nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2023‒05‒01
ten papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Resampling-Based Maximum Likelihood Estimation By Takahiro Ito
  2. The Value of Electricity Reliability: Evidence from Battery Adoption By Brown, David P.; Muehlenbachs, Lucija
  3. Traceability, value, and trust in the coffee market: A natural experiment in Ethiopia By Ludovic Mbakop; Glenn P. Jenkins; Leonard Leung; Kamil Sertoglu
  4. Car dependency in the urban margins: the influence of perceived accessibility on mode choice By Blandin, Lola; Vecchio, Giovanni; Hurtubia, Ricardo; Aitken, Ignacio Tiznado
  5. Fighting Free with Free: Freemium vs. Piracy By Antoine Dubus; Christine Halmenschlager; Patrick Waelbroeck
  6. Recursive Preferences and Ambiguity Attitudes By Marinacci Massimo; Principi Giulio; Stanca Lorenzo
  7. Platform pricing choice : Exclusive deals or uniform prices By Shekhar, Shiva
  8. Quasi-experimental evidence on carbon pricing By Vrolijk, Kasper; Sato, Misato
  9. Do Grocery Feedback Systems Enabling Access to Past Consumption Impact Individual Food Purchase Behavior? By Koski, Heli; Kuikkaniemi, Kai; Pantzar, Mika
  10. Estimation of characteristics-based quantile factor models By Chen, Liang; Dolado, Juan José; Gonzalo, Jesús; Pan, Haozi

  1. By: Takahiro Ito (Graduate School of International Cooperation Studies, Kobe University)
    Abstract: This study develops a novel distribution-free maximum likelihood estimator and formulates it for linear and binary choice models. The estimator is consistent and asymptotically normally distributed (at the rate of ???1/2). Monte Carlo simulation results show that the estimator is strongly consistent and efficient. For the binary model, when the linear combination of regressors is leptokurtic, the efficiency loss of having no distribution assumption is virtually nonexistent, and the estimator is always superior to the probit and other semiparametric estimators. The results further show that the estimator performs exceedingly well in the presence of a typical perfect prediction problem.
    Keywords: semiparametric estimator, distribution-free maximum likelihood estimation, Monte Carlo Resampling with Replacement, binary choice model, perfect prediction problem
  2. By: Brown, David P. (University of Alberta, Department of Economics); Muehlenbachs, Lucija (University of Calgary)
    Abstract: To avoid electric-infrastructure-induced wildfires, millions of Californians have had their power cut for hours to days at a time. We show that rooftop solar-plus-battery storage systems increased in zip codes with the longest power outages. Rooftop solar panels alone will not help a household avert outages, but a solar-plus-battery-storage system will. Using this fact, we obtain a revealed preference estimate of the willingness to pay for electricity reliability, the Value of Lost Load, a key parameter for electricity market design. Our estimate, of around $4, 300/MWh, suggests California's wildfire-prevention outages resulted in losses from foregone consumption of $322 million to residential electricity consumers.
    Keywords: batteries; reliability; averting expenditures; power outages; Value of Lost Load
    JEL: Q40 Q54 Q58
    Date: 2023–04–18
  3. By: Ludovic Mbakop (Department of Economics, Eastern Mediterranean University, Famagusta, Northern Cyprus via Mersin 10, Turkey); Glenn P. Jenkins (Department of Economics, Queens University, Kingston, Ontario, Canada and Cambridge Resources International Inc.); Leonard Leung (Asian Development Bank, Manilla, The Philippines); Kamil Sertoglu (Department of Economics, Eastern Mediterranean University, Famagusta, Northern Cyprus via Mersin 10, Turkey)
    Abstract: This study measures the impact of traceability attributes on international buyers’ willingness to pay for coffee produced in Ethiopia and the impact of accurate information on the production location of the coffee on the pricing according to its type and grade. Two sets of regressions models were used to investigate the important determinant factors affecting the export prices of trader and producer coffee, one each for trader and producer coffee, to measure the impact of the ECX on the prices and to evaluate the effect of the coffee types and grades on the prices. The results show that after coffee was forced to be traded via the ECX, traceable coffee export prices increased more than the reported price of non-traceable coffee. We also found that after the introduction of the ECX, the reported export prices of coffee were much more closely aligned to the movements in the international prices of coffee than before the ECX. Furthermore, we also find evidence that exporters and overseas buyers do not trust the results of the inspection and grading of coffee by the ECX unless traceability is also present. This is the first study to evaluate foreign buyers’ willingness to pay for the attribute of traceability of Ethiopian coffee and to see how traceability has affected buyers’ trust in the grades given by the ECX for the coffee it graded.
    Keywords: Ethiopian commodity exchange; Ethiopian coffee; Coffee traceability; Commoditization.
    JEL: D40 E23 Q17
    Date: 2023–04–08
  4. By: Blandin, Lola (Grenoble Applied Economics Lab); Vecchio, Giovanni; Hurtubia, Ricardo; Aitken, Ignacio Tiznado
    Abstract: Car dependence is a dimension of transport poverty whose subjective components have been limitedly explored. Research on car dependence highlights the incidence of transport costs on family budgets, assesses the multidimensional vulnerability of car-dependent subjects and the possibility to access valued opportunities. However, people’s perceptions and their perceived ability to access relevant places can also influence the way in which they move in car dependent settings. In this paper, we aim to examine to which extent perceived accessibility influences mode choices in such areas. Based on a survey carried out in four peripheral and periurban municipalities in the Metropolitan Region of Santiago de Chile, we examine how subjective perceptions of accessibility contribute to explain modal choice in the outskirts of Santiago. Results show that perceived accessibility has a negative net impact on the utilities for both car and public transport, which means that a low perceived accessibility increases the likelihood of choosing motorized modes. Moreover, residents from peripheral municipalities tend to perceive a higher accessibility than households from periurban areas, which are excluded from the public transport system. These findings show the importance of providing nearby opportunities and convenient alternatives to the car in order to limit car dependency, especially in periurban areas.
