When a sample combines data from two or more groups, multivariate regression yields a matrix-weighted average of the group-specific coefficient vectors. However, it is possible that the weighted average of a specific coefficient falls outside the range of the group-specific coefficients, and it...

In this paper, we propose the Fama-Macbeth (FM) regression with sparsity, which is named FM-LASSO. We impose a l2 penalty across time to make sure that the factors are sparse. The factors in our model are shrinked with consistency. If a factor is 0 once, then it is always 0. If a factor is not...

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...