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

Dieses Objekt wird bereitgestellt von:
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

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