Appendix C

Vector Autoregression Modeling

(Source: Dekimpe and Hanssens [1])

Dekimpe and Hanssens [1] introduced vector autoregression modeling under the framework of persistence modeling. Persistence modeling addresses the problem of long-run market-response quantification by combining into one measure of ‘net long-run impact’ the chain reaction of consumer response, firm feedback, and competitor response that emerges following the initial marketing action. Persistence modeling is a multi-step process. In the first step, unit-root tests are used to determine whether or not the different variables are stable or evolving. In case several of the variables are found to have a unit root, one subsequently tests for cointegration. Depending on the outcome of these two preliminary steps, one estimates a vector autoregression (VAR) model in the levels, in the differences, or in error-correction format. Finally, the parameter estimates from this VAR model are used to derive impulse-response functions (IRFs), from which various summary statistics on the short- and-long-run dynamics of the system can be derived. Each of these steps is elaborated briefly as below.

Get Statistical Methods in Customer Relationship Management now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.