nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2011‒02‒26
ten papers chosen by
Philip Yu
Hong Kong University

  1. The role of the reference alternative in the specification of asymmetric discrete choice models By Lorenzo Masiero; John M. Rose
  2. Accounting for WTP/WTA discrepancy in discrete choice models: Discussion of policy implications based on two freight transport stated choice experiments By Lorenzo Masiero; Rico Maggi
  3. Price sensitivity to tourism activities: looking for determinant factors By Lorenzo Masiero; Juan L. Nicolau
  4. Stick to the Plan? A Revealed-Preference Study of Behavioural Impacts of Traffic Information By Yin-Yen Tseng; Jasper Knockaert; Erik T. Verhoef
  5. Biases in Willingness-To-Pay Measures from Multinomial Logit Estimates due to Unobserved Heterogeneity By Vincent van den Berg; Eric Kroes; Erik T. Verhoef
  6. Incorrectly accounting for taste heterogeneity in choice experiments: Does it really matter for welfare measurement? By Colombo, Sergio; Hanley, Nick; Torres, Cati
  7. Estimating monetary policy reaction functions : A discrete choice approach By Jef Boeckx
  8. Automobile Replacement: A DynamicStructural Approach By Pasquale Schiraldi
  9. Semiparametric Estimation of Markov Decision Processeswith Continuous State Space By Oliver Linton; Sorawoot Srisuma
  10. An instrumental variable model of multiple discrete choice By Andrew Chesher; Adam Rosen; Konrad Smolinski

  1. By: Lorenzo Masiero (Institute for Economic Research (IRE), Faculty of Economics, University of Lugano, Switzerland); John M. Rose (Institute of Transport and Logistics Studies (ITLS), Faculty of Economics and Business, The University of Sydney, Australia)
    Abstract: Within the discrete choice modelling literature, there has been growing interest in including reference alternatives within stated choice survey tasks. Recent studies have investigated asymmetric utility specifications by estimating discrete choice models that include different parameters according to gains and losses relative to the values of the reference attributes. This paper analyses asymmetric discrete choice models by comparing specifications expressed as deviations from the reference point and specifications expressed in absolute values. The results suggest that the selection of the appropriate asymmetric model specification should be based on the type of the stated choice experiment.
    Keywords: stated choice experiments, reference alternative, preference asymmetry, willingness to pay
    JEL: C25
    Date: 2011–01
  2. By: Lorenzo Masiero (Institute for Economic Research (IRE), Faculty of Economics, University of Lugano, Switzerland); Rico Maggi (Institute for Economic Research (IRE), Faculty of Economics, University of Lugano, Switzerland)
    Abstract: A key input in cost-benefit analysis is represented by the marginal rate of substitution which expresses the willingness to pay, or its counterpart willingness to accept, for both market and non-market goods. The consistent discrepancy between these two measures observed in the literature suggests the need to estimate reference dependent models able to capturing loss aversion by distinguishing the value attached to a gain from the value attached to a loss according to reference dependent theory. This paper proposes a comparison of willingness to pay and willingness to accept measures estimated from models with both symmetric and reference dependent utility specifications within two different freight transport stated choice experiments. The results show that the reference dependent specification outperforms the symmetric specification and they prove the robustness of reference dependent specification over datasets designed according different attributes levels ranges. Moreover we demonstrate the policy relevance of asymmetric specifications illustrating the strong implications for cost-benefit analysis in two case studies.
    Keywords: WTP/WTA discrepancy, freight choice, policy evaluation
    JEL: C25 L91
    Date: 2011–01
  3. By: Lorenzo Masiero (Institute for Economic Research (IRE), Faculty of Economics, University of Lugano, Switzerland); Juan L. Nicolau (Dpt. of Financial Economics, Accounting and Marketing, Faculty of Economics, University of Alicante, Spain)
    Abstract: Literature shows evidence that there is a marked heterogeneity in price responses to tourism products, leading to a great variety of tourist sensitivities to price. It means that the role price plays is complex and, particularly challenging is that its effect is not unambiguous, thereby dismissing the idea that demand for tourism products and tourist activities is always that of ordinary goods. The objective of this article is to identify and explain, as a novelty for the tourism industry, price sensitivities to tourism activities -individual by individual-. The operative formalization follows a Mixed Logit Model to estimate the individual sensitivities to price and then, a regression analysis to detect their determinants. The empirical application finds that motivations -influenced by age- and length of stay -with a non-linear effect- are explanatory factors of the tourists' price sensitivity to activities.
