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What is the value of knowing the propensity score for estimating average treatment effects?
Froelich, Markus - School of Economics and Political Science, Universität … - 2002
Propensity score matching is widely used in treatment evaluation to estimate average treatment effects. Nevertheless …
Persistent link: https://www.econbiz.de/10005797660
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Nonparametric IV estimation of local average treatment effects with covariates
Froelich, Markus - School of Economics and Political Science, Universität … - 2002
In this paper nonparametric instrumental variable estimation of local average treatment effects (LATE) is extended to incorporate confounding covariates. Estimation of local average treatment effects is appealing since their identification relies on much weaker assumptions than the...
Persistent link: https://www.econbiz.de/10005453938
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A generalization of the balancing property of the propensity score
Froelich, Markus - School of Economics and Political Science, Universität … - 2002
Propensity score matching is a nonparametric technique frequently used for estimating average treatment effects. Yet … its applicability is not confined to treatment evaluation. In this paper the propensity score property is generalized to … the setting of selection on unobservables. It is shown that propensity score matching can be used to decompose effects due …
Persistent link: https://www.econbiz.de/10005453940
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Programme Evaluation with Multiple Treatments
Froelich, Markus - School of Economics and Political Science, Universität … - 2002
This paper reviews the main identification and estimation strategies for microeconometric policy evaluation. Particular … nonparametric matching and weighting estimators of the average treatment effects and their properties are examined. …
Persistent link: https://www.econbiz.de/10005696723
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Regression discontinuity design with covariates
Frölich, Markus - School of Economics and Political Science, Universität … - 2007
In this paper, the regression discontinuity design (RDD) is generalized to account for differences in observed covariates X in a fully nonparametric way. It is shown that the treatment effect can be estimated at the rate for one-dimensional nonparametric regression irrespective of the dimension...
Persistent link: https://www.econbiz.de/10005200689
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A Note on the Relation of Weighting and Matching Estimators
Lechner, Michael - School of Economics and Political Science, Universität … - 2007
This paper compares the inverse-probability-of-selection-weighting estimation principle with the matching principle and … derives conditions for weighting and matching to identify the same and the true distribution, respectively. This comparison …
Persistent link: https://www.econbiz.de/10005200691
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The Effect of Disability on Labour Market Outcomes in Germany: Evidence from Matching
Lechner, Michael; Vazquez-Alvarez, Rosalia - School of Economics and Political Science, Universität … - 2003
status on labour market outcomes using matching methods associated with treatment effect techniques for program evaluation …
Persistent link: https://www.econbiz.de/10005200669
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Anchoring Bias and Covariate Nonresponse
Vazquez-Alvarez, Rosalia - School of Economics and Political Science, Universität … - 2003
Non-random item nonreponse makes identification if parameters problematic. Such nonresponse can occur with respect to both dependent and conditioning variables. A method often used to reduce nonresponse is that of adding unfolding brackets as follow up to open-ended questions. With these,...
Persistent link: https://www.econbiz.de/10005200672
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User-Friendly Parallel Computations with Econometric Examples
Creel, Michael - Society for Computational Economics - SCE - 2005
This paper shows how a high level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of...
Persistent link: https://www.econbiz.de/10005343007
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Density Estimation and Combination under Model Ambiguity
D'Amico, Stefania - Society for Computational Economics - SCE - 2004
This paper proposes a method for estimating the probability density of a variable of interest in the presence of model ambiguity. In the first step, each candidate parametric model is estimated minimizing the Kullback-Leibler "distance" (KLD) from a reference nonparametric density estimate....
Persistent link: https://www.econbiz.de/10005345310