, negative correlation with classification of sex and marital status of household head, number of family members 15 years old and over, job status of household head, and toilet facilities. A scatter plot of total income and family size is shown in Figure 1. The correlation coefficients of the variables are presented in Annex 2. Regression Analysis The resulting regression run produced three models for total family income as the dependent variable. . Model 3 shows that among the demographic and economic variables, the variables family size (number of family members), education (years of schooling), and sex classification of household head are the best predictors for total income. The model shows goodness of fit with
Figure 1.
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R2 equal to 69.1%. The ANOVA for model 3 also revealed that it is significant at F=67.781 (p=.000). While the diagnostic test was not done, let us assume for this study that the model conforms to the assumption of error terms having a mean equal to 0, constant variance, normality, and independence. CONCLUSION
Households with low income do not necessarily qualify them as poor. Poverty is a function of income and family size. It is clear that one of the means of escaping from poverty is having a small family size.
The results of the study have shown that certain characteristics of households are highly correlated to total income of poor families. Total income is also correlated to consumption expenditures. Most significant of these characteristics is family size as this appears as a strong predictor for total income of poor families. Aside from family size, the regression test (model 3) reveals that the variables education (years of schooling) and sex of the household head were the other strong predictors.
An understanding of the characteristics of poor families will assist the policy makers, data users, and researchers in identifying the underlying causes and resulting situation of those
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living in poverty. These will serve as basis for the formulation of strategic policies and programs that would address poverty alleviation, particularly in the areas of education, family planning, housing, skills enhancement, welfare assistance, livelihood, water supply, electricity, as well as accessibility of social services.
The study offers opportunities for future research studies that seek to analyze and
compare the characteristics of poor and non-poor families over time.
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