metadata: authors: 0: author: Canagarajah,Roy S.
1: author: Ngwafon, John
2: author: Thomas, Saji
count: Nigeria
docna: 0: docna: The evolution of poverty and welfare in
            Nigeria, 1985-92
docty: Policy Research Working Paper
subtopic: Reproductive Health,Early Child and Children's Health,Educational Sciences,Poverty Impact Evaluation,Poverty Monitoring & Analysis,Gender and Development,Inequality,Poverty Assessment,Poverty Diagnostics,Poverty Lines,Small Area Estimation Poverty Mapping
teratopic: Poverty Reduction
abstracts: cdata!: The authors profile Nigerian poverty,
            showing its evolution from 1985 to 1992.  This paper is
            divided into 6 sections, beginning with an overview.
            Section 2 looks at the sources of data used.  Section 3
            examines household income and expenditure distribution,
            interprets poverty indices, and calculates relative poverty
            lines for Nigeria.  Section 4, the paper's core,
            presents the spatial characteristics of poverty in Nigeria
            and their evolution over the seven-year period, indicating
            in which regions and states the poor are located and the
            extent and severity of their poverty; lays out the
            poor's basic demographic characteristics including time
            use and employment patterns, detailing how these have
            evolved; features the roles the poor play in various sectors
            of the economy; and discuss how changes in poverty could be
            explained by growth-related and redistribution factors.
            Section 5 discusses the evolution of expenditures and
            explains how expenditure patterns correspond to poverty.
            Section 6 presents conclusions, among them: the extremely
            poor -who dominate the ranks of the uneducated- became
            poorer, while all other income groups had a higher standard
            of living; an increase in mean per capita household spending
            reduced the proportion of the population in poverty but
            different regions did not share equally in the benefits of
            growth; household spending grew faster in southern and
            central Nigeria and slower in the north; and poverty was
            overwhelmingly rural and regional, but also greatly
            influenced by age, educaton, and the nature of employment.
geo_reg_key: 1927320,517191
repnme: repnme: The evolution of poverty and welfare in
            Nigeria, 1985-92
display_title: The evolution of poverty and welfare
            in Nigeria, 1985-92
listing_relative_url: /research/1997/01/695029/evolution-poverty-welfare-nigeria-1985-92
topicv3: Infant and Child Mortality m1326544 1446,Poverty m1326687 695,Poverty Measurement and Analysis m1326941 707,Education m1327048 470,Gender m1327621 615
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Poverty Reduction
origu: AFT: Human Development 3 (AFTH3)
no_of_pages: 100
model_extractions: POLICY RESEARCH WORK[NC, PAPER 1 715

# Summary findings

Canagarajah, Ngwafon, and Thomas present a poverty profile of Nigeria for the years 1985 and 1992 and show how poverty changed between those years. They show the nature of poverty in both years for different deciles of the population, different levels of education, different ages for household heads, and different parts of the country, including urban and rural areas There is no official poverty line in Nigeria, so they selected one based on two-thirds of average per capita spending in 1985 (N 395 a year per capita in 1985 prices). N198 (one third of mean per capita household spending) is used to indicate extreme poverty. The bottom 17 to 18 percent of income distribution had a lower standard of living in 1992 than in 1985 by any measure, but all other income groups had a higher standard of living.

An increase in mean per capita household spending reduced the proportion of the population in poverty from 43 percent to 34 percent.

But the benefits of growth were not shared equally by different parts of the country. Growth of household spending was faster in the southern and middle parts of the country and slower in the north. Poverty in Nigeria is overwhelmingly rural and regional, but is also greatly influenced by age, education, and the nature of employment. Most of the poor, especially the extremely poor, are uneducated.

The 8.9 percent decline in poverty was the net result of a + 13.6 percent growth factor and a -4.7 percent income distribution factor.

Improving the quality of data collection and analysis and establishing systems for monitoring poverty are important for policymaking. Canagarajah, Ngwafon, and Thomas recommend an integrated living standards survey to provide baseline data and to permit analysis of household behavior.

This paper - a joint product of Human Development 3 and Institutional and Social Policy, Africa Technical Families - is part of a larger effort in the region to analyze welfare and poverty issues. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Betty Casely-Hayford, room J8-270, telephone 202-473-4672, fax 202-473-8065, Internet address bcaselyhayford@q)worldbank.org. January 1997. (84 pages)

**_Thbe Policy Research Working Paper Series disseminates the findings_** _of_ **_work in progress to encourage the exchange of ideas about_** _developmtent issues. An_ **_objective_** _of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the n.-'nes of the authors and should be cited accordingly. The findings,_ **_interpretations, and conclusions expressed in this_** _paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent._

Produced by the Policy Research Dissemination Center
# THE EVOLUTION OF POVERTY AND WELFARE IN NIGERIA (1985-92)

**Sudharshan Canagarajah John Ngwafon Saji Thomas**

This document was prepared in close collaboration with the staff of the Federal Office of Statistics, Nigeria. We acknowledge valuable comments and technical advice from Martin Ravallion, Hazel Denton, Lionel Demery and David Bigman, and greatly appreciate the financial support provided by UNICEF.
# **TABLE OF CONTENTS**

|1. INTRODUCTION ...............................................|1|
|---|---|
|2. NATIONAL CONSUMER SURVEY ...............................................|3|
|3. THE MEASUREMENT OF WELFARE AND POVERTY .........................|......................<br>4|
|_3.1 Household Expenditure ..............................................._|_4_|
|_3.2 Price Index .._|_5_|
|_3.3 Poverty Lines in Nigeria ..............................................._|_6_|
|_3.4 Basic Needs Approach to Poverty ................................................_|_7_|
|_3.5 Poverty Line ..............................................._|_8_|
|_3.6 Poverty Indices ..............................................._|_9_|
|_3.7 Macro-economic Background .............................................._|_11_|
|4. EVOLUTION OF POVERTY IN NIGERIA ..............................................|I 1|
|_4. 1 The Evolution of Mean Expenditure in Nigeria ........................................_|_......_<br>_11_|
|_4.2 Evoluition of Regional Poverty in Nigeria .............................................._|_17_|
|_4.3 Evolution of Poverty and Household Composition ..................................._|_..........._<br>_25_|
|_4.3 Poverty and Employment ...._<br>_.........................................._|_30_|
|_4.3 Decomposition of Changes in Poverty .............................................._|_35_|
|_4.5 Implications for Targeting ..............................................._|_39_|
|_4.6 Sensitivity Analysis of Poverty .............................................._|_42_|
|_4. 7 Dominance Test of Poverty .............................................._|_49_|
|_5._EXPENDITURE PATTERNS OF THE POOR .............................................|.<br>46|
|6. CONCLUDING REMARKS||
|_6.1. Analytic Methodology .............................................._|_50_|
|_6.2. Beyond the Poverty Profile .............................................._|_50_|
# **LIST OF TABLES**

|Table 3.1|Nominal and Real GDP Growth 1986-92|11|
|---|---|---|
|Table 4.1|Distribution of Per Capita Expenditures by Population Deciles|13|
|Table 4.2|Distribution of per capita food expenditures by population deciles|14|
|Table 4.3|Pattern of Real Household Per Capita Expenditures by region|15|
|Table 4.4|Pattern of Real Household Per Capita Expenditures by<br>Geographic regions|15|
|Table 4.5|Rural/Urban Pattern of Real Household Per Capita<br>Expenditures by Geographic regions|17|
|Table 4.6|Poverty Incidence in Nigeria by Region|18|
|Table 4.7|Incidence of Extreme Poverty in Nigeria by Region<br>(Poverty line=N 197.71)|18|
|Table 4.8|Rural/Urban Incidence of Poverty by Geographical Regions<br>(Poverty line=N 395.41)|19|
|Table 4.9|Decomposition of Poverty by Geographical Regions<br>(Poverty line=N 395.41)|20|
|Table 4.10|Rural/Urban poverty incidence by Agro-climatic zones<br>(Poverty line= N395.41)|21|
|Table 4.11|Rural/Urban poverty Decomposition by Agro-climatic zones<br>Poverty line=N395.41)|21|
|Table 4.12|Poverty Incidence in Nigeria by State<br>(Poverty Line=395.41)|22|
|Table 4.13|Contribution of Poverty Incidence by State<br>(Poverty Line =395.41)|23|
|Table 4.14|Incidence of Extreme Poverty in Nigeria by State<br>(Poverty Line= 197.71)|24|
|Table 4.15|Decomposition of Extreme Poverty Incidence by State<br>(Poverty Line= 197.71)|25|
|Table 4.16|Poverty Incidence by Age Group of Household Head (1985-92)<br>(Poverty Line=395.41)|26|
|Table 4.17|Decomposition of Poverty by Age Group of Household<br>Head (1985-92)|27|
|Table 4.18|Poverty Incidence by Gender of Head of Household (1985-92)<br>(Poverty Line = 395.41)|28|
|Table 4.19|Poverty Incidence by Educational level of Head of Household (1985-|92)|
||(Poverty Line=395.41)|29|
|Table 4.20|Incidence of Extreme Poverty by Education of Head (1985-92)<br>(Poverty Line= 197.71)|29|
|Table 4.21|Poverty Incidence by Occupation of Head of Household (1985-92)<br>(Poverty Line=395.41)|32|
|Table 4.22|Incidence of Extreme Poverty by OcuLpation of Head of Household<br>(Poverty Line= 197.71)|33|
|Table 4.23|Poverty Incidence by Employment Status of Head of Household||
|---|---|---|
||(Poverty Line=395.41)|34|
|Table 4.24|<br>Incidence of Extreme Poverty by Employment Status of Head<br>(Poverty Line=197.71)|34|
|Table 4.25|Urban/Rural Decomposition of Change in Poverty into<br>Growth and Redistribution Components|37|
|Table 4.26|Regional Decomposition of Change in Poverty into<br>Growth and Redistribution Components|38|
|Table 4.27|Decomposition of Change in Poverty into<br>Intersectoral, Population Shift and Interaction Effects|39|
|Table 4.28|<br>Targeting Indices by Various Indicators 1992-92<br>(Poverty Line=395.41)|41|
|Table 4.29|Poverty Simulation with Varying CPI (1985 = 100) 52|43|
|Table 4.30|Projected Impact of (5%) Distributionally Neutral Growth<br>in Real Per Capita Expenditure on Poverty (1993-2005)|45|
|Table 5.1|Evolution of (Real) Per Capita Expenditure by<br>Type and Poverty Group (Poverty Line=395.41)|48|
|Table 5.2|Evolution of (Real) Per Capita Expenditure by Type, Region<br>and Gender (Poverty Line=395.41)|48|
|Table 5.3<br>**FIGURES A**|Evolution of (Real) Per Capita Expenditure by Type<br>and Geographical Region (Poverty Line=395.41)<br>**ND GRAPHS**|49|
|Figure 4.1|Evolution of Household Expenditure by Expenditure Decile|14|
|Figure 4.2|Lorenz Curves for Mean Per Capita Expenditure by Region|16|
|Figure 4.3|First Order Dominance Test For Poverty Line in Nigeria|45|
|**APPENDIX**|**1**|53|
|Table Al. 1|Evolution of (Real) Per Capita Food Expenditure by Type and<br>Region|54|
|Table A1.2|Evolution of (Real) Per Capita Food Expenditure by Type and<br>Gender of Head of Household|55|
|Table A1.3|Evolution of (Real) Per Capita Non Food Expenditure by Type,<br>Region and Gender|56|
|Table Al.4|<br>Evolution of (Real) Per Capita Non Food Expenditure by Type and<br>Region and Gender|57|
|Table A1.5|<br>Evolution of (Real) Per Capita Non Food Expenditure by Type and<br>Geographical Regions|57|
|Table A1.6|Evolution of (Real) Per Capita Income by Income Source|58|
|Table Al.7|Evolution of (Real) Per Capita Income by Poverty Levels|58|
|Table Al.8|Evolution of (Real) Per Capita Income by Region and Gender|59|
60

# **APPENDIX 2**

|Fig A2. 1-A2|.3 Poverty incidence curves for 1985/86 and 1992/93<br>60-61|
|---|---|
|Fig A2.4-A2|.6 Poverty deficit curves for 1985/86 and 1992/93.<br>62-63|
|Fig A2.7-A2|.9 Poverty severity curves for 1985/86 and 1992/93.<br>63-64|
|**APPENDIX**|**3**<br>65|
|Table A3.1|Rural-Urban per capita expenditure differentials<br>65|
|Table A3.2|State Price Deflators<br>68|
|Table A3.3|Regional Cost of Living Indices by State (1985-93)<br>70|
|Table A3.4|Population Estimates and Extrapolation Factors by State and Region 71|
|Table A3.5|Composite Consumer Price Indices (1985-93)<br>72|
|Table A3.6|Unemployment Rates in Nigeria (1985-93)<br>73|
|**APPENDIX**|**4**<br>74|
|Table A4.1|Summary of Past Studies on poverty in Nigeria<br>74|
|**APPENDIX**|5<br>75|
|TableA5.1|<br>The estimation of Household accounts from the<br>National Consumer Survey<br>77|
|Table A5.2|Per-Capita Expenditure by Decile (Untreated data: 1985/86)<br>79|
|Table A5.3|Per-Capita Expenditure by Decile (Untreated data: 1992/93)<br>79|
# **CURRENCY EQUIVALENTS**

Currency Unit: Naira (N) Official Rate: US$1.00 = N 1.0818 (Mean 1985/1986) US$1.00 = N 22.00 (Mean 1992/93)

# **LIST OF ABBREVIATIONS AND ACRONYMS**

|CBN|=>|Central Bank of Nigeria|
|---|---|---|
|CDR|=>|Crude Death Rate|
|CEM|=>|Country Economic Memorandum|
|CES|>|Consumption Expenditure Survey|
|CPI|=|Consumer Price Index|
|CSER|=>|Center for Social and Economic Research|
|EA|=>|Enumeration Area|
|ESW|=>|Economic and Sector Work|
|FOS|z>|Federal Office of Statistics|
|FGT|=>|Foster-Greer-Thorbecke|
|GDP|=>|Gross Domestic Product|
|IFAD|z>|Institute for Food and Agricultural Development|
|ILO|=>|International Labor Organization|
|IMR|=>|Infant Mortality Rate|
|JASPA|=|Jobs and Skills Program for Africa|
|LSMS|=>|Living Standards Measurement Survey|
|NCS|=>|National Consumer Survey|
|NGO|=>|Non-Governmental Organization|
|NISER|=:'|Nigerian Institute for Scientific and Economic Research|
|NISH|=>|National Integrated Survey of Households|
|PCE|=>|Average per capita expenditure|
|SAP|=>|Structural Adjustment Program|
|SDA|=>|Social Dimensions of Adjustment|
|SSA|=>|Sub-Saharan Africa|
|UNICEF|=>|United Nations Children's Fund|
|UPE|=>|Universal Primary Education|
|WID|=>|Women in Development|

# **GOVERNMENT FISCAL YEAR**

January 1 - December 31
# 1. **INTRODUCTION**

The analysis of the evolution of poverty and welfare over time in Nigeria has been difficult, because there are empirical or data considerations which make the task daunting. The social and economic data base to analyze this issue is either non-existent or missing in many Sub-Saharan countries, including Nigeria. However under the National Survey of Integrated Households (NISH) two National Consumer Surveys (NCS) were conducted, one in 1985 and the other 1992, which provide the minimum requirement towards undertaking such an analysis. It does not, however, enable us to address the detailed issues of household and individual welfare.

This paper looks at the household welfare determined by the capabilities and constraints of its members for income generation and access to publicly financed services. In the rural areas, since most households are engaged in agriculture, access to land, credit and other productive inputs, and their human capital, determine their capacity for income generation. For the nonagricultural population, particularly for urban dwellers, labor market operation and their human capital are decisive in determining their status. Human capital is generally dependent on the availability and access to a critical mass of health, education and nutritional services. Since each one of them complements the effect of the other, a critical minimum of each is required. In Nigeria, though there is a large private sector, the provision of social services, particularly education and health have been primarily in the domain of the public sector. The level and quality of provision of social services, especially for the poor, has eroded over time.

In terms of health indicators, noticeable improvements have been made since the 1970s, but a lot still needs to be done. Nigeria's health indicators such as morbidity and mortality rates, are high. The crude death rate (CDR) had declined by half from 27 per 1000 in 1965 to 15 per 1000 in 1993. The infant mortality rate (IMR) in 1993 was estimated at 83 per 1000 live births, down from 140 per 1000 in 1970. Towards the end of the 1980s, the maternal mortality rates were estimated to have reached 8 per 1000 live births. Life expectancy at birth had risen from 39 years in 1960, to 51 in 1993 (World Bank, 1995).

These indicators, however, show that Nigeria fared badly compared to many countries at the same level of GDP per capita, and not much better than other countries of Sub-Saharan Africa.

About 80 percent of the deaths are still caused by preventable diseases such as measles, malaria, pneumonia, diarrhea, gonorrhea, whooping cough, schistosomiasis, chicken pox and tuberculosis. In addition, fewer than 30 percent of pregnant women received modern pre- and post-natal care. These causes of morbidity and mortality are reinforced by the prevalence of unhygienic traditional delivery practices and the lack of adequate family planning practices.

In the education sector, gross primary enrollment rate increased from 42 percent in 1960 (World Bank, 1989a and 1995) to 92 percent at its peak in 1982/83, after which it subsided to 78 percent in 1992. Secondary and tertiary gross enrollment also increased until the early 1980s after which a downward trend ensued in the second half. The adult literacy rate, the best indicator of the extent to which education has spread, increased steadily from 15 percent in 1960, to a
2 modest level of 51 percent in 1992. Comparison of literacy rates for countries such as Ghana, Cote d'Ivoire and Kenya in SSA, and Indonesia, a country similar to Nigeria in many respects, however, indicate Nigeria has fallen far behind.

