A Bayesian Semiparametric Approach for Endogeneity and Heterogeneity in Choice Models

Published Online:https://doi.org/10.1287/mnsc.2013.1811

References

  • Ansari A, Iyengar R (2006) Semiparametric Thurstonian models for recurrent choices: A Bayesian analysis. Psychometrika 71:631–657.CrossrefGoogle Scholar
  • Ansari A, Mela C (2003) E-customization. J. Marketing Res. 40: 131–145.CrossrefGoogle Scholar
  • Antoniak C (1974) Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems. Ann. Statist. 2:1152–1174.CrossrefGoogle Scholar
  • Berry S (2003) Comment: Bayesian analysis of simultaneous demand and supply by Yang, Chen and Allenby. Quant. Marketing Econom. 1:285–291.CrossrefGoogle Scholar
  • Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63:841–890.CrossrefGoogle Scholar
  • Blackwell D, MacQueen JB (1973) Ferguson distributions via Polya Urn schemes. Ann. Statist. 2:353–355.CrossrefGoogle Scholar
  • Bronnenberg BJ, Kruger MW, Mela CF (2008) The IRI marketing data set. Marketing Sci. 27:745–748.LinkGoogle Scholar
  • Burda M, Harding M, Hausman J (2008) A Bayesian mixed logit-probit model for multinomial choice. J. Econometrics 147: 232–246.CrossrefGoogle Scholar
  • Ching AT (2010) Consumer learning and heterogeneity: Dynamics of demand for prescription drugs after patent expiration. Internat. J. Indust. Organ. 28:619–638.CrossrefGoogle Scholar
  • Chintagunta P (2001) Endogeneity and heterogeneity in a probit demand model: Estimation using aggregate data. Marketing Sci. 20:442–456.LinkGoogle Scholar
  • Chintagunta P, Dubé JP, Goh KY (2005) Beyond the endogeneity bias: The effect of unmeasured brand characteristics on household-level brand choice models. Management Sci. 51:832–849.LinkGoogle Scholar
  • Conley TG, Hansen CB, McCulloch RE, Rossi PE (2008) A semi-parametric Bayesian approach to the instrumental variable problem. J. Econometrics 144:276–305.CrossrefGoogle Scholar
  • Dubé JP, Chintagunta P (2003) Comment: Bayesian analysis of simultaneous demand and supply by Yang, Chen and Allenby. Quant. Marketing Econom. 1:293–298.CrossrefGoogle Scholar
  • Ferguson TS (1973) A Bayesian analysis of some nonparametric problems. Ann. Statist. 1:209–230.CrossrefGoogle Scholar
  • Fisher RA (1931) Properties of Hh functions. British Association Mathematical Tables, vol. 1 (Cambridge University Press, Cambridge, UK).Google Scholar
  • Geweke J (1989) Bayesian inference in econometric models using Monte Carlo integration. Econometrica 57:1317–1339.CrossrefGoogle Scholar
  • Geweke J, Keane MP (1999) Mixture of normals probit models. Hsiao C, Lahiri K, Lee LF, Pesaran MH, eds. Analysis of Panels and Limited Dependent Variable Models (Cambridge University Press, Cambridge, UK), 49–78.CrossrefGoogle Scholar
  • Geweke J, Keane MP (2001) Computationally intensive methods for integration in econometrics. Heckman JJ, Leamer E, eds. Handbook of Econometrics (Elsevier Science, New York), 3463–3568.CrossrefGoogle Scholar
  • Goolsbee A, Petrin A (2004) The consumer gains from direct broadcast satellites and the competition with cable TV. Econometrica 72:351–381.CrossrefGoogle Scholar
  • Guadagni PM, Little JDC (1983) A logit model of brand choice calibrated on scanner data. Marketing Sci. 3:203–238.LinkGoogle Scholar
  • Hajivassiliou V, McFadden D (1998) The method of simulated scores for the estimation of LDV models. Econometrica 66:863–896.CrossrefGoogle Scholar
  • Hausman JA (1996) Valuation of new goods under perfect and imperfect competition. Bresnahan TF, Gordon RJ, eds. The Economics of New Goods, Studies in Income and Wealth, Vol. 58 (University of Chicago Press, Chicago), 209–247.Google Scholar