    Date: 2023–03–28
  5. By: Antoine Dubus (D-MTEC - Department of Management, Technology, and Economics [ETH Zürich] - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]); Christine Halmenschlager; Patrick Waelbroeck
    Abstract: In this article, we show how freemium business models can deter piracy. We analyze a simple freemium model in which a firm offers both a free version and a premium version. The firm can restrict the use of the free version. Consumers can choose between the free and the premium version, but can also get an illegal digital copy. More restrictions can increase the number of premium users but divert other users to piracy. On the contrary, fewer restrictions deter online piracy. We show that with a low level of piracy, the firm sets a high level of restrictions on the free version, which makes the traditional premium business model more profitable than the freemium model. We therefore challenge the idea that strong copyright laws are necessary to protect digital markets. We argue that there are market solutions to fight free with free that better segment consumer audiences according to their willingness to pay for digital music.
    Keywords: Online piracy, versioning, freemium, streaming, copyright, music
    Date: 2023–02–16
  6. By: Marinacci Massimo (Department of Decision Sciences and IGIER, Bocconi University, Italy;); Principi Giulio (Department of Economics, New York University, USA;); Stanca Lorenzo (Department of Economics, Social Studies, Applied Mathematics and Statistics (ESOMAS) and Collegio Carlo Alberto, University of Torino, Italy;)
    Abstract: We illustrate the strong implications of recursivity, a standard assumption in dynamic environments, on attitudes toward uncertainty. In intertemporal consumption choice problems, recursivity always implies constant absolute ambiguity aversion (CAAA) when applying the standard dynamic extension of monotonicity. Our analysis also yields a functional equation called ``generalized rectangularity", as it generalizes the standard notion of rectangularity for recursive maxmin preferences to general certainty equivalents. Our results highlight that if uncertainty aversion is modeled as a form of convexity of preferences, recursivity limits us to only recursive variational preferences.
    Keywords: Dynamic choice, Recursive utility, uUncertainty aversion, Absolute attitudes, Generalized rectangularity.
    JEL: C61 D81
    Date: 2023–04
  7. By: Shekhar, Shiva (Tilburg University, School of Economics and Management)
    Date: 2022
  8. By: Vrolijk, Kasper; Sato, Misato
    Abstract: A growing literature suggests that carbon emissions are most efficiently reduced by carbon pricing. The evidence base on the effectiveness of market-based mechanisms, however, faces three key limitations: studies often (a) predict, rather than evaluate effects, (b) show large difference in findings, and (c) cannot always infer causal relations. Quasi-experimental studies can address these challenges by using variation in policies over time, space, or entities. This paper systematically reviews this new literature, outlines the benefits and caveats of quasi-experimental methodologies, and verifies the reliability and value of quasi-experimental estimates. The overall evidence base documents a causal effect between carbon pricing and emission reductions, with ambiguous effects on economic outcomes, and there are important gaps and inconsistencies. This review underscores that estimates should be interpreted with care because of: (a) inappropriate choice of method, (b) incorrect implementation of empirical analysis (e.g., violate identifying assumptions), and (c) data limitations. More cross-learning across studies and use of novel empirical strategies is needed to improve the empirical evidence base going forward.
    Keywords: carbon pricing; quasi-experimental designs
    JEL: H23 Q58 C21
    Date: 2023–03–29
  9. By: Koski, Heli; Kuikkaniemi, Kai; Pantzar, Mika
    Abstract: Abstract This article empirically explores whether and how providing consumers with detailed access to their past food purchase data at different levels of aggregation affects their subsequent food purchase behavior. We employ unique data covering more than 84, 000 quarterly observations on Finnish consumers’ purchases of various food items from August 2018 to January 2021, as well as their usage of a digital application that provides past purchase data. The data indicate that a digital feedback application that provides consumers with detailed visual and numerical information about their past food item purchases, including both monetary and health-related measures, can impact their future purchase patterns. We find apparent food item-specific and sex-, age- and household-type-specific differences in the ways that the usage of digital feedback applications affects consumers’ food purchase patterns. We find that the feedback system’s usage had the most noticeable and comprehensive impact on the purchase of fruit and vegetables, which was its most promoted and salient feature and provided more detailed purchase information than that for any other food category since the launch of the feedback system. Our empirical findings thus indicate that information salience does matter.
    Keywords: Behavioral economics, Consumer choice, Bounded rationality, Salience, Food purchases, Digital feedback applications, Nudging
    JEL: D12 D83 D9 O33
    Date: 2023–04–18
  10. By: Chen, Liang; Dolado, Juan José; Gonzalo, Jesús; Pan, Haozi
    Abstract: This paper studies the estimation of characteristic-based quantile factor models where the factor loadings are unknown functions of observed individual characteristics while the idiosyncratic error terms are subject to conditional quantile restrictions. We propose a three-stage estimation procedure that is easily implementable in practice and has nice properties. The convergence rates, the limiting distributions of the estimated factors and loading functions, and a consistent selection criterion for the number of factors at each quantile are derived under general conditions. The proposedestimation methodology is shown to work satisfactorily when: (i) the idiosyncratic errors have heavy tails, (ii) the time dimension of the panel dataset is not large, and (iii) the number of factors exceeds the number of characteristics. Finite sample simulations and an empirical application aimed at estimating the loading functions of the daily returns of a large panel of S&P500 index securities help illustrate these properties.
    Keywords: Quantile Factor Models; Nonparametric Quantile Regression; Principal Component Analysis
    Date: 2023–04–14

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