nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2016‒02‒12
nine papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Hypothetical bias for private goods: does cheap talk make a difference? By Maurice Doyon; Laure Saulais; Bernard Ruffieux; Denise Bweli
  2. Income-comparison Attitudes in the US and the UK: Evidence from Discrete-choice Experiments By Hitoshi Shigeoka; Katsunori Yamada
  3. A model of two-destination choice in trip chains with GPS data By Arthur (Yan) Huang; David Levinson
  4. Measuring Willingness to Pay for Environmental Attributes in Seafood By Villas-Boas, Sofia B; Hilger, James; Stevens, Andrew; Hallstein, Eric
  5. Waiting or acting now? The effects on willingness-to-pay of delivering inherent uncertainty information in choice experiments By Cati Torres; Michela Faccioli; Antoni Riera
  6. Job sector and public service motivation: evidence from Colombia By Pablo Sanabria
  7. Testing Monotonicity in Unobservables with Panel Data By Liangjun Su; Stefan Hoderlein; Halbert White
  8. Parametric Recovery Methods: A Comparative Experimental Study By Halevy, Yoram; Zrill, Lanny
  9. Semiparametric Estimation of Random Coefficients in Structural Economic Models By Stefan Hoderlein; Lars Nesheim; Anna Simoni

  1. By: Maurice Doyon (Université Laval); Laure Saulais (Institut Paul Bocuse); Bernard Ruffieux (GAEL - Laboratoire d'Economie Appliquée de Grenoble - Institut national de la recherche agronomique (INRA) - Université Grenoble Alpes - Grenoble 2, Institut National Polytechnique de Grenoble); Denise Bweli (Egg Farmers of Canada)
    Abstract: Economists and market researchers often need to accurately gauge consumers’ willingness-to-pay for private goods. The experimental literature has identified a problem of hypothetical bias when using stated preferences techniques, such as open-ended questions. It has been suggested that using a cheap talk script has the potential to resolve this bias. Yet, few empirical studies on the efficiency of cheap talk for private goods exist. This study uses a between-subjects experimental design to compare consumers’ willingness-to-pay for DHA-enriched milk using three elicitation methods: 1) Hypothetical open-ended stated preference question, without monetary consequence for the respondent; 2) Idem to the first with the addition of a cheap talk script; and 3) A Vickrey auction with real monetary consequences. In this experiment subjects have the choice to participate, or not, at each period. Our results indicate a significant hypothetical bias. While the use of cheap talk has no impact on this bias, it does however increase the level of participation to the market.
    Keywords: experimental economics,willingness to pay,cheap talk,hypothetical bias
    Date: 2015
  2. By: Hitoshi Shigeoka; Katsunori Yamada
    Abstract: Economists have long been aware of utility externalities such as a tendency to compare own income with others'. If welfare losses from income comparisons are significant, any governmental interventions that alter such attitudes may have large welfare consequences. We conduct an original online survey of discrete-choice questions to estimate such attitudes in the US and the UK. We find that the UK respondents compare incomes more than US respondents do. We then manipulate our respondents with simple information to examine whether the attitudes can be altered. Our information treatment suggesting that comparing income with others may diminish welfare even when income levels increase makes UK respondents compare incomes more rather than less. Interestingly, US respondents are not affected at all. The mechanism behind the UK results seems to be that our treatment gives moral license to make income comparisons by providing information that others do so.
    Date: 2015–03
  3. By: Arthur (Yan) Huang; David Levinson (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)
    Abstract: Abstract Studying trip chaining behavior has been a challenging endeavor which requires the support of microscopic travel data. New insights can be gained given real-time GPS travel data. This research introduces a framework that considers two-destination choice in the context of home-based trip chains. We propose and empirically compare three alternatives of building choice sets where we consider various relationships of the two destinations (such as major-minor destinations, selecting one first, and select- ing two concurrently). Our choice set formation alternatives use survival models to determine the selection probability of a destination. Our results reveal that trip chaining behavior is shaped by the features of retail clusters, spatial patterns of clusters, transportation networks, and the axis of travel. This research supports our hypothesis that not only the spatial relationship but also the land use relationship of the destinations in a trip chain affect the decision making process. Keywords: GPS data, trip chaining, axis of travel, destination choice
    JEL: R14 R41 R42
    Date: 2016
  4. By: Villas-Boas, Sofia B; Hilger, James; Stevens, Andrew; Hallstein, Eric
    Keywords: Social and Behavioral Sciences
    Date: 2016–02–08
  5. By: Cati Torres (Universitat de les Illes Balears); Michela Faccioli (Universitat de les Illes Balears); Antoni Riera (Universitat de les Illes Balears)
    Abstract: With a focus on expected climate change (CC) risks, this paper analyzes the effects of inherent uncertainty on the willingness-to-pay for a preservation policy. To do this, it relates outcome uncertainty to the probability of occurrence of an expected CC impact within a given time horizon. Thus, unlike the existing studies, this paper links outcome uncertainty to the uncontrollable component of environmental uncertainty derived from the stochastic nature of ecosystems’ behavior. Results show the support for the preservation policy is stronger in the presence of inherent uncertainty, this indicating risk aversion. In contrast, findings are not conclusive with respect to individuals’ sensitivity to the probability of impact occurrence. These results are policy relevant since they can serve to stimulate rather than discourage environmental action when it comes to contexts characterized by many uncertainties.
