Practical Procedures to Deal with Common Support Problems in Matching Estimation
Journal
Econometric Reviews
ISSN
0747-4938
Type
journal article
Date Issued
2019
Author(s)
Abstract
This paper assesses the performance of common estimators adjusting for differences in covariates, like matching and regression, when faced with so-called common support problems. It also shows how different procedures suggested in the literature to tackle common support problems affect the properties of such estimators. Based on an Empirical Monte Carlo simulation design, a lack of common support is found to increase the root mean squared error (RMSE) of all investigated parametric and semiparametric estimators. Dropping observa¬tions that are off support usually improves their performance, although the amount of improvement depends on the particular method used.
Language
English
Keywords
Empirical Monte Carlo Study
matching estimation
regression
common support
outlier
small sample performance.
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Taylor & Francis
Volume
38
Number
2
Start page
193
End page
207
Pages
15
Subject(s)
Eprints ID
238807
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Name
Practical Procedures to Deal with Common Support Problems in Matching Estimation.pdf
Size
1.15 MB
Format
Adobe PDF
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