Small Area Estimation-Based Prediction Methods to Track Poverty : Validation and Applications
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 re...
Main Authors: | , , , |
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Format: | Policy Research Working Paper |
Language: | English |
Published: |
2012
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Subjects: | |
Online Access: | http://www-wds.worldbank.org/external/default/main?menuPK=64187510&pagePK=64193027&piPK=64187937&theSitePK=523679&menuPK=64187510&searchMenuPK=64187283&siteName=WDS&entityID=000158349_20110615112641 http://hdl.handle.net/10986/3447 |
Summary: | 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 -- an
assumption that cannot usually be tested directly. This
study analyzes the performance of poverty prediction models
based on small area estimation 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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