nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2023‒02‒06
twelve papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. E-commerce users' preferences for delivery options By Yuki Oyama; Daisuke Fukuda; Naoto Imura; Katsuhiro Nishinari
  2. Ask a local: improving the public pricing of land titles in urban Tanzania By Manara, Martina; Regan, Tanner
  3. Fitting mixed logit random regret minimization models using maximum simulated likelihood By Ziyue Zhu; \'Alvaro A. Guti\'errez-Vargas; Martina Vandebroek
  4. Is online retail killing coffee shops? Estimating the winners and losers of online retail using customer transaction microdata By Relihan, Lindsay
  5. Willingness to Accept, Willingness to Pay, and Loss Aversion By Jonathan Chapman; Mark Dean; Pietro Ortoleva; Erik Snowberg; Colin Camerer
  6. The Beta-Delta-DELTA Sweet Spot By David Laibson; Peter Maxted
  7. Technology Choice, Externalities in Production, and a Chaotic Middle-Income Trap By Takao Asano; Akihisa Shibata; Masanori Yokoo
  8. Initiation of knowledge and technology transfer from academia to industry: Opportunity recognition and transfer channel choice By Matthias Huegel; Philip Doerr; Martin Kalthaus
  9. Mandatory Seatbelt Laws and Traffic Fatalities: A Reassessment By Anderson, D. Mark; Liang, Yang; Sabia, Joseph J.
  10. Non-Stochastic CDF Estimation Using Threshold Queries By Princewill Okoroafor; Vaishnavi Gupta; Robert Kleinberg; Eleanor Goh
  11. Ensemble MCMC sampling for robust Bayesian inference By Böhl, Gregor
  12. Bayesian Contextual Choices under Imperfect Perception of Attributes By Junnan He

  1. By: Yuki Oyama; Daisuke Fukuda; Naoto Imura; Katsuhiro Nishinari
    Abstract: Many e-commerce marketplaces offer their users fast delivery options for free to meet the increasing needs of users, imposing an excessive burden on city logistics. Therefore, understanding e-commerce users' preference for delivery options is a key to designing logistics policies. To this end, this study designs a stated choice survey in which respondents are faced with choice tasks among different delivery options and time slots, which was completed by 4, 062 users from the three major metropolitan areas in Japan. To analyze the data, mixed logit models capturing taste heterogeneity as well as flexible substitution patterns have been estimated. The model estimation results indicate that delivery attributes including fee, time, and time slot size are significant determinants of the delivery option choices. Associations between users' preferences and socio-demographic characteristics, such as age, gender, teleworking frequency and the presence of a delivery box, were also suggested. Moreover, we analyzed two willingness-to-pay measures for delivery, namely, the value of delivery time savings (VODT) and the value of time slot shortening (VOTS), and applied a non-semiparametric approach to estimate their distributions in a data-oriented manner. Although VODT has a large heterogeneity among respondents, the estimated median VODT is 25.6 JPY/day, implying that more than half of the respondents would wait an additional day if the delivery fee were increased by only 26 JPY, that is, they do not necessarily need a fast delivery option but often request it when cheap or almost free. Moreover, VOTS was found to be low, distributed with the median of 5.0 JPY/hour; that is, users do not highly value the reduction in time slot size in monetary terms. These findings on e-commerce users' preferences can help in designing levels of service for last-mile delivery to significantly improve its efficiency.
    Date: 2022–12
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2301.00666&r=dcm
  2. By: Manara, Martina; Regan, Tanner
    Abstract: Information on willingness-to-pay is key for public pricing and allocation of services but not easily collected. Studying land titles in Dar-es-Salaam, we ask whether local leaders know and will reveal plot owners' willingness-to-pay. We randomly assign leaders to predict under different settings then elicit owners' actual willingness-to-pay. Demand is substantial, but below exorbitant fees. Leaders can predict the aggregate demand curve and distinguish variation across owners. Predictions worsen when used to target subsidies, but adding cash incentives mitigates this. Finally, we demonstrate that leader-elicited information can improve the public pricing of title deeds, raising uptake while maintaining public funds.
    Keywords: property rights; willingness-to-pay; public pricing; local publicly provided goods
    JEL: O17 H40 R21 D80
    Date: 2022–04–28
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:117856&r=dcm
  3. By: Ziyue Zhu; \'Alvaro A. Guti\'errez-Vargas; Martina Vandebroek
    Abstract: This article describes the mixrandregret command, which extends the randregret command introduced in Guti\'errez-Vargas et al. (2021, The Stata Journal 21: 626-658) incorporating random coefficients for Random Regret Minimization models. The newly developed command mixrandregret allows the inclusion of random coefficients in the regret function of the classical RRM model introduced in Chorus (2010, European Journal of Transport and Infrastructure Research 10: 181-196). The command allows the user to specify a combination of fixed and random coefficients. In addition, the user can specify normal and log-normal distributions for the random coefficients using the commands' options. The models are fitted using simulated maximum likelihood using numerical integration to approximate the choice probabilities.
