nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2022‒04‒25
eleven papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Discrete choice analysis of health worker job preferences in Ethiopia: separating attribute non-attendance from taste heterogeneity By Arora, Nikita; Quaife, Matthew; Hanson, Kara; Lagarde, Mylène; Woldesenbet, Dorka; Seifu, Abiy; Crastes dit Sourd, Romain
  2. The value of environmentally unsustainable hotel service components to guests - A discrete choice experiment By von Briel, Dorine; Kemperman, Astrid; Dolnicar, Sara
  3. Fueling Alternatives: Gas Station Choice and the Implications for Electric Charging By Jackson Dorsey; Ashley Langer; Shaun McRae
  4. Improving Willingness-to-Pay Elicitation by Including a Benchmark Good By Rebecca Dizon-Ross; Seema Jayachandran
  5. Market Effects of New Product Introduction: Evidence from the Brew-at-home Coffee Market By Gayle, Philip; Lin, Ying
  6. The Biases in Applying Static Demand Models under Dynamic Demand By Takeshi Fukasawa
  7. Identification and Estimation of Categorical Random Coeficient Models By Gao, Z.; Pesaran, M. H.
  8. Commute Mode Share and Access to Jobs across US Metropolitan Areas. By Hao Wu; Andrew Owen; David Levinson
  9. Keeping up with "The Joneses": reference dependent choice with social comparisons By Alastair Langtry
  10. Bivariate Distribution Regression with Application to Insurance Data By Yunyun Wang; Tatsushi Oka; Dan Zhu
  11. Consumer Behavior in the Process of Buying Fashion Products: a Study of Generational Differences in Terms of Shopping Channel Preferences By Richard Fedorko

  1. By: Arora, Nikita; Quaife, Matthew; Hanson, Kara; Lagarde, Mylène; Woldesenbet, Dorka; Seifu, Abiy; Crastes dit Sourd, Romain
    Abstract: When measuring preferences, discrete choice experiments (DCEs) typically assume that respondents consider all available information before making decisions. However, many respondents often only consider a subset of the choice characteristics, a heuristic called attribute non-attendance (ANA). Failure to account for ANA can bias DCE results, potentially leading to flawed policy recommendations. While conventional latent class logit models have most commonly been used to assess ANA in choices, these models are often not flexible enough to separate non-attendance from respondents’ low valuation of certain attributes, resulting in inflated rates of ANA. In this paper, we show that semi-parametric mixtures of latent class models can be used to disentangle successfully inferred non-attendance from respondent’s ‘weaker’ taste sensitivities for certain attributes. In a DCE on the job preferences of health workers in Ethiopia, we demonstrate that such models provide more reliable estimates of inferred non-attendance than the alternative methods currently used. Moreover, since we find statistically significant variation in the rates of ANA exhibited by different health worker cadres, we highlight the need for well-defined attributes in a DCE, to ensure that ANA does not result from a weak experimental design.
    Keywords: attribute non-attendance; Preference heterogeneity; discrete choice experiment; health workers; Grant 212771/Z/18/Z);; Gates Global Health Grant Number: OPP1149259
    JEL: C01 C35 D01 D80
    Date: 2022–02–17
  2. By: von Briel, Dorine; Kemperman, Astrid; Dolnicar, Sara (The University of Queensland)
    Abstract: To contribute to the global effort of making production and consumption more sustainable, the tourism industry must reduce the provision of non-essential service components with negative environmental consequences. This study (1) identifies unsustainable non-essential accommodation services, (2) determines their comparative importance, (3) pinpoints which can be removed with minimal impact on the value of the hotel package for guests, and (4) assesses the potential of two alternative theory-based approaches informed by framing theory (risk reduction by providing autonomy and gain- and loss-framing of price) as implementation strategies for the phasing out of non-essential unsustainable service components. Results from a discrete choice experiment at aggregate and market segment level suggest that tourists see little value in most non-essential unsustainable service components and that gain-framing the price represents the most promising phase-out strategy.
