A correlation between regressors and disturbances presents challenging problems in linear regression. Issues like omitted variables, measurement error and simultaneity render ordinary least squares (OLS) biased and inconsistent. In the context of heteroscedastic linear regression, this note...

Purpose: To assess the predictive validity of Lott and Varney's (2022) ordinary least squares (OLS) multiple regression (MRA) causal model of the effect of immigrant population numbers, as a proportion of the total population, on the homicide victim rate for 31 European countries.Methods: The...

We provide necessary and sufficient conditions for expected utility and risk-averse expected utility to rationalize behavior when the decision maker faces linear probability-prize tradeoffs. The setting subsumes those proposed in Andreoni and Harbaugh (2009) and Crosetto and Filippin (2013). The...

The analysis of public debt determinants is well documented in the literature. However, previous studies give more focus to the economic determinants neglecting the role played by socio-political factors. The purpose of this study is to fill that gap observed in the literature by investigating...

This study examines the factors affecting Ethiopia's private bank performance. The study followed a causational research design employing data from 2010-to 2021. The study unit of analysis is Eleven private banks in Ethiopia. The study also uses PLS-SEM with Gaussian copula (GC) estimation...

We develop a methodology for estimating and testing the effect of anomalies in conditional asset pricing models when premia are time-varying. Our method, which builds on the two-pass methodology, is developed for ordinary and weighted least-squares estimation, considering both cases of correct...