nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2022‒06‒20
fourteen papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Identification of Dynamic Discrete Choice Models with Hyperbolic Discounting Using a Terminating Action By Chao Wang; Stefan Weiergraeber; Ruli Xiao
  2. Preferences for Energy Retrofit Investments Among Low-income Renters By Schmitz, Hendrik; Madlener, Reinhard
  3. Dynamic demand for differentiated products with fixed-effects unobserved heterogeneity By Victor Aguirregabiria
  4. Working from Home during a Pandemic – A Discrete Choice Experiment in Poland By Lewandowski, Piotr; Lipowska, Katarzyna; Smoter, Mateusz
  5. Generalizing Heuristic Switching Models By Galanis, Giorgos; Kollias, Iraklis; Leventidis, Ioanis; Lustenhouwer, Joep
  6. A Note on "A survey of preference estimation with unobserved choice set heterogeneity" by Gregory S. Crawford, Rachel Griffith, and Alessandro Iaria By C. Angelo Guevara
  7. Climate change and migration decisions: A choice experiment from the Mekong Delta, Vietnam. By Tra Thi Trinh; Alistair Munro
  8. Is online retail killing coffee shops? Estimating the winners and losers of online retail using customer transaction microdata By Lindsay E. Relihan
  9. Does climate change concern alter tax morale preferences? Evidence from an Italian survey By Cascavilla, Alessandro
  10. How green is green enough? Landscape preferences and water use in urban parks By Doll, Claire A.; Burton, Michael P.; Pannell, David J.; Rollins, Curtis L.
  11. Multivariate ordered discrete response models By Tatiana Komarova; William Matcham
  12. Intertemporal Choice with Continuity Constraints By Marcus Pivato
  13. Estimating Discrete Games of Complete Information: Bringing Logit Back in the Game By Paul S. Koh
  14. Open vs Closed-ended questions in attitudinal surveys -- comparing, combining, and interpreting using natural language processing By Vishnu Baburajan; Jo\~ao de Abreu e Silva; Francisco Camara Pereira

  1. By: Chao Wang (Indiana University, Department of Economics); Stefan Weiergraeber (Indiana University, Department of Economics); Ruli Xiao (Indiana University, Department of Economics)
    Abstract: We study the identification of dynamic discrete choice models with hyperbolic discounting using a terminating action. We provide novel identification results for both sophisticated and naive agents’ discount factors and their utilities in a finite horizon framework under the assumption of a stationary flow utility. In contrast to existing identification strategies we do not require to observe the final period for the sophisticated agent. Moreover, we avoid normalizing the flow utility of a reference action for both the sophisticated and the naive agent. We propose two simple estimators and show that they perform well in simulations.
    Keywords: hyperbolic discounting, dynamic discrete choice model, identification
    Date: 2022–06
  2. By: Schmitz, Hendrik (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)); Madlener, Reinhard (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))
    Abstract: Energy poverty research has received increased attention in the energy economics literature in recent years. We analyze the preferences of low-income renters in the city of Graz, Austria, for different energy retrofitting options. Using data collected from a Discrete Choice Experiment, we find that households are willing to forego significant future energy cost savings in order to avoid investment costs in the present. This can be caused by several factors, including liquidity constraints, a short investment horizon, and myopia among the participants. Furthermore, participants show a significant Willingness to Pay for the reduction of CO2 emissions. We also present simulations for different forms of subsidies for retrofitting and their effects on market shares and emissions. The results have important policy implications regarding the optimal subsidy policies, in particular for low-income households. Specifically, policy makers should focus on reducing the investment burden for liquidity-constrained renters and inducing a longer investment horizon.
