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Estimating demand for differentiated products with error in market shares

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  • Amit Gandhi

    (Institute for Fiscal Studies and University of Wisconsin-Madison)

  • Zhentong Lu
  • Xiaoxia Shi

Abstract

In this paper we introduce a new approach to estimating a differentiated product demand system that allows for error in market shares as measures of choice probabilities. In particular, our approach allows for products with zero sales in the data, which is a frequent phenomenon that arises in product differentiated markets but lies outside the scope of existing demand estimation techniques. Although we find that error in market shares generally undermine the standard point identification of discrete choice models of demand, we exploit shape restrictions on demand implied by discrete choice to generate a system of moment inequalities that partially identify demand parameters. These moment inequalities are fully robust to the variability in market shares yet are also adaptive to the information revealed by market shares in a way that allows for informative inferences. In addition, we construct a profiling approach for parameter inference with moment inequalities, making it feasible to study models with a large number of parameters (as typically required in demand applications) by focusing attention on a profile of the parameters, such as the price coefficient. We use our approach to study consumer demand from scanner data using the Dominick's Finer Foods database, and find that even for the baseline logit model, demand elasticities nearly double when the full error in market shares is taken into account.

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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP03/13.

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Date of creation: Feb 2013
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Handle: RePEc:ifs:cemmap:03/13

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Keywords: Demand Estimation; Diff erentiated Products; Profi le; Measurement Error; Moment Inequality.;

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  1. Nair, Harikesh S. & Dube, Jean-Pierre & Chintagunta, Pradeep, 2004. "Accounting for Primary and Secondary Demand Effects with Aggregate Data," Research Papers 1949, Stanford University, Graduate School of Business.
  2. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-90, July.
  3. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July.
  4. Joseph P. Romano & Azeem M. Shaikh, 2010. "Inference for the Identified Set in Partially Identified Econometric Models," Econometrica, Econometric Society, vol. 78(1), pages 169-211, 01.
  5. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
  6. Guillermo Israilevich, 2004. "Assessing Supermarket Product-Line Decisions: The Impact of Slotting Fees," Quantitative Marketing and Economics, Springer, vol. 2(2), pages 141-167, June.
  7. Steven Berry & Panle Jia, 2010. "Tracing the Woes: An Empirical Analysis of the Airline Industry," American Economic Journal: Microeconomics, American Economic Association, vol. 2(3), pages 1-43, August.
  8. Hausman, Jerry A & Leonard, Gregory K, 2002. "The Competitive Effects of a New Product Introduction: A Case Study," Journal of Industrial Economics, Wiley Blackwell, vol. 50(3), pages 237-63, September.
  9. Austan Goolsbee & Amil Petrin, 2004. "The Consumer Gains from Direct Broadcast Satellites and the Competition with Cable TV," Econometrica, Econometric Society, vol. 72(2), pages 351-381, 03.
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