caa a22 4500 467896402 CHVBK 20180627160944.0 cr unu---uuuuu 170328e20060601xx s 000 0 eng 10.1007/s00181-005-0019-4 doi (NATIONALLICENCE)springer-10.1007/s00181-005-0019-4 Frölich Markus Department of Economics, University College London, Gower Street, WC1E 6BT, London, UK aut Semiparametric estimation of conditional mean functions with missing data [Elektronische Daten] Combining parametric moments with matching [Markus Frölich] A new semiparametric estimator for estimating conditional expectation functions from incomplete data is proposed, which integrates parametric regression with nonparametric matching estimators. Besides its applicability to missing data situations due to non-response or attrition, the estimator can also be used for analyzing treatment effect heterogeneity and statistical treatment rules, where data on potential outcomes is missing by definition. By combining moments from a parametric specification with nonparametric estimates of mean outcomes in the non-responding population within a GMM framework, the estimator seeks to balance a good fit in the responding population with low bias in the non-responding population. The estimator is applied to analyzing treatment effect heterogeneity among Swedish rehabilitation programmes. Springer-Verlag, 2006 Empirical Economics Physica-Verlag 31/2(2006-06-01), 333-367 0377-7332 31:2<333 2006 31 181 https://doi.org/10.1007/s00181-005-0019-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00181-005-0019-4 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Frölich Markus Department of Economics, University College London, Gower Street, WC1E 6BT, London, UK aut NATIONALLICENCE 773 0- Empirical Economics Physica-Verlag 31/2(2006-06-01), 333-367 0377-7332 31:2<333 2006 31 181 Metadata rights reserved Springer special CC-BY-NC licence nationallicence SWISSBIB 467896402 BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer