Utilizing comprehensive firm-level data from 2005 to 2021 across various African nations,
our study investigates the effect of a firm's greenhouse gas (GHG) emissions on its corporate …

The pystacked command implements stacked generalization (Wolpert, 1992, Neural
Networks 5: 241–259) for regression and binary classification via Python's scikit-learn …

This chapter synthesizes and critically reviews the modern instrumental variables (IV)
literature that allows for unobserved heterogeneity in treatment effects (UHTE). We start by …

Utilizing data from the 2016 Vietnam Household Living Standard Survey, we undertake an
empirical investigation into the influence of energy poverty on the health expenditure of …

Abstract “The use of health care claims datasets often encounters criticism due to the
pervasive issues of omitted variables and inaccuracies or mis-measurements in available …

This paper discusses pairing double/debiased machine learning (DDML) with stacking, a
model averaging method for combining multiple candidate learners, to estimate structural …

Abstract The Gender Wage Gap (GWG) is a classic topic in labour economics. Simply put,
how do we explain the observed gap in earnings between men and women? Traditionally …

In this article, we introduce a new command, classifylasso, that implements the classifier-
lasso method (Su, Shi, and Phillips, 2016, Econometrica 84: 2215–2264) to simultaneously …

This paper investigates whether female leaders of firms in developing countries tend to hire
more female workers. We develop a theoretical model in which female leaders increase the …

In an era of increasing data complexity and volume, integrating machine learning (ML) into
economics has become not only relevant but also essential. The advent of Double/Debiased …