    Keywords: tourism activities, response to prices, market heterogeneity, tourist choice
    JEL: C25 L83
    Date: 2011–01
  4. By: Yin-Yen Tseng (VU University Amsterdam); Jasper Knockaert (VU University Amsterdam); Erik T. Verhoef (VU University Amsterdam)
    Abstract: We estimate a revealed-preference scheduling model of morning peak behaviour that allows us to determine the impact of traffic information on traveller behaviour. Specifically, we distinguish between the marginal impact of expected travel times versus that of deviations from this expectation upon user behaviour. We find that participants that chose to receive a smart-phone with traffic information as a reward in our experiment respond to the deviation of actual travel times from the expectation, which they did not do before. This we interpret as evidence that traffic information indeed affects behaviour. We also find that participants who did not choose the smart-phone, but instead opted for monetary rewards, also respond to the deviation of actual travel times from the expectation. This suggests that these drivers use other sources of information to help their trip planning.
    Keywords: Traffic Information; Discrete Choice Analysis; Revealed Preference; Value of Travel Time Savings; Value of Schedule Delay
    JEL: R41 D12
    Date: 2010–07–14
  5. By: Vincent van den Berg (VU University Amsterdam); Eric Kroes (VU University Amsterdam); Erik T. Verhoef (VU University Amsterdam)
    Abstract: It is a common finding in empirical discrete choice studies that the estimated mean relative values of the coefficients (i.e. WTP's) from multinomial logit (MNL) estimations differ from those calculated using mixed logit estimations, where the mixed logit has the better statistical fit. However, it is less clear under exactly what circumstances such differences arise, whether they are important, and if they can be seen as biases in the WTP estimates from MNL. We use datasets created by Monte Carlo simulation to test, in a controlled environment, the effects of the different possible sources of bias on the accuracy of WTP's estimated by MNL. Consistent with earlier research we find that random unobserved heterogeneity in the marginal utilities does not in itself biases the MNL estimates. Furthermore, whether or not the unobserved heterogeneity is symmetrically shaped also does not affect the accuracy of the WTP estimates of MNL. However, we find that if two heterogeneous marginal utilities are correlated then the WTP's from MNL may be biased. If the correlation between the marginal utilities is negative, then the bias in the MNL estimate is negative, whereas if the correlation is positive the bias is positive.
    Keywords: Discrete Choice; Biases in WTP's; Multinomial Logit; Correlated Heterogeneous Marginal Utilities
    JEL: C13 C25
    Date: 2010–01–28
  6. By: Colombo, Sergio; Hanley, Nick; Torres, Cati
    Abstract: A range of empirical approaches to representing preference heterogeneity have emerged in choice modelling. Researchers have been able to explore the differences which selection of a particular approach makes to welfare measures in a particular dataset, and indeed have been able to implement a number of tests for which approach best fits a particular set of data. However, the question as to the degree of error in welfare estimation from an inappropriate choice of empirical approach has not been addressed. In this paper, we use Monte Carlo analysis to address this question. Given the high popularity of both the random parameter logit (RPL) and latent class models among choice modellers, we examine the errors in welfare estimates from using the incorrect model to account for taste preference heterogeneity. Our main finding is that using an RPL specification with log-normally distributed preferences seems the best bet.
    Keywords: Monte Carlo analysis; choice experiments; efficiency; welfare measurement,; accuracy; preference heterogeneity
    Date: 2011–02
  7. By: Jef Boeckx (National Bank of Belgium, Research Department)
    Abstract: I propose a discrete choice method for estimating monetary policy reaction functions based on research by Hu and Phillips (2004). This method distinguishes between determining the underlying desired rate which drives policy rate changes and actually implementing interest rate changes. The method is applied to ECB rate setting between 1999 and 2010 by estimating a forward-looking Taylor rule on a monthly basis using real-time data drawn from the Survey of Professional Forecasters. All parameters are estimated significantly and with the expected sign. Including the period of financial turmoil in the sample delivers a less aggressive policy rule as the ECB was constrained by the lower bound on nominal interest rates. The ECB's non-standard measures helped to circumvent that constraint on monetary policy, however. For the pre-turmoil sample, the discrete choice model's estimated desired policy rate is more aggressive and less gradual than least squares estimates of the same rule specification. This is explained by the fact that the discrete choice model takes account of the fact that central banks change interest rates by discrete amounts. An advantage of using discrete choice models is that probabilities are attached to the different outcomes of every interest rate setting meeting. These probabilities correlate fairly well with the probabilities derived from surveys among commercial bank economists.
    Keywords: monetary policy reaction functions, discrete choice models, interest rate setting, ECB
    JEL: C25 E52 E58
    Date: 2011–02
  8. By: Pasquale Schiraldi
    Abstract: This paper specifies and estimates a structural dynamic model of consumer demand for newand used durable goods. Its primary contribution is to provide an explicit estimationprocedure for transaction costs, which are crucial to capturing the dynamic nature ofconsumer decisions. In particular, transaction costs play a key role in determining consumerreplacement behavior in both primary and secondary markets for durable goods. The uniquedata set used in this paper has been collected by the Italian Motor Registry and covers theperiod from 1994 to 2004. It includes information about sales dates for individual cars overtime as well as the initial stock of cars in the sample period. Identification of transactioncosts is achieved from the variation in the share of consumers choosing to hold a given cartype each period, and from the share of consumers choosing to purchase the same car typethat period. Specifically, I estimate a random coefficients discrete choice model thatincorporates a dynamic optimal stopping problem in the spirit of Rust (1987). I apply thismodel to evaluate the impact of scrappage subsidies on the Italian automobile market in 1997and 1998.
    Date: 2010–06
  9. By: Oliver Linton; Sorawoot Srisuma
    Abstract: We propose a general two-step estimation method for the structural parameters ofpopular semiparametric Markovian discrete choice models that include a class ofMarkovian Games andallow for continuous observable state space. The estimation procedure is simpleas it directly generalizes the computationally attractive methodology of Pesendorferand Schmidt-Dengler (2008) that assumed finite observable states. This extensionis non-trivial as the value functions, to be estimated nonparametrically in the firststage, are defined recursively in a non-linear functional equation. Utilizingstructural assumptions, we show how to consistently estimate the infinitedimensional parameters as the solution to some type II integral equations, thesolving of which is a well-posed problem. We provide sufficient set of primitives toobtain root-T consistent estimators for the finite dimensional structural parametersand the distribution theory for the value functions in a time series framework.
    Keywords: Discrete Markov Decision Models, Kernel Smoothing, Markovian Games, Semi-parametric Estimation, Well-Posed Inverse Problem.D
    Date: 2010–08
  10. By: Andrew Chesher (Institute for Fiscal Studies and University College London); Adam Rosen (Institute for Fiscal Studies and University College London); Konrad Smolinski (Institute for Fiscal Studies)
    Abstract: <p><p>This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities. </p> </p><p><p>We show that the model delivers set, not point, identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which in parametric models require little more calculation than what is involved in a conventional maximum likelihood analysis. The results are illustrated using a model which is essentially the parametric conditional logit model of McFadden (1974) but with potentially endogenous explanatory variables and instrumental variable restrictions.</p> </p><p><p>The method employed has wide applicability and for the first time brings instrumental variable methods to bear on structural models in which there are multiple unobservables in a structural equation.</p></p>
    Date: 2011–02

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