Environmental Policy and Firm Performance in Europe: A Difference-in-Differences Approach with Spillovers with F. Moscone and E. Tosetti
[Draft available at https://arxiv.org/abs/2512.15377]
Abstract: In this paper we investigate the causal impact of the European Union Emissions Trading System, a cap-and-trade scheme limiting greenhouse gas emissions of firms, on their environmental performance. Although previous studies have focused primarily on the effect of the emission cap imposed by the policy, we argue that the trading mechanism creates complex interdependencies among firms that can change the policy's intended effects. We develop a novel Difference-in-Differences approach that disentangles the direct causal effects of the scheme on regulated firms from the indirect spillover effects arising from trading among firms. By incorporating potential interference between treated units, our methodology allows a more comprehensive assessment of the policy's overall effectiveness. Monte Carlo simulations show that our proposed estimators perform well in finite samples, confirming the reliability of our approach. To assess the direct and indirect effects of the scheme, we construct a novel database on emissions of European industrial sites by matching information on treated plants from the European Commission's Community Independent Transaction Log with emission data from the European Pollutant Release and Transfer Register for the years from 2001 to 2017. We find that the scheme reduced emissions only for non-trading plants, but such reduction is entirely offset when accounting for spillovers from trading plants, thus suggesting that the trading mechanism neutralizes the environmental benefits of the policy. Our findings have important implications for the design of future environmental policies and the ongoing evaluation of cap and trade policies.
Distributional Difference-in-Differences Models with Multiple Time Periods
[Draft available at http://arxiv.org/abs/2408.01208]
Abstract: Researchers are often interested in evaluating the impact of a policy on the entire (or specific parts of the) distribution of the outcome of interest. In this paper, I provide a method to recover the whole distribution of the untreated potential outcome for the treated group in non-experimental settings with staggered treatment adoption by generalizing the existing quantile treatment effects on the treated (QTT) estimator proposed by Callaway and Li (2019). Besides the QTT, I consider different approaches that anonymously summarize the quantiles of the distribution of the outcome of interest (such as tests for stochastic dominance rankings) without relying on rank invariance assumptions. The finite-sample properties of the estimator proposed are analyzed via different Monte Carlo simulations. Despite being slightly biased for relatively small sample sizes, the proposed method’s performance increases substantially when the sample size increases.
[Draft available at Department of Economics, Ca' Foscari University of Venice]
Abstract: This paper provides novel evidence on the impact of a cost-containment measure first introduced in Italy in 2007 – Piani di Rientro sanitari (PdRs) – on the quality and efficiency of Regional Health Services (RHSs). Thus far, ten out of twenty-one RHSs have undergone at least one round of PdRs – three managed to exit, but seven are still treated – raising the question of whether cost reduction has had any unintended negative effect on the quality of treated RHSs. I answer this question using the Two-way Mundlak approach. Compared to the classic Two-way Fixed Effects, this method explicitly models the staggered nature of the policy by allowing me to analyze how the treatment effect varies along different dimensions. Further, it allows the estimation of the long-run impact of PdRs. Overall, I find that Piani di Rientro managed to reduce costs. However, cost reduction was not followed by a boost in the efficiency of RHSs and the appropriateness of care provided, as expected by the policymaker. Conversely, reduced budgets made available to regions only resulted in an unintended deterioration in the quality of healthcare services. Results also hold in the long run and are robust to a set of bounded-variations assumptions.🏥