Estimating Advertising Half-life and the Data Interval Bias

Tim R. L. Fry, Simon Broadbent and Janine M. Dixon

No 267379, Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: We compare three methods of estimating the duration, or half-life, of advertising using computer simulation experiments. In particular, we investigate 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" estimation 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" estimation procedure to obtain estimates of the underlying micro-period half-life from a variety of common (macro) data frequencies.

Keywords: Research and Development/Tech Change/Emerging Technologies; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 32
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Persistent link: https://EconPapers.repec.org/RePEc:ags:monebs:267379

DOI: 10.22004/ag.econ.267379

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