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Journal of Economic Geography Advance Access originally published online on January 7, 2005
Journal of Economic Geography 2005 5(1):101-118; doi:10.1093/jnlecg/lbh056
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Journal of Economic Geography, Vol. 5, No. 1, © Oxford University Press 2005; all rights reserved.

Imputed welfare estimates in regression analysis

Chris Elbers*, Jean O. Lanjouw** and Peter Lanjouw***

* Amsterdam Institute for International Development and Vrije Universiteit Amsterdam, The Netherlands. email: <celbers{at}feweb.vu.nl.>
** ARE Department, University of California, Berkeley, Brookings Institution and the Center for Global Development, Washington, DC, USA. email: <jlanjouw{at}are.berkeley.edu.>
*** World Bank, Washington, DC 20433, USA. email: <planjouw{at}worldbank.org.>

Abstract

We discuss the use of imputed data in regression analysis, in particular the use of highly disaggregated welfare indicators (from so-called ‘poverty maps’). We show that such indicators can be used both as explanatory variables on the right-hand side and as the phenomenon to explain on the left-hand side. We try out practical ways of adjusting standard errors of the regression coefficients to reflect the error introduced by using imputed, rather than actual, welfare indicators. These are illustrated by regression experiments based on data from Ecuador. For regressions with imputed variables on the left-hand side, we argue that essentially the same aggregate relationships would be found with either actual or imputed variables. We address the methodological question of how to interpret aggregate relationships found in such regressions.

Keywords: poverty, poverty maps, imputed regressors, two-step estimation,
JEL classifications: O15, O18, C13, C21
Date submitted: 1 October 2003     Date accepted: 21 September 2004


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