    Date: 2023–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2301.01091&r=dcm
  4. By: Relihan, Lindsay
    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
    JEL: D12 J20 L81 R12
    Date: 2022–03–03
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:117805&r=dcm
  5. By: Jonathan Chapman; Mark Dean; Pietro Ortoleva; Erik Snowberg; Colin Camerer
    Abstract: We use four incentivized representative surveys to study the endowment effect for lotteries in 4, 000 U.S. adults. We replicate the standard finding of an endowment effect—the divergence between Willingness to Accept (WTA) and Willingness to Pay (WTP), but document three new findings. First, we find little evidence that the endowment effect is related to loss aversion for risky prospects, counter to predictions of popular theories in economics. Second, WTA and WTP not only diverge, but are, at best, weakly correlated. Third, WTA and WTP strongly relate to other aspects of risk preferences. The structure of these behaviors points to different theories of the endowment effect.
    JEL: C90 D81 D91
    Date: 2023–01
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:30836&r=dcm
  6. By: David Laibson; Peter Maxted
    Abstract: When solving discrete-time consumption models with present-biased time preferences, backwards induction generates equilibria that are non-robust in the sense that policy functions are often sensitive to parameter choices, including the modeler's choice of the time-step. The current paper identifies a range of "sweet-spot" time-steps that (i) contains the psychologically relevant present bias horizons, and, (ii) generates numerically indistinguishable (i.e., robust) policy functions. This sweet spot includes both a computationally feasible range of discrete-time cases and the limiting continuous-time case (Harris and Laibson, 2013). Accordingly, researchers modeling present bias in buffer stock models can choose either discrete-time cases calibrated to be in the sweet spot or the analytically tractable continuous-time case; these approaches yield essentially identical policy functions.
    JEL: C6 D15 D9 D99 E03 E21 E7 G51
    Date: 2023–01
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:30822&r=dcm
  7. By: Takao Asano (Okayama University); Akihisa Shibata (Kyoto University); Masanori Yokoo (Okayama University)
    Abstract: We incorporate the external effects of capital in production and endogenous technology choice into the standard overlapping generations model. We demonstrate that our model can exhibit a poverty trap, a middle-income trap, and perpetual growth paths. We also show that, under some economic conditions, an economy exhibits all three of these phenomena, depending on its initial capital level, and that the economy caught in the middle-income trap can exhibit chaotic fluctuations in the long run. In obtaining these results in the standard overlapping generations model, the combination of technology choice and externalities in production plays a crucial role.
    Keywords: External effect; Technology choice; Overlapping generations model, Middle-income trap; Chaos
    Date: 2023–01
    URL: http://d.repec.org/n?u=RePEc:kyo:wpaper:1090&r=dcm
  8. By: Matthias Huegel (Friedrich Schiller University Jena, Department of Economics); Philip Doerr (Friedrich Schiller University Jena, Department of Economics); Martin Kalthaus (Friedrich Schiller University Jena, Department of Economics)
    Abstract: The transfer of knowledge and technology from academia to industry is usually understood as a process. While previous research focuses on phenomena along the process and its outcomes, the starting point of the process – the initiation of a transfer activity – remains unstudied. We provide first empirical insights on the initiation of the transfer process and conceptualize this initiation as a simultaneous recognition of a transfer opportunity and the choice of a transfer channel. We focus on Science-Industry collaboration, Intellectual Property Rights and spin-off creation as relevant channels. We use survey data from 1, 149 scientists from the German state of Thuringia and utilize seemingly unrelated regressions to account for selection and multiple channel choices in our econometric approach. Our results show a positive relationship between scientists’ probability to recognize a transfer opportunity and different kinds of prior knowledge. Contrary to our expectation, scientific quality reduces the likelihood of recognizing a transfer opportunity. For the choice of the transfer channel, the results show a positive relationship between choosing the spin-off channel and risk willingness, as well as basic research. Applied research increases the likelihood to choose Intellectual Property Rights as a channel. Furthermore, role models are positively associated with these two channels.
