nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2020‒10‒05
ten papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Preferences of Prospective Visitors for Nature-Based Recreational Activities in the Salamanca Island Protected Area, Colombia By Andrés Vargas Pérez; David Díaz Florián; Tatiana Cantillo
  2. Robust discrete choice models with t-distributed kernel errors By Rico Krueger; Prateek Bansal; Michel Bierlaire; Thomas Gasos
  3. How People Know their Risk Preference By Ruben C. Arslan; Martin Brümmer; Thomas Dohmen; Johanna Drewelies; Ralph Hertwig; Gert G. Wagner
  4. Heterogeneous variable selection in nonlinear panel data models: A semiparametric Bayesian approach By Anoek Castelein; Dennis Fok; Richard Paap
  5. Intertemporal Choice Experiments and Large-Stakes Behavior By Diego Aycinena; Szabolcs Blazsek; Lucas Rentschler; Charles Sprenger
  6. My Taxes are Too Darn High: Tax Protests as Revealed Preferences for Redistribution By Brad C. Nathan; Ricardo Perez-Truglia; Alejandro Zentner
  7. Airline Schedule Buffers and Flight Delays: A Discrete Model By Achim I. Czerny; Alberto A. Gaggero; Jan K. Brueckner
  8. Independence of alternatives in ranking models By Lambrecht, Marco
  9. randregret: A command for fitting Random Regret Minimization Models By Álvaro A. Gutiérrez Vargas; Michel Meulders; Martina Vandebroek
  10. The Frisch--Waugh--Lovell Theorem for Standard Errors By Peng Ding

  1. By: Andrés Vargas Pérez; David Díaz Florián; Tatiana Cantillo
    Abstract: To develop financially viable, nature-based tourism, in protected areas, park managers need to make decisions as to what outdoor recreational activities should be offered. Using a discrete choice experiment (DCE), we estimate domestic prospective visitors’ willingness to pay (WTP) for a range of recreational activities and identify those with the greatest potential to attract visitors to Vía Parque Isla de Salamanca, a protected area (PA) in the Barranquilla-Santa Marta region, Colombia. We considered five activities offered by the PA: birding, cultural exchange, nautical sports, walking tours on the beach, and a mangrove boat tour. Results revealed that respondents have strong preferences for cultural exchange activities, while the activities prioritized by PA managers, birding and mangrove boat tours, are the least preferred by respondents. These results suggest that bundling strategies for nature-based tourist products in the PA may be needed to compensate for these unexpected visitor preferences. These results illustrate the usefulness of DCE to inform the design of nature-based tourism strategies in protected areas.
    Keywords: discrete choice experiment; nature-based tourism; outdoor activities; protected areas, bundling tourist products.
    Date: 2020–09–11
  2. By: Rico Krueger; Prateek Bansal; Michel Bierlaire; Thomas Gasos
    Abstract: Models that are robust to aberrant choice behaviour have received limited attention in discrete choice analysis. In this paper, we analyse two robust alternatives to the multinomial probit (MNP) model. Both alternative models belong to the family of robit models, whose kernel error distributions are heavy-tailed t-distributions. The first model is the multinomial robit (MNR) model in which a generic degrees of freedom parameter controls the heavy-tailedness of the kernel error distribution. The second alternative, the generalised multinomial robit (Gen-MNR) model, has not been studied in the literature before and is more flexible than MNR, as it allows for alternative-specific marginal heavy-tailedness of the kernel error distribution. For both models, we devise scalable and gradient-free Bayes estimators. We compare MNP, MNR and Gen-MNR in a simulation study and a case study on transport mode choice behaviour. We find that both MNR and Gen-MNR deliver significantly better in-sample fit and out-of-sample predictive accuracy than MNP. Gen-MNR outperforms MNR due to its more flexible kernel error distribution. Also, Gen-MNR gives more reasonable elasticity estimates than MNP and MNR, in particular regarding the demand for under-represented alternatives in a class-imbalanced dataset.
