nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2019‒05‒20
eight papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Why do (or don't) people carpool for long distance trips? A discrete choice experiment in France By Guillaume Monchambert
  2. Nonparametric Estimates of Demand in the California Health Insurance Exchange By Pietro Tebaldi; Alexander Torgovitsky; Hanbin Yang
  3. Demand and Welfare Analysis in Discrete Choice Models with Social Interactions By Debopam Bhattacharya; Pascaline Dupas; Shin Kanaya
  4. Demand and Welfare Analysis in Discrete Choice Models with Social Interactions By Debopam Bhattacharya; Pascaline Dupas; Shin Kanaya
  5. The Devil is in the Details: Risk Preferences, Choice List Design, and Measurement Error By Holden , Stein T.; Tilahun , Mesfin
  6. Does Access to Agricultural Credit Explain Land Use Choice? A Case of Odukpani in Cross River State, Nigeria By Etowa, Egbe B.; Elum, Zelda A.; Mwiido, Wmmanuel D.
  7. Using multiple reference levels in Multi-Criteria Decision aid: The Generalized-Additive Independence model and the Choquet integral approaches By Christophe Labreuche; Michel Grabisch
  8. Who is willing to stay sick for the collective? – Individual characteristics, experience, and trust By Carlsson, Fredrik; Jacobsson, Gunnar; Jagers, Sverker C.; Lampi, Elina; Robertsson, Felicia; Rönnerstrand, Björn

  1. By: Guillaume Monchambert (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique, UL2 - Université Lumière - Lyon 2, Université de Lyon)
    Abstract: Long-distance carpooling is an emerging mode in France and Europe, but little is known about monetary values of this mode attributes in transport economics. We conducted a discrete choice experiment to identify and measure the values of attributes of long-distance transport modes for a trip as a driver and as a passenger, with a special focus on carpooling. Around 1.700 French individuals have been surveyed. We use discrete mixed logit models to estimate the probability of mode choice. We find that the value of travel time for a driver who carpools is on average 13% higher than the value of travel time when driving alone in his/her car. The average value of travel time for a carpool trip as passenger is around 26 euros per hour, 60% higher than for a train trip and 20% higher than for a bus trip. Moreover, our study confirms a strong preference for driving solo over taking carpoolers in one's car. We also show that individuals traveling as carpool passenger incur a "discomfort" cost of on average 4.5 euros per extra passenger in the same vehicle. Finally, we identify robust socioeconomic effects affecting the probability of carpooling, especially gender effects. When they drive a car, females are less likely to carpool than male, but they prefer to carpool two passengers over only one passenger. JEL Codes: R41; C35
    Keywords: Value of time,Long-distance,Carpooling,Discrete choice experiment
    Date: 2019–05–06
    URL: http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02121589&r=all
  2. By: Pietro Tebaldi; Alexander Torgovitsky; Hanbin Yang
    Abstract: We estimate the demand for health insurance in the California Affordable Care Act marketplace (Covered California) without using parametric assumptions about the unobserved components of utility. To do this, we develop a computational method for constructing sharp identified sets in a nonparametric discrete choice model. The model allows for endogeneity in prices (premiums) and for the use of instrumental variables to address this endogeneity. We use the method to estimate bounds on the effects of changing premium subsidies on coverage choices, consumer surplus, and government spending. We find that a $10 decrease in monthly premium subsidies would cause between a 1.6% and 7.0% decline in the proportion of low-income adults with coverage. The reduction in total annual consumer surplus would be between $63 and $78 million, while the savings in yearly subsidy outlays would be between $238 and $604 million. Comparable logit models yield price sensitivity estimates towards the lower end of the bounds.
    JEL: C14 C3 C5 I13
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25827&r=all
  3. By: Debopam Bhattacharya (University of Cambridge); Pascaline Dupas (Stanford University); Shin Kanaya (University of Aarhus and CREATES)
    Abstract: Many real-life settings of consumer-choice involve social interactions, causing targeted policies to have spillover-effects. This paper develops novel empirical tools for analyzing demand and welfare-effects of policy-interventions in binary choice settings with social interactions. Examples include subsidies for healthproduct adoption and vouchers for attending a high-achieving school. We establish the connection between econometrics of large games and Brock-Durlauf-type interaction models, under both I.I.D. and spatially correlated unobservables. We develop new convergence results for associated beliefs and estimates of preference-parameters under increasing-domain spatial asymptotics. Next, we show that even with fully parametric specifications and unique equilibrium, choice data, that are sufficient for counterfactual demand - prediction under interactions, are insufficient for welfare-calculations. This is because distinct underlying mechanisms producing the same interaction coefficient can imply different welfare-effects and deadweightloss from a policy-intervention. Standard index-restrictions imply distribution-free bounds on welfare. We illustrate our results using experimental data on mosquito-net adoption in rural Kenya.
