nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2023‒10‒09
eight papers chosen by
Edoardo Marcucci, Università degli studi Roma Tre


  1. Moment-Based Estimation of Diffusion and Adoption Parameters in Networks By L. S. Sanna Stephan
  2. Bandwidth Selection for Treatment Choice with Binary Outcomes By Takuya Ishihara
  3. Do Losses Matter? The Effect of Information-Search Technologies on Risky Choices By Luigi Mittone; Mauro Papi
  4. Firm Export Dynamics in Interdependent Markets By Alonso Alfaro-Urena; Juanma Castro-Vincenzi; Sebastian Fanelli; Eduardo Morales
  5. Business strategy pathways for short food supply chains: sharing value between consumers and producers By F. Cirone; M. Masotti; P. Prosperi; S. Bosi; G. Dinelli; M. Vittuari
  6. Privately-Owned versus Shared Automated Vehicle: The Roles of Utilitarian and Hedonic Beliefs By Fatemeh Nazari; Yellitza Soto; Mohamadhossein Noruzoliaee
  7. Charting the Course: How Does Information about Sea Level Rise Affect the Willingness to Migrate? By Laura Bakkensen; Quynh Nquyen; Toan Phan; Paul Shuler
  8. The Mundlak Spatial Estimator By Badi H. Baltagi

