nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2020‒11‒02
28 papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre
  1. Effects of rescaling the EU energy label on household preferences for top-rated appliances By Faure, Corinne; Guetlein, Marie-Charlotte; Schleich, Joachim
  2. Nudging and Subsidizing Farmers to Foster Smart Water Meter Adoption By Benjamin Ouvrard; Raphaële Préget; Arnaud Reynaud; Laetitia Tuffery
  3. Dealing with Demand Heterogeneity on Health Care Provider Choice –The Case of Rural China By Martine Audibert; Yong He; Jacky Mathonnat
  4. Harnessing Ambient Sensing & Naturalistic Driving Systems to Understand Links Between Driving Volatility and Crash Propensity in School Zones: A generalized hierarchical mixed logit framework By Behram Wali; Asad Khattak
  5. Contingent choice By Richard S.J. Tol
  6. WTP v WTAC By Richard S.J. Tol
  7. Are Consumers Abandoning Diesel Automobiles because of Contrasting Diesel Policies? Evidence from the Korean Automobile Market By Yoo, Sunbin; Koh, Kyung Woong; Yoshida, Yoshikuni
  8. Valuing carbon offsets By Richard S.J. Tol
  9. Does Open Source Pay off in the Plug-in Hybrid and Electric Vehicle Industry? A Study of Tesla's Open-Source Initiative By Yihan Yan
  10. Random utility models of travel costs By Richard S.J. Tol
  11. Do citizens of a city that owns a local public airport have attachment to the airport and use it? By Morimoto, Yu
  12. Stated preference methods By Richard S.J. Tol
  13. How People Know Their Risk Preference By Ruben C. Arslan; Martin Brümmer; Thomas Dohmen; Johanna Drewelies; Ralph Hertwig; Gert G. Wagner
  14. Benefit transfer By Richard S.J. Tol
  15. Cost-efficient transition to clean energy transportation services By Comello, Stephen; Glenk, Gunther; Reichelstein, Stefan
  16. Contingent valuation By Richard S.J. Tol
  17. Travel costs By Richard S.J. Tol
  18. Valuing Stonehenge By Richard S.J. Tol
  19. Revealed preferences By Richard S.J. Tol
  20. Potential problems with contingent valuation By Richard S.J. Tol
  21. Are there rebound effects from electric vehicle adoption? Evidence from German household data By Huwe, Vera; Gessner, Johannes
  22. Defensive expenditures By Richard S.J. Tol
  23. On the cost of Bayesian posterior mean strategy for log-concave models By Gadat, Sébastien; Panloup, Fabien; Pellegrini, C.
  24. Options for greenhouse gas emission reduction By Richard S.J. Tol
  25. Modelling the costs of greenhouse gas emission reduction By Richard S.J. Tol
  26. Environmental economics before Adam Smith By Richard S.J. Tol
  27. Hedonic pricing By Richard S.J. Tol
  28. Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice By Andrii Babii; Xi Chen; Eric Ghysels; Rohit Kumar
  1. By: Faure, Corinne; Guetlein, Marie-Charlotte; Schleich, Joachim
    Abstract: The European Union has decided to replace its current A+++ to D labelling scheme for cold appliances with a rescaled A to G labelling scheme. Employing a demographically representative discrete choice experiment on refrigerator adoption using an online survey among more than 1000 households in Germa-ny, this paper explores the effects of the rescaled scheme compared to the old scheme on the stated uptake of top-rated refrigerators. Since in practice both schemes will be shown for a transitory period, the paper also analyses the ef-fects of displaying both labels simultaneously. The findings from estimating a mixed logit model suggest that showing the rescaled A to G label alone signifi-cantly increases valuation of top-rated refrigerators compared to showing the current A+++ to D label alone. In comparison, when the A+++ to D and the re-scaled A to G schemes are shown simultaneously, no benefits of introducing the rescaled label are found. Thus, policymakers should strive to enforce the application of the rescaled label scheme as quickly as possible and to shorten transitory periods where both labels are shown simultaneously.