The primary manifestation of poverty occurs at the household (individual) level, the understanding of which requires data at the same level of disaggregation. Unfortunately, economic and social statistics in Nigeria are limited and unreliable particularly for such microlevel analysis. Furthermore, data on income and expenditures are absent or outdated. Although attemptsl/ have been made to fill the gap in household level information through a series of studies and household surveys, published government sources are inadequate due to the lack of proper accounting of sources and uses of income, imprecision in definition and the lack of household distribution by income (expenditure) groupings.

This paper's objective is to document the evolution of household welfare and poverty in Nigeria in the period of 1985-92. The present exercise is the first which investigates the changes in and implications for household welfare and poverty. The Nigerian economy achieved an impressive growth performance over the years for which survey data are available (around 5 percent GDP growth rate per annum on average), which implies that the average living standards rose over the survey period. However, the benefits of economic growth were not distributed equally. The extent to which the poor benefited from economic growth (about 1.13 million people rose above the poverty line) is therefore an issue of considerable policy interest. This paper focuses on the sub-groups of population by social and economic breakdown to understand which groups of people benefited from the economic reforms and which groups did not. The welfare changes that have taken place in each household is decomposed to facilitate the analysis of policy consequences of the economic measure introduced. However, unlike some other studies, this analysis does not adopt a formal general equilibrium model; instead it tries to understand each issue in a partial equilibrium setting. Although this might have disadvantages in terms of deriving economy-wide relevant policy lessons, it has the advantage of enabling the data to be fully utilized for each policy consideration. It is hoped that this will provide policy makers with relevant information for assessing the impact of past policies and designing new policies towards reducing poverty.

For the analysis, detailed price indices were developed to be used in conjunction with the household expenditure data used in this study. The methodology used in this exercise is similar to one utilized in other countries (World Bank, 1990; Ravallion, 1993). Since the main redistributive feature of the adjustment process was a shift in the rural-urban terms of trade towards rural areas, the effects can be highlighted by disaggregating results along rural/urban and (geographical) regional dimensions. However, for policy relevant analysis, it is important to identify even further, where poverty and welfare effects were concentrated, by looking at who were the losers and gainers. As this study is concerned with understanding how the overall incidence, depth and severity of poverty has evolved, and what changes may have occurred in the 1/ See Appendix 4, for previous research on poverty in Nigeria.
3 regional and socioeconomic patterns of poverty, the results are disaggregated by socio-economic groups.

This paper is made up of six sections, including the present Introduction section. Section II looks at the sources of data used for the study. Section III looks into household income and expenditure distribution in Nigeria and provides an interpretation of poverty indices and the calculation of a relative poverty line for Nigeria. Section IV makes up the core of this paper, presenting the spatial characteristics of poverty in Nigeria and how they have evolved over a seven year period from 1985 to 1992, indicating in which regions and states the poor are located in and the extent and severity of their poverty; the basic demographic characteristics of the poor including time use and employment patterns, describing in detail how these characteristics have evolved over the period; and how the poor feature in various sectors of the economy and the poverty decompositions, vulnerability and targeting; discusses how the changes in poverty could be explained by factors that are growth-related and those that are due to redistribution. Section V discusses the evolution of expenditures in Nigeria and explains how the patterns of expenditure correspond to poverty, by decomposing the sources of expenditure. Section VI concludes with some final remarks.

# **2. NATIONAL CONSUMER SURVEY**

The main data sets used in this study were collected by the Federal Office of Statistics (FOS) of Nigeria under the National Integrated Survey of Households (NISH). Both the 1985/86 and 1992/93 surveys were used to construct the poverty profile and consequent analysis. Both surveys start in April of the first year and end in March of the following year. The main objective of the data set is to provide periodic information to revise the consumer price index. The data on income is used to prepare a system of national accounts. The expenditure data and socioeconomic information are used to assess the impact of policy on general consumption patterns. The coverage of the data set is not as wide as one would wish, for detailed welfare and poverty analysis. For example, the surveys do not gather data to help analyze the production patterns of the poor, for the rural areas, the crop mix, the quality of their land, the value of their assets such as livestock, or even the degree to which they rely on wage labor compared to better off farmers. There is no information on the asset base typical of the poor and the sort of assets the poor lose first, when coping with survival crises. The lack of these indicators makes it difficult to build up a comprehensive picture of the capabilities and resources of the poor - in terms of physical assets and human resource endowment.

The 1985/86 sample is designed to be nationally representative. A two-stage stratified sample design is used. In the first stage, 1224 enumeration areas (EAs) were selected with probability proportional to the number of census households in the area. Stratification is done on rural/urban and state of residence basis. A total of 70 EAs comprising 40 from urban and 30 from rural were selected. From each EA 20 households were selected. In the second stage, sampled areas were randomly allocated to each month with 4 urban and 3 rural EAs.
4 The 1992/93 was based on the sample design of 1987 which had 22 states. In each state a total of 120 EAs, 48 urban, 12 semi-urban, and 60 rural, were studied. These 120 EAs are allocated over the 12 survey months of the year covering 10 EAs in the ratio of 5:4:1 for rural, urban and semi-urban respectively in each state. Otherwise the sample was similar in design to the 1985/86 survey.

The Sample was weighted on the basis of the probability of selecting an EA within a state and choosing a household within an EA. A diary was given to each household to record flows of income to and expenditure from the household within the reference period or reference month2/. Field staff usually made daily visits to each household to ensure quality of entry and also to help those households who have no one literate to fill in the diary. This information was then transferred on a daily basis to the enumerator's memo book. The enumerator's book was then deposited in the field office where it was checked for quality and consistency by the supervisor.

The survey collected information on the following items on each household:

- (a) Household Demographic Statistics: age, gender, location and type of housing of the household.

- (b) Household Expenditure: Expenditure on all goods and services incurred by the household during the survey period. It also includes all monetary transactions (savings, donations and Esusu3/ contributions)

- (c) Imputed Rent on owner-occupied and rent-free dwelling

- (d) Cash Income: Income from wages, overtime, bonuses, professional fees that is received by the household.

# **3.** THE MEASUREMENT OF WELFARE AND POVERTY

# **3.1 Household Expenditure**

The measurement of household welfare or standard of living is a question which has not been resolved completely (Sen, 1987). There are many ways one could go about addressing this issue depending on the context, need and availability of information. Since quality of life has to

> 2/ "The sampling unit of the survey is the household defined as all persons living under the same roof and having a common eating arrangement. The boarders are included as members of the household and lodgers are excluded. Members of the household who are temporarily absent are included". See "Social Statistics in Nigeria", Federal Office of Statistics (FOS), Nigeria, 1980, p 1.

> 2/ Esusu refers to a system whereby a group of individuals or family gets together either on a weekly, biweekly or monthly basis, and each person contributes a certain sum of money, usually the same amount per individual. This is given on a rotating basis to each individual in the group. This results in a large sum of money which the individual can invest or simply save. It is worth noting that there might be differences in the arrangements in different regions, although fundamentally it is similar in effect.
5 take into consideration all direct and indirect consumption, both tangible and intangible items, measuring welfare has become a daunting task.. The most common a single indicator of welfare in the literature is to generate value of consumption basket both market purchases and consumption of own production, using appropriate price measures. In the present case, since expenditure is expressed only in terms of value there is no need to construct a vector of prices which then can be used to convert the quantity information into a value. Nominal figures were first deflated with regional price index, in order to make expenditure figures comparable within the two periods. Subsequently, all expenditures of both surveys were expressed in constant 1985 Naira.

The measure of household welfare used in the present analysis is the household total expenditure expressed in terms of per person. The attractiveness of using this measure as a welfare indicator as opposed to income has been well emphasized in the literature. What is needed is a measure of "permanent income" which is devoid of short-term income fluctuations. Hence consumption which reflects substitution between current and future consumption through savings and therefore is less prone to volatility generated by short-term fluctuations in income, and would be the best indicator of permanent income. In the present exercise, total expenditure is used to measure household welfare.

It is important that the welfare measure takes into consideration the size and composition of the household to be truly representative of each household. However, this involves construction of an endogenous scale, namely the adult equivalence scale, which is a difficult conceptual exercise with substantial data requirements at the household level, which do not exist in the present data base ( see Deaton and Muellbauer, 1980). Hence, the calculation of such a scale is not attempted in this paper. A more standard measure of per capita expenditure is used, which is derived by dividing the total household expenditure by the size of each household.

Two other measures which are used in measuring household welfare are per capita food expenditure and the share of expenditure devoted to food. The former has been preferred because non-food expenditure is harder to measure than food expenditure. Food expenditure might thus represent a better indicator of actual standard of living than total expenditure. But the disadvantage is that non-food expenditure which is not generally proportionally related to food expenditure will not be factored into the analysis and might distort the conclusions. The latter measure, food share, is justified on the basis of Engel's Law, which says that the proportion of expenditure devoted to food will fall as total expenditure increases, and therefore can be used as a proxy for measurement of living standards. The disadvantage is that Engle's Law need not necessarily hold for each segment and socio economic grouping of the population and does not enable comparison of the relative welfare levels of various groups which is important for policy purposes.

# **3.2 Price Index**

In order to use total expenditure as the basis of standard of living we need to adjust the indicator needs to be adjusted by correcting for regional price differences. Since different households face different prices, either because they are located in different regions and/or
6 because they are surveyed at different periods in time, we need to take this into account before comparing living standards through total expenditure measure. It becomes extremely difficult to obtain information on the prices of items from various markets. This paper uses the best information that could be generated.

In order to express expenditure in constant prices of a reference region and reference time period we could use Laspeyres index or Paasche index. The Paasche index is more attractive because it gives more easily interpretable Laspeyres index of real expenditure when it is used to deflate nominal expenditure. The Paasche index may be constructed as follows: 7t **_irI_** X _WirPi_ **_Pir_** Where **_Pi,_** is price of commodity i (i=l ....... n) in region r (r=l ...... R) and time period t (t=l .... T), **_Pi,_** refers to price of same commodity in the reference region (r-1), **_Wi,_** is the share of total expenditure in the region r accounted by commodity i and **_Pir_** is the Paasche cost of living index for region r in time period t.

In the case of 1985/86, prices for 50 different items were used to construct weights using the consumption proportion of households who fell below 30 percent of average household expenditure in constructing the state wide indices. The latter choice was to make it relevant for analyzing the quality of life of the poor people. These were in turn used to deflate the household expenditure figures which we used for the poverty analysis. In the case of 1992/93, it was possible to obtain prices for only 30 items.

Since the analysis of poverty is inter-temporal, regional price indices are allowed to reflect temporal differences. Since the same amount of price disaggregation information is not available in both periods, it is difficult to construct price indices for each item relative to a reference time period. Therefore, price indices are constructed for each state using a "poverty weighted" Consumer Price Index (CPI) in contrast to a standard CPI, while maintaining the 1985/86 regional price variation.

# **3.3 Poverty Lines in Nigeria**

The poverty analysis of any country requires establishing a poverty line which then would be used in conjunction with welfare indicators. There are two main broad approaches to the construction of a poverty line, namely absolute and relative poverty line. The absolute poverty line is based on minimum nutritional requirement which is converted into minimum food expenses, to this is added may be considered necessary non-food expenses. This poverty line therefore would be influenced by differing food habits along with social, cultural and economic conventions. Hence the absolute poverty line is relative in one sense.

The relative poverty line is more visibly arbitrary. One approach has been to determine some amount which demarcates a preselected percent of the population. Another approach that has found increased acceptance is the taking of an arbitrary proportion of the mean as poverty
7 line (Boateng _et al,_ 1992). For instance one-third and two-third of means have been regularly used. In this document we use the latter approach and construct a relative poverty line since there is no absolute poverty line available for Nigeria.

The poverty lines that have been constructed for Nigeria include the following: The International Labor Organization (ILO) under the JASPA study (1982) constructed poverty lines on the basis of 1978 income data which amounted to 65 Naira per month per family in urban area and 35 Naira per month per family in rural areas. The poverty line assumed in the case of urban households 50 Naira per month per family for food and the rest for housing, clothing and the rest, and set the rural prices to be 40 percent below urban level. According to these guidelines it was estimated that 34 percent were poor in urban areas (instead of 15 percent in 1974), while 40 percent were below the poverty line in rural area. The other study is the World Bank Food Security Study of 1989 which draws its results on the basis of unprocessed 1985/86 FOS data.4/ Poverty lines are set at NI 50 for urban and NI 10 for rural using only food expenditures. This leads to 22.2 percent urban households and 17.2 percent of rural households falling below the poverty line or are food insecure, resulting in around 18 percent of all households nationally being poor.

Bevan et al (1988) drew an absolute rural poverty line based on 1952/53 data dividing the bottom 20 percent and 40 percent of the population. They concluded that in 1983/84 there were 17 percent and 58 percent respectively under those lines. This indicates that "moderate" poverty has worsened although the "hard core" poverty has not changed dramatically.

Both UNICEF and ILO have been concerned with developing poverty analyses. The former has been mainly interested in the qualitative side of the poverty analysis, while the latter has done some of the early work on poverty using survey data, as noted above.

In addition, there have been various other small scale studies or revisions of poverty lines which led to different proportions falling below poverty lines. For instance a World Bank(1994) study, constructed a poverty line which was based on earlier studies, and concluded that 57.7 percent of the urban population and 66.2 percent of then rural population lived under poverty.

# **3.4 Basic Needs Approach to Poverty**

As mentioned earlier many studies have attempted to understand poverty through indicators of basic needs. One of the first issues that needs to be resolved is what is covered by "basic needs". In the Nigerian context there have been some lengthy exchange of views among scholars and policy makers on this issue. One of the early definitions of basic needs was put forward by the ILO (1981) entitled "First things First" which included food, water, shelter, health

> 4/ The present analysis is based on the same data set, except that now it is processed, edited and allowance has been made for regional price differences and so forth before the poverty analysis. According to the current estimate 49.5 percent of the rural population and 31.7 percent of the urban population fell below the poverty line, resulting in around 43 percent of the national population being poor. It is worth noting that poor households are much larger than non-poor households and this also contributes to the difference in household versus population percentage under poverty line, apart from the differences in poverty lines used.
8 service, learning and work. Following that were two other proponents, the first by CSER (1982) which identified food, nutrition, health, education, housing and the environment, while the second was by the NISER (1986) which identified food, housing, health services, public transportation, access to informnation and potable water.

The first comprehensive study on Nigerian poverty using a basic needs approach was done by Stewart (1985). Apart from stating some of the figures on basic needs she alludes to the fact that there is substantial under-reporting in basic needs indicators, especially in child mortality, disease and morbidity. She also states that there is positive urban bias in government expenditure for basic services. Through a descriptive discussion on incomes and expenditures she concludes that half the population has significantly inadequate income to meet basic food needs, let alone basic services.

An ILO study (1981) led by Seers also provided some basic indicators of the state of basic services especially in relation to the poor. Most of the discussion was at a national aggregate level. Other than showing the general adverse situation in the rural areas and agricultural inequality, potable water supply, it also refers to issues of nutrition. For instance, it states that 30 percent in Oyo state are malnourished. It also states that in Lagos more than 72 percent of the households live in one room houses. It is also highlighted that access to health services may vary from two-thirds of the population in the South to one-third in the North.

Other than these broad based studies many other micro studies, especially by Nigerians, have been conducted. Sada (1975) using neighborhood incomes as a base measure shows urban poverty to be 65 percent in Lagos in 1972. Oshuntogun (1975) provides a profile of the poor in five villages in Western state. On the other hand Adeyokunnu (1975) finds that despite 85 percent of expenditure being allocated to food it is not adequate to meet basic daily nutritional needs. There is also a study by IFAD (1992) which states that 51 percent of the rural population lived below the poverty line as of 1988.

In the recent past a detailed study in selected districts by the Central Bank of Nigeria (CBN) INISER group (1992) has some interesting findings about poverty and welfare pre/post structural adjustment program (SAP). Apart from showing some general patterns in relation to income levels by various occupational groups it also shows that household expenditures on social services have increased from an average of 44.3 percent pre-SAP to 52 percent post-SAP. Real income per household has declined precipitously, major declines being noted for farmers. Government social expenditures have increased on average by about 15 percent. In terms of nutrition there is evidence to the effect that there is less meat and more bean consumption and calorie deficiences.

# **3.5 Poverty Line**

Whatever approach is chosen to analyze poverty, the poverty line is an arbitrary divider of poor and non-poor. Hence it has become common to do sensitivity analysis whereby different poverty lines are established around the chosen line to see how sensitive is the number of poor to the different lines. Therefore it is important to construct a poverty line which has relevance for policy makers and which will be deemed to be an acceptable cut-off point. Also it is important
9 to do sensitivity tests using alternative measures to test the robustness of the poverty line. This paper refers to two alternative measures which have been used in other poverty analyses. The first is the minimum wage of the target group converted appropriately to account for per capita level. The second is the concept of "generalized poverty line" proposed in World Development Report (1990), which are set at US$370 and US$275 per person per year in 1985 prices. These are converted to comparable indicators using currency conversion factors developed by the World Bank. The latter have the attractiveness of being comparable across countries and useful for relative welfare analysis across countries.

In inter-temporal poverty analysis, even if a relative poverty line is chosen for the initial period, by keeping it constant when looking at other periods of time the line becomes absolute. Also, this paper is more interested in the distribution of poverty within a country than its level. The former is more useful for orienting poverty alleviation measures towards those groups most affected by poverty. Sensitivity analysis is also used to make sure that the distribution of poverty is not highly sensitive to the exact choice of the poverty line.

