Tropentag, October 6 - 8, 2009 in Hamburg "Biophysical and Socio-economic Frame Conditions for the Sustainable Management of Natural Resources"

Development of Absolute Expenditure Poverty Indicators in Northern Viet Nam

University of Hohenheim, Department of Agricultural Economics and Social Sciences in the Tropics and Subtropics, Germany

Abstract

In Viet Nam, the poverty assessment method (MOLISA tool) screens poor households annually in order to allocate subsidised services in the area of credit, health, housing, and education. However, this method suffers from a number of shortcomings since it uses complex indicators (such as income) as well as strongly depends on how knowledgeable neighbours are about each others' poverty situation. The paper investigates two major hypotheses.
First, the MOLISA tool leads to high undercoverage of the poor, and high leakage of scarce public resources to the non-poor. Second, a new tool based on regression analysis will lead to lower undercoverage and leakage errors while using less complex indicators. Both hypotheses are accepted in the analysis.
The study measures per-capita daily expenditures, as a proxy of income, of a 300-household-random sample which is representative for Yen Chau district, Son La province. To capture a considerable amount of seasonality in agricultural productions and incomes in the area, two expenditure survey rounds were implemented, following the methodology of the Living Standard Measurement Survey of the World Bank. Four regressions have been used: Ordinary Least Square, Quantile, Linear Probability Model and Probit with more than 200 poverty indicators to identify the best10 and best15 indicators within the survey that most accurately reflect the ‘'true'' poverty status of each household.
It is found that the quantile regression has highest accurate performance among other regressions. It almost perfectly predicts the observed poverty rate with an optimal point of estimation set at the 31^st percentile. The leakage amounts to 26% when using the new tool as compared to 66% for the MOLISA tool. Moreover, the best derived poverty indicators are reliable and also cost-effective to measure poverty but allow to give high accuracy criteria compared to the currently used method and promise to improve targeting efficiency of policies in Viet Nam. These results will be shared in a feedback workshop to stakeholders in Son La province in September 2009, and the paper presentation at the Tropentag will also include feedback by government institutions and communities on their perceptions about the usefulness of the new poverty assessment tool.

Keywords: Poverty, poverty indicators, quantile, targeting efficiency, Viet Nam

Contact Address: Thi Tuyet Van Dinh, University of Hohenheim, Department of Agricultural Economics and Social Sciences in the Tropics and Subtropics, Schloß Osthof-Süd, 70599 Stuttgart, Germany, e-mail: dinhthiuni-hohenheim.de