Deriving dynamic marketing effectiveness from econometric time series models
January 2003
Research Paper
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To understand the relevance of marketing efforts, it has become standard practice to estimate the long-run and short-run effects of the marketing-mix, using, say, weekly scanner data. A common vehicle for this purpose is an econometric time series model. Issues that are addressed in the literature are unit roots, cointegration, structural breaks and impulse response functions. In this paper we summarize the most important concepts by reviewing all possible empirical cases that can be encountered in practice using a prototypical model. We provide guidelines for practitioners, and illustrate these for a detailed workedout example.
Keywords
Classifications using
Journal of Economic Literature (JEL) Classification System
- M : Business Administration and Business Economics; Marketing; Accounting
- C32 : Time-Series Models; Dynamic Quantile Regressions
- C44 : Statistical Decision Theory; Operations Research
- M31 : Marketing
Automatically Extracted Terms
- effect
- marketing
- change
- response
- price
- model
- advertising
- level
- figure
- action
- market
- series
- dekimpe
- expenditure
- marketing mix
- marketing action
- research
- hanssen
- profitability
- increase
