nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2023‒08‒28
four papers chosen by
Edoardo Marcucci, Università degli studi Roma Tre


  1. 大学中退の逐次意思決定モデルの構造推定 By Murasawa, Yasutomo
  2. Using Probabilistic Stated Preference Analyses to Understand Actual Choices By Romuald Meango
  3. Managerial Preferences towards Employees Working from Home: Post-Pandemic Experimental Evidence By Aga Kasperska; Anna Matysiak; Ewa Cukrowska-Torzewska
  4. Reliability of international benefit transfer in cultural economics: Non-market valuation of theater in Denmark and Poland By Aleksandra Wiśniewska; Ewa Zawojska; Andrea Baldin; Joanna Rachubik

  1. By: Murasawa, Yasutomo
    Abstract: Using the four-year academic records of 301 male students who enrolled in a specific department at a certain university in April 2016, this paper estimates the structural parameters of a sequential decision model of college dropout and conducts a counterfactual analysis. A well-known method for structural estimation of a dynamic discrete choice model is the Conditional Choice Probability (CCP) method, which recovers the integrated value function from a nonparametric estimate of the reduced-form dropout probability function (CCP function) and constructs a correction term to be added to a binary logit model of staying/dropout to ensure consistent estimation of the structural parameters. The CCP method is especially easy to apply to optimal stopping models, given the value of stopping (expected lifetime earnings after dropout). If dropouts are rare, however, ML estimation of the binary logit model may fail due to complete separation. To avoid this problem, this paper considers a modification of the CCP method, which uses a nonparametric estimate of the log odds ratio of staying/dropout as the dependent variable to apply the least squares method. Monte Carlo experiments show that precise estimation of the structural parameters requires precise estimation of the reduced-form CCP function, which requires a large sample since some states may rarely occur in optimal stopping models. Indeed, precise estimation of the structural parameters was difficult with our data. Nevertheless, given the discount factor and the scale parameter, certain counterfactual behaviors are identifiable independently from the remaining structural parameters. As an example, this paper estimates the effect of four-year tuition subsidies on the dropout probability of the male students in our data. The results show that a tuition subsidy of 100, 000 yen per semester reduces the four-year cumulative dropout probability by approximately 2.2%. However, the lower cumulative dropout probability is due to later dropout decisions, and does not necessarily imply a higher graduation probability.
    Keywords: Dynamic discrete choice model; Optimal stopping model; Short panel; Conditional Choice Probability (CCP) method; Counterfactual analysis; Treatment effect
    JEL: C25 C41 I21
    Date: 2023–08–04
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:118183&r=dcm
  2. By: Romuald Meango
    Abstract: Can stated preferences help in counterfactual analyses of actual choice? This research proposes a novel approach to researchers who have access to both stated choices in hypothetical scenarios and actual choices. The key idea is to use probabilistic stated choices to identify the distribution of individual unobserved heterogeneity, even in the presence of measurement error. If this unobserved heterogeneity is the source of endogeneity, the researcher can correct for its influence in a demand function estimation using actual choices, and recover causal effects. Estimation is possible with an off-the-shelf Group Fixed Effects estimator.
    Date: 2023–07
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2307.13966&r=dcm
  3. By: Aga Kasperska (University of Warsaw, Faculty of Economic Sciences); Anna Matysiak (University of Warsaw, Faculty of Economic Sciences); Ewa Cukrowska-Torzewska (University of Warsaw, Faculty of Economic Sciences)
    Abstract: Work from home (WFH) has been a part of the professional landscape for over two decades, yet it was the COVID-19 pandemic that has substantially increased its prevalence. The impact of WFH on careers is rather ambiguous, and a question remains open about how this effect is manifested in the current times considering the recent extensive and widespread use of WFH during the pandemic. In an attempt to answer these questions, this article investigates whether managerial preferences for promotion, salary increase and training allowance depend on employee engagement in WFH. We also explore the heterogeneity of the effects of WFH on careers across different populations by taking into account the employee’s gender, parenthood status, frequency of WFH as well as the prevalence of WFH in the team. An online discrete choice experiment was run on a sample of over 1, 000 managers from the United Kingdom. The experiment was conducted between July and December 2022, and thus after the extensive use of this working arrangement during the COVID-19 pandemic. The findings indicate that employees who WFH are less likely to be considered for promotion, salary increase and training than on-site workers. The pay and promotion penalties for WFH are particularly true for men (both fathers and non-fathers) and childless women, but not mothers. We also find that employees operating in teams with a higher prevalence of WFH do not experience negative career effects when working from home. The findings underline the importance of individual factors and familiarisation as well as social acceptance of flexible working arrangements in their impact on careers.
    Keywords: career, experiment, family, gender, promotion, work from home
    JEL: J12 J13 J16 J21
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:war:wpaper:2023-16&r=dcm
  4. By: Aleksandra Wiśniewska (University of Warsaw, Faculty of Economic Sciences); Ewa Zawojska (University of Warsaw, Faculty of Economic Sciences); Andrea Baldin (Ca’Foscari Univeristy of Venice, Copenhagen Business School); Joanna Rachubik (Copenhagen Business School)
    Abstract: Cultural goods provide numerous non-market benefits to society. Estimates of the benefits are needed for benefit-cost analyses, helping to inform cultural policy decisions and aiming at the efficient allocation of public funds. The non-market benefits cannot be assessed through market transactions. While original non-market valuation studies require substantial budgets and time, a benefit transfer approach offers an alternative. It enables the application of empirical estimates from existing original studies conducted at one site to approximate the value at another site. This study provides the first international benefit transfer for performing arts and examines the reliability of various benefit transfer approaches. We use empirical data from two separate stated preference valuation surveys conducted in Denmark and in Poland. Our results suggest that the benefit function transfer accounting for differences in purchasing power parity between the countries can generate transfer errors as low as 3-6%, indicating high reliability of the transferred values.
    Keywords: international benefit transfer, performing arts, contingent valuation, discrete choice experiment, transfer errors
    JEL: Z11 Z18 D61 H40
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:war:wpaper:2023-19&r=dcm

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