Randomized controlled trials (RCTs) are increasingly prominent in economics, with pre-registration and pre-analysis plans (PAPs) promoted as important in ensuring the credibility of findings. We investigate whether these tools reduce the extent of p-hacking and publication bias by collecting and...

Amazon Mechanical Turk is a very widely-used tool in business and economics research, but how trustworthy are results from well-published studies that use it? Analyzing the universe of hypotheses tested on the platform and published in leading journals between 2010 and 2020 we find evidence of...

Amazon's Mechanical Turk is a very widely-used tool in business and economics research, but how trustworthy are results from well-published studies that use it? Analyzing the universe of hypotheses tested on the platform and published in leading journals between 2010 and 2020 we find evidence of...

In this paper, we examine the relationship between p-hacking and datasharing policies for published articles. We collect 38,876 test statistics from 1,106 articles published in leading economic journals between 2002-2020. While a data-sharing policy increases the provision of research data to...

Eingliederungszuschüsse sind zeitlich befristete Lohnkostenzuschüsse, die Arbeitgeber bei der Einstellung von Personen mit eingeschränkter Vermittelbarkeit erhalten können. In Deutschland sind sie ein wichtiges Instrument der aktiven Arbeitsmarktpolitik. Dieser Beitrag nutzt Prozessdaten der...

We investigate the finite sample properties of a large number of estimators for the average treatment effect on the treated that are suitable when adjustment for observable covariates is required, like inverse probability weighting, kernel and other variants of matching, as well as different...

Summary This paper estimates the effects of several German labor market programs - starting in March 2003 - on the employment outcomes of participants using propensity score matching. The main objective is to analyze how estimated average treatment effects vary with the choice of the...

Using a simulation design that is based on empirical data, a recent study by Huber, Lechner and Wunsch (2012) finds that distance-weighted radius matching with bias adjustment as proposed in Lechner, Miquel and Wunsch (2011) is competitive among a broad range of propensity score-based estimators...

We investigate the finite sample properties of a large number of estimators for the average treatment effect on the treated that are suitable when adjustment for observable covariates is required, like inverse pro¬bability weighting, kernel and other variants of matching, as well as different...