    Date: 2020–09
  3. By: Ruben C. Arslan; Martin Brümmer; Thomas Dohmen; Johanna Drewelies; Ralph Hertwig; Gert G. Wagner
    Abstract: People differ in their willingness to take risks. Recent work found that revealed preference tasks (e.g., laboratory lotteries)—a dominant class of measures—are outperformed by survey-based stated preferences, which are more stable and predict real-world risk taking across different domains. How can stated preferences, often criticised as inconsequential “cheap talk,” be more valid and predictive than controlled, incentivized lotteries? In our multimethod study, over 3,000 respondents from population samples answered a single widely used and predictive risk-preference question. Respondents then explained the reasoning behind their answer. They tended to recount diagnostic behaviours and experiences, focusing on voluntary, consequential acts and experiences from which they seemed to infer their risk preference. We found that third-party readers of respondents’ brief memories and explanations reached similar inferences about respondents’ preferences, indicating the intersubjective validity of this information. Our results help unpack the self perception behind stated risk preferences that permits people to draw upon their own understanding of what constitutes diagnostic behaviours and experiences, as revealed in high-stakes situations in the real world.
    Keywords: risk preferences, self-reports, revealed preferences, intersubjective validity, BASE-II, SOEP-IS
    Date: 2020
  4. By: Anoek Castelein (Erasmus University Rotterdam); Dennis Fok (Erasmus University Rotterdam); Richard Paap (Erasmus University Rotterdam)
    Abstract: In this paper, we develop a general method for heterogeneous variable selection in Bayesian nonlinear panel data models. Heterogeneous variable selection refers to the possibility that subsets of units are unaffected by certain variables. It may be present in applications as diverse as health treatments, consumer choice-making, macroeconomics, and operations research. Our method additionally allows for other forms of cross-sectional heterogeneity. We consider a two-group approach for the model's unit-specific parameters: each unit-specific parameter is either equal to zero (heterogeneous variable selection) or comes from a Dirichlet process (DP) mixture of multivariate normals (other cross-sectional heterogeneity). We develop our approach for general nonlinear panel data models, encompassing multinomial logit and probit models, poisson and negative binomial count models, exponential models, among many others. For inference, we develop an efficient Bayesian MCMC sampler. In a Monte Carlo study, we find that our approach is able to capture heterogeneous variable selection whereas a ``standard'' DP mixture is not. In an empirical application, we find that accounting for heterogeneous variable selection and non-normality of the continuous heterogeneity leads to an improved in-sample and out-of-sample performance and interesting insights. These findings illustrate the usefulness of our approach.
    Keywords: Individualized variable selection, Dirichlet process, Stochastic search, Heterogeneity, Attribute non-attendance, Feature selection, Bayesian
    JEL: C23 C11
    Date: 2020–09–22
  5. By: Diego Aycinena (Department of Economics, Universidad del Rosario; Economic Science Institute, Chapman University); Szabolcs Blazsek (Escuela de Negocios, Universidad Francisco Marroqu´ın); Lucas Rentschler (Department of Economics and Finance, Utah State University;; Charles Sprenger (California Institute of Technology;
    Abstract: Intertemporal choice experiments are increasingly implemented to make inference about discounting and marginal utility, yet little is known about the predictive power of resulting measures. This project links standard experimental choices to a decision on the desire to smooth a large-stakes payment — around 10% of annual income — through time. In a sample of around 400 Guatemalan Conditional Cash Transfer recipients, we find that preferences over large-stakes payment plans are closely predicted by experimental measures of patience and diminishing marginal utility. These represent the first findings in the literature on the predictive content of such experimentally elicited measures of discounting and marginal utility for a large-stakes decision.
