Skip to main content
SpringerLink
Log in

Modelling multivariate stochastic time series for prediction: another look at the Lydia Pinkham data

  • Chapter
The Practice of Econometrics

Part of the book series: International Studies in Economics and Econometrics ((ISEE,volume 15))

Abstract

Market research very often considers different time series simultaneously and analyses their interdependence within the regression framework. The most prominent example is the relationship between sales and advertisement of which the carryover effect of advertising on sales has attracted much interest. Clarke’s (1976) well-known survey lists 69 studies up to 1975 and Aaker & Carman (1982) review several additional studies since then. The main emphasis in these studies has been on proper statistical modelling of the lag structure in the spirit of the empirical-econometrics tradition. The most common statistical specification has been the Koyck model for adaptive behaviour.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  • Aaker DA and Carman JM. 1982. Are you overadvertising? Journal of Advertising Research, 22: 57–69.

    Google Scholar 

  • Aaker DA, Carman JM and Jacobson R. 1982. Modelling advertising-sales relationship involving feedback: a time series analysis of six cereal brands. Journal of Marketing Research, 19: 116–125.

    Article  Google Scholar 

  • Abraham B. 1982. Temporal aggregation and time series. International Statistical Review, 50: 285–291.

    Article  Google Scholar 

  • Ashley R, Granger CWJ and Schmalensee R. 1980. Advertising and aggregate consumption: an analysis and causality. Econometrica, 48, 5: 1149–1167.

    Article  Google Scholar 

  • Bhattacharyya MN. 1982. Lydia Pinkham data remodelled. Journal of time series analysis, 3, 2: 81–102.

    Article  Google Scholar 

  • Bretschneider SI, Carbone R and Longini RL. 1982. An adaptive multivariate approach to time series forecasting. Decision Sciences, 13, 4: 668–680.

    Google Scholar 

  • Brewer KWR. 1973. Some consequences of temporal aggregation and systematic sampling for ARMA and ARM AX models. Journal of Econometrics, 1: 133–154.

    Article  Google Scholar 

  • Caines PE, Sethi SP and Brotherton TW. 1977. Impulse response identification and causality detection for the Lydia Pinkham data. Annals of Economic and Social Measurement, 6: 147–163.

    Google Scholar 

  • Chan WY and Wallis KF. 1978. Multiple time series modelling, another look at the mink-muskrat interaction. Applied Statistics, 27, 2: 168–175.

    Article  Google Scholar 

  • Clarke DG. 1976. Econometric measurement of the duration of advertising effects on sales. Journal of Marketing, 13: 345–357.

    Article  Google Scholar 

  • Cramer JS. 1969. Empirical econometrics. Amsterdam/London: North-Holland Publishing Co.

    Google Scholar 

  • Cramer JS. 1978. On prediction. Proceedings Bicentennial Congress Wiskundig Genootschap, Amsterdam: MC tract serie, 100–101, 123–132.

    Google Scholar 

  • Fase MMG. 1969. An econometric model of age-income profiles. Rotterdam: Rotterdam University Press.

    Google Scholar 

  • Fase MMG. 1971. On the estimation of lifetime income. Journal of the American Statistical Association, 66: 686–692.

    Article  Google Scholar 

  • Fase MMG. 1972. The distribution of lifetime earnings: a problem of intertemporal aggregation. Statistica Neerlandica, 26: 103–111.

    Article  Google Scholar 

  • Fase MMG. 1981. Op het breukvlak van micro- en macro-economie. Leiden: Stenfert Kroese.

    Google Scholar 

  • Granger CWJ. 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 3: 424–438.

    Article  Google Scholar 

  • Guilkey DK and Salemi MK. 1982. Small sample properties of three tests for Granger-causal ordering in a bivariate stochastic system. Review of Economics and Statistics, 67, 4: 668–680.

    Article  Google Scholar 

  • Hanssens DM. 1980. Bivariate time-series analysis of the relationship between advertising and sales. Applied Economics, 12: 329–339.

    Article  Google Scholar 

  • Helmer RM and Johansson JK. 1977. An exposition of the Box-Jenkins transfer function analysis with an application to the advertising-sales relationship. Journal of Marketing Research, 14, 227–239.

    Article  Google Scholar 

  • Hsiao CH. 1979. Autoregressive modelling of Canadian money and income data. Journal of the American Statistical Association, 74: 553–560.

    Article  Google Scholar 

  • Hsiao CH. 1982. Autoregressive modelling and causal ordering of economic variables. Journal of Economic Dynamics and Control, 4: 243–259.

    Article  Google Scholar 

  • Jenkins GM. 1974. The. interaction between the muskrat and mink cycles in North Canada, in: Proceedings of the 8th international biometric conference, August 1974 Constanta Rumania, edited by L.C. A. Corsten and T. Postelnicu. Editura Academici Republicii Socialiste Romania, 55–71.

    Google Scholar 

  • Kang H. 1981. Necessary and sufficient conditions for causality testing in multivariate ARMA models. Journal of Time Series Analysis, 2, 2: 95–101.

    Article  Google Scholar 

  • Kapoor SG, Madhok P and Wu SM. 1981. Modelling and forecasting sales data by time series analysis. Journal of Marketing Research, 18: 94–100.

    Article  Google Scholar 

  • Maravall A. 1981. A note on identification of multivariate time-series models. Journal of Econometrics, 16, 2: 237–247.

    Article  Google Scholar 

  • Nerlove M, Grether DM and Carvalho JL. 1979. Analysis of economic time series: a synthesis. New York: Academic Press.

    Google Scholar 

  • Osborn DR. 1984. Causality testing and its implications for dynamic econometric models. Economic Journal, 94 (supplement), 82–96.

    Google Scholar 

  • Palda KS. 1964. The measurement of advertising effects. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • Sims CA. 1972. Money, income and causality. American Economic Review, 62: 540–552.

    Google Scholar 

  • Theil H. 1958. Economic forecasts and policy. Amsterdam: North-Holland Publishing Co.

    Google Scholar 

  • Tiao GC and Box GEP. 1981. Modelling multiple time series with applications. Journal of the American Statistical Association, 76: 802–816.

    Article  Google Scholar 

  • Tiao GC and Tsay RS. 1983. Multiple time series modelling and extended sample cross-correlations. Journal of Business and Economic Statistics, 1, 1: 43–56.

    Article  Google Scholar 

  • Umashankar S and Ledolter J. 1983. Forecasting with diagonal multiple time series models: an extension of univariate models. Journal of Marketing Research, 20: 58–63.

    Article  Google Scholar 

  • Wei WWS. 1978. Some consequences of temporal aggregation in seasonal time series models, in: Seasonal Analysis of Economic Time Series, edited by A. Zellner. Washington: 433–444.

    Google Scholar 

  • Zellner A. 1979. Causality and econometrics, in: The aspects of policy and policymaking, edited by K. Brunner and A.H. Meltzer. Amsterdam: North-Holland Publishing Co., 9–54.

    Google Scholar 

Download references

Authors
  1. Martin M. G. Fase
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands

    Risto Heijmans  & Heinz Neudecker  & 

Rights and permissions

Reprints and permissions

Copyright information

© 1987 Martinus Nijhoff Publishers, Dordrecht

About this chapter

Cite this chapter

Fase, M.M.G. (1987). Modelling multivariate stochastic time series for prediction: another look at the Lydia Pinkham data. In: Heijmans, R., Neudecker, H. (eds) The Practice of Econometrics. International Studies in Economics and Econometrics, vol 15. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3591-4_14

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-3591-4_14

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-8106-1

  • Online ISBN: 978-94-009-3591-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation