Imputed Welfare Estimates in Regression Analysis

Imputed Welfare Estimates in Regression Analysis

The authors discuss the use of imputed data in regression analysis, in particular the use of highly disaggregated welfare indicators (from so-called "poverty maps"). They show that such indicators can be used both as explanatory variables...

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Bibliographic Details
Main Authors:	Elbers, Chris, Lanjouw, Jean O., Lanjouw, Peter
Format:	Policy Research Working Paper
Language:	English en_US
Published:	World Bank, Washington, D.C. 2013
Subjects:	IMPUTED COSTS REGRESSION ANALYSIS WELFARE INDICATORS POVERTY MAPS AGGREGATE GROWTH MODELS ECONOMIC GROWTH BOOTSTRAP CALCULATION CAPITA CONSUMPTION CAPITA EXPENDITURE CENSUS DATA CENSUS HOUSEHOLDS CENTER CLUSTER CORRELATION COEFFICIENTS COMMUNITY INEQUALITY COMPILE COMPUTATION CONDITIONAL EXPECTATION CONSISTENT ESTIMATES CONSISTENT ESTIMATOR CONSISTENT STANDARD ERRORS CONSUMPTION EXPENDITURE CONSUMPTION LEVEL CONSUMPTION MODEL CONSUMPTION REGRESSION COVARIANCE DEPENDENCY DEPENDENT VARIABLE DEPENDENT VARIABLES DIAGONAL MATRIX DISTURBANCE TERM ECONOMIC ANALYSIS ECONOMIC OUTCOMES ERROR ERROR TERM ERROR VARIANCE ERROR VARIANCES ESTIMATION PROCEDURE EXOGENOUS VARIABLES EXPECTED VALUE EXPENDITURE MODEL EXPLANATORY VARIABLES HOUSEHOLD CONSUMPTION HOUSEHOLD LEVEL HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEY DATA HOUSEHOLD-LEVEL HOUSEHOLDS IDIOSYNCRATIC ERROR INSTRUMENTAL VARIABLES LEVEL OF AGGREGATION LINEAR APPROXIMATION LIVING STANDARDS MATRICES MATRIX MEASURE OF POVERTY PARAMETER ESTIMATES PARAMETER VECTOR POVERTY ALLEVIATION POVERTY MAPPING POVERTY MEASURES POVERTY STATUS PREDICTION RANDOM COMPONENTS RANDOM EFFECTS REGRESSION EQUATION REGRESSION MODEL RESAMPLING SIGNIFICANCE LEVEL SIMULATION SIMULATIONS STANDARD ERROR STANDARD ERRORS TIME PERIOD WEALTH
Online Access:	http://documents.worldbank.org/curated/en/2004/05/4265592/imputed-welfare-estimates-regression-analysis http://hdl.handle.net/10986/14102

Description
Summary:	The authors discuss the use of imputed data in regression analysis, in particular the use of highly disaggregated welfare indicators (from so-called "poverty maps"). They 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. The authors 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, the authors argue that essentially the same aggregate relationships would be found with either actual or imputed variables. They address the methodological question of how to interpret aggregate relationships found in such regressions.

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