Outlier robust analysis of long-run marketing effects for weekly scanning data

We consider econometric modeling of weekly observed scanning data on a fast moving consumer good (FMCG), with a specific focus on the relationship bet ween market share, distribution, advertising, price, and promotion. Such da ta can show non-stationary characteristics. Therefore, we use cointegration techniques to quantify the long-run effects of marketing efforts. Since we ekly scanning data can contain aberrant observations due to, e.g., out-of-s tock situations or measurement errors, we favor an outlier robust cointegra tion method, which we outline in detail. In our illustrative FMCG example, we find different results across robust and non-robust methods for the long -run marketing effects. (C) 1999 Elsevier Science S.A. All rights reserved. JEL classification: M31; C32; M32.