Product attributes and models of multiple discreteness

Journal of Econometrics

Volumn 138, Issue 1, 2007, Pages 208-230

  Kim, Jaehwan ^a   Allenby, Greg M ^b   Rossi, Peter E ^c  

^a Korea University   (South Korea)

^b OHIO STATE UNIVERSITY   (United States)

^c UNIVERSITY OF CHICAGO   (United States)

Author keywords

Characteristic model; Multiple discreteness; Non homothetic utility; Product attributes

Indexed keywords

FINITE DIFFERENCE METHOD; FUNCTION EVALUATION; MATHEMATICAL MODELS; NONLINEAR EQUATIONS; PARAMETER ESTIMATION;

CHARACTERISTIC MODEL; MULTIPLE DISCRETENESS; NON-HOMOTHETIC UTILITY; PRODUCT ATTRIBUTES;

PRODUCT DEVELOPMENT;

EID: 33947393561     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jeconom.2006.05.020     Document Type: Article

References (10)

1. Berry, S., Pakes, A., 2002. The pure characteristics discrete choice model of differentiated products demand. Working paper, Yale University.
2. Berry S., Levinsohn J., and Pakes A. Automobile prices in market equilibrium. Econometrica 63 4 (1995) 841-890
3. Chan, T., 2003. Estimating a continuous hedonic choice model with an application to demand for soft drinks. Working paper, Washington University, St Louis.
4. Fader P.S., and Hardie B.G.S. Modeling consumer choice among SKUs. Journal of Marketing Research 33 (1996) 442-452
5. Gentzkow, M., 2005. Valuing new goods in a model with complementarity: online newspapers. Working paper, University of Chicago.
6. Kamakura W.A., and Srivastava R.K. An ideal-point probabilistic choice model for heterogeneous preferences. Marketing Science 5 3 (1986) 199-218
7. Kim J., Allenby G.M., and Rossi P.E. Modeling consumer demand for variety. Marketing Science 21 3 (2002) 229-250
8. Lancaster K. A new approach to consumer theory. Journal of Political Economy 74 2 (1966) 132-157
9. Newton M.A., and Raftery A.E. Approximating Bayesian inference with the weighted likelihood boostrap. Journal of the Royal Statistical Society (B) 56 (1994) 3-48
10. Rossi P.E., Allenby G.M., and McCulloch R. Bayesian Statistics and Marketing (2005), Wiley, New York