    Keywords: preference analysis, inherent uncertainty, choice experiment, adaptation, climate change.
    JEL: D6 D81 Q51 Q54
    Date: 2015
  6. By: Pablo Sanabria (Faculty of Economics and Management, Pontificia Universidad Javeriana Cali)
    Abstract: In this article I examine the determinants of job sector choice with a particular interest in the relationship with the so-called concept of public service motivation (PSM), in the context of a developing country. I use multinomial logit (MNL) to understand individuals’ decisions to take jobs in one of four sectors: government, nonprofit, for-profit, or academic jobs in Colombia. My analysis is based on data about a sample of participants on the Colombian scholarship program, Colfuturo, drawn from between 2002 and 2007. My results indicate that there are important differences in terms of the determinants of job sector choices across the four different sectors and that PSM appears to have a role on such decisions.
    Keywords: organizational behavior; human talent; motivation
    JEL: D23 D73 H7 J45 M12
    Date: 2016–02
  7. By: Liangjun Su (Singapore Management University); Stefan Hoderlein (Boston College); Halbert White
    Abstract: Monotonicity in a scalar unobservable is a crucial identifying assumption for an important class of nonparametric structural models accommodating unobserved heterogeneity. Tests for this monotonicity have previously been unavailable. This paper proposes and analyzes tests for scalar monotonicity using panel data for structures with and without time-varying unobservables, either partially or fully nonseparable between observables and unobservables. Our nonparametric tests are computationally straightforward, have well behaved limiting distributions under the null, are consistent against pre- cisely specified alternatives, and have standard local power properties. We provide straightforward bootstrap methods for inference. Some Monte Carlo experiments show that, for empirically relevant sample sizes, these reasonably control the level of the test, and that our tests have useful power. We apply our tests to study asset returns and demand for ready-to-eat cereals.
    Keywords: monotonicity, nonparametric, nonseparable, specification test, unobserved heterogeneity
    JEL: C12 C14 C33
  8. By: Halevy, Yoram; Zrill, Lanny
    Abstract: We propose and implement an experimental methodology for comparing the predictive success of various methods for recovering individual preferences from choice data. We apply the proposed approach to a comparison of two parametric recovery methods: Non Linear Least Squares (NLLS) and the Money Metric Index (MMI). The former is based on minimizing the distance between observed and predicted choices while the latter is based on eliminating incompatibility between the ranking information encoded in choices and the ranking induced by the parametric specification. The experiment, in the context of choice under risk, involves a two-part design where choices made by subjects in the first part are used to construct their choice sets in the second part of the experiment in order to separate the predictions of the two recovery methods. We find that the Money Metric Index predicts better than NLLS in all cases and significantly better when the recovered parameters imply non-convex preferences.
    Keywords: Revealed Preference, Recoverability, Identification, Non-Convex Preferences, Pairwise Choice, First-Order Risk Aversion, Portfolio Choice, Laboratory
    JEL: C18 C91 D81 G11
    Date: 2016–01–09
  9. By: Stefan Hoderlein (Boston College); Lars Nesheim (University College London); Anna Simoni (CNRS - CREST)
    Abstract: This paper discusses nonparametric estimation of the distribution of random coefficients in a structural model that is nonlinear in the random coefficients. We establish that the problem of recovering the probability density function (pdf ) of random parameters falls into the class of convexly-constrained inverse problems. The framework offers an estimation method that separates computational solution of the structural model from estimation. We first discuss nonparametric identification. Then, we propose two alternative estimation procedures to estimate the density and derive their asymptotic properties. Our general framework allows us to deal with unobservable nuisance variables, e.g., measurement error, but also covers the case when there are no such nuisance variables. Finally, Monte Carlo experiments for several structural models are provided which illustrate the performance of our estimation procedure.
    Keywords: Nonlinear random coefficients, mixture models, structural models, heterogeneity, inverse problems
    Date: 2015–04–14

This nep-dcm issue is ©2016 by Edoardo Marcucci. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.