    Keywords: energy efficiency,energy label,appliances,choice experiment
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:zbw:fisisi:s112020&r=all
  2. By: Benjamin Ouvrard (TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Raphaële Préget (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Arnaud Reynaud (TSE - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Laetitia Tuffery (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
    Abstract: In a global context of increasing water scarcity, reducing water use in the agricultural sector is one of the spearheads of sustainable agricultural and environmental policies. New technologies such as smart water meters are promising tools for addressing this issue, but their voluntary adoption by farmers has been limited. Conducting a discrete choice experiment with randomized treatments, we test two policy instruments designed to foster the voluntary adoption of smart water meters: a conditional subsidy and green nudges. The conditional subsidy is offered to farmers who adopt a smart meter only if the rate of adoption in their geographic area is sufficiently high (25%, 50% or 75%). In addition, we implement informational nudges by providing farmers specific messages regarding water scarcity and water management. With the responses of 1,272 French farmers, we show that both policy instruments are effective tools for fostering smart water meter adoption. Surprisingly, our results show that the willingness to pay for the conditional subsidy does not depend on the collective adoption threshold. We also demonstrate that farmers who receive an informational nudge are more likely to opt for a smart water meter. This result calls for a careful joint design of these two policy instruments..
    Keywords: Behavioural economics,Choice experiment,Nudges,French farmers,Smart water meters,Social norms.
    Date: 2020–10–06
    URL: http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02958784&r=all
  3. By: Martine Audibert (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique); Yong He (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique); Jacky Mathonnat (FERDI - Fondation pour les Etudes et Recherches sur le Développement International)
    Abstract: We built a database of two samples of patients surveyed within the same regions in rural China over a time interval of 18 years, and presumed varying demand heterogeneity due to income increase and people aging. We find that while the mean price and distance negative effects on patients choice were present in both time periods, their differences in heterogeneity, which were confirmed with the mixed multinomial logit (MMNL), could have crucial importance in avoiding erroneous policy making based merely on mean price and distance effects. We also find that while both the multinomial logit (MNL) and the MMNL are able to predict price and distance effects with low heterogeneity, only the MMNL appears able to detect the price effect when heterogeneity is high. These findings suggest using caution when interpreting estimation results with the MNL in cases of high heterogeneity.
    Keywords: Chinese rural households,Healthcare choice,Distance effect,Price effect,Mixed multinomial logit models,Multinomial logit,Preference heterogeneity
    Date: 2020–10–07
    URL: http://d.repec.org/n?u=RePEc:hal:journl:halshs-02963761&r=all
  4. By: Behram Wali; Asad Khattak
    Abstract: With the advent of seemingly unstructured big data, and through seamless integration of computation and physical components, cyber-physical systems (CPS) provide an innovative way to enhance safety and resiliency of transport infrastructure. This study focuses on real world microscopic driving behavior and its relevance to school zone safety expanding the capability, usability, and safety of dynamic physical systems through data analytics. Driving behavior and school zone safety is a public health concern. The sequence of instantaneous driving decisions and its variations prior to involvement in safety critical events, defined as driving volatility, can be a leading indicator of safety. By harnessing unique naturalistic data on more than 41,000 normal, crash, and near-crash events featuring over 9.4 million temporal samples of real-world driving, a characterization of volatility in microscopic driving decisions is sought at school and non-school zone locations. A big data analytic methodology is proposed for quantifying driving volatility in microscopic real-world driving decisions. Eight different volatility measures are then linked with detailed event specific characteristics, health history, driving history, experience, and other factors to examine crash propensity at school zones. A comprehensive yet fully flexible state-of-the-art generalized mixed logit framework is employed to fully account for distinct yet related methodological issues of scale and random heterogeneity, containing multinomial logit, random parameter logit, scaled logit, hierarchical scaled logit, and hierarchical generalized mixed logit as special cases. The results reveal that both for school and non-school locations, drivers exhibited greater intentional volatility prior to safety-critical events... ...
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2010.12017&r=all
  5. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of the contingent choice method to value the environment
    Keywords: environmental economics, value, stated preference, contingent choice, choice modelling, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2035&r=all
  6. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of willingness to pay and willingness to accept compensation as values of the environment
    Keywords: environmental economics, value, stated preference, revealed preference, equivalent variation, compensating variation, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2038&r=all
  7. By: Yoo, Sunbin; Koh, Kyung Woong; Yoshida, Yoshikuni
    Abstract: We investigate whether the contrasting set of transportation policies in Korea---reductions in fuel taxes and increases in diesel automobile prices---has decreased emissions. Using a random-coefficient discrete choice model and hypothetical policy sets, we estimate the automobile demand of consumers, the market share of cars by fuel type, and total emissions, assuming that consumer preferences for driving costs change over time. Then, we separately analyze the effect of each policy set on automobile sales and emissions, particularly carbon dioxide, nitrogen oxide, and particulate matter. Our analyses reveal that Korean consumers have become more sensitive toward fuel costs over time and that the emission consequences of Korean policies depend on consumer preferences.