# **3.6 Poverty Indices**

It has become customary to use the so called P-alpha measures in analyzing poverty. The measures relate to different dimensions of the incidence of poverty. P0 Pi, and P2 and are used for headcount, depth and severity of poverty respectively.

The mathematical formulation and poverty measures described below, are drawn from Foster, Greer and Thorbecke (1984). The three measure are all based on a single formula, but each index puts different weights on the degree to which a household or individual falls below the poverty line. To see how the measures are defined, let consumption or household expenditures be arranged in ascending order, from the poorest **Y 1 ,** the next poorest Y2...... with the least poor Yq. The poverty gap index is defined as follows: where Z = the poverty line; q = the number of individuals below the poverty line; N = the total number of individuals in the reference population; Y1 = the expenditure of the household in which individual i lives; x = the Forster-Greer-Thorbecke (FGT) index and takes on the values 0, 1, 2. The quantity in parentheses is the proportionate shortfall of income below the poverty line. This quantity is raised to a power a. By increasing the value of a, the "aversion" to poverty as measured by the index is also increased (See Boateng _et al,_ 1992).

Suppose o _=_ 0, so that the index measures no aversion to poverty, then P0 = H = q/n is the proportion of the population that falls below the poverty line. This is the "headcount Ratio" defined as the proportion of the population for whom consumption falls
10 below poverty line, in a population of n. Then the headcount ratio is: H = q/n = the proportion of the population deemed to be poor. For example if there are 10 poor people out of 100, the ratio H = 10/100 or 0.1.

Suppose now that a = 1 so that the "aversion to poverty" is increased, then This multiplies the "head-count ratio" or the proportion of the population below the poverty line, i.e. H, by the income or expenditure gap between the average poor person and the poverty line. To continue the example, if each of the 10 people above had an income of 40 percent of the poverty line, then the P2 measure would be 10/100 * 0.4 which equals 0.04. To better understand this, suppose q people are poor, i.e,.

PI = q/n * (Z-Y)/Z = HI, where H = q/n and I = (Z-Y)/Z.

Suppose now that a = 2. This weights the poverty of the poorest individual more heavily than those just slightly below the poverty line. This is done by squaring the gap between their incomes and the poverty line in order to increase its weight in the overall poverty measure.

The _Pa_ measure has the further advantage of being decomposable. For example, the national level measure of poverty can be expressed as the sum of regional measures weighted by the population share of each region: _P,,, = Y- kj Pa J_ where j=l .... m regions kj= population share of region j.

This in turn enables us to calculate the contribution cj of each region to national poverty.

kjPc,J Pct_ This measure has direct relevance for policy. This enables us to understand the impact of various policy measures in different groups and regions of the country. Also the knowledge about the share of each region or group in total poverty is essential for targeted interventions.

Having discussed the framework of our analysis we now have to outline the implementation of the framework and issues ensuing from it. The data set for this study was obtained from the National Integrated Survey of Households, undertaken by the Federal Office of Statistics (FOS). We have already noted the coverage of the data set and its main characteristics and now turn to a more practical look at the data, given the proposed framework for poverty analysis.
11

# **3.7 Macro-economic Background**

Since the start of the adjustment program in 1986, a growing debate has emerged as to the efficiency of these programs to bring about sustainable growth, and as to their short and long term impact on poverty and basic needs fulfillment. It is much less clear what the impact has been on the poor and the social sector in particular. Initial claims of a strong negative impact were based on inadequate empirical evidence and a too limited conceptual approach. This section presents some macro-economic indicators to evaluate their change over the period 1985 to 1993.

**Table 3.1: Nominal and Real GDP Growth, 1985-92**

||**1985**|**1986**|**1987**|**1988**|**1989**|**1990**|**1991**|**1992**|**Average**|
|---|---|---|---|---|---|---|---|---|---|
|Nominal GDP at market prices<br>(N billion)|72.4|73.1|108.9|145.2|224.8|260.8|324.0|549.8|244.3|
|Real GDP at market prices<br>(N billion)|108.3|110.3|108.9|119.3|128.4|138.4|145.9|150.0|128.8|
|Real Growth rates|9.8|1.8|-1.3|9.6|7.6|7.8|5.4|2.8|3.8|
|(in percent)||||||||||
|Real per capita private consumption<br>(in 1987 Naira)|1117|1003|852|864|893|878|877|851|917|

Source: Nigeria Unified Survey, March 1996

1. Table 3.1 shows that in 1986 nominal GDP grew by 1.8 percent, but the growth rate of real GDP was negative in 1987 at -1.3 percent. However, GDP growth picked up and reached a high of 9.6 percent in 1988 and has stabilized at 7.8 percent, 5.4 percent and 2.8 percent in 1990. 1991, and 1992 respectively. In 1993, the relative constancy in the growth rate from the prior year is attributed to the recovery in the services sector, which offset the steady but not increasing oil production levels (World Bank, 1994).

# **4. EVOLUTION OF POVERTY IN NIGERIA**

# **4.1 The Evolution of Mean Expenditure in Nigeria**

It is daunting to try to analyze income distribution in Nigeria. More so than in many developing countries, the availability of relevant data constitutes one of the most serious obstacles to analysis. We do not have an accepted population distribution for Nigeria by age and sex. Almost no national aggregate data exists for the rural areas that would allow us to make a confident judgement about intra-sectoral income distribution. Furthermore, Nigeria is an extremely heterogeneous society. We cannot expect that culturally associated understandings of what constitutes wealth and poverty and the ways people are grouped will necessarily be the same throughout the country. Thus if we want to understand the import of interpersonal, interstate and intersectoral income distinctions, this necessitates sensitivity to the variety of meanings attached to wealth and poverty in different parts of the country.

A number of tentative studies do give various measures of concentration of income in Nigeria or parts of Nigeria. Teriba and Philips (1971) using data from the income tax returns of
12 1966/67 in the former Western state, put the concentration coefficient (or Gini) at 0.47. Adeboye in a survey of 1635 households conducted in 1967 in all states except three, of the then Eastern Region, found a concentration ratio of 0.58. A number of scholars doing cross-national studies have presented various measures of inequality in Nigeria. Adelman and Morris (1971) presented data for Nigeria showing the richest 5 percent accounting for over 38 percent of income in Nigeria and the poorest 20 percent accounting for 7 percent of income in Nigeria. Odafalo (1981) gave the poorest 34 percent of taxpayers about 7 percent of income and concluded that the degree of inequality in Nigeria was widening.

There has been substantial inquiry into the pattern of income distribution in Nigeria. In an edited volume (Bienen and Diejomoah, 1981) many authors address this issue in detail using fragmented studies and national survey, a study which has attracted many criticisms. Bienen estimates that the national income inequality coefficient has moved from 0.5 in 1960 to 0.7 in 1975/76. He also speculates the worsening of it with the oil boom. There have been studies indicating the pattern of income distribution as far back as 1960 by Adelman and Morris (1971) and Vielrose (1963), although due to different methodologies and sample differences the figures do not compare very well. Anusionwu (1981) estimated income distribution by state using public sector employees for 1976 and gives Gini coefficients of 0.442 for Oyo, 0.494 for Niger, 0.496 for Bendel, 0.37 for Cross River and 0.524 for Sokoto. Most of the studies agree that rural inequality is similar to urban inequality. Aigbokhan (1988), who did the other major study on income distribution shows a decline in income inequality from 0.51 in 1960 to 0.37 in 1980 using consumer surveys. Studies by Collier (1983) and Bevan et al (1988) also provide estimates of changes in income composition and income inequality. Collier provides income inequality and land inequality in terms of different crop growers and regions, while Bevan _et al_ provide intrarural and inter-temporal income distribution.

Another issue of interest has been the general distribution of incomes between urban and rural areas. Bevan _et_ al(1988) indicated using nominal expenditure differentials, that between 1950 and 1980, there was a considerable expenditure differential in favor of urban residents because food was cheaper in the rural but manufactures were dearer. Between 1952 and 1954 per capita urban expenditure were 81 percent higher than rural per capita expenditures. It is worth noting that according to the present analysis, in 1985/86 urban per capita expenditures were only 32 percent higher than rural per capita expenditures, and in 1992/93 it was 13.5 percent higher. Faruqee (1993) argues that the gap which was in favor of urban areas at 58 percent in 1980/81 reduced to 8 percent in 1985/86 and reversed to be in favor of rural areas after 1986.

Most of the discussion on evolution of income (or expenditures) distribution included in here will focus on two surveys, the 1985/86 and 1992/93 National Consumer Survey. The first presentations in Table 4.1 below show the mean per capita expenditure distribution of households by expenditure deciles for 1985/86 and 1992/93. Table 4.1 shows that the bottom five percent had a large declining mean per capita expenditure from N 118.11 to N 70.24, between 1985/86 and 1992/93. The table also shows that households in the second five percent had average per capita expenditures of N 175.22 in 1985/86 and a mean expenditure of N 140.5 in 1992/93, a decline of almost 20 percent. The households in the third to tenth deciles show mean per capita expenditures increasing between the two periods from 5 percent in the third
13 decile to 47.5 percent in the tenth decile. The highest increase is in the last decile with 47.5 percent within the seven years of this study. Overall, mean per capita expenditures increased by 34 percent over the seven year period.

However, overall income distribution as shown by the Gini coefficient worsened slightly. In 1985/86 the Gini coefficient was 0.387, the value increased to 0.45 in 1992/93. The table also shows that in 1985/86 there were 35.8 million people (or 43 percent) in poverty as defined by households in which individuals live on less than N 395 per annum or almost a dollar a day. In 1992/93 the population in poverty was 34.7 million individuals or 34.1 percent.

**Table 4.1: Distribution of Per Capita Expenditure by Population Deciles (Constant 1985/86 Naira Per Annum)**

|**Decile**|**1985/86 PCE**|**1992/93 PCE**|**Percentage Change**|
|---|---|---|---|
|First five percent|118.11|70.24|_-40.5_|
|Second five percent|175.22|140.5|-19.8|
|Second Decile|229.47|210.94|-8.1|
|Third Decile|289.98|304.58|5.0|
|Fourth Decile|351.86|404.13|14.9|
|Fifth Decile|421.40|505.68|20.0|
|Sixth Decile|512.03|633.59|23.7|
|Seventh Decile|624.13|806.09|29.2|
|Eighth Decile|769.02|1050.90|36.6|
|Ninth Decile|998.29|1424.91|42.7|
|Tenth Decile|1688.69|2489.99|47.5|
|Mean PCE|592.81|792.64|33.7|
|Moderate Poverty Line|395.41|395.41||
|(2/3 mean PCE in 1985)||||
|Core Poverty Line|197.71|197.71||
|(1/3 mean PCE in 1985)||||
|Moderate Poverty(%)|31.0|20.5|-10.5|
|Core Poverty (%)|12.0|13.6|+1.6|
|Non Poverty(%)|57.0|65.1|+8.1|
|Gini Index|0.387|0.450|16.0|

Source: NCS, 1985/86 and 1992/93.

Table 4.2 shows the distribution by decile of mean per capita household food expenditure. Except for the bottom two deciles, all others indicate an increase in real food expenditures over the seven year period. Overall, there was 41.7 percent increase in mean food expenditure compared to a 34 percent increase in mean per capita total expenditure.

Table 4.1 shows mean per capita expenditure by deciles in both periods. It is clear from the table that except for the first two deciles, incomes have increased in all deciles from 5.0 percent in the third decile to 47.5 percent in the tenth decile. Although the Average per capita expenditure (PCE) has increased by 34 percent nationally, it is important to note that income distribution has worsened with a Gini coefficient of 0.387 to 0.45. Figure 4.1 shows that the proportion of total expenditure by each decile for both periods. It is notable that every decile has a lower share in 1992/93 compared to 1985/86, except the tenth decile. This is also reflected in
14 the Gini coefficient. Figure 4.2 shows the Lorenz curves for Rural, Urban excluding Lagos, Lagos Urban and Nigeria for 1985/86 and 1992/93. The figure shows that Lagos urban distribution has actually improved. The worsening in national income distribution is thus caused mainly by the worsening rural distribution. The Gini coefficients for rural, other urban and Lagos

**Table 4.2: Distribution of Per Capita Food Expenditure by Population Deciles (Constant 1985/86 Naira Per Annum**

|Decile|1985/86**PCE**|**1992/93 PCE**|**Percentage Change**|
|---|---|---|---|
|First five percent|99.20|53.85|-45.7|
|Second five percent|145.89|110.41|-24.3|
|Second Decile|186.50|163.89|-12.1|
|Third Decile|224.17|236.95|5.7|
|Fourth Decile|260.98|309.41|18.5|
|Fifth Decile|295.78|374.01|26.45|
|Sixth Decile|353.27|461.17|30.54|
|Seventh Decile|408.63|567.06|38.77|
|Eighth Decile|482.14|698.77|44.93|
|Ninth Decile|595.65|947.83|59.13|
|Tenth Decile|1047.96|1472.48|40.51|
|Nigeria|391.63|554.92|41.7|

Source: NCS, 1985/86 and 1992/93 urban are shown in Table 4.3. In Lagos urban, the Gini coefficient increased from 0.340 to 0.399. For other urban excluding Lagos, the value increased from 0.366 to 0.441 and in the rural areas, the Gini increased from 0.391 to 0.456 showing a worsening of income distribution. This worsening is reflected in the national Gini coefficient which increased from 0.387 to 0.450.

**Fig 4.1: Evolution of Household Expenditures by Expenditure deciles**

<!-- Start of picture text --> 35 __.. .w<br>Z 30<br>25<br>-s20<br>20<br>15<br>00<br>0 5-<br>0.<br>1 2 3 4 5 6 7 8 9 10<br>Population deciles<br>*1985 01992<br><!-- End of picture text -->
15 Tables 4.3 through 4.5 show the changes in PCE between 1985 and 1992 on a regional basis. For the country as a whole, real household expenditure per capita increased on average by 34 percent over the 1985-92 period. This is consistent with the real positive growth in GDP during this period, and with national account figures on aggregate consumption. The largest increase was recorded in rural areas with 46.8 percent despite a worsening in their distribution. However, other urban areas have also shown an increase in expenditure (25.6 percent) below the national average and even below rural expenditures. Table 4.4 and Table 4.5 show changes by agro-climatic belts together with rural/urban disaggregation. The largest increase in per capita expenditures is in the southern belt region of the country, where per capita expenditures increased from N 660.63 in 1985/86 to N 934.48 in 1992/93. This reflects an increase of 41.4 percent. This increase is followed by middle belt with 40.5 percent. The Northern belt shows the smallest per capita increase of 17.26 percent. Table 4.5 shows the regional changes by urban/ rural split. It shows that the increase in the Middle belt, was due to a large rural increase of 57 percent. The small increase in the Northern belt however, is caused by a small decrease in urban incomes. Nationally, all rural areas show an increase of 46.8 percent compared to 16.08 percent for urban areas.

**Table 4.3: Pattern of Real Household Per Capita Expenditures by Region**

||1985|/86||1992/93||
|---|---|---|---|---|---|
|**Region**|**PCE**|**Gini**|**PCE**|**Percentage**|**Gini**|
|||||**change**||
|Lagos Urban|762.67|0.340|748.62|-1.84|0.399|
|Other Urban|650.28|0.366|816.71|25.59|0.441|
|Rural|531.28|0.391|779.96|46.81|0.456|
|Nigeria|592.81|0.387|792.64|33.7|_0.450_|

**Table 4.4: Pattern of Real Household Per Capita Expenditures by Geographic Regions**

|**Geographic Region**|**1985/86 PCE**|**1992/93 PCE**|**Percentage change**|
|---|---|---|---|
|Northern Belt|540.58|633.91|17.26|
|Middle Belt|536.15|753.56|40.55|
|Southern Belt|660.63|934.48|41.45|
|Nigeria|592.81|792.64|33.71|
16 Figure 4.2: Lorenz Curves for Mean per Capita Expenditures by Region <!-- Start of picture text --> Lorenz Curves for Expenditure<br>Proportions (National 1985-93)<br><!-- End of picture text --> <!-- Start of picture text --> Lorenz Curve for Expenditure<br>Distribution (Rural 1985-93)<br><!-- End of picture text --> <!-- Start of picture text --> Pro.portion T. Tots. Expenditure<br>1 0 a1 /<br>a 600<br>4 000<br>2 00 4<br>00 0.O1 02 0 3 0 4 0 5 0 6 0 7 08 0 9 1 0<br>Proportion of POpulation<br>t19 8 19 93<br><!-- End of picture text --> <!-- Start of picture text --> Proportion of Total Expend iture<br>1 0 0 0<br>a 00<br>4 00<br>200/''''<br>00 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~~0<br>00 01 0 2 0 3 0 4 05 00 0 7 0 8 0 9 10<br>Population 0.1-s<br>19985 - 9 93<br><!-- End of picture text --> <!-- Start of picture text --> Lorenz Curve for Expenditure<br>Distribution (Urban 1985-93)<br><!-- End of picture text --> <!-- Start of picture text --> Proportion 0f Torai Expend.ture<br>100 0 I1000<br>800<br>600<br>400<br>200<br>O<br>00 0 1 02 0.3 04 05 06 07 08 09 10<br>Proportion xf Popularion<br>- 1985 + 1993<br>Stl.-. 1-1-sf 1.1-X3 CES<br><!-- End of picture text --> <!-- Start of picture text --> Lorenz Curve for Expenditure<br>Distribution (Lagos Urban 1985-93)<br><!-- End of picture text --> <!-- Start of picture text --> Proportion ot Total Expenditure<br>I<br>800<br>90 0<br>400<br>2 00<br>~~~~~~~~~~~~~~~~~~~~~~~~~0~0<br>00 01 02 03 04 05 06 07 0.8 09 10<br>Proportion 0l Pop.;xt.on<br>-1985 + 1993<br>S.-ce*6S$. 1iiiS9 ces<br><!-- End of picture text -->
17

# **Table 4.5: Rural/Urban Pattern of Real Household Per Capita Expenditures by Geographic Region**

|||**RU**|**RAL**||**UR**|**BAN**|
|---|---|---|---|---|---|---|
|**Region**|**1985/86**|**1992/93**|**Percentage change**|**1985/86**|**1992/93**|**Percentage change**|
|Northern|476.58|629.75|32.14|682.63|643.4|-5.75|
|Middle Belt|<br>488.44|766.11|56.85|631.74|732.67|15.98|
|Southern|607.68|936.70|54.14|732.98|931.78|27.12|
|Nigeria|531.28|779.96|46.81|700.35|812.95|16.08|
|Source: NCS,|1985/86 and 1|992/93.|||||

# **4.2 Evolution of Regional Poverty in Nigeria**

This section examines the evolution of poverty between 1985 and 1992. In analyzing the extent of poverty, it would generally be preferable to use individuals rather than household as the unit of analysis. Re-weighting the data according to household size is an alternative, but this makes the assumption that consumption is evenly distributed within the households. Given that there is inadequate information to construct adult equivalence scales, Average per capita expenditure (PCE) is used as the basis for poverty analysis.

