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Estimating Advertising Half-Life and the Data Interval Bias


  • Fry, T.R.L.
  • Broadbent, S.
  • Dixon, J.M.


We compare three methods of estimating the duration, or half-life, of how well each method works with the data aggregated over different time intervals. In contrast with the existing theory on the, so called, data interval bias, our experiments are based upon realistic advertising schedules. Our results appear to indicate that the indirect "t-ratio" estimating procedure favoured by practitioners works well in the presence of such temporal aggregation. Additionally, we suggest a transformation that can be used in combination with the indirect "t-ratio" estimating procedure to obtain estimates of the underlying microperiod half- life from a variety of common (macro) data frequencies.

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  • Fry, T.R.L. & Broadbent, S. & Dixon, J.M., 1999. "Estimating Advertising Half-Life and the Data Interval Bias," Monash Econometrics and Business Statistics Working Papers 6/99, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:1999-6

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    References listed on IDEAS

    1. Hyndman, R.J. & Yao, Q., 1998. "Nonparametric Estimation and Symmetry Tests for Conditional Density Functions," Monash Econometrics and Business Statistics Working Papers 17/98, Monash University, Department of Econometrics and Business Statistics.
    2. Grunwald, Gary K. & Hyndman, Rob J., 1998. "Smoothing non-Gaussian time series with autoregressive structure," Computational Statistics & Data Analysis, Elsevier, vol. 28(2), pages 171-191, August.
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    More about this item


    Adstock; half-life; data interval bias.;

    JEL classification:

    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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