This paper questions traditional approaches for testing the day-of-the-week effect on stock returns. We propose an alternative approach based on the closure test principle introduced by Marcus, Peritz and Gabriel (1976), which has become very popular in Biometrics and Medical Statistics. We test...

This article introduces the R package ExtremeBounds to perform extreme bounds analysis (EBA), a sensitivity test that examines how robustly the dependent variable of a regression model is related to a variety of possible determinants. ExtremeBounds supports Leamer's EBA that focuses on the upper...

Recreational services are demanded because they generate benefits. The recreational benefits connected with a destination can be valued based on visitor preferences, which can aid in the formulation of an appropriate Natural Resource Management policy. Environmental and natural resource...

The objective of this paper is to examine the impact of demutualization upon the performance of stock exchanges' in terms of their liquidity as per the share turnover velocity and the returns that are generated from the broad indexes. The impact of demutualization has been examined upon a global...

Women are underrepresented in academia in general and economics in particular. I introduce a test to detect an under-researched form of hiring bias: implicit quotas. I derive a test under the null hypothesis of gender-blind hiring that requires no additional information about individual hires...

Forecasts are useless whenever the forecast error variance fails to be smaller than the unconditional variance of the target variable. This paper develops tests for the null hypothesis that forecasts become uninformative beyond some limiting forecast horizon h. Following Diebold and Mariano (DM,...

Marketing scientists often estimate causal effects using data from pre/post test/control quasi-experimental settings. We propose a new, easy to implement Augmented Difference-in-Differences (ADID) method that complements existing approaches to estimate the average treatment effect on the treated...

We provide a simple distribution regression estimator for treatment effects in the difference-in-differences (DiD) design. Our procedure is particularly useful when the treatment effect differs across the distribution of the outcome variable. Our proposed estimator easily incorporates covariates...