The evolution of regional poverty is shown in Table 4.6. In 1992 about 23 million people (36.4 percent) were poor in the rural areas, accounting for about 66 percent of the poor in Nigeria. There was a 13 percentage point decline in rural headcount or the number of poor. However, taking into consideration all below the poverty line in Nigeria, rural areas accounted for about 73 percent of the poor in 1985 and 66 percent of the poor in 1992. In 1985 the depth of poverty was about 30 percent higher in the rural than in the urban areas. This value however, despite the decline in poverty in 1992, had increased to two times the depth in "Other urban" excluding Lagos and almost 17 times the depth in Lagos urban. The severity of poverty in the rural areas in 1985 was three times as high as it was for Lagos. In 1992, the value for rural was over 4 times that of Lagos.

Table 4.7 shows the evolution of regional core or extreme poverty. The table shows that the incidence of extreme poverty increased slightly in the seven year period of this study. The depth of extreme poverty and the severity of extreme poverty also increased during this period. The increase in the severity of extreme poverty was observed to be more in the urban than in rural areas. However, the rural areas continue to contribute the largest share to all the indicators.
18

**Table 4.6: Poverty Incidence in Nigeria by Region, 1985-93 (Poverty Line=N395.41)**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**REGION**|**P0**|P1|P2|P0|**P1**|**P2**|
|Other Urban (Excluding Lagos)|0.320|0.070|0.038|0.306|0.101|0.048|
|Rural|0.495|0.189|0.095|0.364|0.122|0.066|
|Lagos Urban|0.240|0.070|0.032|0.279|0.161|0.095|
|AllNigeria|0.430|0.157|0.079|0.341|0.147|0.085|

**Rural/Urban Decomposition of Poverty Incidence**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**REGION**|**P0**|**P1**|P2|Po|**P1**|**P2**|
|Other Urban (Excluding Lagos)|26.3|14.8|12.4|32.6|26.9|_25.5_|
|Rural|73.1|84.9|87.3|65.7|71.9|73.5|
|Lagos Urban|0.6|0.3|0.3|1.7|1.2|0.1|
|All Nigeria|100.0|100.0|100.0|100.0|100.0|100.0|
|Source: NCS, 1985/86 and 1992/9|3.||||||

# **Table 4.7: Incidence of Extreme Poverty in Nigeria by Region, 1985-93 Poverty Line=N197.71)**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**REGION**|**P0**|**PI**|P2|**P0**|**P1**|P2|
|Other Urban (Excluding Lagos)|0.049|0.009|0.003|0.111|0.037|0.018|
|Rural|0.161|0.042|0.017|0.154|0.060|0.032|
|Lagos Urban|0.043|0.015|0.006|0.072|0.021|0.008|
|AllNigeria|0.120|0.042|0.016|0.136|0.085|0.034|

**Rural/Urban Decomposition of Incidence of Extreme Poverty**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**REGION**|P0|**PI**|P2|**P0**|**PI**|**P2**|
|Other Urban (Excluding Lagos)|14.4|3.5|2.6|29.6|20.7|19.4|
|Rural|85.2|96.3|97.2|69.3|78.7|80.2|
|Lagos Urban|0.4|0.2|0.2|1.1|0.5|0.3|
|All Nigeria|100.0|100.0|100.0|100.0|100.0|100.0|

Source: NCS, 1985/86 and 1992/93.

As seen in Table 4.8, rural Southern belt has the largest decline (16.6 percentage points) in headcount, 4.2 percentage points decline in depth and 0.9 percentage points decline in
19 severity. Also, the Northern belt has a 9.1 percentage points decline in headcount, 2.1 percentage points decline in depth and 0.4 percentage points increase in severity.

**Table 4.8: Rural/Urban Poverty Incidence in Nigeria by Geographical Belts, 1985-93 (Poverty Line-N395.41)**

||||**_RURAL_**||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/93**||
|**Region**|**P0**|**P1**|**P2**|**P0**|**P,**|P2|
|Northern|0.555|0.219|0.112|0.464|0.198|0.116|
|Middle Belt|0.521|0.219|0.120|0.385|0.179|0.112|
|South Belt|0.420|0.144|0.066|0.254|0.102|0.057|
|_All Rural_|_0.495_|_0.169_|_0.098_|_0.364_|_0.167_|_0.098_|

_URBAN_

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**Region**|**Pr**|**P1**|**P2**|**P0**|**P,**|**P2**|
|Northern|0.331|0.105|0.047|0.417|0.180|0.095|
|MiddleBelt|0.381|0.117|0.049|0.371|0.153|0.086|
|South|0.289|0.075|0.028|0.221|0.093|0.050|
|_All Urban_|_0.317_|_0.124_|_0.051_|_0.304_|_0.140_|_0.076_|

Note: Northern belt comprises: Bauchi, Borno, Sokoto, and Kano. Middle belt comprises: Kaduna, Benue, Kwara, FCT, Niger and Plateau states. Southern belt comprises: Anambra, Cross River, Gongola, Imo, Bendel, Lagos, Ogun, Ondo, Rivers and Oyo States.

Source: NCS, 1985/86 and 1992/93.

Looking at the urban areas in Table 4.8, the headcount in northern belt has increased by 8.1 points and the depth of poverty by 7.5 points. Also, the southern belt shows a higher decline of 6.8 points in headcount compared to 1.0 point in middle belt. Table 4.9 also shows that despite the decline in headcount in the middle belt, its contribution to urban headcount increased by 1 percentage point. In the south, which had displayed a larger decline in headcount there was a decline of 8.3 percentage points in its contribution to urban headcount from 46.7 points in 1986 to 38.4 points in 1992.
20

**Table 4.9: Rural/Urban Poverty Decomposition by Geographical Regions 1985-93, (Poverty Line=N395.41)**

||||**_RURAL_**||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/93**||
|**Region**|**P0**|**PI**|**P2**|**P0**|**P1**|**P2**|
|Northern|46.8|52.8|53.4|51.3|50.84|60.24|
|Middle Belt|19.2|21.7|23.6|20.6|22.06|23.35|
|Southern|34.1|25.4|22.9|28.1|17.10|16.41|
|_All Rural_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|
|||**1985/86**|_URBAN_||**1992/93**||
|**Region**|**P0**|**P1**|**P2**|**Po**|**P,**|**P2**|
|Northern|34.2|38.6|41.6|38.7|49.6|48.5|
|Middle|19.0|23.9|24.2|22.9|24.94|26.04|
|Southern|46.7|37.5|34.2|38.4|25.4|25.5|
|_All Urban_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|

Source: NCS, 1985/86 and 1992/93.

Tables 4.10 and 4.11 show the poverty incidence indicators by agroclimatic zones. In 1985, 54.9 percent was poor in rural north and 34.2 percent in urban north. In 1992, the corresponding figures are 44.2 percent and 40.3 percent respectively. The Southern region classified into Southwest and Southeast is very illuminating. Poverty in the cocoa producing rural Southern regions is the lowest. This comes out convincingly in Table 4.11, where rural Southwest contributes the least to national rural poverty with 17.1 percent in 1985 and 15.3 percent in 1992. Even in urban areas, the Southwest decline in poverty incidence is very pronounced. In terms of depth and severity of poverty, Southwest is performing well. Except for rural Southeast, where poverty severity has worsened over the seven year period, all indicators of agroclimatic zones show a general trend of improvement.

Table 4.12 shows the evolution in poverty measures, by state. Taking the head count (P0) first, the table shows that Gongola, Cross River and Sokoto are the only states that show an increase in head count index of poverty during 1985/86-1992/93. The sharpest decline in head count (26%) was for the state of Bendel, Cross Rivers, Sokota are the states indicating an increase in the depth (PI) of poverty. Six states however, show an increase in severity (P2 ) of poverty during the seven year period of this study. The highest increase in P2 (6.4 percentage points) occurred in Sokoto.
21

# **Table 4.10: RuralUrban Poverty Incidence in Nigeria by Agro-climatic Zones, 1985-93 (Poverty Line=N395.41)**

**_RURAL_**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**Region**|**P0**|**P,**|P2|**P0**|P,|**P2**|
|Northern|0.549|0.220|0.115|0.442|0.198|0.117|
|Southeast|0.434|0.158|0.075|0.260|0.117|0.070|
|Southwest|0.419|0.141|0.064|0.271|0.113|0.062|
|_All Rural_|_0.495_|_0.194_|_0.098_|_0.364_|_0.167_|_0.098_|
|||**1985/86**|_URBAN_||**1992/93**||
|**Region**|**P0**|**P1**|P2|**P0**|**P1**|**P2**|
|Northern|0.342|0.106|0.046|0.403|0.160|0.086|
|Southeast|0.273|0.072|0.027|0.226|0.097|0.057|
|Southwest|0.324|0.087|0.034|0.230|0.084|0.044|
|_All Urban_|_0.317_|_0.093_|_0.038_|_0.304_|_0.140_|_0.076_|

Source: NCS, 1985/86 and 1992/93.

**Table 4.11: Rural/Urban Poverty Decomposition by Agro-climatic Zones, 1985-93 (Poverty Line=N395.41)**

**_RURAL_**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**Region**|**P0**|**P1**|**P2**|**Po**|**P1**|**P2**|
|Northern|61.8|70.3|72.5|67.9|56.1|78.8|
|Southeast|21.2|17.3|16.2|16.8|8.2|17.1|
|Southwest|17.1|12.4|11.3|15.3|7.2|4.1|
|_All Rural_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|
|||**1985/86**|**_URBAN_**||**1992/93**||
|**Region**|**P0**|**PI**|**P2**|**Po**|**PI**|**P2**|
|Northern|48.4|_55.5_|58.4|57.6|71.3|68.5|
|Southeast|24.9|19.4|17.7|19.1|15.2|15.1|
|Southwest|26.7|25.1|23.9|23.2|13.5|16.4|
|_Al/ Urban_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|

Source: NCS, 1985/86 and 1992/93.

Since the North did not show substantial improvements, one could use Table 4.12 to see which states did well and which did not. Focusing on the poverty measures of Bauchi, Kaduno, Kano and Sokoto in alphabetical order, Kaduna shows a 25.1 percentage points decline in headcount, 8.3 percentage points decline in depth and 3.4 percentage points in severity. The state of Bauchi shows 3.1 points decline in headcount, 1.1 points increase in depth and 0.1 percentage
22 points increase in severity. The state of Kano shows 2.5 percentage points in head count, 3.5 percentage points decline in depth and 2.8 percentage points decline in severity. State of Sokoto shows 5.7 points increase in headcount, 7.1 percentage points increased in depth and 6.4 percentage points increase in severity.

Table 4.13 shows that Sokoto was the highest contributor to all indicators in 1985, with a contribution of 12.5 percentage points to headcount, 14.1 percentage points to depth and 14.7 points to severity respectively. The values were very closely followed by Kano with 11.3, 11.5 and 10.9 percentage points for headcount, depth and severity respectively. Some states (Bauchi and Plateau) show large increases in contribution to all three indicators for the seven years covered in this study. These two states contribute the highest to poverty incidence, depth and severity even in 1992/93.

**Table 4.12: Poverty Incidence in Nigeria by State, 1985-93 (Poverty Line=N395.41)**

|||1985/86|||1992/93||
|---|---|---|---|---|---|---|
|**STATE**|**P0**|**P1**|P2|Po|**P1**|**P2**|
|Lagos (Urban)|0.240|0.070|0.032|0.279|0.009|0.003|
|FCT|0.000|0.000|0.000|0.495|0.245|0.157|
|Anambra|0.309|0.104|0.045|0.163|0.059|0.031|
|Bauchi|0.587|0.247|0.132|0.556|0.236|0.133|
|Bendel|0.417|0.146|0.067|0.162|0.061|0.033|
|Benue|0.460|0.183|0.093|0.368|0.176|0.114|
|Borno|0.421|0.168|0.087|0.418|0.185|0.108|
|Cross River|0.421|0.139|0.061|0.330|0.156|0.094|
|Gongola|0.488|0.191|0.098|0.317|0.129|0.068|
|Imo|0.322|0.101|0.045|0.144|0.066|0.040|
|Kaduna|0.498|0.180|0.087|0.247|0.097|0.053|
|Kano|0.483|0.164|0.076|0.508|0.199|0.104|
|Kwara|0.413|0.130|0.054|0.314|0.136|0.082|
|Lagos (Rural)|0.361|0.116|0.052|0.361|0.145|0.076|
|Niger|0.566|0.285|0.182|0.444|0.200|0.122|
|Ogun|0.454|0.145|0.062|0.263|0.097|0.048|
|Ondo|0.445|0.179|0.093|0.266|0.112|0.066|
|Oyo|0.315|0.072|0.024|0.229|0.088|0.047|
|Plateau|0.475|0.172|0.087|0.426|0.188|0.113|
|Rivers|0.358|0.097|0.036|0.379|0.158|0.088|
|Sokoto|0.469|0.185|0.094|0.526|0.256|0.158|
|**All Nigeria**|**0.430**|**0.157**|**0.079**|**0.341**|**0.147**|**0.085**|

Source: NCS, 1985/86 and 1992/93.
23

**Table 4.13: Decomposition of Poverty Incidence by State, 1985-93 (Poverty Line=N395.41)**

|||1985/86|||1992/93||
|---|---|---|---|---|---|---|
|**STATE**|**P0**|**P1**|**P2**|**Po**|**PI**|P2|
|Lagos (Urban)|0.6|0.3|0.3|0.0|0.0|0.0|
|FCT|0.0|0.0|0.0|1.4|1.9|2.2|
|Anambra|4.5|2.9|2.6|3.1|1.1|0.9|
|Bauchi|5.8|8.9|9.7|6.9|9.5|9.4|
|Bendel|4.1|3.7|3.5|2.0|0.7|0.7|
|Benue|4.4|4.9|5.1|4.0|4.1|4.7|
|Bomo|5.0|5.3|5.6|6.1|6.7|6.8|
|Cross River|6.0|5.2|4.7|4.4|4.1|4.3|
|Gongola|5.1|6.1|6.3|3.6|2.7|2.5|
|Imo|4.8|3.0|2.7|2.8|1.1|1.1|
|Kaduna|9.0|10.1|10.0|5.6|3.2|3.0|
|Kano|11.3|11.5|10.9|15.3|18.1|16.4|
|Kwara|3.0|2.4|2.1|3.0|2.4|2.5|
|Lagos (Rural)|_1.5_|1.3|1.2|4.6|3.9|3.6|
|Niger|2.8|4.9|6.4|3.3|3.9|4.2|
|Ogun|2.9|2.6|2.3|1.9|1.1|0.9|
|Ondo|3.9|4.3|4.6|3.7|2.5|2.5|
|Oyo|6.6|2.9|1.9|5.8|3.0|2.8|
|Plateau|3.9|4.1|4.3|6.1|6.8|7.1|
|Rivers|2.5|1.5|1.1|3.2|3.0|2.9|
|Sokoto|12.5|14.1|14.7|13.1|19.8|21.3|
|**All Nigeria**|**100.0**|**100.0**|**100.0**|**100.0**|**100.0**|**100.0**|

Source: NCS, 1985/86 and 1992/93 Tables 4.14 and 4.15 shows the evolution of extreme poverty by state. Ten out of the 19 state structure show increases in extreme poverty. We find from the table that the following states have shown an increase in headcount of extreme poverty. Anambra (0.6 percentage points), Cross Rivers (6.7 percentage points), Plateau (4.0 percentage points), Sokoto (9.8 percentage points), Kaduna (7.7 percentage points), Kano (3.9 percentage points), Kwara (4.4 percentage points), Ogun (0.7 percentage points) and Rivers (12.6 percentage points). Also, eleven states have registered an increase in the depth of extreme poverty as follows: Anambra (0.2 percentage points), Benue (3.5 percentage points), Bauchi (0.9 percentage points), Cross River (4.1 percentage points), Kano (2.6 percentage points), Kwara (4 percentage points), Ondo (0.3 percentage points), Oyo (2.5 percentage points), Plateau (3.5 percentage points), and Rivers (4.6 percentage points).
24

