Imputed welfare estimates in regression analysis

被引:16
作者
Elbers, C [1 ]
Lanjouw, JO
Lanjouw, P
机构
[1] Amsterdam Inst Int Dev, Amsterdam, Netherlands
[2] Vrije Univ Amsterdam, Amsterdam, Netherlands
[3] Brookings Inst, Washington, DC USA
[4] Ctr Global Dev, Washington, DC USA
[5] Univ Calif Berkeley, ARE Dept, Berkeley, CA 94720 USA
[6] World Bank, Washington, DC 20433 USA
关键词
poverty; poverty maps; imputed regressors; two-step estimation;
D O I
10.1093/jnlecg/lbh056
中图分类号
F [经济];
学科分类号
02 [经济学];
摘要
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.
引用
收藏
页码:101 / 118
页数:18
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