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...

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...

This paper presents a parametric counter-factual model identifying average treatment effects (ATEs) by conditional mean independence when externality (or neighborhood) effects are incorporated within the traditional Rubin-potential outcome model. As such, it tries to generalize the usual...

Abstract not available.

Abstract not available.

This presentation presents a parametric counterfactual model identifying average treatment effects (ATEs) by conditional mean independence when externality (or neighborhood) effects are incorporated within the traditional Rubin potential-outcome model. As such, it tries to generalize the usual...

Following in the footsteps of the Stata user-written command ivtreatreg, recently proposed by the author (Cerulli, 2012), the paper presents a new Stata routine— contreatreg—for estimating a Dose Response Treatment Model under continuous treatment endogeneity and heterogeneous...

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...