Template-Type: ReDIF-Paper 1.0
Author-Name: Fok, D.
Author-Name-Last: Fok
Author-Name-First: Dennis
Author-Name: Franses, Ph.H.B.F.
Author-Name-Last: Franses
Author-Name-First: Philip Hans
Author-Person: pfr226
Title: Seasonality on non-linear price effects in scanner-data based market-response models
Abstract: Scanner data for fast moving consumer goods typically amount to panels of time series where both N and T are large. To reduce the number of parameters and to shrink parameters towards plausible and interpretable values, multi-level models turn out to be useful. Such models contain in the second level a stochastic model to describe the parameters in the first level. In this paper we propose such a model for weekly scanner data where we explicitly address (i) weekly seasonality in a limited number of yearly data and (ii) non-linear price effects due to historic reference prices. We discuss representation and inference and we propose an estimation method using Bayesian techniques. An illustration to a market-response model for 96 brands for about 8 years of weekly data shows the merits of our approach.
Creation-Date: 2005-01-01
File-URL: https://repub.eur.nl/pub/7032/EI2005-45.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2005-45
Keywords: Bayes estimation, MCMC, non-linearity, panels of time series, threshold models, weekly seasonality
Handle: RePEc:ems:eureir:7032