Betas from return regressions are commonly used to measure systematic financial market risks. "Good" beta measurements are essential for a range of empirical inquiries in finance and macroeconomics. We introduce a novel econometric framework for the nonparametric estimation of time-varying betas...

This study aims to investigate the sociodemographic determinants of school attendance in Mauritania. The study utilizes the national household survey 2019 and a logistic regression econometric model is used to analyze the association between sociodemographic variables and the dependent variable...

This is the first paper about the existence of non-linear relations between auditor quality and tax avoidance (TA), using a quantile regression approach. We find that the relation between auditor quality and TA depends on the degree of TA. Specifically, for greater tax aggressive firms, being...

This research paper focuses on investigating the macroeconomic determinants of capital market performance in South Asia, using the Arbitrage Pricing Theory and multiple panel regression for the period of 2010-2019.While previous studies have explored the impact of macroeconomic variables on the...

Recent papers show that coefficients in two-way fixed effect (TWFE) and event study (ES) regressions can hardly be interpreted as the average treatment effect, depending on heterogeneity in the treatment effects. This paper proposes to contrast estimates with and without weighting to detect...

We develop an estimation procedure of multiple regression function and its derivatives (formarginal e¤ects) based on multivariate maximum entropy (ME) density estimation. The relevantmoments and cross moments conditions are selected to be inlcuded in the inferred distribution.Finite sample and...

We demonstrate how mothers, fathers, and 15–17-year-old students alter their schedules around the K-12 academic year. Using regression discontinuity (RDD) methods, combined with dates on school year start and end dates by locality, we document several notable results. First, mothers are...

A unified approach to regularize maximum likelihood models for linear, multivariate normal, logistic (binomial and polytomous), Poisson, and Cox proportional hazards based on between-predictor correlation is presented. Regularization is accomplished via penalization based on the strength of...

Covariates in regressions may be linked to each other on a network. Knowledge of the network structure can be incorporated into regularized regression settings via a network penalty term. However, when it is unknown whether the connection signs in the network are positive (connected covariates...

This paper introduces a novel simulation-based filtering method for general state space models. It allows for the computation of time-varying conditional means, quantiles, and modes, but also for the prediction of latent variables in general. The method relies on generating artificial samples of...