**Table 4.14: Incidence of Extreme Poverty in Nigeria by State, 1985-93 (Poverty Line=N197.71)**

|||1985/86|||1992/93||
|---|---|---|---|---|---|---|
|**STATE**|**P0**|**PI**|P2|Po|P,|P2|
|Lagos (Urban)|0.043|0.015|0.006|0.072|0.021|0.008|
|FCT|0.000|0.000|0.000|0.252|0.108|0.067|
|Anambra|0.055|0.012|0.005|0.061|0.014|0.006|
|Bauchi|0.221|0.066|0.025|0.208|0.075|0.040|
|Bendel|0.099|0.017|0.005|0.052|0.020|0.011|
|Benue|0.187|0.043|0.014|0.174|0.078|0.054|
|Bomo|0.160|0.042|0.017|0.163|0.067|0.036|
|Cross River|0.090|0.021|0.009|0.157|0.062|0.034|
|Gongola|0.144|0.043|0.021|0.117|0.033|0.017|
|Imo|0.062|0.015|0.005|0.080|0.025|0.012|
|Kaduna|0.156|0.036|0.013|0.079|0.031|0.016|
|Kano|0.128|0.027|0.009|0.167|0.053|0.025|
|Kwara|0.071|0.015|0.004|0.115|0.055|0.034|
|Lagos (Rural)|0.076|0.019|0.006|0.131|0.057|0.023|
|Niger|0.295|0.129|0.076|0.176|0.084|0.053|
|Ogun|0.069|0.019|0.006|0.076|0.020|0.008|
|Ondo|0.168|0.040|0.013|0.104|0.043|0.023|
|Oyo|0.011|0.001|0.000|0.076|0.026|0.013|
|Plateau|0.140|0.043|0.019|0.180|0.078|0.044|
|Rivers|0.028|0.006|0.002|0.154|0.052|0.024|
|Sokoto|0.182|0.043|0.014|0.280|0.107|0.055|
|**All Nigeria**|**0.120**|**0.042**|**0.016**|**0.136**|**0.085**|**0.034**|
|Source: NCS, 198|5/86 and 199|2/93.|||||

More than half (11 states) of the states indicate an increase in the severity of poverty, as follows: Anambra (0.1 percentage points), Bauchi (1.5 percentage points), Benue (1.1 percentage points), Cross River (2.5 percentage points), Kano (1.6 percentage points), Kwara (3.0 percentage points), Ondo (1.0 percentage points), Oyo (1.3 percentage points), Plateau (2.5 percentage points), and Rivers (2.2 percentage points). Seven of the states that show increases in headcount also show increases in all three poverty measures. On aggregate there is a doubling of 1.8 points in the severity of core poverty in Nigeria. From Table 4.15, it can be seen that in 1985, three Northern states (Kaduna, Kano and Sokoto) accounted for 38 percent of all the core poor, contributed 34.0 percent to the depth of poverty and 28.7 percent to the severity of poverty. In 1992 the numbers had reduced by 4 percentage points for headcount, 8 and 11 percentage points for the depth and severity respectively. On the other hand, five states have shown dramatic increases in the headcount, depth, and severity of core poverty. They are Kwara, Oyo, Rivers, Plateau and Sokoto. Lagos urban areas made almost no contribution to extreme poverty in 1992/93.
25

**Table 4.15: Decomposition of Extreme Poverty Incidence by State, 1985-93 (Poverty Line=N197.71)**

|||1985/86|||1992/93||
|---|---|---|---|---|---|---|
|**STATE**|**P0**|**P1**|P2|**P0**|P,|P2|
|Lagos (Urban)|0.4|0.2|0.2|1.1|0.4|0.3|
|FCT|0.0|0.0|0.0|1.7|2.9|3.4|
|Anambra|2.9|0.9|0.8|2.9|0.6|0.5|
|Bauchi|7.9|12.6|11.9|6.4|7.6|7.6|
|Bendel|3.5|1.4|1.1|1.6|_0.5_|_0.5_|
|Benue|6.4|6.7|5.3|4.7|5.8|7.5|
|Bomo|6.9|7.1|7.3|6.0|6.3|6.3|
|Cross Rivers|2.4|2.5|6.8|5.3|5.2|5.4|
|Gongola|5.4|5.7|6.8|3.3|1.7|1.7|
|Imo|3.3|1.2|1.0|3.9|1.6|1.3|
|Kaduna|10.1|9.0|7.9|4.4|2.1|2.1|
|Kano|10.8|7.2|5.9|12.6|10.6|9.3|
|Kwara|1.9|0.7|0.5|2.7|2.4|2.7|
|Lagos (Rural)|1.2|0.6|0.4|4.1|2.7|2.1|
|Niger|5.1|16.3|23.8|3.3|4.4|5.2|
|Ogun|1.6|0.7|0.6|1.4|0.5|0.3|
|Ondo|5.3|5.1|4.3|3.6|2.4|2.4|
|Oyo|0.8|0.0|0.0|4.8|1.9|1.8|
|Plateau|4.1|4.3|4.8|6.5|7.9|8.5|
|Rivers|0.7|0.1|0.1|3.3|2.7|2.3|
|Sokoto|17.1|17.8|14.8|17.4|29.4|28.5|
|All**Nigeria**|**100.0**|**100.0**|**100.0**|**100.0**|**100.0**|**100.0**|

Source: NCS, 1985/86 and 1992/93.

# **4.3 Evolution of Poverty and Household Composition**

Table 4.16 shows the incidence of poverty by age groups. It should be noted that in the rural areas, the largest decline in headcount of 15.4 percentage points has been in the 66 and over age cohort, followed by the 36 to 45 age group with 14.7 percentage points. The 16 to 25 age cohort showed a 1.1 percentage points decline in headcount. The large decline in the headcount of the 56 and older heads of households in the rural areas can be explained by the fact that most of these are households whose heads are retired and returned to the rural areas thus helping to reduce poverty in these age groups.
26

**Table 4.16: Incidence of Poverty by Age Group of Head of Household 1985-93 (Poverty Line=N395.41)**

||||**_RURAL_**||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/93**||
|**Age**Group|**P0**|**P,**|P2|**P0**|**P,**|**P2**|
|16 to 25|0.273|0.093|_0.054_|0.262|0.128|0.097|
|26 to 35|0.389|0.120|0.060|0.305|0.096|0.052|
|36to45|0.512|0.160|0.078|0.365|0.155|0.091|
|46to55|0.512|0.188|0.096|0.391|0.169|0.098|
|56 to 65|0.552|0.190|0.094|0.398|0.180|0.106|
|66andOver|0.570|0.207|0.108|0.358|0.162|0.100|
|_All Rural_|_0.495_|_0.169_|_0.085_|_0.364_|_0.167_|_0.098_|
||||**_URBAN_**||||
|||**1985/86**|||**1992/93**||
|Age Group|**P0**|P1|P2|**P,**|**P,**|P2|
|16 to 25|0.101|0.056|0.020|0.172|0.061|0.023|
|26 to 35|0.226|0.077|0.029|0.182|0.106|0.062|
|36 to 45|0.304|0.124|0.051|0.316|0.138|0.077|
|46to55|0.411|0.147|0.060|0.364|0.136|0.068|
|56 to 65|0.390|0.166|0.076|0.393|0.161|0.081|
|66andOver|0.406|0.135|0.052|0.344|0.170|0.101|
|_All Urban_|_0.317_|_0.124_|_0.051_|_0.304_|_0.140_|_0.076_|

Source: NCS, 1985/86 and 1992/93.

Focusing on the urban areas, we find the largest decline (6.2 percentage points) in headcount is within the 66 & over age-group, closely followed by the 46 to 55 age-group with 4.7 points decline in headcount.
27

**Table 4.17: Contribution of Poverty by Age Group of Head of Household, 1985-93 (Poverty Line=N395.41)**

||||_RURAL_||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/9**|**3**|
|**Age Group**|**P0**|**P,**|**P2**|**P0**|P,|**P2**|
|16 to 25|1.7|2.3|1.3|1.9|1.5|2.0|
|26 to 35|14.2|8.5|10.0|14.6|8.9|8.2|
|36 to 45|30.2|23.5|27.7|27.8|27.7|27.7|
|46 to 55|26.5|29.4|29.3|27.0|29.2|28.7|
|56 to 65|17.6|26.8|19.5|19.5|22.5|22.6|
|66 and Over|9.6|10.3|12.2|10.1|9.5|9.9|
|_Al/ Rural_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|
||||_URBAN_||||
|||**1985/86**|||**1992/93**||
|**Age Group**|**P0**|**P,**|**P2**|**P0**|**P,**|**P2**|
|16 to 25|1.2|_0.5_|0.4|2.0|0.0|0.6|
|26 to 35|17.6|6.1|9.6|13.1|10.1|10.9|
|36to45|29.9|35.8|28.8|31.9|31.9|33.1|
|**46**to 55|28.6|24.5|32.2|28.4|27.9|25.9|
|56 to 65|14.0|20.9|20.4|15.3|17.8|16.7|
|66 and Over|8.8|11.7|8.6|9.2|11.4|12.5|
|_All Urban_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|
|Source: NCS, 1|985/86 and 19|92/92.|||||

Table 4.18 shows the incidence of poverty by gender of head of household. Taking the rural areas first, in 1985 the headcount for male and female headed households was 50.5 percent and 42.1 percent respectively. In 1992 the values were 37.9 percent and 21.8 percent for male and female headed households respectively. There was a decline of 12.6 percentage points among male headed households and a much larger decline of 20.3 percentage points among the female headed households in the rural areas. There was a 2.7 percentage points decline in the depth of poverty among rural male headed households, compared to 4.8 points decline among rural female headed households. The table also shows that there was 0.4 percentage points increase in the severity of poverty among male headed households in rural areas, compared to 2.5 percentage points increase in urban areas. In the urban areas, there were 0.9 percentage points decline in headcount, 1.5 percentage points increase in depth and 2.5 percentage points increase in severity among male headed households within the period of our study. Looking at the urban female headed households, there were 7.2 percentage points decline in headcount, 2.0 and 0.3 percentage points decline in depth and severity respectively, during the period of our study. The poverty measures for female headed households show that they fared much better than the male headed households in terms of all three measures of poverty. However, it should be recalled that female headed households make up only 10 percent of all households in Nigeria.
28

**Table 4.18: Incidence of Poverty by Gender of Head of Household, 1985-93 (Poverty Line=N395.41)**

||||**_RURAL_**||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/93**||
|**Gender of Head**|||||||
|**of Household**|**P0**|**P,**|**P2**|**Po**|**PI**|P2|
|Male Headed|0.505|0.185|0.089|0.379|0.158|0.093|
|Female Headed|0.421|0.142|0.061|0.218|0.094|0.056|
|_All Rural_|_0.495_|_0.169_|_0.085_|_0.364_|_0.167_|_0.098_|
||||_URBAN_||||
|||**1985/86**|||**1992/93**||
|**Gender of Head**|||||||
|**of Household**|**P0**|**P,**|**P2**|**P0**|**PI**|**P2**|
|Male Headed|0.326|0.128|0.053|0.317|0.143|0.078|
|Female Headed|0.277|0.090|0.032|0.209|0.070|0.035|
|_All Urban_|_0.317_|_0.124_|_0.051_|_0.304_|_0.140_|_0.076_|
|Source: NCS, 1985|/86 and 199|2/93.|||||

Table 4.19 shows the incidence of poverty by the educational level of head of household. Taking the rural areas first, in 1985 more than _50_ percent of households whose heads had no education were poor. All the poverty measures show an exponential decline with increasing education, in both periods. However, some interesting facts seem to emerge out of this table. There is a decline of 2.4 percentage points in headcount, 3.2 percentage points increase in depth and 3.4 percentage points increase in severity respectively among the uneducated in rural areas, but for primary school leavers while the head count has declined, the depth and severity has increased. For secondary and post secondary school leavers, the results are mixed. For the secondary school leavers, there was a very small (3.1 percentage points) decline in headcount, a 2.1 percentage point increase in depth, and a 2.4 percentage point increase in severity of poverty. For the post secondary school leavers, there was an increase in all measures during the period of our study. In the urban areas, there was a decline in headcount, depth and severity of poverty for households whose heads had below primary education. Again for the post secondary school leavers, the trend was similar to that of the rural areas, resulting in higher depth and severity of poverty.
29

# **Table 4.19: Incidence of Poverty by Educational Level of Head of Household, 1985-93 (Poverty Line=N395.41)**

||||**_RURAL_**||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/93**||
|**Education**<br>**Level**|**P0**|**P,**|P2|**P0**|**P1**|**P2**|
|No Education|0.519|0.187|0.095|0.495|0.219|0.129|
|Primary Educ.|0.475|0.142|0.069|0.289|0.118|0.064|
|Second. Educ.|0.288|0.075|0.032|0.257|0.096|0.058|
|Post Secondary|0.162|0.000|0.000|0.215|0.112|0.069|
|_All Rural_|_0.495_|_0.169_|_0.085_|_0.364_|_0.167_|_0.098_|
||||_URBAN_||||
|||**1985/86**|||**1992/93**||
|**Education Level**|**P0**|**P1**|**P2**|**Po**|**P,**|**P2**|
|No Education|0.378|0.148|0.065|0.428|0.162|0.077|
|Primary Educ.|0.286|0.102|0.038|0.282|0.113|0.065|
|Second. Educ.|0.211|0.053|0.018|0.214|0.087|0.046|
|Post Secondary|0.238|0.000|0.000|0.235|0.084|0.044|
|_All Urban_|_0.317_|_0.124_|_0.051_|_0.304_|_0.140_|_0.076_|

Source: NCS, 1985/86 and 1992/93.

**Table 4.20 Incidence of Extreme Poverty by Educational Level of Head of Household (Poverty Line=N197.71)**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**Education**<br>**Level**|**P0**|**P,**|**P2**|**P0**|**P,**|**P2**|
|No Education|0.148|0.049|0.018|0.162|0.061|0.032|
|Primary Educ.|0.065|0.023|0.007|0.109|0.038|0.020|
|Secondary Educ.|0.089|0.004|0.004|0.078|0.031|0.018|
|Post Secondary|0.000|0.000|0.000|0.093|0.030|0.017|
|_All Nigeria_|_0.120_|_0.042_|_0.016_|_0.136_|_0.085_|_0.034_|
|**Contr**|**ibution of**|**Extreme Pove**<br>**1985/86**|**rty Incidence**|**by Educatio**|**n of Head**<br>**1992/93**||
|**Education**<br>**Level**|**P0**|**PI**|**P2**|**P0**|**PI**|**P2**|
|No Education|80.0|89.2|90.6|71.5|81.18|80.7|
|Primary Educ.|18.5|10.7|9.3|18.2|12.9|13.1|
|Secondary Educ.|_1.5_|0.1|0.1|7.0|4.0|4.3|
|Post Secondary|0.0|0.0|0.0|3.3|1.8|1.9|
|_All Nigeria_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|

Source: NCS, 1985/86 and 1992/93.

In Nigeria, as elsewhere, education can play a key role in reducing poverty over the long term, both indirectly through improving the productivity and efficiency of the labor force,
30 leading to faster rates of economic growth, or directly by giving the poor the skills they need to raise their productivity and hence incomes. For the latter, primary education or its equivalence is of prime importance.

# **4.3 Poverty and Employment**

Unemployment was primarily one of high school graduates. In December 1985 6/, 68.3 percent of the unemployed were secondary and post secondary school leavers. Their unemployment as a percent of the national unemployed increased to 71.5% in 1986 and peaked at 76% in 1987. Although in general education improves household prospects of escaping poverty, the analysis above shows that in the years of our study, many secondary and post secondary school leavers might be expected to be in poverty.

It is important to note here that those who reported themselves as illiterate appear to be only slightly poorer than individuals who declared themselves literate. This may well be indicative of a number of factors related to the supply and demand for education. On the demand side, it might very well be that the benefits of education are not adequately rewarded in the labor markets in Nigeria by increased incomes because skill and technical training are important along with formal educational attainments.

But just how uneducated are the poor? Based on the chosen poverty line, most of the population lives in households where 64.5 percent of the time, the head is illiterate, it is very likely that a lot of the women in the poor households are illiterate. The negative relationship between education and per capita expenditures confirms this hypothesis. Low educational attainment among the adult population, however, is more an indication of past levels of access to education than of present. Enrollment ratios, especially in primary school represent therefore a better measure of current access to education, and the potential for future reduction in poverty through human capital investments.

Although one would expect that the fall in real wages would enhance employment prospects, experience in Nigeria during the 1980s does not support the theory. Table A3.6 (Appendix 3) shows that urban unemployment increased from 7.3 percent in 1983 to about 10.8 percent in 1987, but gradually decreased to 4.2 percent by 1993. Essentially, 3 to 4 million of the labor force were out of work in 1986. This period corresponds to the recession in Nigeria when macroeconomic stabilization was being sought without growth and structural adjustment. Due to critical shortages of foreign exchange, enterprises ran at far less than capacity, and large cuts in employment were effected through involuntary retrenchments. For instance, between 1984 and 1985, the employment in three industrial occupations (manufacturing, trading/services, and building and construction) dropped from 76,560 to 72,604 showing a contraction of over _5_ percent in employment.7/ Although the size seems small, the sharpest cut occurred in building and construction (36 percent), though numerically, manufacturing sustained the largest cut.

5/ See Appendix Table 3.6

**6/** See Lemma Merrid( 1991).
31 Who were the unemployed and how did they fare? Three pieces of information are given in Table A3.6 (Appendix 3) to illustrate the point; viz. unemployment by age group, level of education, and geographical distribution. Examining the patterns of distribution by age group, a distinct feature of the situation is that unemployment was centered among the youth.

