This paper presents a counter-factual model identifying Average Treatment Effects (ATEs) by Conditional Mean Independence when externality (or neighbourhood) effects are incorporated within the traditional potential outcome model. As such, it tries to generalize the usual approach, widely used...

By starting from the consideration that non-profit organizations cover a significant re-distributive function beside that of governmental agencies, the paper questions why government prefers to finance via transfers private entities likewise lucrative and non-lucrative entities rather than...

This working paper uses machine learning to identify Cleantech companies in the Orbis database, based on self-declared business descriptions. Identifying Cleantech companies is challenging, as there is no universally accepted definition of what constitutes Cleantech. This novel approach allows...

We present a Super-Learning Machine (SLM) to predict economic outcomes which improves prediction (i) by cross-validated optimal tuning, (ii) by comparing/combining results from different learners. Our application to a labor economics dataset shows that different learners may behave differently....

The relationship between decentralization and the quality of governments is one of the core issues of decentralization studies. This paper aims to make two contributions to this research. Firstly, we conduct an empirical analysis at the local level, covering 174 regions across the European...

This paper presents an original econometric model for estimating a dose-response function through a regression approach when: (i) treatment is continuous, (ii) individuals may react heterogeneously to observable confounders, and (iii) selection-into-treatment may be potentially endogenous. After...

This paper presents a counter-factual model identifying Average Treatment Effects (ATEs) by Conditional Mean Independence when externality (or neighbourhood) effects are incorporated within the traditional potential outcome model. As such, it tries to generalize the usual approach, widely used...

Many countries have taken non-pharmaceutical interventions (NPIs) to contain the spread of the coronavirus (COVID-19) and push the recovery of national economies. This paper investigates the effect of these control measures by comparing five selected countries, China, Italy, Germany, the United...

Reweighting is a popular statistical technique to deal with inference in presence of a nonrandom sample. In the literature, various reweighting estimators have been proposed. This paper presents the author-written Stata routine treatrew, which implements the reweighting on the propensity-score...

In recent years, much interest has focused on network analysis. This study presents and applies to real data a new user-written Stata command called datanet, which facilitates the dataset organization for the purpose of network analysis. Given a fixed number of units (or nodes) belonging to the...