Outlier Robust Analysis of Market Share and Distribution Relations for Weekly Scanning Data

In this paper we consider empirical econometric models for nine brands of fast-moving nondurable consumer product using weekly observed scanning data on market share and distribution conditional on advertising, price, and promotion activities. Since the data show nonstationary characteristics, we rely on cointegration techniques to estimate long-run and short-run parameters. Additionally, as there are many outlying observations in our weekly scanning data, we apply robust cointegration methods. We find different results across robust and non-robust methods for the long-run relations between market share and distribution and for the short-run response to disequilibrium situations.