nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2009‒08‒16
five papers chosen by
Philip Yu
Hong Kong University

  1. Finite-Sample Properties of the Maximum Likelihood Estimator for the Binary Logit Model With Random Covariates By Qian Chen; David E. Giles
  2. Justifiable choice By Heller, Yuval
  3. Weathering the Storm: Measuring Household Willingness-to-Pay for Risk-Reduction in Post-Katrina New Orleans By Craig E. Landry; Paul Hindsley; Okmyung Bin; Jamie B. Kruse; John C. Whitehead; Kenneth R. Wilson
  4. Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers By Steven T. Berry; Philip A. Haile
  5. Coverage of Retail Stores and Discrete Choice Models of Demand: Estimating Price Elasticities and Welfare Effects By Franco Mariuzzo; Patrick Paul Walsh; Ciara Whelan

  1. By: Qian Chen (School of Public Finance & Public Policy, Central University of Finance & Economics, People's Republic of China); David E. Giles (Department of Economics, University of Victoria)
    Abstract: We examine the finite sample properties of the maximum likelihood estimator for the binary logit model with random covariates. Analytic expressions for the first-order bias and second-order mean squared error function for the maximum likelihood estimator in this model are derived, and we undertake some numerical evaluations to analyze and illustrate these analytic results for the single covariate case. For various data distributions, the bias of the estimator is signed the same as the covariate’s coefficient, and both the absolute bias and the mean squared errors increase symmetrically with the absolute value of that parameter. The behaviour of a bias-adjusted maximum likelihood estimator, constructed by subtracting the (maximum likelihood) estimator of the first-order bias from the original estimator, is examined in a Monte Carlo experiment. This bias-correction is effective in all of the cases considered, and is recommended when the logit model is estimated by maximum likelihood with small samples.
    Keywords: Logit model, bias, mean squared error, bias correction, random covariates
    JEL: C01 C13 C25
    Date: 2009–08–05
  2. By: Heller, Yuval
    Abstract: In many situations a decision maker has incomplete psychological preferences, and the weak axiom of revealed preference (WARP) is often violated. In this paper we relax WARP, and replace it with convex axiom of revealed non-inferiority (CARNI). An alternative x is revealed inferior to y if x is never chosen when y is in the convex hull of the choice set. CARNI requires that an alternative is chosen if it is not inferior to all other alternatives in the convex hull of the choice set. We apply CARNI in two models and axiomatize non-binary choice correspondences. In the first model we impose the standard axioms of expected utility model, except that WARP is replaced by CARNI. We prove that it has a multiple-utility representation: There is a unique convex set of vN-M utilities, such that an alternative is chosen if and only if it is best with respect to one of the utilities in this set. In the second model we impose the axioms of the subjective expected utility, relax WARP in a similar way, and get multiple-prior representation: There is a unique convex set of priors over the state of nature, such that an alternative is chosen if and only if it is best with respect to one of these priors. Both representations are closely-related to psychological insights of justifiable choice: The decision maker has several ways to evaluate acts, each with a different justification. Observable payoff-irrelevant information during the choice triggers her to use a specific “anchoring” justification for the evaluation of the alternatives.
    Keywords: uncertainty; multiple priors; multiple utilities; incomplete preferences; anchoring; framing; non-binary choice.
    JEL: D81
    Date: 2009–06–10
  3. By: Craig E. Landry; Paul Hindsley; Okmyung Bin; Jamie B. Kruse; John C. Whitehead; Kenneth R. Wilson
    Abstract: The city of New Orleans suffered extensive damage as a result of Hurricane Katrina. Katrina overwhelmed the natural and built environment, inundating the city. As rebuilding proceeds, decisions on investment in protective measures will include the choice of lines of defense and the storm severity that design criteria should meet. An exhaustive list of protective measures has been studied in planning documents such as the Louisiana Coastal Protection and Restoration Technical Report (2009), with public comment solicited in town hall meetings. In this study we employ a different approach to examine public sentiment towards the selection and investment in protective measures. Our study utilizes a stated choice experiment with a stratified sample to investigate individuals’ willingness-to-pay for rebuilding New Orleans’ man-made storm defenses, restoring natural storm protection, and improving evacuation options through a modernized transportation system. We target residents of the New Orleans metropolitan area as well as other US citizens. Our results indicate that individuals are willing-to-pay for increased storm protection for New Orleans, but the allocation of these resources differs among residents of the New Orleans metro area and other US citizens. Key Words: storm surge mitigation, conjoint analysis, willingness to pay, Hurricane Katrina, flood control, stated choice, rebuilding New Orleans, recovery
    JEL: H43 Q51 R53
    Date: 2009
  4. By: Steven T. Berry (Cowles Foundation, Yale University); Philip A. Haile (Cowles Foundation, Yale University)
    Abstract: We consider identification of nonparametric random utility models of multinomial choice using "micro data," i.e., observation of the characteristics and choices of individual consumers. Our model of preferences nests random coefficients discrete choice models widely used in practice with parametric functional form and distributional assumptions. However, the model is nonparametric and distribution free. It allows choice-specific unobservables, endogenous choice characteristics, unknown heteroskedasticity, and high-dimensional correlated taste shocks. Under standard "large support" and instrumental variables assumptions, we show identifiability of the random utility model. We demonstrate robustness of these results to relaxation of the large support condition and show that when it is replaced with a weaker "common choice probability" condition, the demand structure is still identified. We show that key maintained hypotheses are testable.
    Keywords: Nonparametric identification, Discrete choice demand, Differentiated products
    JEL: C35
    Date: 2009–09
  5. By: Franco Mariuzzo (The Geary Institute University College Dublin); Patrick Paul Walsh (SPIRe and The Geary Institute University College Dublin); Ciara Whelan (Univesity College Dublin)
    Abstract: Since retail stores tend to host a subset of products available in the market, Ackerberg and Rysman (2005) allow logit errors to represent idiosyncratic unobserved consumer preferences over retail stores and products. Having product level data on store coverage we are able to estimate their logit, nested logit and random coefficients logit models of product demand jointly with cost, in a structural model of equilibrium, for Carbonated Soft Drink products. As Ackerberg and Rysman’ (2005) Monte Carlo study suggests; using standard logit errors does lead to predictable biases in estimated price elasticities and welfare. A counterfactual that imposes full coverage of stores by products, in our structural equilibrium, increases the estimated price elasticities and welfare. Competition in markets is more curtailed than assumed when one works with standard logit errors.
    Keywords: Carbonated Soft Drinks, Differentiated products, discrete choice, Store coverage, structural model, price elasticities, welfare.
    JEL: L11 L62
    Date: 2009–07–21

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