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 tobacco control policies while addressing major methodological and data limitations...

The four-parameter generalized beta distribution of the second kind (GBII) has been proposed for modelling insurance losses with heavy-tailed features. The aim of this paper is to present a parametric composite GBII regression modelling by splicing two GBII distributions using mode matching...

In this paper, we propose a new approach to the estimation of social networks and we apply it to the estimation of productivity spillovers in the U.S. Congress. Social networks such as the social connections among lawmakers are not generally directly observed, they can be recovered only using...

We provide nonparametric quantile regressions to test for autocorrelation patterns for weekly and monthly stock returns. We test in four developed markets (North America, Europe, Japan, and Asia without Japan) and five market-size portfolios. We find greater heteroskedasticity for the...

The standard Zipf regression involves a linear relation between the natural logs of the rank and the natural logs of a score on a certain variable. If there are measurement errors in the scores, then the regressor is endogenous and renders Ordinary Least Squares inappropriate. Instrumental...

We provide a new theory for nodewise regression when the residuals from a tted factor model areused. We apply our results to the analysis of the consistency of Sharpe Ratio estimators when there are many assets in a portfolio. We allow for an increasing number of assets as well as time...

The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent of machine learning techniques in the discriminatory phase...

We provide a justification for why, and when, endogeneity will not cause bias in the interpretation of the coefficients in a regression model. This technique can be a viable alternative to, or even used alongside, the instrumental variable method. We show that when performing any comparative...

This paper employs a meta-regression analysis of 473 estimates from 15 studies to take stock of the empirical literature on Chinese aid effectiveness. After accommodating publication selection bias, we find that, on average, Beijing’s foreign assistance has had a positive impact on economic...

We revisit classical asymptotics when testing for a structural break in linear regression models by obtaining the limit theory of residual-based and Wald-type processes. First, we establish the Brownian bridge limiting distribution of these test statistics. Second, we study the asymptotic...