Policy evaluation of waste pricing programs using heterogeneous causal effect estimation
利用机器学习方法在准实验环境中研究垃圾按量收费对家庭垃圾产生量和市政成本的异质性影响，发现垃圾需求非线性且政策在三年后降低所有城市的垃圾管理成本。
Using machine learning methods in a quasi-experimental setting, I study the heterogeneous effects of introducing waste prices – unit prices on household unsorted waste disposal – on waste demands and municipal costs. Using a unique panel of Italian municipalities with large variation in prices and observables, I show that waste demands are nonlinear. I find evidence of constant elasticities at low prices, and increasing elasticities at high prices driven by income effects and waste habits before policy. The policy reduces waste management costs in all municipalities after three years of adoption, when prices cause significant reductions in total waste.