In some years, the rates were very high, take for example the two age groups comprising cohorts 15-19 and 20-24 years, the unemployment rate increased from 28.6 percent in 1985 to 30.1 percent in 1986 (commencement of the adjustment program), for the former and decreased from 39 percent to 37.2 percent for the latter. However, unemployment is highest in the 20-24 age cohort. The rate peaked at 43.3 percent in 1988 and has been fluctuating since then. Following the overall decline in unemployment, youth unemployment declined to 25.1 percent the first year of the adjustment program (June 1987) and 23.9 percent the second year (March 1988) for the 15-19 cohorts and 38.5 percent and 35.7 percent (1990) respectively for the 20-24 year age group.

Looking at the regional distribution, Table A3.6 also shows that unemployment was more pronounced in the southern states, where unemployment rates of 11-13 percent were registered. Most of the unemployed were located in the south, where 47 percent of Nigeria's population lives. The middle states had unemployment rates between 7-8 percent but the number was not estimated to be large since only 18 percent of the population lived in this region at the time.

The urban unemployment rate in 1986 was 10 percent compared to 4.8 percent for rural. This implied that the forces that could induce urban to rural exodus were not strong enough. To the extent that the urban unemployed were the educated youth, agriculture, the largest economic activity in the rural areas did not attract their attention. Even if they decided to take up rural residence, the lack of land and agricultural skills do not seem to support an urban to rural movement. Moreover, to the extent that the unemployed expected urban labor market to revive eventually, the perception of higher urban income is likely to encourage them to stay in the urban areas.

With this background information in mind, this sub-section looks at the effect of labor market on poverty and the sectors/industries in which the poor were employed. Poverty by occupational category showed a high incidence in 1985/86 in the agriculture group. This continues to be the case in 1992/93. There is also an indication that distribution of income has changed against this group as is evident from the distributionally sensitive poverty measures like depth and severity of poverty. Table 4.21 shows that the rural headcount in agriculture reduced by 9.2 percentage points, depth by 3.4 percentage points and severity by 1.1 percentage points between the two periods. This has accounted for the reduction in poverty in the rural areas.

Table 4.21 also shows that rural poverty in the production and transportation area declined substantially. Headcount declined by 23.4 percentage points, the highest of any sector. The depth of poverty declined by 1.4 points while the severity of poverty increased by 1.6 percentage points in the rural areas. The table further shows that in the urban areas, the largest decline in head count was in manufacturing and processing. In this sector there was also a 1.5 percentage points increase in depth and a 2.7 percentage points decline in severity of poverty.
32 Despite the scope for improving agricultural growth and the poverty focus of existing agricultural programs, about 87 percent of the core poor in 1986 and about 89 percent of the hard core poor in 1992 are engaged in some form of agriculture. The bulk of depth and severity in poverty 97.4 percent and 97.9 percent respectively in 1986 are in agriculture. The same trend is shown in 1992.

**Table 4.21: Poverty Incidence in Nigeria by Occupation of Head of Household 1985-92 (Poverty Line=N395.41)**

|||**_RU_**|**_RAL_**||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/93**||
|**Main Occupation of**|||||||
|**Household Head**|**P0**|**P,**|**P2**|**Po**|**P,**|**P2**|
|Profess./Technic.|0.293|0.107|0.050|0.329|0.120|0.059|
|Admin./Managers|0.417|0.131|0.069|0.611|0.158|0.083|
|Clerical Related|0.327|0.084|0.040|0.234|0.106|0.051|
|Sales Workers|0.319|0.080|0.033|0.266|0.110|0.059|
|Service Industry|0.373|0.088|0.037|0.228|0.090|0.046|
|Agric./Forestry|0.543|0.210|0.108|0.391|0.176|0.106|
|<br>Product./Transp.|0.447|0.119|0.052|0.213|0.133|0.068|
|Manufact./Process.|0.341|0.103|0.043|0.337|0.072|0.023|
|Others|0.378|0.094|0.034|0.257|0.093|0.045|
|Student/Apprentice|0.220|0.096|0.045|0.318|0.120|0.068|
|_All Rural_|_0.495_|_0.169_|_0.085_|_0.364_|_0.167_|_0.098_|
|||_UR_|_BAN_||||
|||**1985/86**|||**1992/93**||
|**Main Occupation of**|||||||
|**Household Head**|**P0**|**P1**|P2|**P0**|**P1**|P2|
|Profess./Technic.|0.309|0.077|0.028|0.273|0.139|0.082|
|Admin./Managers|0.177|0.037|0.007|0.269|0.102|0.037|
|<br>Clerical Related|0.219|0.058|0.020|0.331|0.114|0.060|
|Sales Workers|0.235|0.071|0.027|0.263|0.103|0.058|
|Service Industry|0.259|0.079|0.030|0.298|0.109|0.056|
|Agric./Forestry|0.473|0.175|0.079|0.357|0.151|0.080|
|Product./Transp.|0.265|0.112|0.051|0.396|0.121|0.057|
|Manufact./Process.|0.351|0.096|0.037|0.233|0.111|0.064|
|Others|0.305|0.087|0.032|0.292|0.100|0.054|
|Student/Apprentice|0.414|0.087|0.029|0.379|0.157|0.086|
|_All Urban_|_0.317_|_0.124_|_0.051_|_0.304_|_0.140_|_0.076_|
|Source: NCS, 1985/86 a|nd 1992/93.||||||

Most rural areas depend on the labor market for their sustenance. Focusing on the link between urban and rural patterns of welfare as mediated through the labor market, an ILO study based on data from 1964 to 1985 demonstrated that except for intermittent increases, real wages in Nigeria declined sharply between 1973 and 1985 (Jamal and Weeks, 1988). The periodic jumps were observed between 1973 and 1975 and again between 1980 and 1983, the first jump corresponding to the oil price shocks of the early 1970s. Not withstanding these exceptions, real wages in 1985 were a little more than half of the 1973 level. Some data available for 1980 to
33 1987 in a recent World Bank economic and sector work illustrates that the fall in real wages continued well into the later half of the 1 980s (World Bank, 1990). By this account, real wages in urban and rural areas in 1987 were 42-47 percent of the level in 1980. For employees on a fixed payroll, during this period, these data show that they fared very badly during most of the years.

**Table 4.22: Incidence of Extreme Poverty by Occupation of Head of Household, 1985-93 (Poverty Line=Nl97.71)**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**Occupation**|**P0**|**PI**|P2|Po|PI|P2|
|Profess./Technic.|0.040|0.009|0.003|0.135|0.062|0.023|
|Admin./Managers|0.044|0.020|0.009|0.075|0.084|0.030|
|Clerical Related|0.024|0.008|0.003|0.106|0.055|0.018|
|Sales Workers|0.033|0.006|0.002|0.087|0.056|0.021|
|Service Industry|0.040|0.008|0.003|0.107|0.048|0.016|
|Agric./Forestry|0.180|0.047|0.018|0.164|0.086|0.035|
|Product./Transp.|0.080|0.012|0.004|0.124|0.059|0.018|
|Manufact./Process.|0.053|0.014|0.004|0.058|0.058|0.018|
|Others|0.039|0.005|0.001|0.087|0.049|0.016|
|Student/Apprent.|0.020|0.011|0.006|0.149|0.064|0.023|
|_All Nigeria_|_0.120_|_0.042_|_0.016_|_0.136_|_0.085_|_0.034_|

**Decomposition of Extreme Poverty Incidence by Occupation**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**Occupation**|**P0**|**P1**|**P2**|**Po**|**P1**|**P2**|
|Profess./Technic.|2.6|0.6|0.5|6.3|4.6|4.3|
|Admin./Managers|0.2|0.1|0.1|0.2|0.3|0.3|
|Clerical Related|0.9|0.2|0.2|4.2|3.5|2.9|
|Sales Workers|4.0|0.6|0.4|10.2|9.3|8.8|
|Service Workers|1.2|0.2|0.2|2.2|1.4|1.2|
|Agric./Forestry|86.6|97.4|97.9|67.4|72.4|75.3|
|Product./Transp.|1.5|0.4|0.4|2.3|1.9|1.5|
|Manufact./Process.|0.8|0.3|0.2|1.0|1.3|1.1|
|Others|2.2|0.2|0.1|3.9|3.3|2.7|
|Student/Apprent.|0.1|0.0|0.0|2.4|1.9|1.8|
|_AllNigeria_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|
|Source: NCS, 1985/86|and 1992/93||||||

Tables 4.23 and 4.24 provide the employment status breakdown of poverty. Here self employed appear to be the hard hit. Here again the pattern remains same between the two periods. Poverty has declined in the wage earner category from an incidence of 51.5 percent to 27.7 percent in the rural areas, and 33.6 percent to 27.8 percent in urban areas. They constitute a substantially large proportion of the poor than their corresponding proportion in the national population.
34 Table 4.23: Incidence of Poverty by Employment Status of Head of Household, 1985-93 (Poverty Line=N395.41)

||||**_RURAL_**||||
|---|---|---|---|---|---|---|
|||**1985/86**|||**1992/93**||
|**Employment**|||||||
|Status of Head|**P0**|**PI**|P2|**P0**|**P,**|**P2**|
|Employer|0.282|0.089|0.038|0.000|0.000|0.000|
|<br>Wage Earners|0.515|0.176|0.089|0.277|0.097|0.046|
|<br>Self Employed|0.514|0.114|0.000|0.367|0.157|0.093|
|<br>Others|0.453|0.053|0.012|0.368|0.163|0.094|
|_All Rural_|_0.495_|_0.169_|_0.085_|_0.364_|_0.167_|_0.098_|
||||_URBAN_||||
|||**1985/86**|||**1992193**||
|**Employment**|||||||
|Status of Head|**P0**|**P,**|**P2**|**Po**|P1|P2|
|Employer|0.256|0.069|0.027|0.000|0.000|0.000|
|<br>Wage Earners|0.336|0.143|0.083|0.278|0.112|0.062|
|<br>Self Employed|0.574|0.204|0.127|0.319|0.139|0.076|
|<br>Others|0.359|0.191|0.104|0.238|0.107|0.043|
|_All Urban_|_0.317_|_0.124_|_0.051_|_0.304_|_0.140_|_0.076_|

Source: NCS, 1985/86 and 1992/93

# **Table 4.24: Incidence of Extreme Poverty by Employment Status of Head of Household, 1985-93 (Poverty Line=N197.71)**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|Employment Status|P0|P,|P2|**Po**|P1|P2|
|Employer|0.038|0.008|0.003||||
|Wage Earner|0.134|0.034|0.013|0.104|0.054|0.020|
|Self Employed|0.206|0.019|0.000|0.142|0.075|0.030|
|Others|0.079|0.000|0.000|0.125|0.079|0.029|
|_Al/Nigeria_|_0.120_|_0.042_|_0.016_|_0.136_|_0.085_|_0.034_|

**Decomposition of Extreme Poverty Incidence by Employment Status**

|||**1985/86**|||**1992/93**||
|---|---|---|---|---|---|---|
|**Employment Status**|**P0**|**P,**|**P2**|**P0**|**PI**|**P2**|
|Employer|4.9|1.1|**1.0**|0.0|0.0|0.0|
|Wage Earner|5.1|3.0|0.0|11.9|9.7|9.1|
|Self Employed|88.9|95.9|99.0|82.7|84.9|85.8|
|Others|1.1|0.0|0.0|5.4|5.4|5.0|
|_All Nigeria_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|

Source: NCS, 1985/86 and 1992/93.
35

# **4.3 Decomposition of Changes in Poverty**

In the extensive literature on the relationship between growth, distribution and poverty, or between population shifts, intra-sectoral shifts and interaction between sectors and poverty, some empirical questions have always been asked by policy makers and analysts. How much of observed changes in poverty are due to changes in the _distribution_ of income, as distinct from the _growth_ in average incomes, or how much of the changes in poverty are demographic - due to movements within regions or sectors. Standard inequality measures can be very misleading in this context. The first set of decompositions in the tables below offer tools for rigorously quantifying the contribution of distributional changes to poverty alleviation controlling for growth effects, and the contribution of growth, controlling for distributional changes. The second set of decompositions allow for another rigorous quantification of the contribution of population shifts to poverty alleviation, controlling for intra-sectoral shifts and interactions within sectors and the contribution of intra-sectoral shifts to poverty alleviation controlling for population shifts and interaction between sectors. However, like any descriptive tool, these decompositions have their limitations. For example, the decomposition cannot explain if an alternative growth process with better distributional implications would have been more effective in reducing poverty or not.

The changes in poverty which occurred in Nigeria between 1985 and 1992 are the net result of two effects: a rise in the mean level of household expenditure per capita and a change in the distribution. It is useful to separate out the two effects, in order to properly assess the policies of the period and to see where future policy needs to be focused. Following Ravallion and Datt (1991), the change in Pa can be written as the sum of a growth component, a redistribution component and a residual. Let

## **Past =P(Ut/z'Pt)**

where Z is the poverty line, Ut is the mean per capita expenditure and Pt is the distribution of expenditure in year t. This decomposition is discussed in detail in Ravallion and Datt (1991), but the basic idea is as follows. For any two periods or dates 0 and 1, the _growth component_ of a change in the poverty measure is defined as the change in poverty due to a change in the mean per capita expenditure from UO to Ul, with no change in income distribution. The _redistribution measure_ is defined as the change in poverty due to a change in income distribution, with no change in mean per capita expenditure. Hence the decomposition can be written as follows:

# **P(U1/Z,pl)-P(UO/Z,po)** = **IP(U1/Z,po)-P(U1 /Z,po)J** + **[P(UO/Z,pl)-P(UO/Z,po)]** + **Residual**

Change in Poverty = Growth Component + Redistribution Component + Residual The change in Pa between 1985 and 1992 can then be written as

**P.,92** - **Pa.85** = **G(85,92;r) + D(85,92;r) + R(85,92r)**
36 where r refers to the reference point, which logically will be 1985. With 1985 as the reference year the components will be as follows:

**G(85,92;85)** ° **Pa(U93/Z,P92 )** - **Pa(U8 5/Z,P8 5) D(85,92;85)** ° **P2(U8 5/Z,p92)** - **Pa(U8 5/Z,P85 )**

The growth component thus captures the changing level of mean expenditure between 1985 and 1992, while maintaining the 1985 income distribution. The redistribution component shows the effect of the changes in distribution between 1985 and 1992, while maintaining mean expenditure at the 1985 level. The residual reflects the interaction between changes in the mean and the distribution. Since the poverty line is kept fixed for both periods, it is important to ensure that the means have been adjusted for changes in the cost of living over the two dates.

Consider now, the second type of decomposition, the sectoral decomposition of a change in poverty. When analyzing the sources of observed reductions in aggregate poverty, one can make use of a simple decomposition formula proposed in Ravallion and Huppi (1989), and also exploiting the additive property of the FGT class of measures. The idea is to shed light on the on the relative importance of changes within sectors versus changes between them, such as due to inter-sectoral population or work-force shifts.

To see how this works, let Pit denote the FGT poverty measure (or any other additive measure) for sector i with population share n1 at date t, where there are k such sectors, and t=l, 2. Then it can be verified that:

# **P2** - P I **S(Pi 2** - **Pi,)** + **S(ni2** - **nil)Pil** + **S(Pi2** - **P1l)(ni 2** - nil)

Total change Intra-sectoral + Population Shift+ Interaction Effect where all summation are over i=1 ...... k. The "intra-sectoral effects" indicates the contribution of poverty changes within sectors, controlling for their base period population shares. The "population shift effects", show how much of the poverty in the first period was reduced by the various changes in population shares of sectors between then and the second date. The "interaction effect' is a covariance term accounting for the interaction of the intra and inter sectoral effects. The results of the decomposition are laid out in Table 4.27. Over the period, there is very little change in the population shares of the three sectors, thus the component for inter-sectoral population and the interaction term turn out to be very small.
37

**Table 4.25: Decomposition of Change in Poverty (Pa, 1985-93) into Growth and Redistribution Components**

|**P,**Indicator|Total Change|Growth Component|Redistribution Component|Residual|
|---|---|---|---|---|
|P0|-0.089|-0.042|0.141|-0.188|
|P,|-0.010|-0.059|0.067|-0.018|
|P2|-0.004|-0.052|0.038|0.018|
|**_Rural_**_Decomposition_|||||
|P0|-0.133|-0.190|0.013|-0.044|
|P,|-0.037|-0.094|0.065|-0.008|
|P2|-0.006|-0.057|0.066|-0.003|
|**_Urban_**_(Excluding_**_Lag_**|**_os) Decomposition_**||||
|P0|-0.014|-0.077|0.099|-0.036|
|P,|0.043|-0.031|0.080|-0.006|
|P2|0.024|-0.015|0.058|-0.019|
|_Lagos_<br>_Urban Decomposit_|_ion_||||
|P0|0.036|0.008|0.043|-0.015|
|P,|0.027|0.003|0.023|0.001|
|P2|0.014|0.001|0.015|-0.002|
|Source:<br>NCS,<br>1985/86|and 1992/93.||||

Table 4.25 shows the estimates of the decomposition of changes in national, rural, urban excluding Lagos and Lagos urban, for per capita expenditures. The tables give the changes in percentage points, in the two periods of our study 1985/86 and 1992/93. For example, the national headcount started at 43.0 percent in 1985/86 and fell by 8.9 points to 34.1 percent in 1992/93. By components, distributionally neutral growth accounted for a decline of 4.2 points, while the distributional shifts accounted for an increase by 14.1 points; the residual effect contributes to decreasing poverty by 18.8 point. The growth component dominates for all measures and contributes more to poverty reduction. This trend is also true for all the regions except the Lagos Urban, where the redistribution effect contributes to decrease in the P0 and P, measures of poverty in Nigeria. However, the effect of the growth component in all the cases, mitigated the adverse effect of the redistribution effect.
38

# **Table 4.26: Decomposition of Change in Regional Poverty (Pa, 1985-93) into Growth and Redistribution Components**

|**P. Indicator**<br>**Total Change**|**Growth**<br>|**Redistribution Component**|**Residual**|
|---|---|---|---|
||**Component**|||
|**_Northern Belt decomposition_**||||
|P0<br>-0.031|-0.082|0.040|0.01O|
|P,<br>-0.037|-0.044|0.053|0.001|
|P2<br>-0.006|-0.026|0.048|0.002|
|**_Middle Belt Decomposition_**||||
|P0<br>-0.087|-0.165|0.054|0.024|
|P,<br>-0.052|-0.081|0.069|-0.040|
|P2<br>-0.016|-0.048|0.062|-0.030|
|**_Southern belt Decomposition_**||||
|**P0**<br>-0.126|-0.159|0.030|0.003|
|P,<br>0.003|-0.067|0.048|0.022|
|P2<br>0.016|-0.034|0.043|0.007|

Source: NCS, 1985/86 and 1992/93.

