TY - JOUR

T1 - msreg

T2 - A command for consistent estimation of linear regression models using matched data

AU - Hirukawa, Masayuki

AU - Liu, Di

AU - Prokhorov, Artem

N1 - Publisher Copyright: © StataCorp LLC 2021.

PY - 2021/3

Y1 - 2021/3

N2 - 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 describe 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.

AB - 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 describe 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.

KW - bias correction

KW - linear regression

KW - matching estimation

KW - msreg

KW - st0630

UR - http://www.scopus.com/inward/record.url?scp=85103596135&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/3b3bbe57-4dcd-38bc-af46-d5809c324f5c/

U2 - 10.1177/1536867x211000008

DO - 10.1177/1536867x211000008

M3 - Review article

AN - SCOPUS:85103596135

VL - 21

SP - 123

EP - 140

JO - Stata Journal

JF - Stata Journal

SN - 1536-867X

IS - 1

ER -