msreg: A command for consistent estimation of linear regression models using matched data

Masayuki Hirukawa (), Di Lu () and Artem Prokhorov
Additional contact information
Masayuki Hirukawa: Ryukoku University
Di Lu: StataCorp

Stata Journal, 2021, vol. 21, issue 1, 123-140

Abstract: Economists often use matched samples, especially when dealing with earning data where some observations are missing in one sample and need to be imputed from another sample. Hirukawa and Prokhorov (2018, Journal of Econometrics 203: 344–358) show that the ordinary least-squares estimator using matched samples is inconsistent and propose two consistent estimators. We de- scribe a new command, msreg, that implements these two consistent estimators based on two samples. The estimators attain the parametric convergence rate if the number of continuous matching variables is no greater than four.

Keywords: msreg; bias correction; linear regression; matching estimation (search for similar items in EconPapers)
Date: 2021
Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-1/st0630/
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1177/1536867X211000008

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:v:21:y:2021:i:1:p:123-140

Ordering information: This journal article can be ordered from
http://www.stata-journal.com/subscription.html

DOI: 10.1177/1536867X211000008

Access Statistics for this article

Stata Journal is currently edited by Nicholas J. Cox and Stephen P. Jenkins

More articles in Stata Journal from StataCorp LLC
Bibliographic data for series maintained by Christopher F. Baum () and Lisa Gilmore ().