Arbeitspapier
Regression with an imputed dependent variable
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 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).
- Sprache
-
Englisch
- Erschienen in
-
Series: ISER Working Paper Series ; No. 2019-07
- Klassifikation
-
Wirtschaft
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
Estimation: General
Macroeconomics: Consumption; Saving; Wealth
- Thema
-
Imputation
Measurement error
Consumption
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Crossley, Thomas F.
Levell, Peter
Poupakis, Stavros
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Essex, Institute for Social and Economic Research (ISER)
- (wo)
-
Colchester
- (wann)
-
2019
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Crossley, Thomas F.
- Levell, Peter
- Poupakis, Stavros
- University of Essex, Institute for Social and Economic Research (ISER)
Entstanden
- 2019
Ähnliche Objekte (12)
Regression with an imputed dependent variable
Regression with an imputed dependent variable
Robust estimation in nonlinear regression and limited dependent variable models
Regression quantiles with errors-in-variables
Instrumental variables regression
What do instrumental variable models deliver with discrete dependent variables?
Bayesian Inference in Regression Models with Ordinal Explanatory Variables
Variable selection in Cox regression models with varying coefficients
Inference in Regression Discontinuity Designs with a Discrete Running Variable
Estimating derivatives in nonseparable models with limited dependent variables
Analysis of discrete dependent variable models with spatial correlation
Kernel Dependent Functions in Nonparametric Regression with Fractional Time Series Errors
Regression with an imputed dependent variable
Regression with an imputed dependent variable
Robust estimation in nonlinear regression and limited dependent variable models
Regression quantiles with errors-in-variables
Instrumental variables regression
What do instrumental variable models deliver with discrete dependent variables?
Bayesian Inference in Regression Models with Ordinal Explanatory Variables
Variable selection in Cox regression models with varying coefficients
Inference in Regression Discontinuity Designs with a Discrete Running Variable
Estimating derivatives in nonseparable models with limited dependent variables
Analysis of discrete dependent variable models with spatial correlation
Kernel Dependent Functions in Nonparametric Regression with Fractional Time Series Errors
Regression with an imputed dependent variable
Regression with an imputed dependent variable
Robust estimation in nonlinear regression and limited dependent variable models
Regression quantiles with errors-in-variables
Instrumental variables regression
What do instrumental variable models deliver with discrete dependent variables?
Bayesian Inference in Regression Models with Ordinal Explanatory Variables
Variable selection in Cox regression models with varying coefficients
Inference in Regression Discontinuity Designs with a Discrete Running Variable
Estimating derivatives in nonseparable models with limited dependent variables
Analysis of discrete dependent variable models with spatial correlation