nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2024‒02‒12
ten papers chosen by
Edoardo Marcucci, Università degli studi Roma Tre


  1. Robust Analysis of Short Panels By Andrew Chesher; Adam M. Rosen; Yuanqi Zhang
  2. Identification of Dynamic Nonlinear Panel Models under Partial Stationarity By Wayne Yuan Gao; Rui Wang
  3. An Experiment on a Multi-Period Beauty Contest Game By Nobuyuki Hanaki; Yuta Takahashi
  4. Identification with possibly invalid IVs By Christophe Bruneel-Zupanc; Jad Beyhum
  5. Unpacking Overconfident Behavior When Betting on Oneself By Mohammed Abdellaoui; Han Bleichrodt; Cédric Gutierrez
  6. Collecting data on sensitive experiences and attitudes: a Malian case study By Olivia Bertelli; Thomas Calvo; Massa Coulibaly; Moussa Coulibaly; Emmanuelle Lavallée; Marion Mercier; Sandrine Mesplé-Somps; Ousmane Z Traoré
  7. Covariance Function Estimation for High-Dimensional Functional Time Series with Dual Factor Structures By Chenlei Leng; Degui Li; Hamlin Shang; Yingcun Xia
  8. The impact of online shopping motivation on customer loyalty in Mobile Applications By Nguyen, Nguyen-Hong; Nguyen, Luan-Thanh
  9. Interactions between dynamic team composition and coordination: An agent-based modeling approach By Dar\'io Blanco-Fern\'andez; Stephan Leitner; Alexandra Rausch
  10. Anonymous and Strategy-Proof Voting under Subjective Expected Utility Preferences By Eric Bahel

  1. By: Andrew Chesher; Adam M. Rosen; Yuanqi Zhang
    Abstract: Many structural econometric models include latent variables on whose probability distributions one may wish to place minimal restrictions. Leading examples in panel data models are individual-specific variables sometimes treated as "fixed effects" and, in dynamic models, initial conditions. This paper presents a generally applicable method for characterizing sharp identified sets when models place no restrictions on the probability distribution of certain latent variables and no restrictions on their covariation with other variables. In our analysis latent variables on which restrictions are undesirable are removed, leading to econometric analysis robust to misspecification of restrictions on their distributions which are commonplace in the applied panel data literature. Endogenous explanatory variables are easily accommodated. Examples of application to some static and dynamic binary, ordered and multiple discrete choice and censored panel data models are presented.
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.06611&r=dcm
  2. By: Wayne Yuan Gao; Rui Wang
    Abstract: This paper studies identification for a wide range of nonlinear panel data models, including binary choice, ordered repsonse, and other types of limited dependent variable models. Our approach accommodates dynamic models with any number of lagged dependent variables as well as other types of (potentially contemporary) endogeneity. Our identification strategy relies on a partial stationarity condition, which not only allows for an unknown distribution of errors but also for temporal dependencies in errors. We derive partial identification results under flexible model specifications and provide additional support conditions for point identification. We demonstrate the robust finite-sample performance of our approach using Monte Carlo simulations, with static and dynamic ordered choice models as illustrative examples.
    Date: 2023–12
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.00264&r=dcm
  3. By: Nobuyuki Hanaki; Yuta Takahashi
    Abstract: We present and conduct a novel experiment on a multi-period beauty contest game motivated by the canonical New-Keynesian model. Participants continuously provide forecasts for prices spanning multiple future periods. These forecasts determine the price for the current period and participants’ payoffs. Our findings are threefold. First, the observed prices in the experiment deviate more from the rational expectations equilibrium prices under strategic complementarity than under strategic substitution. Second, participants’ expectations respond to announcements of future shocks on average. Finally, participants employ heuristics in their forecasting; however, the choice of heuristic varies with the degree of strategic complementarity.
    Date: 2023–09
    URL: http://d.repec.org/n?u=RePEc:dpr:wpaper:1213r&r=dcm
  4. By: Christophe Bruneel-Zupanc; Jad Beyhum
    Abstract: This paper proposes a novel identification strategy relying on quasi-instrumental variables (quasi-IVs). A quasi-IV is a relevant but possibly invalid IV because it is not completely exogenous and/or excluded. We show that a variety of models with discrete or continuous endogenous treatment, which are usually identified with an IV - quantile models with rank invariance additive models with homogenous treatment effects, and local average treatment effect models - can be identified under the joint relevance of two complementary quasi-IVs instead. To achieve identification we complement one excluded but possibly endogenous quasi-IV (e.g., ``relevant proxies'' such as previous treatment choice) with one exogenous (conditional on the excluded quasi-IV) but possibly included quasi-IV (e.g., random assignment or exogenous market shocks). In practice, our identification strategy should be attractive since complementary quasi-IVs should be easier to find than standard IVs. Our approach also holds if any of the two quasi-IVs turns out to be a valid IV.
