Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/248483 
Autor:innen: 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
DIW Discussion Papers No. 1980
Verlag: 
Deutsches Institut für Wirtschaftsforschung (DIW), Berlin
Zusammenfassung: 
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 social welfare. First, using a unique panel of Italian municipalities with large variation in prices and observables, I show that waste demands are nonlinear. - find evidence of constant elasticities at low prices, and increasing elasticities at high prices driven by income effects and waste habits before policy. Second, I estimate policy impacts on pollution and municipal management costs, and compute the overall social cost savings for each municipality. Social welfare effects are positive for all municipalities after three years of adoption, when waste prices cause significant waste avoidance.
Schlagwörter: 
Waste pricing
Causal effect heterogeneity
Machine learning
Welfare
JEL: 
C14
C21
C52
Q53
Dokumentart: 
Working Paper

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