    Keywords: Discrete Choice, Demand Estimation, Emissions, Transportation, Fuel Cost
    JEL: D1 D12 R4 R41
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:103311&r=all
  8. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of application of the contingent choice method to value carbon offsets
    Keywords: environmental economics, value, stated preference, contingent choice, choice modelling, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2036&r=all
  9. By: Yihan Yan
    Abstract: In June 2014, Tesla, a leading manufacturer of electric vehicles, announced it would make its software and hardware available for free to other automakers. This paper analyzes the effect of Tesla's open source initiative on the plug-in hybrid and electric vehicle (PHEV) industry in the US. On the one hand, open source allows PHEV manufacturers to use the advanced technology of Tesla, which could lead to lower investment costs and a higher incentive to invest. Open source also partially removes the entry barriers and could attract more entrants and induce economies of scale, leading to decreased manufacturing costs. On the other hand, underinvestment of Tesla's rivals may occur as a result of free riding, which could result in slower quality improvements in the industry. I quantify these impacts by estimating a dynamic structural model, where players make investment and entry decisions to maximize discounted future returns. My results show that Tesla's initiative was beneficial for the industry and Tesla. I find a 60% drop in investment cost, and a decrease of 100 million in entry cost into the PHEV industry. Counterfactual analysis shows that, had Tesla not provided open source, the industry would have had 33% fewer PHEVs and Tesla would have had one billion less in profit.
    Keywords: Open Source, Dynamics, Quality, Differentiated Products, Discrete Choice, Automobile Industry
    JEL: L11 L15 L62
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2020_218&r=all
  10. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of the use of random utility models in the travel cost method to value the environment
    Keywords: environmental economics, value, revealed preference, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2029&r=all
  11. By: Morimoto, Yu
    Abstract: In this research, it is investigated whether passengers living in a city with a local public airport have attachment to the airport and tend to use it. Focusing on the Greater Kansai area with three airports and Kobe City that owns Kobe Airport as an example, an empirical analysis is conducted by Nested logit model using micro data. The result of the basic model shows that passengers living in Kobe city prefer Kobe Airport compared to other passengers. Additional analysis based on a questionnaire survey revealed that passengers who are attached to Kobe Airport choose it because they love it, which means that the non-economic factor of attachment influences passengers’ decisions. The results of this research suggest that enhancing attachment to the airport might be a possible idea for policy makers of airport cities to increase passengers of it.
    Keywords: Airport choice, Multiple airport region, Airport city, Attachment, Nested logit model
    JEL: L93
    Date: 2020–09–12
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:103442&r=all
  12. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of the principles of stated preference methods to value the environment
    Keywords: environmental economics, value, stated preference, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2031&r=all
  13. 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-report, self-perception
    JEL: D80 D81 D91 D01
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2020_217&r=all
  14. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of benefit transfer to value the environment
    Keywords: environmental economics, value, stated preference, revealed preference, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2037&r=all
  15. By: Comello, Stephen; Glenk, Gunther; Reichelstein, Stefan
    Abstract: Comprehensive global decarbonization will require that transportation services cease to rely on fossil fuels. Here we develop a generic life-cycle cost model to address two closely related questions central to the emergence of sustainable transportation: (i) the utilization rates (hours of operation) that rank-order alternative drivetrains in terms of their cost, and (ii) the cost-efficient share of clean energy drivetrains in a vehicle fleet of competing drivetrains. Calibrating our model framework in the context of urban transit buses, we examine how the comparison between diesel and battery-electric buses varies with the specifics of the duty cycle (route). We find that even for less favorable duty cycles, battery-electric buses will entail lower life-cycle costs once utilization rates exceed 20% of the annual hours. Yet, the current economics of that particular application still calls for a one-third share of diesel drivetrains in a cost-efficient fleet.
