Geographic Decomposition of Inequality in Health and Wealth : Evidence from Cambodia

The small-area estimation developed by Elbers, Lanjouw and Lanjouw (2002, 2003), in which a census and a survey are combined to produce the estimates of welfare measures for small geographic areas, has become a standard tool for poverty analysis in developing countries. The small-area estimates are typically plotted on a map, which are commonly called a poverty map. Poverty maps proved useful for policy analysis and formulation, and have become increasingly popular among policy-makers and researchers. In Cambodia, poverty maps have been used by various international organizations, ministries and non-governmental organizations for analyzing the poverty situations for their operation areas, selecting the potential locations for their projects and programs, and educating students in classrooms (Fujii, 2007). Besides creating poverty maps, the small-area estimation has been used for a wide array of purposes. For example, it has been used to analyze geographic targeting (Elbers et al., 2007 and Fujii, 2008), consumption inequality (Elbers et al., 2004), local inequality and crime (Demombynes and zler, 2005), and impacts of trade liberalization (Fujii and Roland-Holst, 2008). In this paper, we offer another new application of the small-area estimation; We use the small-area estimation to look at whether poverty is more spatially unequally distributed than child undernutrition. More precisely, we decompose inequality of consumption and child nutrition status into the within-group and between-group inequalities at various levels of spatial aggregation, and compare the decomposition results. While it is widely known that the health and wealth are positively correlated, it is not clear whether the spatial inequality in health and wealth necessarily exhibits a similar pattern. The significance of this point can be easily understood in a simple example. Suppose that the wealthy people in a country only live in the north and poor people only in the south, and suppose further that mosquitoes carrying malaria parasites exist uniformly across the country. Since wealthy people have better knowledge to cope with malaria, and resources to prevent the infection (such as mosquito repellants and mosquito nets), they are less likely to get infection than poor people. However, since there is no perfect preventive measure, the incidence of malaria would be less unequally distributed than poverty across the country. This example is extreme, of course. But it is of interest to see how different the spatial patterns of inequality in poverty and undernutrition are. The knowledge of spatial inequality in consumption and health is valuable for geographic targeting, because the spatial inequality prescribes the potential gains from geographic targeting. In the example given above, the resources for anti-poverty programs can be fully efficiently used if they are delivered to the south because everyone is poor and thus the resources all go to poor people. However, if we deliver all the resources (say, malaria tablets) to the south, the outcome may not be fully efficient. We would be giving the tablets to some in the south who are less vulnerable to malaria while not giving to others in the north who are more vulnerable to malaria. If geographic information is the only information available to the policy-maker, geographic targeting is still useful (and efficient given the available information), but the extent to which one may gain from geographic targeting is determined by the pre-existing spatial inequality. This paper is organized as follows. In the next section, we review the related literature. In Section 3, we shall discuss the small-area estimation methods for consumption and child nutrition status. We shall develop a unified framework for the standard small-area estimation developed by Elbers, Lanjouw and Lanjouw (2002, 2003) and its extension for the estimation of the prevalence of alnutrition by Fujii (2005). In Section 4, we shall discuss the method of inequality decomposition. In Section 5, we shall discuss the data we use. We then present the decomposition results in Section 6. Section 7 provides concludes.estimates of welfare, Cambodia, poverty map, Wealth, consumptionstatus, child nutrition status, inequality decomposition

Two-sample estimation of poverty rates for disabled people: an application to Tanzania

Estimating poverty measures for disabled people in developing countries is difficult,partly because relevant data are not available. We develop two methods to estimate poverty by the disability status of the household head. We extend the small area estimation proposed by Elbers, Lanjouw and Lanjouw (2002, 2003) so that we can run a regression on head's disability status even when such information is unavailable in the survey. We do so by aggregation and by moment adjusted two sample instrumental variable estimation. Our results from Tanzania show that both methods work well, and that disability is indeed associated with poverty.poverty, disability, Tanzania, aggregation, two-sample instrumental variable estimation

How Does Vietnam's Accession to the World Trade Organization Change the Spatial Incidence of Poverty?