    Date: 2022–03–07
  3. By: Jackson Dorsey; Ashley Langer; Shaun McRae
    Abstract: This paper estimates an imperfect information discrete choice model of drivers’ refueling preferences and analyzes the implications of these preferences for electric vehicle (EV) adoption. Drivers respond four times more to stations’ long-run average prices than to current prices and value travel time at $27.54/hour. EV adopters with home charging receive $829 per vehicle in benefits from avoiding travel to gas stations, whereas refueling travel and waiting time costs increase by $9,169 for drivers without home charging. Increasing the charging speed of the existing network yields 4.7 times greater time savings than a proportional increase in the number of stations.
    JEL: L9 Q42 Q55
    Date: 2022–03
  4. By: Rebecca Dizon-Ross; Seema Jayachandran
    Abstract: We propose and validate a simple way to augment the standard Becker-DeGroot-Marschak method that researchers use to elicit willingness to pay (WTP) for a good. The augmentation is to measure WTP for another good ("benchmark good"), one unrelated to both the good the researcher is interested in and the independent variables of interest, and to use WTP for the benchmark good as a control variable in analyses. We illustrate the method and how it can eliminate noise in measured WTP using data collected in Uganda.
    JEL: C83 O1
    Date: 2022–03
  5. By: Gayle, Philip; Lin, Ying
    Abstract: The introduction of new products has always been an important source of economic development and improvement in consumer welfare. With retail coffee data spanning five years after the single-cup brew coffee pods were introduced to grocery chains, this paper empirically studies the market effects of new product introduction in the brew-at-home coffee market. We use a structural model of demand and supply to capture the changes in consumers’ preference for this new product over time. The demand estimates suggest that consumers’ relative preference and willingness-to-pay for the new product grew substantially over the sample periods. The analysis reveals the extent to which the introduction and growing presence of the new product simultaneously expanded the relevant market and cannibalized the sales of pre-existing substitute products (traditional auto-drip brew coffee products). Furthermore, we quantify the annually expanding welfare gains of the average consumer attributable to the new product.
    Keywords: New product introduction; Willingness-to-pay; Market-expansion; Demand-cannibalization; Brew-at-home coffee market
    JEL: D12 L13 L66
    Date: 2022–02–28
  6. By: Takeshi Fukasawa (Graduate School of Economics, The University of Tokyo and Junior Research Fellow, Research Institute for Economics and Business Administration, Kobe University, JAPAN)
    Abstract: This article investigates why applying static demand models yields biased results under dynamic demand. Recent empirical studies analyzing markets with dynamic demand have found that applying static demand models yields biased estimates of utility parameter estimates and price elasticities of demand. By developing an analytical framework, this study shows how the biases arise and when they are large. There are three sources of biases: inconsistent utility parameter estimates, disregard of state variables (affecting short-run price elasticity), and changing expectations of consumers (affecting long-run price elasticity). The study shows that we can obtain consistent utility parameter estimates by introducing time-group fixed effect terms under some conditions. Short-run own elasticity is overestimated under static models given consistent utility parameter estimates and nonexistence of unobserved consumer heterogeneity. Especially when the focus is on the large market share products, the second and the third sources of biases induce large biases in price elasticities.
    Keywords: Dynamic demand; Static demand model; Estimation bias; Price elasticity of demand; Dynamic discrete choice
    Date: 2022–04
  7. By: Gao, Z.; Pesaran, M. H.
    Abstract: This paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A Generalized Method of Moments estimator is proposed, and its finite sample properties are examined using Monte Carlo simulations. The utility of the proposed method is illustrated by estimating the distribution of returns to education in the U.S. by gender and educational levels. We find that rising heterogeneity between educational groups is mainly due to the increasing returns to education for those with postsecondary education, whereas within group heterogeneity has been rising mostly in the case of individuals with high school or less education.
