首页 | 本学科首页   官方微博 | 高级检索  
     


Matching estimators and optimal bandwidth choice
Authors:Markus?Fr?lich  author-information"  >  author-information__contact u-icon-before"  >  mailto:markus.froelich@unisg.ch"   title="  markus.froelich@unisg.ch"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author
Affiliation:(1) University College London and University of St. Gallen, Bodanstrasse 8, CH-9000 St. Gallen, Switzerland;(2) Institute for the Study of Labor (IZA), Bonn
Abstract:Optimal bandwidth choice for matching estimators and their finite sample properties are examined. An approximation to their MSE is derived, as a basis for a plug-in bandwidth selector. In small samples, this approximation is not very accurate, though. Alternatively, conventional cross-validation bandwidth selection is considered and performs rather well in simulation studies: Compared to standard pair-matching, kernel and ridge matching achieve reductions in MSE of about 25 to 40%. Local linear matching and weighting perform poorly. Furthermore, the scope for developing better bandwidth selectors seems to be limited for ridge matching, but non-negligible for kernel and local linear matching.
Keywords:covariate adjustment  nonparametric regression  propensity score  missing data  counterfactual  treatment effect
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号