Peter Lanjouw

Micro--Level Estimation of Poverty and Inequality

Recent theoretical advances have brought income and wealth distributions back into a prominent position in growth and development theories, and as determinants of specific socio-economic outcomes, such as health or levels of violence. Empirical investigation of the importance of these relationships, however, has been held back by the lack of sufficiently detailed high quality data on distributions. Household surveys that include reasonable measures of income or consumption can be used to calculate distributional measures, but at low levels of aggregation these samples are rarely representative or of sufficient size to yield statistically reliable estimates. At the same time, census (or other large sample) data of sufficient size to allow disaggregation either have no information about income or consumption, or measure these variables poorly. This note outlines a statistical procedure to combine these types of data to take advantage of the detail in household sample surveys and the comprehensive coverage of a census. It extends the literature on small area statistics (Ghosh and Rao (1994), Rao (1999)) by developing estimators of population parameters that are nonlinear functions of the underlying variable of interest (here unit level consumption), and by deriving them from the full unit level distribution of that variable. In examples using Ecuadorian data, our estimates have levels of precision comparable to those of commonly used survey based welfare estimates—but for populations as small as 15,000 households, a ‘town.’ This is an enormous improvement over survey based estimates, which are typically only consistent for areas encompassing hundreds of thousands, even millions, of households. Experience using the method in South Africa, Brazil, Panama, Madagascar, and Nicaragua suggest that Ecuador is not an unusual case (Alderman et al. (2002), and Elbers et al. (2002)).

Non-Agricultural Earnings in Peri-Urban Areas of Tanzania: Evidence from Household Survey Data

Abstract This study draws on purposive survey data of approximately 600 households in peri-urban Tanzania to describe the degree and nature of non-farm diversification in these settings. With the exception of relatively dynamic cities such as Dar es Salaam and Arusha, overall non-farm incomes shares are not unambiguously higher than in rural areas as a whole. Non-farm income shares rise sharply and monotonically with quintiles defined in terms of per capita food consumption. In that sense the sector appears to offer an important route out of poverty. The evidence suggests that education, and access to infrastructure, are important determinants of non-farm incomes in peri-urban areas. Women appear to be poorly placed vis a vis the non-farm sector, even after controlling for education, age and other characteristics. Kinship and tribal affinities, and time devoted to communal activities, appear to deter entrepreneurial activity and non-farm employment, but trust in officials and public servants and strong heterogeneous village associations, are important in stimulating non-farm activity.

Nonfarm Employment and Poverty in Rural El Salvador

Abstract This paper analyzes two complementary data sets to study poverty and the nonfarm sector in rural El Salvador. We find that rural poverty in El Salvador remains acute and significantly higher than in urban areas. While the rural poor are mainly agricultural laborers and marginal farmers, some nonfarm activities are also of importance to the poor. In fact, nonfarm activities in El Salvador account for a significant share of rural employment and income for both the poor and the nonpoor. The poor, on the one hand, are engaged in “last resort” nonfarm activities that are not associated with high levels of labor productivity. The nonpoor, on the other, are engaged in productive nonfarm activities which are likely to present a potent force for upward mobility. Significant correlates of these high-productivity occupations include education, infrastructure, location, and gender. While most of the analysis is at the household level, the data also permit some focus on small-scale rural enterprise activities. It appears that in El Salvador very few rural enterprises report utilizing formal credit in setting up their activities. In addition, a significant proportion of enterprises are engaged in subcontracting arrangements with some larger, often urban-based, firm.

Economic development in Palanpur over five decades

This book provides an account of economic development in Palanpur, a village in rural North India, based on five detailed surveys of the village over the period 1957 to 1993. These five decades have seen economic well-being rise in some important respects, but stagnation and even decline in other areas. The analysis presented here focuses on the reasons behind this uneven progress. The authors tie in the background issues of the evolution of poverty and inequality and mobility over time with causal factors such as technological progress, demographic and sectoral changes, the operation of markets, and the role of public action. The richness and unique nature of the qualitative and quantitative data collected and presented by Lanjouw and Stern yields an analysis which illuminates questions of direct importance to researchers in a wide variety of disciplines.

