Tracking poverty is predicated on the availability of comparable consumption data and reliable price deflators. However, regular series of strictly comparable data are only rarely available. Price deflators are also often missing or disputed. In response, poverty prediction methods that track consumption correlates as opposed to consumption itself have been developed. These methods typically assume that the estimated relation between consumption and its predictors is stable over time—assumptions that cannot usually be tested directly. This study analyzes the performance of poverty prediction models based on small area estimation (SAE) techniques. Predicted poverty estimates are compared with directly observed levels in two country settings where data comparability over time is not a problem. Prediction models that employ either non-staple food or non-food expenditures or a full set of assets as predictors are found to yield poverty estimates that match observed poverty well. This offers some support to the use of such methods to approximate the evolution of poverty. Two further country examples illustrate how an application of the method employing models based on household assets can help to adjudicate between alternative price deflators.
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The paper has benefited from comments by two anonymous referees and participants in the UNU-WIDER “Frontiers of Poverty Analysis” Conference held in Helsinki, 26–27 September, 2008. Part of the study was completed during Luc Christiaensen’s 2-year sabbatical at UNU-WIDER in Helsinki, whose support is gratefully acknowledged. The findings, interpretations, and the findings, interpretations, and conclusions expressed in this paper are entirely those of the authors, They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
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Christiaensen, L., Lanjouw, P., Luoto, J. et al. Small area estimation-based prediction methods to track poverty: validation and applications. J Econ Inequal 10, 267–297 (2012). https://doi.org/10.1007/s10888-011-9209-9
- Consumption prediction
- Price deflator
- Poverty dynamics
- Small area estimation