This paper provides an introduction to Double/Debiased Machine Learning (DML). DML is a general approach to performing inference about a target parameter in the presence of nuisance functions: objects that are needed to identify the target parameter but are not of primary interest. Nuisance...

As investors increasingly use Environmental, Social, and Governance (ESG) criteria, a key challenge remains: ESG data is typically reported annually, while financial markets move much faster. This study investigates whether incorporating annual ESG scores can improve monthly stock return...

Debate persists over whether classical econometric or modern machine learning (ML) approaches provide superior forecasts for volatile monthly price series. Despite extensive research, no systematic cross-domain comparison exists to guide model selection across diverse asset types. In this study,...

Abadie, Diamond, and Hainmueller's (2015) analysis of the costs of German reunification is a flagship study for the "synthetic control method" (SCM). Yet three issues can be identified. First, Abadie et al. remove countries that performed poorly in the 1990s from their donor pool, potentially...

This document introduces the R library estimateW to estimate spatial weight matrices for Bayesian spatial econometric panel models. The approach focuses on spatial weights that are binary prior to row-standardization. However, unlike recent literature our approach requires no strong a priori...

Design-based econometrics, centred on average treatment effects in the potential-outcomes framework, treats causal effects as population-level expectations under hypothetical interventions and thereby offers an expectation-based, mechanism-agnostic conception of causality. This conception is...

The COVID-19 pandemic generated highly heterogeneous economic effects across territories, reflecting differences in local production structures and spatial organization. This paper examines the geography of short-run economic fragility during the first wave of the pandemic by identifying...

This textbook introduces readers to the economic dynamics of growth and distribution and presents dynamic mathematical tools essential to understanding various economic phenomena. From ordinary differential equations to partial differential equations and stochastic differential equations, it...

The sport economic literature relies on the city size to proxy for the size of the home market of sports teams. This paper seeks to clarify whether the commonly used definition for home market size in sports economics is actually a valid measure for revenue potential in the modern digital age....

We use a rigorous three-stage many-analysts design to assess how different researcher decisions—specifically data cleaning, research design, and the interpretation of a policy question—affect the variation in estimated treatment effects. A total of 146 research teams each completed the same...

Star variables, such as potential output and the neutral real interest rate, are fundamental to economic policymaking but challenging to identify due to their latent nature. Buncic, Pagan, and Robinson (2023) highlight the difficulty of identifying star variables within short macroeconomic...

Recent rises in macroeconomic volatility have prompted the introduction of quantile vector autoregression (QVAR) models to forecast macroeconomic risk. This paper provides an extensive evaluation of the predictive performance of QVAR models in a pseudo-out-of-sample experiment spanning 112...

This article provides empirical researchers with an introduction and guide to research designs based on variation in judge and examiner tendencies to administer treatments or other interventions. We review the basic theory behind the research design, outline the assumptions under which the...

In this paper, we address the identification and estimation of insurance models where insurees have private information about their risk and risk aversion. The model includes random damages and allows for several claims, while insurees choose from a finite number of coverages. We show that the...

In this study, we employ a newly developed time series econometric approach to investigate the development in crime rates in various members states of the European Union (EU) between 1968 and 2019. We propose a panel data model with stochastically time-varying factors that also includes...

The most widely used textbooks on Introductory Econometrics conflate three distinct population parameters: the population regression function (PRF), the conditional expectation function (CEF), and the causal effect. They also incorrectly suggest, and sometimes state, that the Conditional Mean...

The most widely used textbooks today conflate three distinct population parameters: the population regression function (PRF), the conditional expectation function (CEF), and the causal effect. They also incorrectly suggest, and sometimes state, that the Conditional Mean Zero assumption implies...

The FIDELIO (Fully Interregional Dynamic Econometric Long-term Input-Output) model is a flexible, multi-region, multi-sector, input-output model developed by the Joint Research Centre to assess socio-economic and environmental impacts of EU trade and industrial policies. It covers 45 countries,...

The paper contains five parts - a theory about entrepreneurial choice under uncertainty, a formal econometric structure for a test, the test, an appraisal of the test, and a description of the data generating process. Here, an entrepreneur is an individual who manages a firm that produces one...