Joy, Joseph (2006): Understanding Advertising Adstock Transformations.
Download (61Kb) | Preview
Advertising effectiveness and Return on Investment (ROI) are typically measured through econometric models that measure the impact of varying levels of advertising Gross Ratings Points (GRPs) on sales or on purchase decision and choice. TV advertising has both dynamic and diminishing returns effects on sales, different models capture these dynamic and nonlinear effects differently. This paper focuses on reviewing the econometric rationale behind the popularized Adstock transformation model that allows the inclusion of lagged and non-linear effects in linear models based on aggregate data.
|Item Type:||MPRA Paper|
|Original Title:||Understanding Advertising Adstock Transformations|
|Keywords:||Advertising, Adstock Model, Non-linear transformation, Marketing-Mix|
|Subjects:||M - Business Administration and Business Economics; Marketing; Accounting > M3 - Marketing and Advertising > M37 - Advertising|
|Depositing User:||Joy V Joseph|
|Date Deposited:||12. Mar 2008 01:45|
|Last Modified:||11. Feb 2013 17:42|
Almon, S. (1965) “The distributed lag between capital appropriations and expenditures”, Econometrica, 33, 178-196. Broadbent, S. (1979) “One Way TV Advertisements Work”, Journal of the Market Research Society Vol. 23 no.3. Dubé, J., Hitsch, G. J., Manchanda, P. (2004) “An Empirical Model of Advertising Dynamics”, Quantitative Marketing and Economics, 3 (2005) 2 Pg. 107-144 Fry, T.R.L., Broadbent, S. and Dixon, J.M. (2000), “Estimating Advertising Half-life and the Data Interval Bias”, Journal of Targeting, Measurement & Analysis in Marketing, 8, 314-334. Leone, R.P. (1995) “Generalizing what is known about temporal aggregation and advertising carry-over”, Marketing Science, 14, G141-G150.