  1. By: L. S. Sanna Stephan
    Abstract: According to standard econometric theory, Maximum Likelihood estimation (MLE) is the efficient estimation choice, however, it is not always a feasible one. In network diffusion models with unobserved signal propagation, MLE requires integrating out a large number of latent variables, which quickly becomes computationally infeasible even for moderate network sizes and time horizons. Limiting the model time horizon on the other hand entails loss of important information while approximation techniques entail a (small) error that. Searching for a viable alternative is thus potentially highly beneficial. This paper proposes two estimators specifically tailored to the network diffusion model of partially observed adoption and unobserved network diffusion.
    Date: 2023–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2309.01489&r=dcm
  2. By: Takuya Ishihara
    Abstract: This study considers the treatment choice problem when outcome variables are binary. We focus on statistical treatment rules that plug in fitted values based on nonparametric kernel regression and show that optimizing two parameters enables the calculation of the maximum regret. Using this result, we propose a novel bandwidth selection method based on the minimax regret criterion. Finally, we perform a numerical analysis to compare the optimal bandwidth choices for the binary and normally distributed outcomes.
    Date: 2023–08
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2308.14375&r=dcm
  3. By: Luigi Mittone; Mauro Papi
    Abstract: Despite its importance, relatively little attention has been devoted to studying the effects of exposing individuals to digital choice interfaces. In two pre-registered lottery-choice experiments, we administer three information-search technologies that are based on well-known heuristics: in the ABS (alternative-based search) treatment, subjects explore outcomes and corresponding probabilities within lotteries; in the CBS (characteristic-based search) treatment, subjects explore outcomes and corresponding probabilities across lotteries; in the Baseline treatment, subjects view outcomes and corresponding probabilities all at once. We find that (i) when lottery outcomes comprise gains and losses (experiment 1), exposing subjects to the CBS technology systematically makes them choose safer lotteries, compared to the subjects that are exposed to the other technologies, and (ii) when lottery outcomes comprise gains only (experiment 2), the above results are reversed: exposing subjects to the CBS technology systematically makes them choose riskier lotteries. By combining the information-search and choice analysis, we offer an interpretation of our results that is based on prospect theory, whereby the information-search technology subjects are exposed to contributes to determine the level of attention that the lottery attributes receive, which in turn has an effect on the reference point.
    Date: 2023–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2309.01495&r=dcm
  4. By: Alonso Alfaro-Urena; Juanma Castro-Vincenzi; Sebastian Fanelli; Eduardo Morales
    Abstract: We estimate a model of firm export dynamics featuring cross-country complementarities. The firm decides where to export by solving a dynamic combinatorial discrete choice problem, for which we develop a solution algorithm that overcomes the computational challenges inherent to the large dimensionality of its state space and choice set. According to our estimated model, firms enjoy cost reductions when exporting to countries geographically or linguistically close to each other, or that share deep trade agreements; and countries, especially small ones, sharing these traits with attractive destinations receive significantly more exports than in the absence of complementarities.
    JEL: F12 F13 F14
    Date: 2023–08
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:31610&r=dcm
  5. By: F. Cirone (Université de Bologne); M. Masotti (Université de Bologne); P. Prosperi (CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes, UMR MoISA - Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - IRD - Institut de Recherche pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); S. Bosi (Université de Bologne); G. Dinelli (Université de Bologne); M. Vittuari (Université de Bologne)
    Abstract: Short food supply chains play a vital role in connecting local producers with consumers, promoting sustainability, supporting local economies, and providing access to fresh, high-quality products. However, their market is still underdeveloped due to the mismatching between consumer demand and producer supply. The aim of this work is to identify a common vision between producers and consumers in short food supply chains proposing key actions for an effective business strategy to improve alternative food systems at a territorial level. The strategic long-term vision to foster short food supply chains is based on a direct farmer-to-retailer model. Grounded on the case of an ancient grains supply chain located in Emilia-Romagna, Italy, this research relies on a mixed-method approach including quantitative and qualitative methodologies. A household survey conducted with a representative sample of 1122 Italian households allowed to identify four consumer profiles. Then, two focus groups conducted with 10 food supply chain stakeholders led to the identification of six thematic areas of action. By the backcasting methodology, ancient grains supply chain actors proposed a set of business actions to reach consumers' preferences. Finally, a two rounds Delphi conducted with 23 food supply chain experts allowed to validate the results and the 18 actions to be adopted from 2023 to 2030 for the business strategy pathway. The business strategy pathway can increase the local market presence of ancient grain products, helping producers to plan future business activities and disclose changes in consumer preferences or market conditions.
    Keywords: SUPPLY CHAIN, PRODUCER CONSUMER RELATIONS, COMPANY STRATEGY, MARKETING TECHNIQUES, SUSTAINABLE FOOD, SHORT SUPPLY CHAIN, PROXIMITY, VALUE, CEREALS, EMILIA ROMAGNA, ITALY, CHAINE D'APPROVISIONNEMENT, RELATION PRODUCTEUR CONSOMMATEUR, STRATEGIE DE L'ENTREPRISE, TECHNIQUE DE VENTE, ALIMENTATION DURABLE, CIRCUIT COURT, PROXIMITE, VALEUR, CEREALE, ITALIE
    Date: 2023–09
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-04186888&r=dcm
  6. By: Fatemeh Nazari; Yellitza Soto; Mohamadhossein Noruzoliaee
    Abstract: Transportation systems will be likely transformed by the emergence of automated vehicles (AVs) promising for safe, convenient, and efficient mobility, especially if used in shared systems (shared AV or SAV). However, the potential tendency is observed towards owning AV as a private asset rather than using SAV. This calls for a research on investigating individuals' attitude towards AV in comparison with SAV to recognize the barriers to the public's tendency towards SAV. To do so, the present study proposes a modeling framework based on the theories in behavioral psychology to explain individuals' preference for owning AV over using SAV, built as a latent (subjective) psychometric construct, by three groups of explanatory latent constructs including: (i) desire for searching for benefits, i.e., extrinsic motive manifested in utilitarian beliefs; (ii) tendency towards seeking pleasure and joy, i.e., intrinsic motive reflected in hedonic beliefs; and (iii) attitude towards three configurations of shared mobility, i.e., experience with car and ridesharing, bikesharing, and public transit. Estimated on a sample dataset from the State of California, the findings can shed initial lights on the psychological determinants of the public's attitude towards owning AV versus using SAV, which can furthermore provide policy implications intriguing for policy makers and stakeholders. Of note, the findings reveal the strongest influential factor on preference for AV over SAV as hedonic beliefs reflected in perceived enjoyment. This preference is next affected by utilitarian beliefs, particularly perceived benefit and trust of stranger, followed by attitude towards car and ride sharing.
    Date: 2023–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2309.03283&r=dcm
  7. By: Laura Bakkensen; Quynh Nquyen; Toan Phan; Paul Shuler
    Abstract: An important yet less studied factor in determining the extent of adaptation to climate change is information: are people adequately informed about their vulnerability to future climate-related risks, and does their willingness to adapt depend on this knowledge? Focusing on how communication about projected sea level rise (SLR) affects the willingness to migrate, we implemented a large randomized control survey experiment with a nationally representative sample of more than 7, 000 respondents across all provinces in Vietnam. We randomly assign respondents to different information treatments. We find that providing a simple text-based information treatment about the general extent of Vietnam's exposure to projected SLR increases all respondents' willingness to migrate (including respondents living in areas not vulnerable to SLR). However, a more spatially precise map information treatment—providing the general text along with a map showing Vietnam's projected SLR exposure—leads to a more targeted effect: it only significantly increases the willingness to migrate of respondents currently residing in vulnerable areas. Finally, adding doubt to the information treatments—mentioning an official repudiation of the scientific projection of SLR—does not reduce the treatments' impact. Our findings are inconsistent with the commonly used perfect information benchmark, which assumes that people are fully informed about future climate-related risks. They also highlight the importance of providing spatially precise information in facilitating climate adaptation.
    Keywords: climate change; sea level rise; migration; disaster risk communication; survey experiment; public information
    JEL: Q5
    Date: 2023–09–14
    URL: http://d.repec.org/n?u=RePEc:fip:fedrwp:96878&r=dcm
  8. By: Badi H. Baltagi (Center for Policy Research, Maxwell School, Syracuse University, 426 Eggers Hall, Syracuse, NY 13244)
    Abstract: The spatial Mundlak model first considered by Debarsy (2012) is an alternative to fixed effects and random effects estimation for spatial panel data models. Mundlak modelled the correlated random individual effects as a linear combination of the averaged regressors over time plus a random time-invariant error. This paper shows that if spatial correlation is present whether spatial lag or spatial error or both, the standard Mundlak result in panel data does not hold and random effects does not reduce to its fixed effects counterpart. However, using maximum likelihood one can still estimate these spatial Mundlak models and test the correlated random effects specification of Mundlak using Likelihood ratio tests as demonstrated by Debarsy for the Mundlak spatial Durbin model.
    Keywords: Mundlak Regression, Panel Data, Fixed and Random Effects, Spatial error model, Spatial Durbin model
    JEL: C33
    Date: 2023–09
    URL: http://d.repec.org/n?u=RePEc:max:cprwps:258&r=dcm

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