    Keywords: Policy targeting, welfare analysis, social interaction, spillover, externality, convergence of Bayesian-Nash equilibria, spatial dependence, Kenya
    JEL: C01 H23 H4 H51 I38 O1
    Date: 2019–04–26
    URL: http://d.repec.org/n?u=RePEc:aah:create:2019-09&r=all
  4. By: Debopam Bhattacharya; Pascaline Dupas; Shin Kanaya
    Abstract: Many real-life settings of consumer-choice involve social interactions, causing targeted policies to have spillover-effects. This paper develops novel empirical tools for analyzing demand and welfare-effects of policy-interventions in binary choice settings with social interactions. Examples include subsidies for health-product adoption and vouchers for attending a high-achieving school. We establish the connection between econometrics of large games and Brock-Durlauf-type interaction models, under both I.I.D. and spatially correlated unobservables. We develop new convergence results for associated beliefs and estimates of preference-parameters under increasing-domain spatial asymptotics. Next, we show that even with fully parametric specifications and unique equilibrium, choice data, that are sufficient for counterfactual demand-prediction under interactions, are insufficient for welfare-calculations. This is because distinct underlying mechanisms producing the same interaction coefficient can imply different welfare-effects and deadweight-loss from a policy-intervention. Standard index-restrictions imply distribution-free bounds on welfare. We illustrate our results using experimental data on mosquito-net adoption in rural Kenya.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1905.04028&r=all
  5. By: Holden , Stein T. (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Tilahun , Mesfin (Centre for Land Tenure Studies, Norwegian University of Life Sciences)
    Abstract: We use a field experiment to estimate the risk preferences of 945 youth and young adult members of 116 rural business groups organized as primary cooperatives in a semi-arid risky environment in northern Ethiopia. Multiple Choice Lists with binary choices between risky prospects and varying safe amounts are used to identify the certainty equivalent for each risky prospect. Rank Dependent Utility Models with alternatively Wilcox’ (2011) Contextual Utility or Busemeyer and Townsend (1992, 1993) Decision Field Theory heteroskedastic error specifications are used to estimate risk preference parameters and parametrized model noise. The study aims to a) assess potential biases associated with Choice List design; b) assess a time-saving elicitation method; c) inspect the predictive power of the predicted risk preference parameters for respondents’ investment, income and endowment variables; d) assess how the predictive power is associated with model noise and the addition of two low probability high outcome risky prospects that may help to capture utility curvature more accurately. Substantial risk parameter sensitivity to Choice List design was detected. The rapid elicitation method appears attractive as it facilitates use of a larger number of Choice Lists with variable attributes although it is sensitive to bias due to random error associated with randomized starting points. The addition of the two Choice Lists with low probability high outcomes substantially enhanced the explanatory power of the predicted risk preference parameters and resulted in substantially higher estimates of the utility curvature parameter.
    Keywords: Risk preferences; rank dependent utility; probability weighting; measurement error; predictive power; field experiment; Ethiopia
    JEL: C90 C93 D14 D81 D90
    Date: 2019–05–01
    URL: http://d.repec.org/n?u=RePEc:hhs:nlsclt:2019_003&r=all
  6. By: Etowa, Egbe B.; Elum, Zelda A.; Mwiido, Wmmanuel D.
    Keywords: Land Economics/Use
    Date: 2017–10
    URL: http://d.repec.org/n?u=RePEc:ags:naae17:288423&r=all
  7. By: Christophe Labreuche (UMP CNRS/THALES - Unité mixte de physique CNRS/Thalès - THALES - CNRS - Centre National de la Recherche Scientifique); Michel Grabisch (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics)
    Abstract: In many Multi-Criteria Decision problems, one can construct with the decision maker several reference levels on the attributes such that some decision strategies are conditional on the comparison with these reference levels. The classical models (such as the Choquet integral) cannot represent these preferences. We are then interested in two models. The first one is the Choquet with respect to a p-ary capacity combined with utility functions, where the p-ary capacity is obtained from the reference levels. The second one is a specialization of the Generalized-Additive Independence (GAI) model, which is discretized to fit with the presence of reference levels. These two models share common properties (monotonicity, continuity, properly weighted,.. .), but differ on the interpolation means (Lovász extension for the Choquet integral, and multi-linear extension for the GAI model). A drawback of the use of the Choquet integral with respect to a p-ary capacity is that it cannot satisfy decision strategies in each domain bounded by two successive reference levels that are completely independent of one another. We show that this is not the case with the GAI model.
    Keywords: Generalized Additive Independence,Multiple criteria analysis
    Date: 2018–06
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-02043265&r=all
  8. By: Carlsson, Fredrik (Department of Economics, School of Business, Economics and Law, Göteborg University); Jacobsson, Gunnar (Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden); Jagers, Sverker C. (Centre for Collective Action Research (CeCAR), University of Gothenburg, Gothenburg, Sweden); Lampi, Elina (Department of Economics, School of Business, Economics and Law, Göteborg University); Robertsson, Felicia (Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden); Rönnerstrand, Björn (Center for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden)
    Abstract: This paper deals with the collective action dilemma of antibiotic resistance. Despite the collective threat posed by antibiotic resistance, there are limited incentives for individuals to consider the contribution of their decisions to use antibiotics to the spread of resistance. Drawing on a novel survey of Swedish citizens (n=1,906), we study factors linked to i) willingness to accept a physician’s decision not to prescribe antibiotics and ii) willingness to limit personal use of antibiotics voluntary. In our study, 53 percent of the respondents stated that they would be willing to accept the physician’s decision despite disagreeing with it, and trust in the healthcare sector is significantly associated with acceptance. When it comes to people’s willingness to voluntarily abstain from using antibiotics, a majority stated that they are willing or very willing not to take antibiotics. The variation in willingness is best explained by concerns about antibiotic resistance and experience of antibiotic therapy, especially if a respondent has been denied antibiotics. Generalized trust seems to be unrelated to willingness to abstain, but the perception that other people limit their personal use of antibiotics is linked to respondents’ own willingness to do so. Few of the individual characteristics can explain the variation in that decision.
    Keywords: collective action; antibiotics use; antibiotic resistance; willingness to abstain
    JEL: D90 I12
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:hhs:gunwpe:0762&r=all

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