The decomposition of poverty in terms of geographical belts is presented in Table 4.26. The highest decline in incidence has taken place in the Southern belt showing a decline of 12.6 percentage points most of which is due to the growth component (-15.9), and partly due to the redistribution component(3.0). In the middle belt, there was a decline of 8.7 percentage points (- 16.5 and +5.5) due to growth and redistribution respectively. In the northern region, the decline was 3.1 percentage points, -8.2 due to growth and +4.0 due to redistribution. Looking at the other measures it is worth noting that the decline in P, in South of 0.3 percentage points is predominantly due to growth. We find that growth reduced the depth of poverty by 4.9 percentage points and redistribution by 0.8 percentage points, while the residual increased the depth by 2.2 percentage points. In most of the measures, the residual is small relative to both growth and redistribution components, implying that the distribution is quite insensitive to a change of reference from the initial to final year (Ravallion and Datt, 1991).

The relationship between population shifts and intra-sectoral shifts and interaction between sectors and poverty is examined in Table 4.27. It attempts to answer some empirical question as to how much of observed changes in poverty are demographic - due to movements within regions or sectors. The decompositions allow for another rigorous quantification of the contribution of population shifts to poverty alleviation, controlling for intra-sectoral shifts and interactions within sectors and the contribution of intra-sectoral shifts to poverty alleviation controlling for popvlation shifts and interaction between sectors.

The changes in national poverty over the period 1985-92 can be readily decomposed as follows:
39

# P92 - P85 **= S(P92** - **Pi85)ni85** + **S(n92** - **n 85)P 85** + **S(Pi 9 2** - **Pi85)(ni 92** - **ni85)**

Total change = Intra-sectoral + Population Shift + Interaction Effect The interaction effects arise from the possible correlation between sectoral gains and population shifts, with the sign of the effect indicating whether people tended to switch to the sectors where poverty was falling or not. The finding can be summarized as follows: the decline in national poverty as expressed by the head count, between 1985-92 was due mainly (97.8 percent) to intra-sectoral effects while 3.4 percent was due to population movements within the country. The interaction effect for the headcount shows that people tended to move to sectors where poverty was falling. For the depth P1 measure, the intra-sectoral, population shifts and interaction effects, all contributed to reducing the depth of poverty. However, for the P2 intensity measure the interaction effect increased poverty by 8.3 points, but the effects were balanced by the more than proportional decrease in the severity caused by the intra-sectoral and population shift effects. We have seen that the decline in rural poverty was mainly due to a decline in agricultural households. 1986 was not a very good agricultural year in Nigeria, the improvements in agriculture were due to the rather favorable terms of trade for cocoa farmers and the abolition of the cocoa board. It is no surprise therefore that the intra-sectoral effects have been so strong in reducing poverty. It is also believed that there was reversed migration with families moving from urban to rural areas, thereby causing a reduction in rural poverty (CBN/NISER, 1992).

**Table 4.27: Decomposition of Change in Poverty (Pa, 1985-93) Into Intersectoral, Population Shift and Interaction Effects**

|**P. Indicator**|**Total Change**|**Intra-Sectoral**|**Population Shift**|**Interaction Effect**|
|---|---|---|---|---|
|**P0**|-0.089|-0.087|-0.003|0.001|
||100.0|97.8|3.4|1.2|
|P1|-0.004|0.001|-0.002|-0.003|
||100.0|-25.0|50.0|75.0|
|P2|0.012|0.001|-0.001|0.012|
||100.0|-8.3|8.3|100.0|

Source: NCS, 1985/86 and 1992/93.

## 4.5 **Implications for Targeting**

From various aspects of the inter-temporal poverty profile presented thus far, one can draw out the implications for targeting, by using two targeting indices. The indices relate to how much impact on aggregate (national) poverty can be expected from a given transfer across different groups defined by a particular household indicator or characteristic. This paper focuses on two benchmark criteria. These correspond to the additive (or uniform) and multiplicative or (proportional) transfers. Additive transfers are generally defined as those transfers where the amount transferred is the same for all persons within the group. These transfers are progressive if it translates into increased or higher proportion of expenditure for the relatively poor. In the second case of multiplicative transfers, the amount received is proportional to the recipient's income or expenditure, these are distributionally neutral transfers. As shown in Kanbur (1987)
40 and Datt and Ravallion (1990), it turns out that, to minimize **Pa** transfers, groups should be targeted in the order of the observed values of:

**PaI,J,** for additive transfers and,

**(Pa Ij** - Paj)/Uj for multiplicative transfers.

where Uj is the mean per capita expenditure for group j. The poverty estimates in this paper already provide the needed information on the targeting index for additive transfers; the multiplicative index is easily calculated as will be shown below. In an earlier discussion on the FGT class of indicators, we saw that the squared poverty gap index, with a=2 (P2), assumes that the policy objective is to accord a greater weight to reducing poverty for those who are relatively poorer. Our focus will thus be on P2, these indices have been normalized by the national values of the same index and expressed as percentages. Thus, for additive transfers, the relative targeting index is simply given as the poverty gap for group j, as a percentage of the national poverty gap, and similarly for the index for multiplicative transfers.

Groups with relatively high values of both indicators may be considered good choices for targeting or for design of policies favoring them. Table 4.28 shows that between rural/urban areas, the rural sector becomes a favored choice for targeting. Additive and multiplicative transfers for rural areas are 95.91 and 93.89 respectively, compared to 72.04 and 74.58 for the other urban areas and 59.73 and 77.86 respectively for Lagos urban. In terms of agro-climatic belts, the northern belt becomes preferable.

In general, households whose heads have no schooling, among the employed, the selfemployed, female headed households, by occupation, clearly agriculture and forestry feature high in order of preference for targeting. In terms of household structure, polygamous households are good candidates for targeting. When we consider the states in 1992/93 in rural/urban sectors, Bauchi, Benue, Borno, Cross rivers, Gongola, Kano, Plateau, Sokoto and FCT are preferred. Although we did not go into details of what communities and possible Local Government Areas (LGAs) should be targeted, we strongly feel that this is an area that needs further research.
41 Table 4.28: Targeting Indices by Various Indicators 1992-93 (Poverty Line=N395.41)

|Groups and<br>Indicators|Targeting I<br>Additive|ndicator for<br>Transfers|Targeting I<br>Multiplicativ|ndicator for<br>e Transfers|
|---|---|---|---|---|
|Nigeria|100.0||100.0||
|Rural|95.41||93.89||
|Urban|72.04||74.58||
|Lagos Urban|59.73||77.86||
|Ecological Belts|Urban|Rural|Urban|Rural|
|Northern|106.34|117.28|144.92|144.31|
|Middle|90.38|105.90|99.84|96.75|
|Southern|54.91|60.14|50.17|51.90|
|Educational Level|Urban|Rural|Urban|Rural|
|No Education|94.68|105.23|119.43|109.85|
|Primary Education|66.90|69.53|62.46|65.53|
|Secondary|51.76|56.64|47.82|44.20|
|Education|||||
|Higher education|49.61|66.26|45.23|47.63|
|Employment Status|Urban|Rural|Urban|Rural|
|Wage Earner|63.34|94.79|77.92|116.43|
|Self Employed|66.36|96.75|67.57|67.46|
|Other|82.54|92.82|87.09|91.18|
|Household Structure|Urban|Rural|Urban|Rural|
|Traditional male|64.71|78.62|77.0|77.45|
|Polygamous|131.00|138.68|214.67|177.56|
|Single male|63.18|45.60|20.82|26.77|
|defacto female|71.34|94.20|57.47|102.06|
|dejure female|36.66|49.94|30.06|33.56|

Source: NCS, 1985/86 and 1992/92.
42

**Table 4.28 (Cont...): Targeting Indices by Various Indicators 1992-93 (Poverty Line=N395.41)**

|**Groups and**<br>**Indicators**|**Targeting I**<br>**Additive**|**ndicator for**<br>**Transfers**|**Targeting I**<br>**Multiplicat**|**ndicator for**<br>**ive transfers**|
|---|---|---|---|---|
|**Main Occupation**|**Urban**|**Rural**|**Urban**|**Rural**|
|Profess/Technic.|82.2|70.9|75.76|78.01|
|Admin. Managers|60.5|93.5|80.65|103.91|
|Clerical Relat.|67.5|62.9|76.00|64.49|
|Sales Workers|61.1|64.9|58.52|59.01|
|Service Industr.|64.4|53.5|68.67|55.86|
|Agric/Forest.|89.5|104.1|101.57|104.71|
|Product/Transp.|71.4|78.7|96.78|77.96|
|<br>Manufact/Process.|65.7|42.7|55.11|58.87|
|Others|59.1|55.3|66.70|54.91|
|Student/Apprent.|93.1|70.9|100.37|59.74|
|**State of Residence**|**Urban**|**Rural**|**Urban**|**Rural**|
|Anambra|42.95|27.49|28.86|24.12|
|Bauchi|125.83|144.01|193.71|254.11|
|Bendel|26.77|42.21|31.52|34.30|
|Benue|95.86|107.97|89.83|103.10|
|Borno|95.13|114.38|119.85|126.31|
|Cross River|72.57|95.94|76.25|80.68|
|Gongola|70.60|78.51|82.57|85.30|
|Imo|40.66|37.97|28.51|30.21|
|Kaduna|48.94|62.18|50.70|50.41|
|Kano|106.79|122.46|224.29|186.58|
|Kwara|49.46|90.21|64.45|71.16|
|Lagos|77.29|90.79|100.75|113.61|
|<br>Niger|92.42|130.55|166.09|136.78|
|Ogun|58.90|55.98|73.84|54.79|
|Ondo|53.57|77.08|50.01|63.47|
|Oyo|54.25|50.14|44.04|46.71|
|<br>Plateau|103.99|118.17|123.61|90.13|
|Rivers|85.88|100.11|122.65|105.89|
|Sokoto|160.08|148.62|230.01|202.90|
|FCT|166.56|130.49|140.70|179.71|

# **4.6 Sensitivity Analysis of Poverty**

The poverty line of N 395.41 has been the basis for poverty incidence, depth and severity indices for 1985/86 and 1992/93 periods. However, these poverty measures are dependent on the chosen poverty line. Hence, it would be meaningful to do some sensitivity analysis of the poverty indices over time and cross sectionally by changing the poverty line. This is done in the tables that follow. Table 4.29 shows that if the poverty line ofN 237.246 was used as the poverty line, then only 18.67 percent of the population would have been in poverty. Similarly, by using N 553.574 as the poverty line almost 48.9 percent of the population would have been in poverty.
43

**Table 4.29: Poverty Simulation with Varying Poverty Line**

|**Poverty Line**|**Head Count**<br>**Index (P0 %)**|**Depth Index**<br>**(Pi %)**|**Severity Index**<br>**(P2 %)**|
|---|---|---|---|
|(Z=N237.246)|18.67|6.67|3.19|
|Elasticities: with respect to Mean Consumption|-1.37|-1.78|-2.19|
|(Z=N316.328) (1)|26.88|10.71|5.64|
|Elasticities: with respect to Mean Consumption|-1.20|-1.51|-1.80|
|(Z=N474.492) (1)|41.89|18.66|10.84|
|Elasticities: with respect to Mean Consumption|-1.00|-1.24|-1 .45|
|(Z=N553.574) (1)|48.95|22.46|13.43|
|Elasticities: with respect to Mean Consumption|-0.90|-1.16|-1.35|
|(Z=N632.656)<br>(1)|54.34|26.08|15.98|
|Elasticities: with respect to Mean Consumption|-0.82|-1.08|-1.26|
|(Z=N711.738)<br>(1)|59.58|29.52|18.47|
|Elasticities: with respect to Mean Consumption|-0.74|-1.02|-1.20|
|(Z=N790.820)<br>(1)|62.2|32.76|20.89|
|Elasticities: with respect to Mean Consumption|-0.67|-0.96|-1.14|

Note: Z= Poverty Line; (1) Indicates Poverty Line in 1985 prices used throughout the paper. Source: NCS, 1985/86 and 1992/93.

An important aspect of this analysis is shown above where poverty is simulated using different poverty lines (Z). The poverty measures used in this paper, are sensitive with respect to the poverty line chosen. The 1985/86 relative poverty line of Z=N395.41 is super-imposed on the 1992/93 expenditure, by using the mean estimated consumer price index. It is obvious that the choice of an index has a bearing on the number of poor and the depth and severity of poverty.

In order to understand the impact in changes in mean consumption and Lorenz curves in general the elasticities of each of the poverty measures need to be estimated. This is also presented in Table 4.29. Since we are estimating point elasticities the estimate differs depending on which point we choose. The poverty lines were chosen depending on different possible rates of inflation. Other than elasticities we also indicate the general changes in poverty indicators. It is useful to note the responsiveness of poverty measures decreasing with higher levels of poverty lines.

# **4.7 Dominance Test of Poverty**

Apart from this broad changes in poverty due to changes in poverty line it is useful to do more detailed analysis of changes in poverty using dominance tests. This involves plotting the entire distribution of expenditures by cumulative proportion of population (or decile) in terms of regions, geographical locations and socio-economic groups.

The usual first test in this, "first order dominance", involves plotting the cumulative percent of people at successive levels of per capita expenditures. If we plot this for a country in two different periods and if period two is always below the initial period then it implies that poverty has declined over time and any change in poverty line will not change this result. However, if ever these lines were to intersect then the welfare implications of this will depend upon where one sets the poverty line and also vary according to different classifications. It is also
44 possible to carry out higher order dominance tests using "poverty deficit curves" which plot the area under the cumulative distribution at each expenditure level. Figure 3 depicts the first order dominance test for Nigeria using 1985 and 1993 information (as in Figure 3) 1/. In all classifications we find that poverty has declined between 1985 and 1993. The figures (in Appendix 2) show the cumulative distribution functions of national, urban, rural and Lagos urban.

In principle, the entire distribution of expenditure must be plotted, but in practice this can be restricted to the highest possible location of the poverty line. We restrict the distribution to 120% of the poverty line, a reasonable upper limit for the poverty line as seen in figure 3. Between 1985/86 and 1992/93 the two curves intersect between 40 percent and 60 percent of the poverty line, (around 45 percent) showing that the conclusions about poverty incidence are sensitive to where in that range the line is set. Any poverty line below 45 percent of the line, will result in an unambiguous increase in poverty.

The higher order dominance tests were carried out by plotting the poverty deficit curve and poverty severity curve. The deficit curve is the area under the incidence curve. A fall in poverty requires that the poverty deficit curve is nowhere lower for 1985 at all points up to the poverty line. As we see in Fig A2.4 (Appendix 2), the 1985 deficit curve intersects the 1992 curve around 35 percent of the poverty line, which makes the second-order dominance test inconclusive. The third order dominance test relies solely on the distribution sensitive measures such as P2. A poverty severity curve is the area under the poverty deficit curve; the dominance test is again inconclusive, since the 1985 severity curve intersects the 1992 curve around 55 percent of the poverty line. This means that conclusions about poverty distributions are not likely to be robust.

If the poverty line was atN 158.16 per annum per person then poverty would increase between 1985-92 from 2.67 percent to 3.69 percent. This indicates that in terms of poverty trends while the whole Nigerian population did not uniformally benefit from the economic growth achieved since the mid 1980s. There are substantial segments of the population, especially those in the bottom decile, who have actually neither participated nor benefited from the economic growth since the mid 1980s. Hence the future growth strategy for Nigeria needs more poverty focus if it has to ever prove beneficial to the extreme poor.

**7/** We also do the dominance tests in higher order (using the poverty deficit curve and poverty severity curve) and also in terms of broader regions and geographical zones. The results are presented in Appendix 2.
45

**Figure 4.3: First order dominance Test 1985-92.**

<!-- Start of picture text --> 100<br>80<br>60<br>C<br>20j 0_<br>0 20 40 60 80 90<br>Percent ofpoverty line<br>0 1985/86 .~.. .- 1992/93<br><!-- End of picture text -->

**Table 4.30: Projected Impact of (5%) Distributionally Neutral Growth in Real per Capita Expenditure on Poverty (1994-2005)**

|**Year**|**Mean Per Capita**<br>**Expenditures**|**Head Count (P0 %)**|**Depth Index (PI %)**|**Severity Index**(P2%)|
|---|---|---|---|---|
|1994|825.34|32.54|13.78|7.85|
|1995|842.18|31.95|13.41|7.61|
|1996|859.37|31.30|13.03|7.38|
|1997|876.91|30.54|12.66|7.16|
|1998|894.80|29.95|12.31|6.94|
|1999|913.07|29.22|11.95|6.72|
|2000|931.71|28.41|11.61|6.51|
|2001|950.72|27.80|11.27|6.31|
|2002|970.12|27.05|10.94|6.11|
|2003|989.92|26.03|10.62|5.92|
|2004|1010.12|25.39|10.32|5.73|
|2005|1030.73|24.75|10.01|_5.55_|

Source: NCS, 1985/86 and 1992/93.