    Keywords: Random coefficient models, categorical distribution, return to education
    JEL: C01 C21 C13 C46 J30
    Date: 2022–04–14
  8. By: Hao Wu; Andrew Owen; David Levinson (TransportLab, School of Civil Engineering, University of Sydney)
    Abstract: How much of the variation in transit mode share is attributable to accessibility is not well understood, despite its significant policy implications. It is hypothesized that better transit accessibility leads to higher transit mode share. This paper explains block group level transit mode share using transit accessibility in a logistic model for 48 major US metropolitan areas. Transit accessibility alone explains much of the variation in transit mode share for all 48 regions despite their geographical differences (adjusted R2 0.61, potential accessibility); models for individual cities have stable and interpretable parameters for transit accessibility. The models better explain mode share in cities with higher person weighted transit accessibility and larger populations; an adjusted R2 of 0.76 is achieved for New York City with transit accessibility as the only explanatory variable. Additional automobile accessibility and income variables modestly improve model fit. Time–decay functions fitted to accessibility measures better explain mode choice than the isochrone accessibility, and suggest the catchment area affecting transit mode choice to be within 35 minutes. This work contributes to the understanding of transit mode share by solidifying its link with accessibility, which is determined by the structure of the transport network and land development.
    Keywords: Access, transit mode share, continuous accessibility
    JEL: R41 C93
    Date: 2021
  9. By: Alastair Langtry
    Abstract: Keeping up with "The Joneses" matters. This paper examines a model of reference dependent choice where reference points are determined by social comparisons. An increase in the strength of social comparisons, even by only a few agents, increases consumption and decreases welfare for everyone. Strikingly, a higher marginal cost of consumption can increase welfare. In a labour market, social comparisons with co-workers create a big fish in a small pond effect, inducing incomplete labour market sorting. Further, it is the skilled workers with the weakest social networks who are induced to give up income to become the big fish.
    Date: 2022–03
  10. By: Yunyun Wang; Tatsushi Oka; Dan Zhu
    Abstract: This article introduces an estimation method for the conditional joint distribution of bivariate outcomes, based on the distribution regression approach and the factorization method. The proposed method can apply for discrete, continuous or mixed distribution outcomes. It is semiparametric in that both marginal and joint distributions are left unspecified, conditional on covariates. Unlike the existing parametric approaches, our method is simple yet flexible to encapsulate distributional dependence structures of bivariate outcomes and covariates. Various simulation results confirm that our method can perform similarly or better in finite samples compared to the alternative methods. In an application to the study of a motor third-part liability insurance portfolio, the proposed method effectively captures key distributional features in the data, especially the value at risks conditional on covariates. This result suggests that this semiparametric approach can serve as an alternative in insurance risk management.
    Date: 2022–03
  11. By: Richard Fedorko (Faculty of Management and Business, University of Presov, Konstantinova 16, 080 01 Presov, Slovakia Author-2-Name: Radovan Bacik Author-2-Workplace-Name: Faculty of Management and Business, University of Presov, Konstantinova 16, 080 01 Presov, Slovakia Author-3-Name: Maria Olearova Author-3-Workplace-Name: Faculty of Management and Business, University of Presov, Konstantinova 16, 080 01 Presov, Slovakia Author-4-Name: Author-4-Workplace-Name: Author-5-Name: Author-5-Workplace-Name: Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:)
    Abstract: "Objective - The main objective of the present study was to investigate, using a sample of 486 Slovak consumers, whether there are differences between Generations X, Y, and Z in how often they use single-channel and cross-channel shopping during the process of buying fashion products. Methodology/Technique - As it turned out, consumers of all generations, regardless of differences, have adopted the innovative online way of shopping due to the development of new technologies, and they seem to be very willing to combine it with the traditional one during the shopping process. Applying the Kruskal Wallis test and boxplots showed that significant differences were measured between Generation X and Y, between Generation X and Z, but not between Generation Y and Z. Findings - Therefore, the results of the analysis suggest that the oldest generation of consumers (Generation X), achieves the lowest frequency in terms of the purchase journey in the mode of searching and at the same time buying fashion products via the internet. The research with its findings contributes to the current literature on the general understanding of consumer behavior from the perspective of single-channel and cross-channel shopping. Novelty - Understanding which shopping channels are preferred by consumers leads to improved consumer trust, increased consumer loyalty, and also increased conversion rate, thus creating more significant sales opportunities for retailers. In light of the ever-changing market environment and the development of new technologies, the results can also be beneficial for retailers, as it is essential to monitor the purchase journey and consumer behaviour continuously. Type of Paper - Empirical"
    Keywords: Consumer Behavior; Shopping Channel; Cross-Channel; Showrooming; Webrooming
    JEL: M30 M31 M37
    Date: 2022–03–31

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