nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2019‒10‒21
five papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Did the Eco-Car program change the customer base of HVs? By Shigeru Matsumoto
  2. Household Cooking Fuel Choice in India, 2004-2012: A Panel Multinomial Analysis By Kuo, Ying-Min; Azam, Mehtabul
  3. Canadian Consumer Acceptance of Gene-Edited Versus Genetically Modified Potatoes: A Choice Experiment Approach By Muringai, Violet; Fan, Xiaoli; Goddard, Ellen
  4. Analyzing learning effects in the newsvendor model by probabilistic methods By Andersson, Jonas; Jörnsten, Kurt; Lillestøl, Jostein; Ubøe, Jan
  5. Nonparametric estimation of the random coefficients model: An elastic net approach By Heiss, Florian; Hetzenecker, Stephan; Osterhaus, Maximilian

  1. By: Shigeru Matsumoto (Aoyama Gakuin University)
    Abstract: For the last several decades, governments have implemented various energy conservation measures aimed at reducing energy consumption and greenhouse gas emissions from the transportation sector. Among these measures, the spread of next-generation vehicles as an immediate policy goal has been particularly emphasized in recent years. By implementing subsidy programs for a limited period of time, governments try to influence the behavior of households that have not previously considered purchasing the products that have desirable properties. However, no literature has yet identified the households that switched from conventional gasoline vehicles to HVs. In this study, we compare the vehicle choice between three sampling periods (before/during/after the Eco-Car rebate program) and examine whether the rebate program changed the customer base of HVs.For the empirical analysis, we use micro-level data from the Japanese National Survey of Family Income and Expenditure (NSFE), which was collected in 2009 and 2014. NSFE collects data on households? socioeconomic characteristics, such as income/expenditure, savings/liabilities, and ownership of durable goods, as well as information related to houses, such as dwelling characteristics and site area. In addition, NSFE also collects vehicle-related information such as the number of vehicles owned, the year of purchase of each vehicle, and the type of vehicle.The empirical results by multinomial logit analysis demonstrate that the likelihood of HV selection increased substantially during the program period and remained at a high level after the program ended. We also find that households with large net wealth purchased HVs during the Eco-Car program period. Finally, we find that households having a higher income used to purchase HVs earlier. However, income has come to play a less important role in the choice between a HV and SGV after the end of the Eco-Car program.
    Keywords: Eco-Car rebate program, Hybrid Vehicle, Japanese National Survey of Family Income and Expenditure, Multinomial Logit Analysis
    JEL: O33 Q48 R20
    Date: 2019–10
    URL: http://d.repec.org/n?u=RePEc:sek:iacpro:9811334&r=all
  2. By: Kuo, Ying-Min (Oklahoma State University); Azam, Mehtabul (Oklahoma State University)
    Abstract: We use two waves of nationally representative India Human Development Survey to examine factors driving the cooking fuel choice in urban and rural India, separately. We utilize a random effects multinomial logit model that controls for unobserved household heterogeneity. We find that a clean-break with the use of traditional fuels is less likely in rural areas, but more probable in urban areas. The household characteristics (e.g. income, education) that are positively correlated with use of clean fuel also increases the probability of fuel stacking for rural households. We also find that access to paved road is an important determinant for rural household adopting clean fuel, and there exists evidence of social spillover effects in rural areas. Moreover, the bargaining power of women that is associated with economic status (e.g. education or economic freedom) is positively associated with the use of clean fuel. Finally, we find considerable impact of liquefied petroleum gas prices on the probability of use of clean fuel for urban households, but no significant impact for rural households.
    Keywords: fuel choice, fuel stacking, random eects multinomial logit, India
    JEL: Q42 O12 O13 C25
    Date: 2019–10
    URL: http://d.repec.org/n?u=RePEc:iza:izadps:dp12682&r=all
  3. By: Muringai, Violet; Fan, Xiaoli; Goddard, Ellen
    Abstract: In 2016, the second-generation genetically modified (GM) potatoes were approved for production and sale in Canada. In this study, we analyze how consumer acceptance of GM potatoes are affected by various factors including the trait introduced (i.e., the product benefits) by using genetic technologies, the type of breeding technology used, and the developer of the potato with any technology. We conduct an online survey and use a stated choice experiment to collect data on consumer acceptance of GM and gene-edited potatoes in Canada. Random utility models are used to analyze the economic value consumers place on the attributes of the GM and gene-edited potatoes. Our results show that consumers are willing to pay more for a health attribute (reduced acrylamide produced when potatoes are fried) as compared to environmental benefits. Respondents in general need to face discounted prices to buy potatoes created by either gene editing or GM (both transgenic and cisgenic/intragenic) technologies. However, consumers are more accepting of the gene editing technology than GM technologies. Our results also show that government is the most preferred developer of the potatoes. Results from this study can help policymakers design better information policies to improve consumer acceptance of gene-edited and GM potatoes.
    Keywords: Agricultural and Food Policy, Crop Production/Industries, Food Consumption/Nutrition/Food Safety
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:ags:aaacwp:294164&r=all
  4. By: Andersson, Jonas (Dept. of Business and Management Science, Norwegian School of Economics); Jörnsten, Kurt (Dept. of Business and Management Science, Norwegian School of Economics); Lillestøl, Jostein (Dept. of Business and Management Science, Norwegian School of Economics); Ubøe, Jan (Dept. of Business and Management Science, Norwegian School of Economics)
    Abstract: In this paper, we use probabilistic methods to analyze learning effects in a behavioral experiment on the newsvendor model. We argue why we should believe that suggested orders follow a multinomial logit distribution, and use the single parameter in that model to extract information on learning effects. We revisit the data, analyzed previously by Bolton et al. (2012), and show that our model predicts the pull-to-center effect in these experimental data very well.
    Keywords: Behavioral OR; experimental economics; bounded rationality; probabilistic methods; pull-to-center effect
    JEL: C00 C70
    Date: 2019–10–11
    URL: http://d.repec.org/n?u=RePEc:hhs:nhhfms:2019_013&r=all
  5. By: Heiss, Florian; Hetzenecker, Stephan; Osterhaus, Maximilian
    Abstract: This paper investigates and extends the computationally attractive nonparametric random coefficients estimator of Fox, Kim, Ryan, and Bajari (2011). We show that their estimator is a special case of the nonnegative LASSO, explaining its sparse nature observed in many applications. Recognizing this link, we extend the estimator, transforming it to a special case of the nonnegative elastic net. The extension improves the estimator's recovery of the true support and allows for more accurate estimates of the random coefficients' distribution. Our estimator is a generalization of the original estimator and therefore, is guaranteed to have a model fit at least as good as the original one. A theoretical analysis of both estimators' properties shows that, under conditions, our generalized estimator approximates the true distribution more accurately. Two Monte Carlo experiments and an application to a travel mode data set illustrate the improved performance of the generalized estimator.
    Keywords: random coefficients,mixed logit,nonparametric estimation,elastic net
    JEL: C14 C25 L
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:zbw:rwirep:824&r=all

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