As mentioned earlier, poverty is widespread and cannot be eliminated without sustained economic growth. Nigeria needs to choose a growth strategy which ensures that the poor benefit. A poverty reducing growth strategy for Nigeria, will need to start with removing any existing restrictions on labor mobility and moving agricultural policy and practices away from a bias towards specific crops to encouraging an environment where producers will shift towards the most profitable crops. A long term vision for growth will be based on broad based export production to provide the cash stimulus to get the economy moving. Under such a strategy, the government would promote exports by creating appropriate conditions by removing those fiscal, regulatory and monetary restrictions that tend to hamper export development. Labor intensive exports would create employment and incomes which would increase the demand for upstream activities and for domestically produced food.
46 The above strategy with a growth rate of 5 percent in real per capita expenditure during the 1990s and the first decade of the next century would produce the results in Table 4.30. This per capita growth rates can be achieved if accelerated GDP growth is accompanied by decelerated population growth. Such a combination of economic growth and decelerated population growth would reduce the percentage of the population below the poverty line, from **8** 32.5 percent in 1994 to 24.7 percent in 2005 . The remaining poor could be brought to the poverty line by targeted transfers.

# 5. EXPENDITURE PATTERNS OF THE POOR

The analysis so far has focused on per capita expenditure, as a measure of welfare. We have mentioned the significance of changes in welfare due to increases in farm income. It is useful to check the importance of this and other sources both in the expenditure and in the income of the household, to see whether these differ according to poverty status. We have also presented disaggregation on a rural/urban split, regional basis, by poverty status and by gender of head of household. As we have done before, we want to distinguish the very poor from the poor and non poor. This has been done by aggregating poor by the core poor and others.

The presentation has been done in two parts. Each table show the share of the different categories in total expenditure, within each group. This presentation is useful to see how important an item or category is for each poverty group. It also indicates the extent by which each group will be affected by changes in the price of the item, for example when subsidies are cut or prices are increased. The tables also present the changes in the per capita expenditure for each item during the period of our study.

According to Table 5.1, in 1985, 83.8 percent and 77.7 percent of expenditures by the core poor and the poor respectively was on food. In 1992 the value had decreased to 76.7 percent for the core poor and 77.7 percent for all poor. For the non poor, the values are 63.4 percent and 65.8 percent for both periods respectively. This clearly shows that even though general economic conditions have improved, in Nigeria as a whole, the share of food in total per capita expenditure does not reflect it. In 1992 the value had increased to 67 percent from 66.1 percent in 1985. Food consumption and in turn nutritional welfare are likely to depict an adverse trend between 1985-93.

Table 5.2 shows the evolution in food and non food expenditures by different regimes and socio-economic groups. Food expenditures have gone up by 51.4 percent for the rural and 27.4 percent for other urban(excluding Lagos) households. In 1985 food expenditures as share of total was 66 percent, and in 1992 the value was 67 percent. This happened despite an increase in the real per capita expenditure and fall in poverty during this period. There are several plausible explanations for this rise in food share. It could be due to change in tastes, increase in the relative price of food, reduction in rationing or over-reporting of non-food expenditure in the first survey and under-reporting of non-food expenditure in the second survey. Although, all or some of these

**8** The simulations are based on per capita household expenditure, with 1992 as the base year; with real income growing at 5 per cent per annum.
47 reasons are plausible, the effect of an increase in the relative price of food (assuming, plausibly that food demand is not price elastic) by 15 percent over the non-food prices is partly responsible for the food shares to be the same during 1985-92, even though the per capita expenditures have increased by 34 percent.

For urban (excluding Lagos) the values are 68.4 percent and 72.95 percent for 1985 and 1992 respectively. An increase of 4.5 points in the urban areas shows a worsening of food consumption welfare. In Lagos urban, we find that in 1985 food expenditures were 70.8 percent of all expenditures. In 1992 the share had increased to 76.0 percent. Although the increase is not as large as for other areas, it is important to stress the fact that welfare levels throughout Nigeria have not performed well over this period. The table gives the values for male and female headed households. In male headed households, 67.8 percent and 74.5 percent are the foodshares for 1985 and 1992 respectively. In female headed households, we find 65.8 percent and 66.5 percent as the share of food in total per capita expenditure for 1985 and 1993 respectively. There is no significant difference between the changes in the male versus female headed households.

Table 5.3 shows the shares of food and non-food expenditures in total expenditure by agro-climatic zones. In the Southern belt, which has shown the largest increase in per capita expenditures over the 7 years period, food as a share of total expenditure was 66.3 percent in 1985 and 74.5 percent in 1992. While the share of food to total expenditure has decreased by 1.09 percentage points and 3.14 percentage points in the northern and middle belt respectively, it has increased by 4.0 points in the South.

Tables A1.1-Al.3 (in Appendix 3) show a breakdown of food expenditure. The tables show that the expenditure on cereals, meat and starchy food items, has increased both for the poor and non poor. The same pattern is observed in the urban and rural breakdown and in the geographical region breakdown. However, there has been a sharp decline in the per capita expenditure on poultry, pulses and nuts. On a geographical basis, we find the a the largest increase in food expenditure was on fats and oils. However, the expenditure on rice, meat and poultry declined in the north. In the south the same pattern holds but we find the largest increase in the Southeast has been on pepper followed by beans and tomatoes.

Tables Al.4-Al.5 show a breakdown of non-food expenditures. There has been a 30.1 percentage points decline in expenditures on non-food, nationally. More so for the poor than the non-poor. The non-food expenditures increased for all items except clothing education and medical expenses (which decreased by 68 percentage points), while the expenditure on transportation (mostly due to durables) has increased by 469 percentage points. Looking at the rural urban split, non-food expenditures have increased only in rural areas and in Lagos Urban. In the rural areas, non food expenditure increased by 36.3 percent, while in the urban areas it increased by 31.24 percent. In the other urban areas, the largest decline was in medical services and the largest increase in household items. The same pattern is seen at the agro-climatic zonal basis. In the northern regions, the largest increase was in household items, while the largest decline was in services. In the south however, the largest increase was in transportation and the largest decline was again in services.
48 On the income side, per capita household income has increased by over 70.7 percent between 1985-92 (Tables Al.6-A1.8), mainly due to a big increase in farm income(324 percent), while non-farm increased by 120.9 percent. Non-farm income showed the biggest increase in Middle and Southern belts. Within the non-farm income group, the biggest increase were due to rent received and other income. Wage income received by households decreased by 5.8 percent during this period. Similar patterns were observed in rural and urban areas and by geographical areas. Wage incomes showed the largest increase in the northern belt and the smallest increase in the southern belt. This may also be reflecting the fact that even at lower real wages more members of the household might have been employed.

**Table 5.1: Evolution of (Real) Per Capita Expenditure by Type and Poverty Group (Poverty Line=N395.41)**

||**PO**|**OR**|**NON-P**|**OOR**|**ALL NI**|**GERIA**|
|---|---|---|---|---|---|---|
|**Expenditure Type**|**85/86**|**92/93**|**85/86**|**92/93**|**85/86**|**92/93**|
|Own Consumption|28.85|56.24|59.00|370.80|44.74|263.55|
|Food Cash Expend.|171.73|119.888|479.14|343.51|346.89|267.27|
|All Food Expend.|197.58|176.12|538.14|714.31|391.62|530.82|
|Non Food Expend.|56.69|50.50|310.30|371.14|201.19|261.82|
|P. C. Expend.|254.27|226.62|848.43|1085.45|592.81|792.64|
||**EXTREM**|**E**<br>**POOR**|**OTH**|**ERS**|**ALL**NIG|ERIA|
||||**(Poverty**|**Line=N197.71)**|||
|Own Consumption|15.83|40.16|48.68|298.85|44.74|263.55|
|Food Cash Expend.|107.81|55.45|379.45|300.74|346.89|267.27|
|All Food Expend.|123.64|95.61|428.13|599.59|391.62|530.82|
|Non Food Expend.|24.30|28.98|225.28|298.62|201.19|261.82|
|P. C. Expend.|147.94|124.59|653.41|898.21|592.81|792.64|

Source: NCS, 1985/85 and 1992/93.

**Table 5.2: Evolution of (Real) Per Capita Expenditure by Type, Region and Gender (Poverty Line=N395.41)**

||**RUR**|**AL**|**OTHER**|**URBAN**|**LAGOS**|**URBAN**|
|---|---|---|---|---|---|---|
|**Expenditure Type**|**85/86**|**92/93**|**85/86**|**92/93**|**85/86**|**92/93**|
|Own Production|53.24|62.54|30.56|18.63|1.20|8.76|
|Food Cash Expend.|288.08|443.96|446.99|577.57|530.63|726.20|
|All Food Expend.|341.32|516.72|477.55|608.36|539.87|748.24|
|Non Food Expend.|189.96|109.91|220.77|183.38|222.80|237.70|
|P. C. Expend.|531.28|707.63|698.32|791.74|762.67|985.94|
||**MALE H**|**EADED**|**FEMALE**|**HEADED**|**ALL NI**|**GERIA**|
|Own Consumption|52.75|44.43|43.64|54.26|44.74|45.45|
|Food Cash Expend.|396.41|487.89|340.07|590.77|346.89|498.48|
|All Food Expend.|449.16|542.94|383.71|659.34|391.62|554.92|
|Non Food Expend.|213.71|185.41|199.47|221.94|201.19|189.17|
|P. C. Expend.|662.87|728.35|583.18|881.28|592.81|744.09|

Source: NCS, 1985/86 and 1992/93.
49

**Table 5.3: Evolution of (Real) Per Capita Expenditure by Type and Geographical region (Poverty Line=N395.41)**

||**NORTHE**|**RN BELT**|**MIDDL**|**E BELT**|
|---|---|---|---|---|
|**Expenditure Type**|**85/86**|**92/93**|**85/86**|**92/93**|
|Own Consumption|54.72|168.24|49.77|344.92|
|Food Cash Expend.|309.14|271.23|324.37|142.50|
|All Food Expend.|363.86|439.47|374.14|487.42|
|Non Food Expend.|174.54|194.44|177.50|266.14|
|P. C. Expend.|538.40|633.91|551.64|753.56|
||**SOUTHE**|**RN BELT**|**ALL NI**|**GERIA**|
|Own Consumption|39.46|304.18|44.74|263.55|
|Food Cash Expend.|371.10|317.15|346.89|267.27|
|All Food Expend.|410.56|621.33|391.62|530.82|
|NonFoodExpend.|245.86|313.15|201.19|261.82|
|P. C. Expend.|656.42|934.48|592.81|792.64|
|Source: NCS, 1985/86 and|1992/93.||||

# **6. CONCLUDING REMARKS**

Poverty declined sharply from 43 percent of the population in 1985 to 34 percent of the population in 1992. However we observe that, despite this, some households suffered a loss in incomes. The top 10 percent of the population had more than 47 percent increase while the bottom 20 percent of households experienced absolute decline by more than 20 percent. The latter group form the extreme poor of Nigeria who have been adversely affected in terms of poverty and welfare during this period Although growth reduced poverty, the distribution of income has worsened during the same period. This is particularly true for the rural sector and the extreme poor for whom the depth and severity of poverty increased between 1985-92. If income distribution had remained unchanged, the national incidence of poverty would have declined further by another 4 percent. The Lagos urban area is the only region where income distribution improved. Hence, for all other regions growth without improvements in income distribution have adversely affected the extreme poor in Nigeria.

Poverty declined in Nigeria mainly due to the 34 percent growth in household expenditures which was a result of economic growth. However, the regional pattern of household expenditure growth is varied in different parts of the country. While the south and middle zones had higher growth rates of household expenditures, the northern zone experienced hardly any growth. This particularly evident in the rural areas of the north.

Poverty in Nigeria differs depending on socio-economic groupings. Those with no education comprise the poor and extreme poor, and this is very true in rural areas. If the household head is older, the probability of being poor increases. Wage workers and self-employed are often poor. Households which are large and families with large number of children are more frequently poor.
_50_

# **6.1. Analytic Methodology**

Several lessons can be learnt from the methodology in this paper. First the results have demonstrated that there is a difference between the poor and the extreme poor. It has also been established that while the headcount declined for the poor and extreme poor, depth and severity actually increased for the extreme poor. This would have been entirely missed if the analysis had used only one poverty line. Second, it is important to check how robust the results are, to changes in the poverty lines and poverty measures. Sensitivity analysis showed that all major patterns remained unchanged with small changes in the poverty lines. Dominance analysis permitted us to broaden that conclusion, and did indicate that caution was needed because for values up to almost half of the present poverty line, the conclusions would be reversed, in the sense that, it would find an increase in poverty over the seven year period. Third, the decomposition analysis of the over-time changes in poverty into growth and redistribution, and further into intra-sectoral and population shifts, was particularly useful to understand the dynamics of poverty and its implications for a continuously changing scene.

The analysis of targeting indicators is very useful to identify vulnerable groups. This is particularly useful to policy makers who always ask the question, who are the vulnerable groups and who should be targeted. Lastly, our use of a multi-dimensional approach in combination with decomposable poverty indices proved to be a very effective tool in linking economic change to welfare of households and individuals within the household. We do not claim in any way to have proved causality, as perhaps we could have done with a comprehensive economy-wide model, but what we do claim is that this collaborative effort has broken ground in the field of poverty in Nigeria. However, a lot of research still needs to be done to explain many of the findings in this paper.

# 6.2. **Beyond the Poverty Profile**

Considering the severe constraints imposed on the poverty profile by the difficulties in accessing and cleaning the Nigerian data sets, it is important that consideration be given to follow-up strategies to improve in-country capacity for data collection and analysis and establishing poverty monitoring systems. A systematic study is needed to fully assess useroriented data needs for Nigeria. This paper recommends the establishment of an annual monitoring report on poverty and welfare in Nigeria. Year-to-year changes in Nigeria were very drastic as we saw, and there is no reason to think that these changes will not occur again. The paper also recommends that both household expenditure and basic needs information is needed, since neither is by itself sufficient to give a full picture of welfare. We recommend that once in every five years an integrated living standards survey be carried out to permit in-depth analysis of household behavior and response.

Apart from that, there should be other quicker monitoring surveys, or even some sort of priority surveys, focusing only on selected basic needs variables of the sort indicated before - for example, for the rural areas, the mix of crops they farm, the quality of their land, the value of their assets such as livestock, or even the degree to which they rely on wage labor compared to better off farmers. There is no information on the asset base, typical of the poor and the sort of
_51_ assets the poor lose first, when coping with survival crises. The lack of these indicators makes it difficult to build up an understanding of the capabilities and resources of the poor - in terms of physical assets and human resource endowment. The survey should include some limited information on household expenditures, solely to provide the means to group households into approximate expenditure quintiles. One rather overwhelming lesson which the research team learned is the complexity, cost and time-consuming nature of analyzing two years of a National Consumer Survey. Expenditure coding was overwhelmingly large. With 1600 codes for household expenditure, one cannot do this type of research without questioning whether these codes could not be aggregated into 50100 key expenditure items, same as the items for which prices are collected.

Another key lesson for the team has been the fact that the Nigerian statistical system is in need of a major overhaul. A complete review of the system is crucial, not only for poverty monitoring, but for the basic information needed to understand welfare in Nigeria.

The data used in this study was particularly weak with respect to information on women. Gender analysis in the paper was limited because of the nature of the data set. In most surveys, and the present one is no exception, women are liable to be missing. This invisibility does not only refer to failure to count women, but also to the way questions are posed and coded. For example, in so far as it is true that men are more likely than women to be participants in the modern sector, then, a focus on that sector will exclude women. We recommend that the next surveys should consider these issues for improved policy-making and planning, and make a significant contribution to the gender dimensions of poverty. Data collection could focus on: (a) female resources: education, responsibility for child care, (b) female economic activity: time use, work actually done by women, whether paid or, more commonly, unpaid, and (c) female poverty: Finally there is need to enrich our knowledge and expand information on measuring poverty in terms of its multi-dimensional nature. There is very scarce reliable information on the social indicators of welfare for Nigeria. It is necessary to collect annual or periodic monitoring indicators for measuring changes in living and welfare conditions. This is fundamental in understanding the deprivations faced by the poor and in designing poverty alleviation programs. A critical analysis of coping strategies of the poor can help design safety net programs for those hardly hit. Also poverty alleviation is not feasible without a comprehensive employment policy. There is very little information about the functioning of labor markets, wage formation and labor legislation. Gender dimensions of poverty need to be understood more clearly to be able to design programs that can target the poor women and children. An integrated "food poverty" analysis together with "money-metric" poverty measures to address the nutritional and health consequences of the poor, is also a high priority.

In summary:

- a) Nigeria needs to establish a demand driven poverty monitoring system which will include a poverty monitoring unit, and a program of both quantitative and qualitative surveys;

- b) The FOS should continue to collect basic welfare indicators through an annual household survey. The current NISH can provide the basis, but a number of improvements can be made
52 to the questionnaire design, the data entry and processing procedures and to the ways in which the data are disseminated and analyzed - so as to improve the quality and timeliness of the results;

- c) A more detailed integrated survey, including full income and consumption details should be carried out once every five years;

- d) The formal statistical surveys need to be supplemented with a program of qualitative studies that would be capable of addressing qualitative aspects of poverty that the surveys do not capture well;

- e) Consideration should be given to the idea of a panel study (or to the establishment of a Sentinel Site Surveillance System, with a permanent panel of sites) for monitoring how changes in moneymetric and other indicators affect the same households over time.