Intersectoral Transfer, Growth, and Inequality in Rural Ecuador

Abstract In this paper we study intersectoral transfer and its impact on the distribution of income in Ecuador. We find that income shares between farm and nonfarm activities are roughly equal, on average, although the rich in rural areas typically receive a greater share of income from nonfarm sources. Thus decomposing inequality by income source reveals that a rise in nonfarm incomes increases inequality. Drawing on a new method to estimate local-level distributional outcomes, growth of the high-productivity nonfarm sector is observed to have a strong and positive association with average consumption and inequality. Growth of the low-productivity nonfarm sector is associated with little change in either average income or income inequality. Irrespective of subsector, growth of the nonfarm sector is associated with a substantial fall in poverty.

Income inequalities in China : Evidence from household survey data

On the basis of a household data set, this paper: compares household income inequality in urban and rural China; decomposes inequality into intra-and interprovincial components; and analyzes the contribution of various income sources to total income equality. The main findings of the paper are, first, that unlike in most developing economies, income inequality in urban areas is lower than in rural areas. Second, nationwide income inequality is due mostly to intraprovincial inequality. Third, components of income associated with economic reforms are more unequally distributed than the rest.

Rural Nonfarm Activities and Poverty in the Brazilian Northeast

Abstract This paper combines two complementary data sets to present a disaggregated spatial profile of poverty in the Brazilian Northeast, and to investigate the importance of nonagricultural activities for its rural dwellers. We present both univariate and multivariate profiles of nonagricultural employment and discuss its determinants. While the main occupational difference between the rural poor and the rural nonpoor in Brazil seems to be the greater reliance of the former on paid agricultural employment (vis-a-vis own cultivation), rather than access to nonagricultural activities, the evidence nevertheless suggests that diversification into this growing sector provides both an important complement to the budgets of the poor, and possibly a self-insurance mechanism against negative shocks. Despite the substantial heterogeneity of the sector, two general findings are robust: returns to education are comparatively high; and location in relation to urban areas is an important determinant of both employment and earnings in rural nonagricultural activities.

Constructing an indicator of consumption for the analysis of poverty : principles and illustrations with reference to Ecuador

This paper is concerned with the derivation of a welfare indicator for households from consumption data. It examines, illustrating with reference the data for Ecuador, several of the steps involved in constructing consumption aggregates and highlights some of the principles which should guide the analysis. The paper emphasizes that specific care is warranted where access is characterized by rationing. Simple methods are outlined to impute a hypothetical rent for owner-occupied housing, to include consumption of basic social services, and to calculate a stream of consumption derived from a stock of consumer durables. The paper demonstrates that the definition of consumption adopted can have a significant bearing on measured poverty, the profile of poverty might be quite robust to alternative consumption definitions. However, it argues that only after robustness has been firmly established should results be emphasized.

Benefit Incidence and the Timing of Program Capture

Survey-based estimates of average program participation conditional on income are often used in assessing the distributional impacts of public spending reforms. But program participation could well be nonhomogeneous, so that marginal impacts of program expansion or contraction differ greatly from average impacts. Using the geographic variation found in sample survey data for rural India for 1993-94, the authors estimate the marginal odds of participating in schooling and antipoverty programs. Their results suggest early capture of these programs by the nonpoor. Thus, conventional methods of assessing benefit incidence underestimate the gains to Indias rural poor from higher public outlays, and their loss from program cuts.

How to Compare Apples and Oranges: Poverty Measurement Based on Different Definitions of Consumption

Poverty rates calculated on the basis of household consumption expenditures are routinely compared across countries and time. The surveys which underlie these comparisons typically differ in the types of food and non‐food expenditures included, often in ways which are easily overlooked by analysts. With several examples we demonstrate that these commonly occurring variations in expenditure definitions can give rise to marked differences in poverty rates where there are no real differences in well‐being. We show that one approach to calculating poverty lines, used with the headcount measure of poverty, can allow comparisons based on data with different definitions of consumption. In addition to allowing comparative poverty analysis using existing survey data, the results suggest that poverty monitoring could be done effectively at lower cost by alternating detailed expenditure surveys with far more abbreviated surveys.