Optimal pricing strategies for a cluster of goods: own- and cross-price effects with correlated tastes

Juan Rosas (), Santiago Acerenza and Peter Orazem

Applied Economics, 2020, vol. 52, issue 7, 742-755

Abstract: Contingent valuation methods are used to identify observed and unobserved preferences of goods and services. We apply these methods, in the context of multivariate probit analysis, to compute willingness to pay for each product of a cluster of goods conditional on having purchased another offered good of the cluster. We also provide a derivation of compensated cross-price elasticities based on unobservable factors, proving to be convenient in situations where cross-prices are not part of the demand equations. As goods belonging to a cluster typically embed correlated taste, their pricing strategy should consider all offered goods simultaneously rather than individually. Therefore, we solve for the set of optimal prices of a social planner whose objective function weights both the producer’s revenues and the consumer’s joint latent utility. We show an application to collegiate sports events, but these methods can be extended in a straightforward fashion to other goods and services. Supplementary materials for this article are available online.Abbreviations: C30, Multiple or Simultaneous Equation Models, General; C35, Discrete Regression and Qualitative Choice Models; C40, Special Topics of Econometric and Statistical Methods; D12, Empirical Analysis of Consumer Economics; D40, Market Structure, Pricing, and Design; D60, Welfare Economics; Z20, Sport Economics

Date: 2020
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Citations: View citations in EconPapers (2)

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Working Paper: Optimal pricing strategies for a cluster of goods: own- and cross-price effects with correlated tastes (2020)
Working Paper: Optimal pricing strategies for a cluster of goods: own- and cross-price effects with correlated tastes (2019)
Working Paper: Optimal pricing strategies for a cluster of goods: Own- and cross-price effects with correlated tastes (2016)
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DOI: 10.1080/00036846.2019.1659502

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