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On the econometrics of the Koyck model

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  • Franses, Ph.H.B.F.
  • van Oest, R.D.

Abstract

The geometric distributed lag model, after application of the so-called Koyck transformation, is often used to establish the dynamic link between sales and advertising. This year, the Koyck model celebrates its 50th anniversary.In this paper we focus on the econometrics of this popular model,and we show that this seemingly simple model is a little more complicated than we always tend to think. First, the Koyck transformation entails a parameter restriction, which should not be overlooked for efficiency reasons. Second, the t-statistic for the parameter for direct advertising effects has a non-standard distribution. We provide solutions to these two issues. For the monthly Lydia Pinkham data, it is shown that various practical decisions lead to very different conclusions.

Suggested Citation

  • Franses, Ph.H.B.F. & van Oest, R.D., 2004. "On the econometrics of the Koyck model," Econometric Institute Research Papers EI 2004-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1190
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    References listed on IDEAS

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    1. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    2. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    3. Carrasco, Marine, 2002. "Misspecified Structural Change, Threshold, and Markov-switching models," Journal of Econometrics, Elsevier, vol. 109(2), pages 239-273, August.
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    Cited by:

    1. Franses, Philip Hans, 2006. "Forecasting in Marketing," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 18, pages 983-1012, Elsevier.
    2. Nicolae-Marius JULA, 2015. "Modelling loans and deposits during electoral years in Romania," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 3(1), pages 43-48, June.
    3. Melvin Woodley, 2021. "Decoupling the individual effects of multiple marketing channels with state space models," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 248-255, June.
    4. Vighneswara Swamy, 2022. "Financial wealth effects and consumption expenditure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1933-1946, April.
    5. Alexandra Horobet & Georgiana Vrinceanu & Consuela Popescu & Lucian Belascu, 2019. "Oil Price and Stock Prices of EU Financial Companies: Evidence from Panel Data Modeling," Energies, MDPI, vol. 12(21), pages 1-17, October.
    6. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    7. Philip Hans Franses, 2004. "Fifty years since Koyck (1954)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 381-387, November.

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