Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- Notes on contributors
- Acknowledgments
- Introduction
- 1 The PIMS project: vision, achievements, and scope of the data
- 2 Putting PIMS into perspective: enduring contributions to strategic questions
- 3 PIMS and COMPUSTAT data: different horses for the same course?
- 4 Order of market entry: empirical results from the PIMS data and future research topics
- 5 Does innovativeness enhance new product success? Insights from a meta-analysis of the evidence
- 6 Marketing costs and prices: an expanded view
- 7 The model by Phillips, Chang, and Buzzell revisited – the effects of unobservable variables
- 8 Causation and components in market share–performance models: the role of identities
- 9 Cargo cult econometrics: specification testing in simultaneous equation marketing models
- 10 PIMS and the market share effect: biased evidence versus fuzzy evidence
- 11 PIMS in the new millennium: how PIMS might be different tomorrow
- Select bibliography
- Author index
- Subject index
- References
8 - Causation and components in market share–performance models: the role of identities
Published online by Cambridge University Press: 22 September 2009
- Frontmatter
- Contents
- List of figures
- List of tables
- Notes on contributors
- Acknowledgments
- Introduction
- 1 The PIMS project: vision, achievements, and scope of the data
- 2 Putting PIMS into perspective: enduring contributions to strategic questions
- 3 PIMS and COMPUSTAT data: different horses for the same course?
- 4 Order of market entry: empirical results from the PIMS data and future research topics
- 5 Does innovativeness enhance new product success? Insights from a meta-analysis of the evidence
- 6 Marketing costs and prices: an expanded view
- 7 The model by Phillips, Chang, and Buzzell revisited – the effects of unobservable variables
- 8 Causation and components in market share–performance models: the role of identities
- 9 Cargo cult econometrics: specification testing in simultaneous equation marketing models
- 10 PIMS and the market share effect: biased evidence versus fuzzy evidence
- 11 PIMS in the new millennium: how PIMS might be different tomorrow
- Select bibliography
- Author index
- Subject index
- References
Summary
The marketing literature contains several structural models, many of them based on the PIMS database, in which one variable is a definitional component of another, related to it through an identity. These definitional relationships have the potential for providing important insights into marketing phenomena, if they are appropriately modeled. On the other hand, they result in inconsistent parameter estimates if they are not separated from other, non-definitional, relationships in the model that need to be empirically estimated. This chapter first discusses the substantive information that can be obtained by studying the definitional components of a composite variable instead of the variable alone. Then, it examines each of the ways in which definitional relationships appear in marketing models, identifies those that are misspecified, analyzes the impact of the misspecification, and then provides the correct specification. It also disproves a commonly held belief that using instrumental variable estimation in a simultaneous equation system resolves the problems caused by mixing definitional relationships with structural ones. Thus, it provides a comprehensive view both of the potential benefits and of the pitfalls of definitional relationships in structural models. Much of the work reviewed in this chapter was inspired and enabled by the PIMS research database, which provides data not only on profitability, but also on each of its cost and revenue components for a variety of strategic business units over multiple years.
- Type
- Chapter
- Information
- The Profit Impact of Marketing Strategy ProjectRetrospect and Prospects, pp. 188 - 217Publisher: Cambridge University PressPrint publication year: 2004
References
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