‘The Rich Are Just Like Us Only Richer’ Poverty Functions or Consumptions Functions?

The concept of a poverty function is introduced, modelling the shortfall of household consumption from the poverty line as a function of reduced form determinants such as human capital and land holdings. The model is estimated using a tobit and data from Uganda. Parameters from the model are found to be similar to those from consumption functions, indicating that the poor receive comparable rates of return on their assets to the non-poor. Education of both men and women appears to raise the welfare of the poor as well as the nonpoor, in both urban and rural areas. In fact, the relevant models of household consumption might be better referred to as `welfare functions', because 1 — unlike orthodox consumption functions — their emphasis is not relations with income but rather on the reduced form determinants of income. Even if poverty is better analyzed by welfare functions than by poverty functions, the earlier point about the lack of multivariate analyses of poverty remains true. Glewwe (1991) provides one of the few examples of such welfare functions. 1 Studies of poverty using household survey data from developing countries have typically concentrated on measurement issues and on describing the characteristics of the poor (see Ravallion, 1992, for a review of the issues and Boateng et al., 1992, for one example of a `poverty profile'). This work is sometimes technically very sophisticated and is a necessary first step for evaluating interventions targeted at the poor (see Anand, 1983, for an illustration). However, there are surprisingly few examples in the literature of multivariate analysis of the determinants of poverty; of estimating what could be termed `poverty functions'. Such poverty functions might give more insight into what type of interventions could reduce poverty. They would also permit more valid inferences about the causes of poverty than are provided by the simple — often bivariate — decompositions of poverty indices presented in conventional poverty profiles. A common aggregate poverty index is the `poverty gap', that is to say the mean negative deviation of consumption from some minimum acceptable level, the poverty line. Consequently, if one aimed to model household poverty, a natural dependent variable is the household poverty gap: how far, if at all, household consumption falls below the poverty line. Explanatory variables could include those factors which might affect welfare including household variables such as demographics, assets and education together with community-level variables such as prices and local infrastructure. Perhaps the main objection to estimating such poverty functions is that it would be better to model household consumption per se on the grounds that censoring the distribution of consumption above the poverty line wastes information. The case for estimating poverty functions rather than consumption functions requires that the information about the consumption of the non-poor is not useful and could be misleading: that the poor may behave differently from the nonpoor . If the hypothesised determinants of welfare, such as human capital and physical assets, have 1 different returns for the poor and non-poor, then consumption functions may give misleading results for the analysis of poverty interventions. For example, consumption functions may show schooling to have large returns on average, but if these arise for only the non-poor, then it would be quite inappropriate to advocate expansion of education as a part of a poverty alleviation package. Thus the choice between consumption functions and poverty functions in part depends on whether people are poor just because they have less assets (including human capital) or whether they also receive lower returns on their assets. This paper compares the results of consumption and poverty functions using data from a recent national survey of Uganda. Section 1 explains the poverty measure adopted and the methods of analysis used. Attention is given to the choice of the appropriate econometric technique for estimating a poverty function, given the censored nature of the dependent variable (the household poverty gap). Section 2 presents the empirical results. Two broad inter-related issues are raised. The first is methodological: is anything gained from modelling poverty per se rather than welfare (proxied by consumption) in general? The second is substantive: what are the determinants of poverty and welfare in Uganda? Particular attention is focused on the role of human capital, in view of the current emphasis by many international agencies upon expanding education as one means of reducing poverty (for example, see World Bank, 1990). Section 3 concludes the paper. It would be possible to construct more comprehensive welfare indices by augmenting expenditure based measures 2 with non-monetary indicators. However, the weighting involved in aggregating the various elements is likely to be rather arbitrary and controversial. This point has been made regarding the Human Development Index (Kanbur, 1993). The equivalence scales reflect WHO calorific requirements for males (reported in West, 1987). 3 The CPI rose by a third during the first four months of 1992, thereafter it was stable (Republic of Uganda, 1994a). 4 The deflator is in fact the absolute poverty line as given in Appleton (1995a), to which the interested reader is referred 5 for further details of construction. Two limitations arise in using it as a price deflator. Firstly, the food basket is defined by national spending patterns, when in fact there are marked regional differences in staple foods. Secondly, `essential' non-food spending as estimated will only rise with non-food prices if the price elasticity of non-food spending is less than unity. The rationale for this is that if such households are sacrificing their minimum adequate calorie intake for non-food 6 items, then these non-food items must be essential. The method of estimation allowed for different non-food requirements over time and across regions. 2 1. Measuring and Modelling Poverty In line with most economic studies, this paper uses a money metric measure of welfare; in this case, total consumption. Consumption of home produced food is included, valued at market prices. However, a number of important non-marketed dimensions of well-being are omitted. These include child schooling and health status, both of which appear to be only weakly, if at all, related to consumption in Uganda (see Heyneman, 1979, Kakande and Nalwadda, 1993, and Mackinnon, 1994). More generally, low correlations between a range of different welfare indicators have been found elsewhere in Africa (Glewwe and van der Gaag, 1988). However, total consumption remains arguably the single most comprehensive indicator of ability to meet wants .Consumption rather 2 than income is used both because it is likely to be more accurately measured and because, following the permanent income hypothesis, it may better reflect longer term economic status (Johnson et al., 1990). Nonetheless, the consumption measure refers only to the year of the survey and will not fully reflect welfare over the life-cycle (Deaton, 1980). The use of panel data is necessary to determine if households are permanently poor or only temporarily impoverished (see Dercon, Krishnan and Kello, 1994). The survey measured consumption at the level of the household and consequently the analysis here abstracts from issues of intra-household allocation. Evidence from the Philippines suggests that the use of household level welfare measures may still provide valid inferences about the correlates and patterns of poverty, even though the neglect of intra-household inequality leads to under-estimates of its level (Haddad and Kanbur, 1989). Welfare is proxied by household consumption per adult equivalents rather than per capita, to reflect the lower needs of children . 3 Substantial variations in prices across regions and during the period of the survey necessitate the deflation of nominal consumption . Non-food prices were not available, so nominal consumption 4 was deflated by the cost of a food basket combined with an estimate of `essential' non-food spending . Essential non-food spending was estimated, following Ravallion and Bidani (1994), as 5 that observed amongst those households whose total consumption was only enough to meet the food poverty line . The food basket was based on the expenditure pattern of the poorest half of 6 the population. Food prices which varied by region and with the time of the survey, were estimated as the median unit values of purchases by households in a given region during two month intervals of the survey year. The poor were defined in a relative manner as the bottom half of the population ranked by real consumption per adult equivalent. Sensitivity analysis was carried out by estimating alternative models where the poor were defined as the bottom 25% and 75% of the population.