  • Ishwaran H, James LF (2001) Gibbs sampling methods for stick-breaking priors. J. Amer. Statist. Assoc. 96:161–173.CrossrefGoogle Scholar
  • Ishwaran H, Zarepour M (2000) Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models. Biometrika 87:371–390.CrossrefGoogle Scholar
  • Keane MP (1994) A computationally practical simulation estimator for panel data. Econometrica 62:95–116.CrossrefGoogle Scholar
  • Kim JG, Menzefricke U, Feinberg FM (2004) Assessing heterogeneity in discrete choice models using a Dirichlet process prior. Rev. Marketing Sci. 2:1–39.CrossrefGoogle Scholar
  • Kuksov D, Villas-Boas JM (2008) Endogeneity and individual consumer choice. J. Marketing Res. 45:702–714.CrossrefGoogle Scholar
  • Lijoi A, Mena RH, Prunster I (2005) Hierarchical mixture modeling with normalized inverse-gaussian priors. J. Amer. Statist. Assoc. 100:1278–1291.CrossrefGoogle Scholar
  • Nevo A (2001) Measuring market power in the ready-to-eat cereal industry. Econometrica 69:307–342.CrossrefGoogle Scholar
  • Park S, Gupta S (2009) Simulated maximum likelihood estimator for the random coefficient logit model using aggregate data. J. Marketing Res. 46:531–542.CrossrefGoogle Scholar
  • Petrin A, Train K (2010) A control function approach to endogeneity in consumer choice models. J. Marketing Res. 47:3–13.CrossrefGoogle Scholar
  • Rivers D, Vuong QH (1988) Limited information estimators and exogeneity tests for simultaneous probit models. J. Econometrics 39:347–66.CrossrefGoogle Scholar
  • Rodríguez A, Dunson DB (2011) Nonparametric Bayesian models through probit stick-breaking processes. Bayesian Anal. 6:145–178.CrossrefGoogle Scholar
  • Rossi PE, Allenby GM, McCulloch R (2005) Bayesian Statistics and Marketing, 1st ed. (John Wiley & Sons, New York).CrossrefGoogle Scholar
  • Sethuraman J (1994) A constructive definition of Dirichlet priors. Statistica Sinica 4:639–650.Google Scholar
  • Song I (2010) Item aggregates and price elasticity. Seoul J. Bus. 16:45–63.CrossrefGoogle Scholar
  • Song PX-K (2000) Multivariate dispersion models generated from Gaussian copula. Scandinavian J. Statist. 27:305–320.CrossrefGoogle Scholar
  • Spiegelhalter DJ, Best NG, Carlin BP, Linde A (2002) Bayesian measures of model complexity and fit. J. Royal Statist. Soc., Series B 64:583–639.CrossrefGoogle Scholar
  • Sudhir K (2001) Structural analysis of manufacturer pricing in the presence of a strategic retailer. Marketing Sci. 20:244–264.LinkGoogle Scholar
  • Villas-Boas JM (2007) A note on limited versus full information estimation in non-linear models. Working paper, University of California, Berkeley, Berkeley.Google Scholar
  • Villas-Boas JM, Winer RS (1994) Endogeneity in brand choice models. Mimeo, University of California, Berkeley, Berkeley.Google Scholar
  • Villas-Boas JM, Winer RS (1999) Endogeneity in brand choice models. Management Sci. 45:1324–1338.LinkGoogle Scholar
  • Villas-Boas JM, Zhao Y (2005) Retailer, manufacturers, and individual consumers: Modeling the supply side in the ketchup marketplace. J. Marketing Res. 42:83–95.CrossrefGoogle Scholar
  • Watanabe S (2010) Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory. J. Machine Learn. Res. 11:3571–3594.Google Scholar
  • Yang M, Dunson DB (2010) Bayesian semiparametric structural equation models with latent variables. Psychometrika 75:675–693.CrossrefGoogle Scholar
  • Yang M, Dunson DB, Baird D (2010) Semiparametric Bayes hierarchical models with mean and variance constraints. Comput. Statist. Data Anal. 54:2172–2186.CrossrefGoogle Scholar
  • Yang S, Chen Y, Allenby GM (2003) Bayesian analysis of simultaneous demand and supply. Quant. Marketing Econom. 1:251–275.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.