nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2014‒10‒03
five papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. An addendum to: A Meta-Analysis of Hypothethical Bias in Stated Preference Valuation By Stefani, Gianluca; Scarpa, Riccardo; Lombardi, Ginevra Virginia
  2. A User's Guide for Two Programs to Estimate and Analyze the Multinomial Logit Allocation Model By Tyrrell, Tim
  3. Socio-economic status and enrollment in higher education: do costs matter? By Koen DECLERCQ; Frank VERBOVEN
  4. A Bootstrap Likelihood approach to Bayesian Computation By Weixuan Zhu; Juan Miguel Marín Diazaraque; Fabrizio Leisen
  5. The Continuous Logit Dynamic and Price Dispersion By Ratul Lahkar; Frank Riedel

  1. By: Stefani, Gianluca; Scarpa, Riccardo; Lombardi, Ginevra Virginia
    Abstract: A recent study published by Murphy et al. (2005) reported results of a meta-analysis of hypothetical bias using 28 valuation studies. The authors found a median ratio of hypothetical to actual values of 1.35 but they did not investigate the ratio of scales of the hypothetical and actual value distributions, which is of great relevance in joint stated and revealed preference analysis. We propose an addendum to Murphy et al. (2005) to provide some insights on the distribution of the scale factor across 23 studies for which relevant data is available. We also describe a method to supply priors to future studies that use Bayesian approaches to model merged revealed and stated preference data.
    Keywords: contingent valuation, experiments, scale identification, meta-analysis, stated preferences, Demand and Price Analysis, Public Economics, Research Methods/ Statistical Methods, C9, H41, Q26, Q28,
    Date: 2014
  2. By: Tyrrell, Tim
    Keywords: Food Consumption/Nutrition/Food Safety, Food Security and Poverty,
  3. By: Koen DECLERCQ; Frank VERBOVEN
    Abstract: We study the impact of socio-economic status on enrollment and study decisions in higher education. We use a discrete choice approach to distinguish between three channels. First, students from disadvantaged backgrounds may be more sensitive to the costs of education. Second, they may have lower preferences for education. Third, they may have developed less academic ability during previous schooling and are therefore less likely to participate. We apply our analysis to Flanders, where tuition fees are low and all high school graduates have access to higher education. We control for unobserved heterogeneity and find that preference and (acquired) ability are more important than cost sensitivity in explaining the lower enrollment of disadvantaged students. Finally, we use the cost sensitivity channel to simulate the impact of tuition fee increases. We find that a uniform tuition fee increase has a fairly small impact on total enrollment, but it especially reduces enrollment of socially disadvantaged students. An alternative discriminatory policy, which combines a tuition fee increase with an extra subsidy to disadvantaged students, can be superior: it reduces the participation gap of disadvantaged students without decreasing total enrollment in higher education.
    Date: 2014–09
  4. By: Weixuan Zhu; Juan Miguel Marín Diazaraque; Fabrizio Leisen
    Abstract: Recently, an increasingly amount of literature focused on Bayesian computational methods to address problems with intractable likelihood. These algorithms are known as Approximate Bayesian Computational (ABC) methods. One of the problems of these algorithms is that the performance depends on the tuning of some parameters, such as the summary statistics, distance and tolerance level. To bypass this problem, an alternative method based on empirical likelihood was introduced by Mengersen et al. (2013), which can be easily implemented when a set of constraints, related with the moments of the distribution, is known. However, the choice of the constraints is crucial and sometimes challenging in the sense that it determines the convergence property of the empirical likelihood. To overcome this problem, we propose an alternative method based on a bootstrap likelihood approach. The method is easy to implement and in some cases it is faster than the other approaches. The performance of the algorithm is illustrated with examples in Population Genetics, Time Series and a recent non-explicit bivariate Beta distribution. Finally, we test the method on simulated and real data random fields.
    Keywords: Approximate Bayesian Computational methods, Bootstrap likelihood, Empirical likelihood, Bivariate Beta distribution, Population genetics
    Date: 2014–09
  5. By: Ratul Lahkar (Department of Economics, Ashoka University); Frank Riedel (Center for Mathematical Economics, Bielefeld University)
    Abstract: We define the logit dynamic for games with continuous strategy spaces and establish its fundamental properties, i.e. the existence, uniqueness and continuity of solutions. We apply the dynamic to the analysis of the Burdett and Judd (1983) model of price dispersion. Our objective is to assess the stability of the logit equilibrium corresponding to the unique Nash equilibrium of this model. Although a direct analysis of local stability is difficult due to technical difficulties, an appeal to finite approximation techniques suggest that the logit equilibrium is unstable. Price dispersion, instead of being an equilibrium phenomenon, is a cyclical phenomenon. We also establish a result on the Lyapunov stability of logit equilibria in negative definite games.
    Keywords: Price dispersion, Evolutionary game theory, Logit dynamic
    JEL: C72 C73 L11
    Date: 2014–08

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