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on Discrete Choice Models |
| By: | Daniel, Aemiro Melkamu (CERE and the Department of Economics, Umeå University); Persson, Lars (CERE and the Department of Economics, Umeå University); Sandorf, Erlend Dancke (CERE and the Department of Forest Economics, SLU) |
| Abstract: | We report on a discrete choice experiment aimed at eliciting Swedish households' willingness-to-accept a compensation for restrictions on household electricity and heating use during peak hours. When analyzing data from discrete choice experiments, we typically assume that people make rational utility maximizing decisions, i.e., that they consider all of the attribute information and compare all alternatives. However, mounting evidence shows that people use a wide range of simplifying strategies that are inconsistent with utility maximization. We use a flexible model capturing a two-stage decision process. In the fi rst stage, respondents are allowed to eliminate from their choice set alternatives that contain an unacceptable level, i.e., restrictions on the use of heating and electricity. In the second stage, respondents choose in a compensatory manner between the remaining alternatives. Our results show that about half of our respondents choose according to an elimination-by-aspects strategy, and that, on average, they are unwilling to accept any restrictions on heating in the evening or electricity use, irrespective of time-of-day. Furthermore, we nd that considering elimination-by-aspects behavior leads to a downward shift in elicited willingness-to-accept. We discuss implications for policy. |
| Keywords: | Choice experiment; Electricity contract; Willingness-to-accept; Household electricity; Elimination-by-aspects; Two-stage decision |
| JEL: | C25 Q41 Q51 R21 |
| Date: | 2017–11–07 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:slucer:2017_007&r=dcm |
| By: | Parag A. Pathak; Peng Shi |
| Abstract: | Discrete choice demand models are widely used for counterfactual policy simulations, yet their out-of-sample performance is rarely assessed. This paper uses a large-scale policy change in Boston to investigate the performance of discrete choice models of school demand. In 2013, Boston Public Schools considered several new choice plans that differ in where applicants can apply. At the request of the mayor and district, we forecast the alternatives' effects by estimating discrete choice models. This work led to the adoption of a plan which significantly altered choice sets for thousands of applicants. Pathak and Shi (2014) update forecasts prior to the policy change and describe prediction targets involving access, travel, and unassigned students. Here, we assess how well these ex ante counterfactual predictions compare to actual outcome under the new choice sets. We find that a simple ad hoc model performs as well as the more complicated structural choice models for one of the two grades we examine. However, the structural models' inconsistent performance is largely due to prediction errors in applicant characteristics, which are auxiliary inputs. Once we condition on the actual applicant characteristics, the structural choice models outperform the ad hoc alternative in predicting both choice patterns and policy relevant outcomes. Moreover, refitting the models using the new choice data does not significantly improve their prediction accuracy, suggesting that the choice models are indeed “structural.” Our findings show that structural demand models can effectively predict counterfactual outcomes, as long there are accurate forecasts about auxiliary input variables. |
| JEL: | C10 C78 D12 I20 |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24017&r=dcm |
| By: | Lea Skræp Svenningsen (Department of Food and Resource Economics, University of Copenhagen); Bo Jellesmark Thorsen (Department of Food and Resource Economics, University of Copenhagen) |
| Abstract: | What role do people think distributional aspects should play in design of climate policy? The literature assessing climate policies has shown that assumptions regarding peoples’ distributional preferences for climate change policy impacts are central for policy assessment, but empirical evidence for such preferences is lacking. We design a discrete choice experiment that varies how climate policies affect the income of people living in the future in three geographical regions. The experiment is implemented on a representative sample of the Danish population and preferences are modelled in a latent class model. Our results show that i) a small majority of Danes expresses preferences for climate policies consistent with inequity aversion, ii) a group expresses preferences resembling simple warm glow, while iii) a small group prefers not to support additional climate policies. Finally a somewhat larger group expresses some form of distributional preferences, but shows positive preferences for costs, suggesting that responses could be influenced by strategic behaviour and over-signalling of commitment. Our results provide support for the inclusion of social preferences regarding distributional effects of climate change policies in policy assessments, and hence for the significant impact on policy this inclusion have. |
| Keywords: | choice experiment, social preferences, inequity aversion, warm glow, altruism, climate change impacts, latent class, social cost of carbon |
| JEL: | D30 H41 Q51 Q54 |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:foi:wpaper:2017_10&r=dcm |
| By: | Bergantino, Angela Stefania; Capurso, Mauro; Hess, Stephane |
| Abstract: | At the Regional level, accessibility is one of the key factors in airports' provision. An efficient public transport network can represent an alternative to maintaining costly and inefficient airports in the same catchment area, notwithstanding residents’ pressures to have a “local” airport. At the same time, airports can better exploit economies of scale aggregating demand. In this paper, we analyse residents' decisions regarding airport access mode in the Apulia region, in Italy, which is characterised by the presence of a system of “local” airports, of which two not fully operating. Both revealed and stated preferences data are collected and are used to estimate probabilistic models (multinomial, nested logit, and mixed logit) in order to calculate the relevant elasticities of dedicated public transit services. Moreover, we measure the effectiveness of specific policies/actions aimed at generating a modal shift from private modes (car and taxi) to public transport, rationalising mobility towards the existing airports. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:sit:wpaper:17_4&r=dcm |