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The Value of Knowing the Propensity Score for Estimating Average Treatment Effects
Rothe, Christoph - 2016
In a treatment effect model with unconfoundedness, treatment assignments are not only independent of potential outcomes given the covariates, but also given the propensity score alone. Despite this powerful dimension reduction property, adjusting for the propensity score is known to lead to an...
Persistent link: https://www.econbiz.de/10012988566
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Quantile Treatment Effects in the Regression Discontinuity Design : Process Results and Gini Coefficient
Frölich, Markus - 2014
This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design. The distributional impacts of social programs such as welfare, education, training programs and unemployment insurance are of large interest to economists. QTE are an...
Persistent link: https://www.econbiz.de/10013069679
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A Note on Parametric and Nonparametric Regression in the Presence of Endogenous Control Variables
Frölich, Markus - 2021
This note argues that nonparametric regression not only relaxes functional form assumptions vis-a-vis parametric regression, but that it also permits endogenous control variables. To control for selection bias or to make an exclusion restriction in instrumental variables regression valid,...
Persistent link: https://www.econbiz.de/10013317591
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Unconditional Quantile Treatment Effects Under Endogeneity
Frölich, Markus; Melly, Blaise - 2021
This paper develops IV estimators for unconditional quantile treatment effects (QTE) when the treatment selection is endogenous. In contrast to conditional QTE, i.e. the effects conditional on a large number of covariates X, the unconditional QTE summarize the effects of a treatment for the...
Persistent link: https://www.econbiz.de/10013324857
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Quantile Treatment Effects in the Regression Discontinuity Design
Frölich, Markus; Melly, Blaise - 2021
This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design (RDD) and proposes simple estimators. Quantile treatment effects are a very helpful tool to characterize the effects of certain interventions on the outcome distribution. The...
Persistent link: https://www.econbiz.de/10013325034
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A Martingale Representation for Matching Estimators
Abadie, Alberto - 2009
Matching estimators are widely used in statistical data analysis. However, the distribution of matching estimators has … matching estimators. This representation allows the use of martingale limit theorems to derive the asymptotic distribution of … matching estimators. As an illustration of the applicability of the theory, we derive the asymptotic distribution of a matching …
Persistent link: https://www.econbiz.de/10012764230
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New Insights on Unemployment Duration andPost Unemployment Earnings in Germany:Censored Box-Cox Quantile Regression at Work
Fitzenberger, Bernd; Wilke, Ralf A. - Forschungsinstitut zur Zukunft der Arbeit <Bonn> - 2007
In light of nonstationary search theory (van den Berg, 1990), this paper estimates the effectsof benefit entitlement periods and the size of unemployment benefits on unemploymentdurations and post-unemployment earnings in West Germany...
Persistent link: https://www.econbiz.de/10005863253
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A data-driven selection of an appropriate seasonal adjustment approach
Webel, Karsten - 2016
Recent releases of X-13ARIMA-SEATS and JDemetra+ enable their users to choose between the non-parametric X-11 and the parametric ARIMA model-based approach to seasonal adjustment for any given time series without the necessity of switching between different software packages. To ease the...
Persistent link: https://www.econbiz.de/10011452778
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A Simple Method to Visualize Results in Nonlinear Regression Models
Henderson, Daniel J. - 2012
A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...
Persistent link: https://www.econbiz.de/10013099782
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Evaluating Nonexperimental Estimators for Multiple Treatments : Evidence from Experimental Data
Flores, Carlos A. - 2009
This paper assesses the effectiveness of unconfoundedness-based estimators of mean effects for multiple or multivalued treatments in eliminating biases arising from nonrandom treatment assignment. We evaluate these multiple treatment estimators by simultaneously equalizing average outcomes among...
Persistent link: https://www.econbiz.de/10013155543