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Assessing the Causal Effect of Curbside Collection on Recycling Behavior in a Non-randomized Experiment with Self-reported Outcome

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  • Henning Best

    (University of Kaiserslautern)

  • Thorsten Kneip

    (Max Planck Institute for Social Law and Social Policy)

Abstract

This paper aims at identifying the causal effect of reducing behavioral costs of participation in household waste recycling through curbside collection. Using propensity score matching and differences-in-differences estimation with individual-level panel data we estimate the effect of curbside collection, its variation between types of recyclables and sociodemographic background variables, and its elasticity with regard to the distance to collection containers in the bring scheme condition. We argue that in a quasi-experimental setting DD may be systematically upward biased due to the outcome variable being self-reported while DDD may be systematically downward biased in the presence of spillover effects. Accordingly, both estimators can be combined to derive upper and lower bounds of the true effect. We find that a curbside scheme has no effect on paper recycling but increases recycling participation by between 10 and 25% points for plastic and packaging. Moreover, we find systematic treatment effect heterogeneity with regard to pre-treatment distance to collection sites and individual environmental attitudes, but not by socio-demography. The results of our analysis therefore have important implications for effective and cost-efficient implementation of environmental protection policies in urban areas.

Suggested Citation

  • Henning Best & Thorsten Kneip, 2019. "Assessing the Causal Effect of Curbside Collection on Recycling Behavior in a Non-randomized Experiment with Self-reported Outcome," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(4), pages 1203-1223, April.
  • Handle: RePEc:kap:enreec:v:72:y:2019:i:4:d:10.1007_s10640-018-0244-x
    DOI: 10.1007/s10640-018-0244-x
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