Discrete Choice Models
http://lists.repec.org/mailman/listinfo/nep-dcm
Discrete Choice Models
2019-05-20
Why do (or don't) people carpool for long distance trips? A discrete choice experiment in France
http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02121589&r=dcm
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
Guillaume Monchambert
Value of time,Long-distance,Carpooling,Discrete choice experiment
2019-05-06
Nonparametric Estimates of Demand in the California Health Insurance Exchange
http://d.repec.org/n?u=RePEc:nbr:nberwo:25827&r=dcm
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.
Pietro Tebaldi
Alexander Torgovitsky
Hanbin Yang
2019-05
Demand and Welfare Analysis in Discrete Choice Models with Social Interactions
http://d.repec.org/n?u=RePEc:aah:create:2019-09&r=dcm
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.
Debopam Bhattacharya
Pascaline Dupas
Shin Kanaya
Policy targeting, welfare analysis, social interaction, spillover, externality, convergence of Bayesian-Nash equilibria, spatial dependence, Kenya
2019-04-26
Demand and Welfare Analysis in Discrete Choice Models with Social Interactions
http://d.repec.org/n?u=RePEc:arx:papers:1905.04028&r=dcm
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.
Debopam Bhattacharya
Pascaline Dupas
Shin Kanaya
2019-05
The Devil is in the Details: Risk Preferences, Choice List Design, and Measurement Error
http://d.repec.org/n?u=RePEc:hhs:nlsclt:2019_003&r=dcm
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.
Holden , Stein T.
Tilahun , Mesfin
Risk preferences; rank dependent utility; probability weighting; measurement error; predictive power; field experiment; Ethiopia
2019-05-01
Does Access to Agricultural Credit Explain Land Use Choice? A Case of Odukpani in Cross River State, Nigeria
http://d.repec.org/n?u=RePEc:ags:naae17:288423&r=dcm
Etowa, Egbe B.
Elum, Zelda A.
Mwiido, Wmmanuel D.
Land Economics/Use
2017-10
Using multiple reference levels in Multi-Criteria Decision aid: The Generalized-Additive Independence model and the Choquet integral approaches
http://d.repec.org/n?u=RePEc:hal:journl:hal-02043265&r=dcm
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.
Christophe Labreuche
Michel Grabisch
Generalized Additive Independence,Multiple criteria analysis
2018-06
Who is willing to stay sick for the collective? – Individual characteristics, experience, and trust
http://d.repec.org/n?u=RePEc:hhs:gunwpe:0762&r=dcm
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.
Carlsson, Fredrik
Jacobsson, Gunnar
Jagers, Sverker C.
Lampi, Elina
Robertsson, Felicia
Rönnerstrand, Björn
collective action; antibiotics use; antibiotic resistance; willingness to abstain
2019-05