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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

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

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

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

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

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

Top incomes, heavy tails, and rank-size regressions

Schluter, Christian - In: Econometrics 6 (2018) 1, pp. 1-16

In economics, rank-size regressions provide popular estimators of tail exponents of heavy-tailed distributions. We discuss the properties of this approach when the tail of the distribution is regularly varying rather than strictly Pareto. The estimator then over-estimates the true value in the...

Persistent link: https://www.econbiz.de/10011995211

An overview of modified semiparametric memory estimation methods

Busch, Marie; Sibbertsen, Philipp - In: Econometrics 6 (2018) 1, pp. 1-21

Several modified estimation methods of the memory parameter have been introduced in the past years. They aim to decrease the upward bias of the memory parameter in cases of low frequency contaminations or an additive noise component, especially in situations with a short-memory process being...

Persistent link: https://www.econbiz.de/10011995214

Permutation entropy and information recovery in nonlinear dynamic economic time series

Henry, Miguel; Judge, George G. - In: Econometrics 7 (2019) 1, pp. 1-16

The focus of this paper is an information theoretic-symbolic logic approach to extract information from complex economic systems and unlock its dynamic content. Permutation Entropy (PE) is used to capture the permutation patterns-ordinal relations among the individual values of a given time...

Persistent link: https://www.econbiz.de/10012696225

Reducing the bias of the smoothed log periodogram regression for financial high-frequency data

Reschenhofer, Erhard; Mangat, Manveer Kaur - In: Econometrics 8 (2020) 4, pp. 1-16

For typical sample sizes occurring in economic and financial applications, the squared bias of estimators for the memory parameter is small relative to the variance. Smoothing is therefore a suitable way to improve the performance in terms of the mean squared error. However, in an analysis of...

Persistent link: https://www.econbiz.de/10012696303

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