    Keywords: Energy Poverty; Discrete Choice Modeling; Residential Energy Consumption; Landlord-Tenant Problem
    JEL: C35 D12 Q48 Q51
    Date: 2021–09
  3. By: Victor Aguirregabiria
    Abstract: This paper studies identification and estimation of a dynamic discrete choice model of demand for differentiated product using consumer-level panel data with few purchase events per consumer (i.e., short panel). Consumers are forward-looking and their preferences incorporate two sources of dynamics: last choice dependence due to habits and switching costs, and duration dependence due to inventory, depreciation, or learning. A key distinguishing feature of the model is that consumer unobserved heterogeneity has a Fixed Effects (FE) structure -- that is, its probability distribution conditional on the initial values of endogenous state variables is unrestricted. I apply and extend recent results to establish the identification of all the structural parameters as long as the dataset includes four or more purchase events per household. The parameters can be estimated using a sufficient statistic - conditional maximum likelihood (CML) method. An attractive feature of CML in this model is that the sufficient statistic controls for the forward-looking value of the consumer's decision problem such that the method does not require solving dynamic programming problems or calculating expected present values.
    Date: 2022–05
  4. By: Lewandowski, Piotr (Institute for Structural Research (IBS)); Lipowska, Katarzyna (Institute for Structural Research (IBS)); Smoter, Mateusz (Institute for Structural Research (IBS))
    Abstract: The COVID-19 pandemic has transformed working from home from a rarity to a widely adopted job amenity. We study workers' willingness to pay for working from home, and how it may be affected by subjective and objective assessments of COVID-19-related risks. We conducted a discrete choice experiment with more than 10,000 workers in Poland. We randomised wage differences between otherwise identical home- and office-based jobs. We also randomised an information provision treatment in which we informed 50% of workers about the level of exposure to contagion in their occupation, and how it may be reduced by working from home. We found that the demand for working from home was substantial – the majority of participants would prefer to work from home if they were offered the same wage for a home-based job as they would earn in an office-based job. On average, workers would sacrifice 5.1% of their earnings for the option to work from home, especially for 2-3 days a week (7.3%) rather than 5 days a week (2.8%). We also found that the perception of COVID-19 mattered, as workers who perceived it as a threat were willing to give up a much higher share of their earnings than those who did not. However, the willingness to pay did not differ significantly between individuals depending on whether their occupation had a high or a low level of exposure, or between individuals treated in the information experiment and those in the control group.
    Keywords: working from home, discrete choice, information provision experiment, occupational exposures, COVID-19
    JEL: J21 J44
    Date: 2022–04
  5. By: Galanis, Giorgos; Kollias, Iraklis; Leventidis, Ioanis; Lustenhouwer, Joep
    Abstract: The growing literature in behavioral finance and macroeconomics that uses dynamic discrete choice models has overwhelmingly assumed that individual choices are made on the basis of a logit framework. While this assumption allows for analytical tractability, it comes with a number of restrictions with regards to the economic environments it can represent. These restrictions are lifted if a probit framework is used instead. In this paper we compare the two approaches and show that, due to its ability to allow for correlations between the random part of different choice alternatives as well as random taste variation, the probit-based model can better fit actual choice data from an existing laboratory experiment, especially if there are more choice alternatives. On the other hand, for the case of two choice alternatives without random taste variation, the probit-based and logit-based models result in very similar dynamics. But even in that case, we find that important qualitative differences arise - in terms of an additional region of chaos - in the cobweb model of the seminal work of Brock and Hommes (1997). Our work highlights the usefulness of using the probit framework for extensions of existing theoretical models and as a way to better fit dynamic experimental or real world choice data.
    Date: 2022–05–11
  6. By: C. Angelo Guevara
    Abstract: Crawford's et al. (2021) article on estimation of discrete choice models with unobserved or latent consideration sets, presents a unified framework to address the problem in practice by using "sufficient sets", defined as a combination of past observed choices. The proposed approach is sustained in a re-interpretation of a consistency result by McFadden (1978) for the problem of sampling of alternatives, but the usage of that result in Crawford et al. (2021) is imprecise in an important matter. It is stated that consistency would be attained if any subset of the true consideration set is used for estimation, but McFadden (1978) shows that, in general, one needs to do a sampling correction that depends on the protocol used to draw the choice set. This note derives the sampling correction that is required when the choice set for estimation is built from past choices. Then, it formalizes the conditions under which such correction would fulfill the uniform condition property and can therefore be ignored when building practical estimators, such as the ones analyzed by Crawford et al. (2021).
