When datasets present long conditional tails on their response variables, algorithms based on Quantile Regression have been widely used to assess extreme quantile behaviors. Value at Risk (VaR) and Conditional Tail Expectation (CTE) allow the evaluation of extreme events to be easily...

This paper is concerned with the problem of variable selection when the marginal effects of signals on the target variable as well as the correlation of the covariates in the active set are allowed to vary over time, without committing to any particular model of parameter instabilities. It poses...

This study examines the effect of oil revenue on the distribution of economic growth across different quantiles in Nigeria over the period from 1981 to 2018. To achieve this objective, the study employs a quantile regression method. For robustness, the quantile regression results are compared...

The article traces the effect of climate policies on the electoral support for governing parties in Sweden. The study uses mixed methods, combining temporal regression discontinuities with a qualitative content text analysis of newspapers. The coded newspaper articles indicate an informed public...

This study investigates how to use regression adjustment to reduce variance in experimental data. We show that the estimators recommended in the literature satisfy an orthogonality property with respect to the parameters of the adjustment. This observation greatly simplifies the derivation of...

A sound understanding of the potency of tobacco control policies is key to tobacco prevention. This study exploits a Smoothed Instrumental Variables Quantile Regression estimator to gauge the effectiveness of these policies while addressing major methodological and data limitations plaguing the...

Estimations of quadratic forms in the parameters of linear models exhibit small-sample bias. The direct computation for a bias correction is not feasible when the number of covariates is large. We propose a bootstrap method for correcting this bias that accommodates different assumptions on the...

In light of widespread evidence of parameter instability in macroeconomic models, many time-varying parameter (TVP) models have been proposed. This paper proposes a nonparametric TVP-VAR model using Bayesian additive regression trees (BART). The novelty of this model stems from the fact that the...

A model of decision-making in a strategic environment is developed, where boundedly rational players care about both implementation complexity costs and computational complexity costs. The choice of strategies is carried out by an algorithm, which itself is seen as the choice of a higher level...

This study adopted a novel quantile regression via moments to explore the effects of military spending on the distribution of economic growth of 14 MENA countries over the period from 1981 to 2019. The method, apart from enabling us to investigate the effects of military spending on the...