    Keywords: clean energy vehicles,transportation services,life-cycle cost,fleet optimization
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:zbw:zewdip:20054&r=all
  16. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of the contingent value method to value the environment
    Keywords: environmental economics, value, stated preference, contingent valuation, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2032&r=all
  17. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of the travel cost method to value the environment
    Keywords: environmental economics, value, revealed preference, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2028&r=all
  18. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of an application of the contingent value method to value Stonehenge
    Keywords: environmental economics, value, stated preference, contingent valuation, stonehenge, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2033&r=all
  19. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of the principles of revealed preference methods for environmental valuation
    Keywords: environmental economics, value, revealed preference, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2026&r=all
  20. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of the possible problems with the contingent value method
    Keywords: environmental economics, value, stated preference, contingent valuation, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2034&r=all
  21. By: Huwe, Vera; Gessner, Johannes
    Abstract: Widespread electric vehicle adoption is considered a major policy goal in order to decarbonize the transport sector. However, potential rebound effects both in terms of vehicle ownership and distance traveled might nullify the environmental edge of electric vehicles. Using cross-sectional household-level microdata from Germany, we identify rebound effects of electric vehicle adoption on both margins for specific subgroups of electric vehicle owners. As our data is cross-sectional, we resort to data-driven methods which are not yet commonly used in the economic literature. For the identification of changes in the number of cars owned after electric vehicle adoption, we predict counterfactual car ownership using a supervised learning approach. Furthermore, we investigate the effect of electric vehicle adoption on household mileage based on a genetic matching of households owning electric vehicles to similar owners of conventional cars. For the selection of covariates for matching, we contrast ad hoc variable selection based on the available literature with a data-driven variable selection method (double LASSO). We cannot verify asignificant increase in the number of cars owned for households with one electric and one conventional vehicle. For the subgroup of households who substitute the electric car for a conventional vehicle, electric vehicle ownership is associated with a significant reduction in annual mileage of -23% of the sample mean. The result indicates a strive for behavior consistent with the environmentally-friendly car choice rather than a rebound effect. Our results are subgroup-specific and may not generalize to the overall population. Methodologically, we find that data-driven variable selection identifies a refined set of covariates and changes the magnitude of the estimation results substantially. It may thus be considered a useful complement, especially in settings with limited theoretical or empirical knowledge established.
    Keywords: Rebound Effect,Electric Vehicle Adoption,Variable Selection
    JEL: R41 Q55
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:zbw:zewdip:20048&r=all
  22. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of defensive expenditure to value the environment
    Keywords: environmental economics, value, revealed preference, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2027&r=all
  23. By: Gadat, Sébastien; Panloup, Fabien; Pellegrini, C.
    Date: 2020–10–15
    URL: http://d.repec.org/n?u=RePEc:tse:wpaper:124826&r=all
  24. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of technical options to reduce greenhouse gas emissions
    Keywords: environmental economics, climate change, undergraduate, postgraduate, video
    JEL: Q54
    Date: 2020–09
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2062&r=all
  25. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of models to estimate the costs of greenhouse gas emission reduction
    Keywords: environmental economics, climate change, undergraduate, postgraduate, video
    JEL: Q54
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2066&r=all
  26. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: History of environmental and resource economics from Zhong Guan to Francois Quesnay
    Keywords: environmental economics, history of economics, undergraduate, video
    JEL: B11 Q50
    Date: 2020–06
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2001&r=all
  27. By: Richard S.J. Tol (Department of Economics, University of Sussex, Falmer, United Kingdom)
    Abstract: Video discussion of hedonic pricing to value the environment
    Keywords: environmental economics, value, revealed preference, undergraduate, video
    JEL: Q50 Q51
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:sus:susvid:2030&r=all
  28. By: Andrii Babii; Xi Chen; Eric Ghysels; Rohit Kumar
    Abstract: The importance of asymmetries in prediction problems arising in economics has been recognized for a long time. In this paper, we focus on binary choice problems in a data-rich environment with general loss functions. In contrast to the asymmetric regression problems, the binary choice with general loss functions and high-dimensional datasets is challenging and not well understood. Econometricians have studied binary choice problems for a long time, but the literature does not offer computationally attractive solutions in data-rich environments. In contrast, the machine learning literature has many computationally attractive algorithms that form the basis for much of the automated procedures that are implemented in practice, but it is focused on symmetric loss functions that are independent of individual characteristics. One of the main contributions of our paper is to show that the theoretically valid predictions of binary outcomes with arbitrary loss functions can be achieved via a very simple reweighting of the logistic regression, or other state-of-the-art machine learning techniques, such as boosting or (deep) neural networks. We apply our analysis to racial justice in pretrial detention.
    Date: 2020–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2010.08463&r=all
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