A Poisson mixture model of discrete choice
In this paper, we introduce a new Poisson mixture model for count panel data where the underlying Poisson process intensity is determined endogenously by consumer latent utility maximization over a set of choice alternatives. This formulation accommodates the choice and count in a single random utility framework with desirable theoretical properties. Individual heterogeneity is introduced through a random coefficient scheme with a flexible semiparametric distribution. We deal with the analytical intractability of the resulting mixture by recasting the model as an embedding of infinite sequences of scaled moments of the mixing distribution, and newly derive their cumulant representations along with bounds on their rate of numerical convergence. We further develop an efficient recursive algorithm for fast evaluation of the model likelihood within a Bayesian Gibbs sampling scheme. We apply our model to a recent household panel of supermarket visit counts. We estimate the nonparametric density of three key variables of interest–price, driving distance, and their interaction–while controlling for a range of consumer demographic characteristics. We use this econometric framework to assess the opportunity cost of time and analyze the interaction between store choice, trip frequency, search intensity, and household and store characteristics. We also conduct a counterfactual welfare experiment and compute the compensating variation for a 10%–30% increase in Walmart prices.
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- Greene, William, 2007.
"Functional Form and Heterogeneity in Models for Count Data,"
Foundations and Trends(R) in Econometrics,
now publishers, vol. 1(2), pages 113-218, August.
- Nicholas Economides, 2007. ""Net Neutrality," Non-Discrimination and Digital Distribution of Content Through the Internet," Working Papers 07-9, New York University, Leonard N. Stern School of Business, Department of Economics.
- Nevo, Aviv, 1998.
"Measuring Market Power in the Ready-To-Eat Cereal Industry,"
Food Marketing Policy Center Research Reports
037, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
- Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-42, March.
- Nevo, Aviv, 1999. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Competition Policy Center, Working Paper Series qt7cm5p858, Competition Policy Center, Institute for Business and Economic Research, UC Berkeley.
- Aviv Nevo, 1998. "Measuring Market Power in the Ready-to-Eat Cereal Industry," NBER Working Papers 6387, National Bureau of Economic Research, Inc.
- Aviv Nevo, 2003. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Microeconomics 0303006, EconWPA.
- Nevo, Aviv, 1998. "Measuring Market Power in the Ready-To-Eat Cereal Industry," Research Reports 25164, University of Connecticut, Food Marketing Policy Center.
- Steven T. Berry & Philip A. Haile, 2009.
"Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers,"
Cowles Foundation Discussion Papers
1718, Cowles Foundation for Research in Economics, Yale University, revised Mar 2010.
- Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," NBER Working Papers 15276, National Bureau of Economic Research, Inc.
- Munkin, Murat K. & Trivedi, Pravin K., 2003. "Bayesian analysis of a self-selection model with multiple outcomes using simulation-based estimation: an application to the demand for healthcare," Journal of Econometrics, Elsevier, vol. 114(2), pages 197-220, June.
- Patrick Bajari & Jeremy Fox & Kyoo il Kim & Stephen P. Ryan, 2009.
"The Random Coefficients Logit Model Is Identified,"
NBER Working Papers
14934, National Bureau of Economic Research, Inc.
- Christian Broda & Ephraim Leibtag & David E. Weinstein, 2009. "The Role of Prices in Measuring the Poor's Living Standards," Journal of Economic Perspectives, American Economic Association, vol. 23(2), pages 77-97, Spring.
- Train,Kenneth E., 2009.
"Discrete Choice Methods with Simulation,"
Cambridge University Press, number 9780521766555, 1.
- Markus Jochmann & Roberto Leon-Gonzalez, 2003.
"Estimating the Demand for Health Care with Panel Data: A Semiparametric Bayesian Approach,"
2003005, The University of Sheffield, Department of Economics, revised Oct 2003.
- Markus Jochmann & Roberto León-González, 2004. "Estimating the demand for health care with panel data: a semiparametric Bayesian approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 1003-1014.
- Mark Aguiar & Erik Hurst, 2007.
"Life-Cycle Prices and Production,"
American Economic Review,
American Economic Association, vol. 97(5), pages 1533-1559, December.
- Silvio Rendón, 2002.
"Fixed And Random Effects In Classical And Bayesian Regression,"
Economics Working Papers
we021503, Universidad Carlos III, Departamento de Economía.
- Silvio R. Rendon, 2013. "Fixed and Random Effects in Classical and Bayesian Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(3), pages 460-476, 06.
- Silvio Rendón, 2002. "Fixed and random effects in Classical and Bayesian regression," Economics Working Papers 613, Department of Economics and Business, Universitat Pompeu Fabra.
- Terza, Joseph V., 1998. "Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects," Journal of Econometrics, Elsevier, vol. 84(1), pages 129-154, May.
- Andrés Romeu & Marcos Vera-Hernández, 2004.
"Counts With An Endogenous Binary Regressor: A Series Expansion Approach,"
Working Papers. Serie AD
2004-36, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Andrés Romeu & Marcos Vera-Hern�ndez, 2005. "Counts with an endogenous binary regressor: A series expansion approach," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 1-22, 03.
- Severini,Thomas A., 2005. "Elements of Distribution Theory," Cambridge Books, Cambridge University Press, number 9780521844727, 1.
- Briesch, Richard A. & Chintagunta, Pradeep K. & Matzkin, Rosa L., 2010. "Nonparametric Discrete Choice Models With Unobserved Heterogeneity," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 291-307.
- Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984.
"Econometric Models for Count Data with an Application to the Patents-R&D Relationship,"
NBER Technical Working Papers
0017, National Bureau of Economic Research, Inc.
- Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-38, July.
- Mannering, Fred L. & Hamed, Mohammad M., 1990. "Occurence, frequency, and duration of commuters' work-to-home departure delay," Transportation Research Part B: Methodological, Elsevier, vol. 24(2), pages 99-109, April.
- Theofanis Sapatinas, 1995. "Identifiability of mixtures of power-series distributions and related characterizations," Annals of the Institute of Statistical Mathematics, Springer, vol. 47(3), pages 447-459, September.
- Martin Burda & Matthew Harding & Jerry Hausman, 2008.
"A Bayesian mixed logit-probit model for multinomial choice,"
CeMMAP working papers
CWP23/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Burda, Martin & Harding, Matthew & Hausman, Jerry, 2008. "A Bayesian mixed logit-probit model for multinomial choice," Journal of Econometrics, Elsevier, vol. 147(2), pages 232-246, December.
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