    Keywords: Structural estimation, Out-of-sample prediction, Discounting, Convex Time Budget
    JEL: D1 D3 D90
    Date: 2020
  6. By: Brad C. Nathan; Ricardo Perez-Truglia; Alejandro Zentner
    Abstract: In all U.S. states, individuals can file a protest with the goal of legally reducing their property taxes. This choice provides a unique opportunity to study preferences for redistribution via revealed preference. We study the motives driving tax protests through two sources of causal identification: a quasi-experiment and a pre-registered large-scale natural field experiment. We show that, consistent with selfish motives, households are highly elastic to their private benefits and private costs from protesting. We also find that social preferences are a significant motive: consistent with conditional cooperation, households are willing to pay higher tax rates if they perceive that others pay high tax rates too. Lastly, we document significant differences between the motivations of Democrats and Republicans.
    JEL: C93 H2 H26 Z13
    Date: 2020–09
  7. By: Achim I. Czerny; Alberto A. Gaggero; Jan K. Brueckner
    Abstract: This paper revisits the airline schedule-buffer choice problem analyzed by Brueckner, Czerny and Gaggero (2020) using a simpler model where the random shocks influencing flight times are discrete rather than continuous. The analysis yields closed-form solutions for the flight and ground buffers as well as full comparative-static results, neither of which were available in the earlier paper. The paper also explores several extensions to the model that were not present in the previous paper
    Date: 2020
  8. By: Lambrecht, Marco
    Abstract: When Luce (1959) introduced his Choice Axiom, this raised immediate criticism by Debreu (1960), pointing out inconsistencies when items are ranked from inferior to superior (instead of ranking them from superior to inferior). As recently shown by Breitmoser (2019), Luce’s Independence of Irrelevant Alternatives (IIA) is equivalent to Luce’s Choice Axiom when positivity holds. This fact seems to have escaped attention so far and might suggest that Debreu’s critique also applies to the notion of IIA, which is widely used in the literature. Furthermore, this notion could potentially be intuitively misleading, as the consequences of this axiom seem to be different than the name suggests. This might spill over to the intuitive interpretation of theoretical results that build on this axiom. This paper motivates the introduction of the notion of Independece of Alternatives (IoA) in the context of ranking models. IoA postulates a property of independence which seems intuitively reasonable (as it exactly captures what Luce himself describes when speaking about IIA), but does not exclusively hold in models where Luce’s Choice Axiom applies. Assuming IoA, expected ranks in the ranking of multiple alternatives can be determined from pairwise comparisons. The result holds in many models which do not satisfy IIA (e.g. certain Thurstone V models, Thurstone (1927)), can significantly simplify the calculation of expected ranks in practice and potentially facilitate analytic methods that build on more general approaches to model the ranking of multiple alternatives.
    Keywords: Ranking models; IIA; IoA; Luce’s Choice Axiom; Thurstone V
    Date: 2020–09–16
  9. By: Álvaro A. Gutiérrez Vargas (Centre for Research Operation and Statistics (ORSTAT), KU Leuven, Belgium); Michel Meulders (Centre for Research Operation and Statistics (ORSTAT), KU Leuven, Belgium); Martina Vandebroek (Centre for Research Operation and Statistics (ORSTAT), KU Leuven, Belgium)
    Abstract: In this article, we describe the randregret command which implements a variety of Random Regret Minimization (RRM) models. The command allows the user to apply the classic RRM model (Chorus, 2010), the Generalized RRM model (Chorus, 2014), and also the mu-RRM and Pure RRM models (Van Cranenburgh, Guevara and Chorus, 2015). We illustrate the usage of the randregret command using stated choice data on route preferences. The command offers robust and cluster standard error correction using analytical expressions of the score functions. It also offers likelihood ratio tests which can be used to assess the relevance of a given model specification. Finally, predicted probabilities from each model can be easily computed using the randregretpred postestimation command.
    Date: 2020–09–11
  10. By: Peng Ding
    Abstract: The Frisch--Waugh--Lovell Theorem states the equivalence of the coefficients from the full and partial regressions. I further show the equivalence between various standard errors. Applying the new result to stratified experiments reveals the discrepancy between model-based and design-based standard errors.
    Date: 2020–09

This nep-dcm issue is ©2020 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.
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