    Date: 2022–05
  7. By: Tra Thi Trinh (National Graduate Institute for Policy Studies, Tokyo, Japan); Alistair Munro (National Graduate Institute for Policy Studies, Tokyo, Japan)
    Abstract: Forecasting the impact of climate change on migration is difficult, given widespread reliance on historical data and limited exposure to actual climate change amongst target populations. This study takes a different approach, developing a new methodology that employs a choice experiment to examine intentions to migrate among farmers living in the Vietnamese Mekong Delta, one of the areas in the world most significantly affected by climate change. The respondents are asked to make migration choices for scenarios constructed using six attributes: drought intensity, flood frequency, income change from migration, migration networks, neighbors’ choices, and crop choice restriction. The results suggest that increasing the intensity/frequency of drought/flood increases the likelihood of migration; the effects are stronger for individuals with prior experience of climate change. Furthermore, the contribution of network attribute is gendered and dependent on migration experience. Finally, crop choice restriction, such as those widely employed by the Vietnamese government to control rice planting, may trigger a higher probability of migration. These findings provide insights into the debate on climate change-migration nexus in rural and lowland areas that are seriously affected by climate change. Furthermore, extensive choice experiment data on migration preferences under a diverse range of climate variabilities facilitates projections of environmentally induced migration.
    Keywords: Climate change; migration; choice experiment; drought and saline intrusion; flood; Vietnam; Mekong Rivers
  8. By: Lindsay E. Relihan
    Abstract: Is online retail a complement or substitute to local offline economies? This paper provides the first evidence that consumers use time saved from online retail to increase their trips for time-intensive services like coffee shops. I use new, detailed data on the daily transactions of millions of anonymized customers. I then estimate a discrete choice model of consumer trip choice, which embeds time use mechanisms and accounts for correlations in trip utility shocks. I show that the model matches key features of observed behaviour that are missed by more standard models, such as the disproportionate increase in trips to nearby coffee shops when consumers switch to online groceries. Model counterfactuals are used to forecast changes in future trip demand and outline strategies, which offline retailers can use to compete against online retail. For consumers, I find that the welfare gains from online grocery platforms go disproportionately to high-income consumers.
    Keywords: online, retail, time use, tips
    Date: 2022–12
  9. By: Cascavilla, Alessandro
    Abstract: Given the increasing relevance of sustainability debates, this paper investigates the relationship between the climate change concern and the willingness to pay an environmental tax, considering the interplay with the general level of individual tax morale. By employing a survey among Italian economics students, we show that the climate change concern affects the attitude towards paying an environmental tax both directly and indirectly, via a change in the preferences between the general and the specific tax morale. We find that also tax immoral subjects are significantly willing to pay an environmental tax as their awareness of climate change increases. Given the goal to increase the public acceptance of an environmental tax, we provide three main policy implications: i) carry on campaigns to increase the general level of tax morale, following the guidelines given by the OECD (2019); ii) raise the climate change awareness among people, for instance through investments in sensibilization campaigns on environmental-related topics; iii) increase awareness about climate change in particular among individuals who show lower attitude towards paying taxes. The evidence about an inconsistent tax preference made us recommend a policy addressed to a specific target group rather than to individuals and based on non-monetary incentives, such as nudging and moral suasion tools.
    Keywords: Energy survey; Carbon tax; Climate change; Tax evasion and avoidance; Environmental Taxes and Subsidies
    JEL: H23 Q40 Q50
    Date: 2022–05
  10. By: Doll, Claire A.; Burton, Michael P.; Pannell, David J.; Rollins, Curtis L.
    Abstract: With climate change, it is becoming more challenging for water-limited cities to sustain historic watering levels in urban parks, leading park managers to consider changes to park designs. But whether and to what extent the public value parks that deviate from conventional designs featuring large areas of irrigated lawn remains uncertain. We use a choice experiment to assess public preferences for different park groundcovers in Perth, Australia. With a scale-adjusted latent class model, we identify optimal groundcover compositions for four preference classes. We find that while having some watered grass in urban parks is important, the public are also accepting of non-irrigated alternatives. Incorporating at least 40% native vegetation cover can increase the utility the public derives from parks and conserve water. Park managers also have a degree of flexibility in designing parks that vary from the optimal groundcover composition but that still deliver near-optimal benefits to communities.