Trade policies can promote aggregate e?ciency, but the ensuing structural adjustments generally create both winners and losers. From an incomes perspective, trade liberalization can raise GDP per capita, but rates of emergence from poverty depend upon individual household characteristics of economic participation and asset holding. To fully realize the growth potential of trade, while limiting the risk of rising inequality, policies need to better account for microeconomic heterogeneity. One approach to this is the geographic targeting, which shifts resources to poor areas. This study combines an integrated microsimulation-CGE model with the small area estimation to evaluate the spatial incidence of Vietnam's accession to the WTO. Provincial-level poverty reduction after full liberalization was heterogeneous, ranging from 2.2 per cent to 14.3 per cent. Full liberalization will bene?t the poor on a national basis, but the northwestern area of Vietnam is likely to lag behind. Furthermore, poverty can be shown to increase under comparable scenarios.trade liberalization, microsimulation, computable general equilibrium, small-area estimation, Vietnam

How does Vietnam's accession to the World Trade Organization change the spatial incidence of poverty?

Trade policies can promote aggregate efficiency, but the ensuing structural adjustments generally create both winners and losers. From an incomes perspective, trade liberalization can raise gross domestic product per capita, but rates of emergence from poverty depend on individual household characteristics of economic participation and asset holding. To fully realize the growth potential of trade, while limiting the risk of rising inequality, policies need to better account for microeconomic heterogeneity. One approach to this is geographic targeting that shifts resources to poor areas. This study combines an integrated microsimulation-computable general equilibrium model with small area estimation to evaluate the spatial incidence of Vietnam's accession to the World Trade Organization. Provincial-level poverty reduction after full liberalization was heterogeneous, ranging from 2.2 percent to14.3 percent. Full liberalization will benefit the poor on a national basis, but the northwestern area of Vietnam is likely to lag behind. Furthermore, poverty can be shown to increase under comparable scenarios.Rural Poverty Reduction,Population Policies,Economic Theory&Research,Achieving Shared Growth

Modeling myopia: Application to non-renewable resource extraction

Ministry of Education, Singapore under its Academic Research Funding Tier

Decomposing the Changes of the Divisia Price Index: Application to Inflation in the Philippines

We propose a method to decompose the logarithmic change of the Divisia price index into the pure price effect, the prefernce effect and the substitution effect. Our empirical results in the Philippines shows the effects of preference change on the Divisia price index are heterogeneous but positive across all regions and income deciles. However, they are dominated by the pure price effect.Divisia price index, preference change, decomposition, Philippines

How Well Can We Target Resources with “Quick-and-Dirty” Data?: Empirical Results from Cambodia

Poverty reduction is a top priority for international organizations, governments and non-governmental organizations. The aid resources available for poverty reduction are, however, severely constrained in many countries. Minimizing the leakage of aid resources to the non-poor is a key to maximize poverty reduction with limited amount of resources availble. One way to minimize such leakage is to target resources geographically. That is, policymakers can move resources to the poorest parts of the country. Geographic targeting can be quite effective when poverty is unevenly distributed across the country, and this proves to be the case in many countries.

Micro-level estimation of child malnutrition indicators and its application in Cambodia

One of the major limitations in addressing child malnutrition is lack of information that could be used to target resources. By combining demographic and health survey (DHS) and population census data, the author disaggregates the estimates of the prevalence of child malnutrition in Cambodia from currently available 17 DHS strata into 1,594 communes. The methodology is built on the small-area estimation technique developed by Elbers, Lanjouw, and Lanjouw. The author extends it to jointly estimate multiple indicators and to allow for a richer structure of error terms. Average standard errors for the commune-level estimates in this study were about 4 percent, a magnitude comparable to those for stratum-level estimates derived from DHS only. The author demonstrates three applications of these estimates. First, he explores the relationship between malnutrition, consumption poverty, and inequality. The nonlinear effects of consumption on nutritional status of children are a key component of the relationship. Second, he conducts a decomposition analysis of health inequality and finds that the between-location share of health inequality is lower than with consumption inequality. Finally, he evaluates the potential gains from geographic targeting. The author finds that the savings in the cost of a nutrition program from commune-level targeting is on average at least two to three times higher than that from stratum-level targeting when the per capita cost of the program is fixed.