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.03990&r=dcm
  5. By: Mohammed Abdellaoui (HEC Paris - Ecole des Hautes Etudes Commerciales); Han Bleichrodt (UA - Université d'Alicante, Espagne); Cédric Gutierrez (Università Bocconi)
    Abstract: Overconfident behavior, the excessive willingness to bet on one's performance, may be driven by optimistic beliefs and/or ambiguity attitudes. Separating these factors is key for understanding and correcting overconfident behavior, as they call for different corrective actions. We present a method to do so, which we implement in two incentivized experiments. The first experiment shows the importance of ambiguity attitudes for overconfident behavior. Optimistic ambiguity attitudes (ambiguity seeking) counterbalanced the effect of pessimistic beliefs, leading to neither over- nor underconfident behavior. The second experiment applies our method in contexts where overconfident behavior is expected to vary: easy versus hard tasks. Our results showed that task difficulty affected both beliefs and ambiguity attitudes. However, although beliefs were more optimistic for relative performance (rank) and more pessimistic for absolute performance (score) on easy tasks compared with hard tasks, ambiguity attitudes were always more optimistic on easy tasks for both absolute and relative performance. Our findings show the subtle interplay between beliefs and ambiguity attitudes: they can reinforce or offset each other, depending on the context, increasing or lowering overconfident behavior. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Funding: This work was supported by HEC Paris research budget and Bocconi junior researchers' grants. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2021.00165 .
    Date: 2023–12–06
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-04383402&r=dcm
  6. By: Olivia Bertelli; Thomas Calvo; Massa Coulibaly; Moussa Coulibaly; Emmanuelle Lavallée; Marion Mercier (LEDa - Laboratoire d'Economie de Dauphine - IRD - Institut de Recherche pour le Développement - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique); Sandrine Mesplé-Somps; Ousmane Z Traoré
    Abstract: In standard household surveys, the data collected are exposed to response bias, particularly for questions considered sensitive. The List Experiment method is an alternative survey technique for limiting these biases. This article presents the results of an experimental survey conducted using this method with 1, 509 individuals throughout Mali. Individuals were surveyed by telephone during the summer of 2021 about their experiences and political attitudes related to insecurity. From a methodological point of view, we have drawn a number of lessons from the survey: among others, a very good understanding and acceptability of the method by the respondents, due in particular to the quality of the interviewers and supervisors; the need for a more complex sample design than for a standard questionnaire; and the importance of a short questionnaire when surveying by telephone. From an analytical point of view, the survey reveals the existence of significant social desirability biases - particularly for questions concerning political attitudes in relation to insecurity.
    Abstract: Dans les enquêtes standards auprès des ménages, les données collectées sont exposées à des biais de réponses, particulièrement pour les questions considérées comme sensibles. La méthode par comptage de réponses est une technique d'enquête alternative permettant de limiter ces biais. Cet article présente les résultats d'une enquête expérimentale menée selon cette méthode auprès de 1 509 individus sur l'ensemble du territoire malien. Les personnes ont été sondées par téléphone durant l'été 2021 à propos d'expériences et d'attitudes politiques liées à l'insécurité. D'un point de vue méthodologique, nous en tirons plusieurs enseignements : entre autres, une très bonne compréhension et acceptabilité de la méthode par les enquêté·e·s, qui tient notamment à la qualité des enquêteur·trice·s et des superviseur·se·s ; la nécessité d'un plan de sondage plus complexe que pour un questionnaire standard ; et l'importance d'un questionnaire court lorsqu'on enquête par téléphone. Du point de vue analytique, l'enquête fait ressortir l'existence de biais déclaratifs significatifs – notamment pour les questions portant sur les préférences politiques en lien avec l'insécurité.