    Keywords: Environmental Economics and Policy, Land Economics/Use
    Date: 2022–05–16
  11. By: Tatiana Komarova; William Matcham
    Abstract: We introduce multivariate ordered discrete response models that exhibit non-lattice structures. From the perspective of behavioral economics, these models correspond to broad bracketing in decision making, whereas lattice models, which researchers typically estimate in practice, correspond to narrow bracketing. There is also a class of hierarchical models, which nests lattice models and is a special case of non-lattice models. Hierarchical models correspond to sequential decision making and can be represented by binary decision trees. In each of these cases, we specify latent processes as a sum of an index of covariates and an unobserved error, with unobservables for different latent processes potentially correlated. This additional dependence further complicates the identification of model parameters in non-lattice models. We give conditions sufficient to guarantee identification under the independence of errors and covariates, compare these conditions to what is required to attain identification in lattice models and outline an estimation approach. Finally, we provide simulations and empirical examples, through which we discuss the case when unobservables follow a distribution from a known parametric family, focusing on popular probit specifications.
    Date: 2022–05
  12. By: Marcus Pivato (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)
    Abstract: We consider a model of intertemporal choice where time is a continuum, the set of instantaneous outcomes (e.g., consumption bundles) is a topological space, and intertemporal plans (e.g., consumption streams) must be continuous functions of time. We assume that the agent can form preferences over plans defined on open time intervals. We axiomatically characterize the intertemporal preferences that admit a representation via discounted utility integrals. In this representation, the utility function is continuous and unique up to positive affine transformations, and the discount structure is represented by a unique Riemann–Stieltjes integral plus a unique linear functional measuring the long-run asymptotic utility.
    Keywords: Intertemporal choice,intergenerational social choice,technological feasibility,continuous utility,Stone-Čech compactification.
    Date: 2021–03–11
  13. By: Paul S. Koh
    Abstract: This paper considers the estimation of static discrete games of complete information under pure strategy Nash equilibrium and no assumptions on the equilibrium selection rule, which is often viewed as computationally difficult due to the need for simulation of latent variables and repeated point-wise testing over a large number of candidate points in the parameter space. We propose computationally attractive approaches that avoid simulation and grid search by characterizing identifying restrictions in closed forms and formulating the identification problem as mathematical programming problems. We show that, under standard assumptions, the inequality restrictions proposed by Andrews, Berry, and Jia (2004) can be expressed in terms of closed-form multinomial logit probabilities, and the corresponding identified set is convex. When actions are binary, the sharp identified set can be characterized using a finite number of closed-form inequalities. We also propose a simple approach to constructing confidence sets for the identified sets. Two real-data experiments are used to illustrate that our methodology can be several orders of magnitude faster than existing approaches.
    Date: 2022–05
  14. By: Vishnu Baburajan; Jo\~ao de Abreu e Silva; Francisco Camara Pereira
    Abstract: To improve the traveling experience, researchers have been analyzing the role of attitudes in travel behavior modeling. Although most researchers use closed-ended surveys, the appropriate method to measure attitudes is debatable. Topic Modeling could significantly reduce the time to extract information from open-ended responses and eliminate subjective bias, thereby alleviating analyst concerns. Our research uses Topic Modeling to extract information from open-ended questions and compare its performance with closed-ended responses. Furthermore, some respondents might prefer answering questions using their preferred questionnaire type. So, we propose a modeling framework that allows respondents to use their preferred questionnaire type to answer the survey and enable analysts to use the modeling frameworks of their choice to predict behavior. We demonstrate this using a dataset collected from the USA that measures the intention to use Autonomous Vehicles for commute trips. Respondents were presented with alternative questionnaire versions (open- and closed- ended). Since our objective was also to compare the performance of alternative questionnaire versions, the survey was designed to eliminate influences resulting from statements, behavioral framework, and the choice experiment. Results indicate the suitability of using Topic Modeling to extract information from open-ended responses; however, the models estimated using the closed-ended questions perform better compared to them. Besides, the proposed model performs better compared to the models used currently. Furthermore, our proposed framework will allow respondents to choose the questionnaire type to answer, which could be particularly beneficial to them when using voice-based surveys.
    Date: 2022–05

This nep-dcm issue is ©2022 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.