Arbeitspapier
Policy evaluation of waste pricing programs using heterogeneous causal effect estimation
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: DIW Discussion Papers ; No. 1980
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Model Evaluation, Validation, and Selection
Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
- Thema
-
Waste pricing
Causal effect heterogeneity
Machine learning
Welfare
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Valente, Marica
- Ereignis
-
Veröffentlichung
- (wer)
-
Deutsches Institut für Wirtschaftsforschung (DIW)
- (wo)
-
Berlin
- (wann)
-
2021
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Valente, Marica
- Deutsches Institut für Wirtschaftsforschung (DIW)
Entstanden
- 2021