Curbside Recycling: Waste Resource or Waste of Resources?
AbstractIn this paper, we estimate the social net benefits of curbside recycling. Benefits are estimated using survey data on household willingness to pay (WTP) from over 4,000 households across 40 western U.S. cities. We calibrate WTP for hypothetical bias using an experimental design that contrasts stated and revealed preferences. Cost estimates are compiled from previous studies by the U.S. Environmental Protection Agency, the Institute for Local Self Reliance, as well as from in-depth interviews with recycling coordinators in our sampled cities. Remarkably, we find that the estimated mean social net benefit of curbside recycling is almost exactly zero. Therefore, the decision of whether to implement or maintain a curbside recycling program (CRP) must be done on a city-by-city basis.
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Bibliographic InfoPaper provided by Utah State University, Department of Economics in its series Working Papers with number 2003-13.
Length: 42 pages
Date of creation: Nov 2003
Date of revision:
curbside recycling; willingness to pay; social net benefits; hypothetical bias; calibration;
Other versions of this item:
- David Aadland & Arthur J. Caplan, 2006. "Curbside recycling: Waste resource or waste of resources?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 25(4), pages 855-874.
- David Aadland & Arthur J. Caplan, 2003. "Curbside Recycling: Waste Resource or Waste of Resources?," Others 0310001, EconWPA.
- Aadland, David & Caplan, Arthur J., 2004. "Curbside Recycling: Waste Resource Or Waste Of Resources?," 2004 Annual meeting, August 1-4, Denver, CO 19971, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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