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Lydia Pinkham Data Remodelled

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  • M. N. Bhattacharyya

Abstract

. There is no effective bivariate feedback relationship between Lydia Pinkham monthly dollar sales and advertising. The effectiveness is measured in terms of the forecasting performance of the bivariate models against the forecasting performance of the respective univariate models, outside the fit period. While the future advertising is better forecast by using the past advertising and sales, the future sales are better forecast by using past sales only. There is no Koyck effect or memory effect of advertising on sales. The results are completely opposite to the conclusion of the previous researchers.

Suggested Citation

  • M. N. Bhattacharyya, 1982. "Lydia Pinkham Data Remodelled," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(2), pages 81-102, March.
    • Handle: RePEc:bla:jtsera:v:3:y:1982:i:2:p:81-102
    DOI: 10.1111/j.1467-9892.1982.tb00331.x
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    Cited by:

    1. José Casals Carro & Miguel Jerez Méndez & Sonia Sotoca López, 2006. "Decomposition of state-space Model with inputs: The theory and an application to estimate the ROI of advertising," Documentos de Trabajo del ICAE 0602, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Michael L. Bagshaw, 1986. "Comparison of univariate ARIMA, multivariate ARIMA and vector autoregression forecasting," Working Papers (Old Series) 8602, Federal Reserve Bank of Cleveland.
    3. Ribeiro Ramos, Francisco Fernando, 2003. "Forecasts of market shares from VAR and BVAR models: a comparison of their accuracy," International Journal of Forecasting, Elsevier, vol. 19(1), pages 95-110.
    4. Francisco F. R. Ramos, 1996. "Forecasting market shares using VAR and BVAR models: A comparison of their forecasting performance," Econometrics 9601003, University Library of Munich, Germany.

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