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Forecasting in marketing

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  • Franses, Ph.H.B.F.

Abstract

With the advent of advanced data collection techniques, there is an increased interest in using econometric models to support decisions in marketing. Due to the sometimes specific nature of variables in marketing, the discipline uses econometric models that are rarely, if ever, used elsewhere. This chapter deals with techniques to derive forecasts from these models. Due to the intrinsic non-linear nature of these models, these techniques draw heavliy on simulation techniques.

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File URL: http://repub.eur.nl/pub/1631/ei200440.pdf
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Bibliographic Info

Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 2004-40.

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Date of creation: 22 Sep 2004
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Handle: RePEc:ems:eureir:1631

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Related research

Keywords: Bass model; Koyck model; attraction model; forecasting; marketing; unobserved heterogeneity;

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References

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  1. Fok, D. & Franses, Ph.H.B.F., 2000. "Forecasting Market Shares from Models for Sales," ERIM Report Series Research in Management ERS-2000-03-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
  2. Klapper, Daniel & Herwartz, Helmut, 2000. "Forecasting market share using predicted values of competitive behavior: further empirical results," International Journal of Forecasting, Elsevier, vol. 16(3), pages 399-421.
  3. Kumar, V., 1994. "Forecasting performance of market share models: an assessment, additional insights, and guidelines," International Journal of Forecasting, Elsevier, vol. 10(2), pages 295-312, September.
  4. Arino, Miguel A. & Franses, Philip Hans, 2000. "Forecasting the levels of vector autoregressive log-transformed time series," International Journal of Forecasting, Elsevier, vol. 16(1), pages 111-116.
  5. Gary J. Russell, 1988. "Recovering Measures of Advertising Carryover from Aggregate Data: The Role of the Firm's Decision Behavior," Marketing Science, INFORMS, vol. 7(3), pages 252-270.
  6. Robert P. Leone, 1995. "Generalizing What Is Known About Temporal Aggregation and Advertising Carryover," Marketing Science, INFORMS, vol. 14(3_supplem), pages G141-G150.
  7. Frank M. Bass & Robert P. Leone, 1983. "Temporal Aggregation, the Data Interval Bias, and Empirical Estimation of Bimonthly Relations from Annual Data," Management Science, INFORMS, vol. 29(1), pages 1-11, January.
  8. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
  9. Bijwaard, G.E. & Franses, Ph.H.B.F. & Paap, R., 2003. "Modeling purchases as repeated events," Econometric Institute Research Papers EI 2003-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  10. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
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Cited by:
  1. Patricia Chelley-Steeley & James Steeley, 2005. "The leverage effect in the UK stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 15(6), pages 409-423.

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