    Keywords: Phone survey, social desirability bias, Mali, List Experiment, Security, Phone survey social desirability bias Mali List Experiment Security
    Date: 2023–12–20
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-04366322&r=dcm
  7. By: Chenlei Leng; Degui Li; Hamlin Shang; Yingcun Xia
    Abstract: We propose a flexible dual functional factor model for modelling high-dimensional functional time series. In this model, a high-dimensional fully functional factor parametrisation is imposed on the observed functional processes, whereas a low-dimensional version (via series approximation) is assumed for the latent functional factors. We extend the classic principal component analysis technique for the estimation of a low-rank structure to the estimation of a large covariance matrix of random functions that satisfies a notion of (approximate) functional "low-rank plus sparse" structure; and generalise the matrix shrinkage method to functional shrinkage in order to estimate the sparse structure of functional idiosyncratic components. Under appropriate regularity conditions, we derive the large sample theory of the developed estimators, including the consistency of the estimated factors and functional factor loadings and the convergence rates of the estimated matrices of covariance functions measured by various (functional) matrix norms. Consistent selection of the number of factors and a data-driven rule to choose the shrinkage parameter are discussed. Simulation and empirical studies are provided to demonstrate the finite-sample performance of the developed model and estimation methodology.
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.05784&r=dcm
  8. By: Nguyen, Nguyen-Hong; Nguyen, Luan-Thanh
    Abstract: With the rapid advancement of technology, online shopping has become increasingly popular, revolutionizing the way consumers make purchases. In recent years, mobile applications have emerged as a convenient platform for online shopping, providing users with anytime, anywhere access to a wide range of products and services. This research aims to investigate the impact of online shopping motivation on consumer behavior within the context of mobile applications, through the Reasoned Action Theory (TRA). Non-probability sampling with judgmental sampling has been chosen as a result. The study develops five hypotheses which are tested using a sample of 99 participants (n=99). Before exploring and elucidating factors affecting customer loyalty, data from citizens of HCMC was gathered using a questionnaire. Hedonic shopping motivation (HSM), utilitarian shopping motivation (USM), perceived ease of use (PEU), perceived quality (PCQ), and experiential value (EXV) were expected to influence the relationships. The results of this study have important consequences for m-commerce practitioners and researchers alike to enhance knowledge of online buying motivation specifically in the setting of mobile applications.
    Keywords: Mobile Applications, Online Shopping Motivation, Customer Loyalty
    JEL: M10 M37
    Date: 2023–11–25
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:119657&r=dcm
  9. By: Dar\'io Blanco-Fern\'andez; Stephan Leitner; Alexandra Rausch
    Abstract: This paper examines the interactions between selected coordination modes and dynamic team composition, and their joint effects on task performance under different task complexity and individual learning conditions. Prior research often treats dynamic team composition as a consequence of suboptimal organizational design choices. The emergence of new organizational forms that consciously employ teams that change their composition periodically challenges this perspective. In this paper, we follow the contingency theory and characterize dynamic team composition as a design choice that interacts with other choices such as the coordination mode, and with additional contextual factors such as individual learning and task complexity. We employ an agent-based modeling approach based on the NK framework, which includes a reinforcement learning mechanism, a recurring team formation mechanism based on signaling, and three different coordination modes. Our results suggest that by implementing lateral communication or sequential decision-making, teams may exploit the benefits of dynamic composition more than if decision-making is fully autonomous. The choice of a proper coordination mode, however, is partly moderated by the task complexity and individual learning. Additionally, we show that only a coordination mode based on lateral communication may prevent the negative effects of individual learning.
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.05832&r=dcm
  10. By: Eric Bahel
    Abstract: We study three axioms in the model of constrained social choice under uncertainty where (i) agents have subjective expected utility preferences over acts and (ii) different states of nature have (possibly) different sets of available outcomes. Anonymity says that agents' names or labels should never play a role in the mechanism used to select the social act. Strategy-proofness requires that reporting one's true preferences be a (weakly) dominant strategy for each agent in the associated direct revelation game. Range unanimity essentially says that a feasible act must be selected by society whenever it is reported as every voter's favorite act within the range of the mechanism. We first show that every social choice function satisfying these three axioms can be factored as a product of voting rules that are either constant or binary (always yielding one of two pre-specified outcomes in each state). We describe four basic types of binary factors: three of these types are novel to this literature and exploit the voters' subjective beliefs. Our characterization result then states that a social choice function is anonymous, strategy-proof and range-unanimous if and only if every binary factor (in its canonical factorization) is of one of these four basic types.
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.04060&r=dcm

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