Sample size analysis is a key part of the planning phase of any research. So far, however, limited literature focusses on sample size analysis methods for two-sample linear rank tests, although these methods have optimal properties at different distributions. This paper provides a new sample...

Skewness is a well-established statistical concept for continuous and to a lesser extent for discrete quantitative statistical variables. However, for ordered categorical variables almost no literature concerning skewness exists, although this type of variables is common for behavioral,...

When analyzing what determines the efficiency of production, regressing efficiency scores estimated by DEA on explanatory variables has much intuitive appeal. Simar and Wilson (2007) show that this nai͏̈ve two-stage estimation procedure suffers from severe flaws, that render its results, and...

This paper analyzes whether startups offer job opportunities to workers potentially facing labor market problems. It compares the hiring patterns of startups and incumbents in the period 2003 to 2014 using administrative linked employer-employee data for Germany that allow to take the complete...

This paper examines weight loss and the formation of healthy habits through cash rewards in the context of a multi-phase randomized controlled trial involving 700 obese individuals. We find effects of monetary incentives for weight loss of up to EUR 300 on body weight during all experimental...

Methods of systematically balanced treatment allocation for economic experiments, as an alternative to random allocation, are gaining increasing attention in recent years. This paper analyzes the benefits and the limits of a systematic allocation of treatments within a linear model framework....

In the presence of financial frictions, banks' capital position may constrain their ability to provide loans. The banking sector may thus have important feedback effects on the macroeconomy. To shed new light on this issue, we combine two approaches. First, we use microeconomic balance sheet...

Most statistical arbitrage strategies in the academic literature soley rely on price time series. By contrast, alternative data sources are of growing importance for professional investors. We contribute to bridging this gap by assessing the price-predictive value of more than nine million...

We present a comprehensive simulation study to assess and compare the performance of popular machine learning algorithms for time series prediction tasks. Specifically, we consider the following algorithms: multilayer perceptron (MLP), logistic regression, naïve Bayes, k-nearest neighbors,...

Over the past 15 years,there have been a number of studies using text mining for predicting stock market data. Two recent publications employed support vector machines and second-order Factorization Machines, respectively, to this end. However, these approaches either completely neglect...