Open Access
Regression with an imputed dependent variable
Loading...
Files
Regression_with_an_imputed_dependent_variable_2022.pdf (1.17 MB)
Full-text in Open Access (Published Version)
License
Attribution 4.0 International
Access Rights
Cadmus Permanent Link
Full-text via DOI
ISBN
ISSN
0883-7252; 1099-1255
Issue Date
Type of Publication
Keyword(s)
LC Subject Heading
Other Topic(s)
EUI Research Cluster(s)
Initial version
Published version
Succeeding version
Preceding version
Published version part
Earlier different version
Initial format
Citation
Journal of applied econometrics, 2022, Vol. 37, No. 7, pp. 1277-1294
Cite
CROSSLEY, Thomas Fraser, LEVELL, Peter, POUPAKIS, Stavros, Regression with an imputed dependent variable, Journal of applied econometrics, 2022, Vol. 37, No. 7, pp. 1277-1294 - https://hdl.handle.net/1814/74920
Abstract
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 offer a consistent and easily implemented two-step estimator, “rescaled regression prediction.” We derive the correct asymptotic standard errors for this estimator and demonstrate its relationship to alternative approaches. We illustrate with empirical examples using data from the US Consumer Expenditure Survey (CE) and the Panel Study of Income Dynamics (PSID).
Table of Contents
Additional Information
Published online: 29 September 2022

