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on Discrete Choice Models |
| By: | Berck, Peter B; Sears, Molly; Taylor, Rebecca; Trachtman, Carly; Villas-Boas, Sofia |
| Abstract: | We estimate consumer preferences and willingness to pay for current beverage container recycling methods, including curbside pick-up services, drop-off at government-subsidized recycling centers, and drop-off at non-subsidized centers. Using a representative online and telephone survey of California households, we estimate a discrete choice model that identifies the key attributes explaining consumers’ beverage container disposal decisions: the refund amount (paid to consumers only if they recycle at drop-off centers), the volume of recyclable material generated by the household, and the effort associated with bringing recyclable materials to recycling centers. Additionally, we use counterfactual policy analy- sis to show that increasing the refund amount increases overall recycling rates, with the largest changes in consumer surplus accruing to inframarginal consumers, who are on the boundary between taking containers to recycling centers and recycling using curbside pick-up, namely white and higher income consumers. Conversely, we show that eliminating government-subsidized drop-off centers does not significantly alter consumer surplus for any major demographic group, and has little impact on recycling rates. |
| Keywords: | Social and Behavioral Sciences, recycling, discrete choice, deposit-refund program, consumer convenience, Bottle Bill |
| Date: | 2020–09–22 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:agrebk:qt3cj7r9nh&r=all |
| By: | Yu, Luqing; Gao, Zhifeng |
| Keywords: | Agribusiness, Research Methods/Statistical Methods, Marketing |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea20:304625&r=all |
| By: | Fan, Yubing; Ma, Wanglin |
| Keywords: | Community/Rural/Urban Development, Resource/Energy Economics and Policy, Research Methods/Statistical Methods |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea20:304661&r=all |
| By: | Lai, Yufeng; Yue, Chengyan |
| Keywords: | Agribusiness, Demand and Price Analysis, Research Methods/Statistical Methods |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea20:304328&r=all |
| By: | Martin Boyer (HEC Montréal - HEC Montréal); Philippe de Donder (TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Claude Fluet (ULaval - Université Laval [Québec]); Marie-Louise Leroux (UQAM - Université du Québec à Montréal = University of Québec in Montréal); Pierre-Carl Michaud (HEC Montréal - HEC Montréal) |
| Abstract: | This paper conducts a stated-choice experiment where respondents are asked to rate various insurance products aimed to protect against nancial risks associated with long-term care needs. Using exogenous variation in prices from the survey design and individual cost estimates, these stated-choice probabilities are used to predict market equilibrium for long-term care insurance. Our results are twofold. First, information frictions are pervasive. Second, measuring the welfare losses associated with frictions in a framework that also allows for selection, it is found that information frictions reduce equilibrium take-up and lead to large welfare losses while selection plays little role. |
| Keywords: | Long-term care insurance,adverse selection,stated-preference,health,insurance |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02929780&r=all |
| By: | Jean-Pierre H. DubŽ (University of Chicago - Booth School of Business); Ali Horta su (University of Chicago); Joonhwi Joo (University of Texas at Dallas, Naveen Jindal School of Management, Department of Finance) |
| Abstract: | Although typically overlooked, many purchase datasets exhibit a high incidence of products with zero sales. We propose a new estimator for the Random-Coefficients Logit demand system for purchase datasets with zero-valued market shares. The identification of the demand parameters is based on a pairwise-differencing approach that constructs moment conditions based on differences in demand between pairs of products. The corresponding estimator corrects non-parametrically for the potential selection of the incidence of zeros on unobserved aspects of demand. The estimator also corrects for the potential endogeneity of marketing variables both in demand and in the selection propensities. Monte Carlo simulations show that our proposed estimator provides reliable small-sample inference both with and without selection-on-unobservables. In an empirical case study, the proposed estimator not only generates different demand estimates than approaches that ignore selection in the incidence of zero shares, it also generates better out-of-sample fit of observed retail contribution margins. |
| Keywords: | consumer demand, pairwise-difference estimation, endogeneity, consideration |
| JEL: | C1 C5 C6 D11 L00 M3 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:bfi:wpaper:2020-13&r=all |