Imputed welfare estimates in regression analysis
讨论在回归分析中使用插值福利指标（如贫困地图）作为解释变量或被解释变量，并尝试调整标准误以反映插值误差，基于厄瓜多尔数据验证，指出插值变量与真实变量在聚合关系上基本一致。
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. © Oxford University Press 2005; all rights reserved.