    Keywords: Transfer Process, Transfer Initiation, Opportunity Recognition, Transfer Channel, Science-Industry Collaboration, Intellectual Property Right, Academic Spin-off
    JEL: L26 O31 O33 O34
    Date: 2023–01–18
    URL: http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2023-002&r=dcm
  9. By: Anderson, D. Mark (Montana State University); Liang, Yang (San Diego State University); Sabia, Joseph J. (San Diego State University)
    Abstract: Using data from the Fatality Analysis Reporting System for the period 1983-1997, Cohen and Einav (Review of Economics and Statistics 2003; 85(4): 828–843) found that mandatory seatbelt laws were associated with a 4 to 6 percent reduction in traffic fatalities among motor vehicle occupants. After successfully replicating their two-way fixed effects estimates, we (1) add 22 years of data (1998-2019) to capture additional seatbelt policy variation and observe a longer post-treatment period, (2) employ the interaction-weighted estimator proposed by Sun and Abraham (2021) to address potential bias due to heterogeneous and dynamic treatment effects, and (3) estimate event-study models to investigate pre-treatment trends and explore lagged post-treatment effects. Consistent with Cohen and Einav (2003), our updated estimates show that primary seatbelt laws are associated with a 5 to 9 percent reduction in fatalities among motor vehicle occupants. Estimated effects of secondary seatbelt laws are smaller in magnitude and sensitive to model choice.
    Keywords: mandatory seatbelt laws, traffic fatalities, traffic safety
    JEL: C13 I12 K32 K42
    Date: 2022–12
    URL: http://d.repec.org/n?u=RePEc:iza:izadps:dp15843&r=dcm
  10. By: Princewill Okoroafor; Vaishnavi Gupta; Robert Kleinberg; Eleanor Goh
    Abstract: Estimating the empirical distribution of a scalar-valued data set is a basic and fundamental task. In this paper, we tackle the problem of estimating an empirical distribution in a setting with two challenging features. First, the algorithm does not directly observe the data; instead, it only asks a limited number of threshold queries about each sample. Second, the data are not assumed to be independent and identically distributed; instead, we allow for an arbitrary process generating the samples, including an adaptive adversary. These considerations are relevant, for example, when modeling a seller experimenting with posted prices to estimate the distribution of consumers' willingness to pay for a product: offering a price and observing a consumer's purchase decision is equivalent to asking a single threshold query about their value, and the distribution of consumers' values may be non-stationary over time, as early adopters may differ markedly from late adopters. Our main result quantifies, to within a constant factor, the sample complexity of estimating the empirical CDF of a sequence of elements of $[n]$, up to $\varepsilon$ additive error, using one threshold query per sample. The complexity depends only logarithmically on $n$, and our result can be interpreted as extending the existing logarithmic-complexity results for noisy binary search to the more challenging setting where noise is non-stochastic. Along the way to designing our algorithm, we consider a more general model in which the algorithm is allowed to make a limited number of simultaneous threshold queries on each sample. We solve this problem using Blackwell's Approachability Theorem and the exponential weights method. As a side result of independent interest, we characterize the minimum number of simultaneous threshold queries required by deterministic CDF estimation algorithms.
    Date: 2023–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2301.05682&r=dcm
  11. By: Böhl, Gregor
    Abstract: This paper proposes a Differential-Independence Mixture Ensemble (DIME) sampler for the Bayesian estimation of macroeconomic models. It allows sampling from particularly challenging, high-dimensional black-box posterior distributions which may also be computationally expensive to evaluate. DIME is a "Swiss Army knife", combining the advantages of a broad class of gradient-free global multi-start optimizers with the properties of a Monte Carlo Markov chain. This includes (i) fast burn-in and convergence absent any prior numerical optimization or initial guesses, (ii) good performance for multimodal distributions, (iii) a large number of chains (the "ensemble") running in parallel, (iv) an endogenous proposal density generated from the state of the full ensemble, which (v) respects the bounds of the prior distribution. I show that the number of parallel chains scales well with the number of necessary ensemble iterations. DIME is used to estimate the medium-scale heterogeneous agent New Keynesian ("HANK") model with liquid and illiquid assets, thereby for the first time allowing to also include the households' preference parameters. The results mildly point towards a less accentuated role of household heterogeneity for the empirical macroeconomic dynamics.
    Keywords: Bayesian Estimation, Monte Carlo Methods, Heterogeneous Agents, Global Optimization, Swiss Army Knife
    JEL: C11 C13 C15 E10
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:zbw:imfswp:177&r=dcm
  12. By: Junnan He (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)
    Abstract: The classical rational choice theory proposes that preferences are context-independent, e.g. independent of irrelevant alternatives. Empirical choice data, however, display several contextual choice effects that seem inconsistent with rational preferences. We study a choice model with a fixed underlying utility function and explain contextual choices with a novel information friction: the agent's perception of the options is affected by an attribute-specific noise. Under this friction, the agent learns useful information when she sees more options. Therefore, the agent chooses contextually, exhibiting intransitivity, joint-separate evaluation reversal, attraction effect, compromise effect, similarity effect, and phantom decoy effect. Nonetheless, because the noise is attribute-specific and common across alternatives, the agent's choice is perfectly rational whenever an option clearly dominates others.
    Keywords: Compromise effect, Context effect, Imperfect perception, Intransitive choices, Joint-separate evaluation reversal, Phantom decoy effect, Stable preferences.
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:hal:spmain:hal-03878378&r=dcm

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