Estimation of Models with Multiple-Valued Explanatory Variables

35 Pages Posted: 3 Apr 2015 Last revised: 12 Jun 2017

See all articles by Alexandre Poirier

Alexandre Poirier

Georgetown University - Department of Economics

Nicolas Ziebarth

University of Iowa

Date Written: June 11, 2017

Abstract

We study estimation and inference when there are multiple values ("matches") for the explanatory variables and only one of the matches is the correct one. This problem arises often when two datasets are linked together on the basis of information that does not uniquely identify regressor values. We offer a set of two intuitive conditions which ensure consistent inference using the average of the possible matches in a linear framework. The first condition is the exogeneity of the false match with respect to the regression error. The second condition is a notion of exchangeability between the true and false matches. Conditioning on the observed data, the probability that each match is correct is completely unrestricted. We perform a Monte Carlo study to investigate the estimator's finite-sample performance relative to others proposed in the literature. Finally, we provide an empirical example revisiting a main area of application: the measurement of intergenerational elasticities in income.

Keywords: Statistical Matching, Data Combination, Regression Methods, Intergenerational Elasticities

JEL Classification: C20, C50, N81

Suggested Citation

Poirier, Alexandre and Ziebarth, Nicolas, Estimation of Models with Multiple-Valued Explanatory Variables (June 11, 2017). Available at SSRN: https://ssrn.com/abstract=2586863 or http://dx.doi.org/10.2139/ssrn.2586863

Alexandre Poirier (Contact Author)

Georgetown University - Department of Economics ( email )

Washington, DC 20057
United States

Nicolas Ziebarth

University of Iowa ( email )

341 Schaeffer Hall
Iowa City, IA 52242-1097
United States

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