Regression with an Imputed Dependent Variable
Peter Levell () and
Stavros Poupakis ()
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Peter Levell: Institute for Fiscal Studies and Institute for Fiscal Studies
No W19/16, IFS Working Papers from Institute for Fiscal Studies
Researchers are often interested in the relationship between two variables, with no single data set containing both. A common strategy is to use proxies for the dependent variable that are common to two surveys to impute the dependent variable into the data set containing the independent variable. We show that commonly employed regression or matching-based imputation procedures lead to inconsistent estimates. We o?er an easily-implemented correction and correct asymptotic standard errors. We illustrate these with Monte Carlo experiments and empirical examples using data from the US Consumer Expenditure Survey (CE) and the Panel Study of Income Dynamics (PSID).
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Working Paper: Regression with an imputed dependent variable (2019)
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