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Modelling the asymmetric volatility of anti-pollution patents in the USA

Author

Listed:
  • Felix Chan

    (University of Western Australia Crawley)

  • Dora Marinova

    (Institute for Sustainability and Technology Policy, Murdoch University Murdoch)

  • Michael McAleer

    (University of Western Australia Crawley)

Abstract

The paper analyses the asymmetric volatility of patents related to pollution prevention and abatement (hereafter, anti-pollution) technologies registered in the USA. Ecological and pollution prevention technology patents have increased steadily over time, with the 1990's having been a period of intensive patenting of technologies related to the environment. The time-varying nature of the volatility of anti-pollution technology patents registered in the USA is examined using monthly data from the US Patent and Trademark Office for the period January 1975 to December 1999. Alternative symmetric and asymmetric volatility models, such as GARCH, GJR and EGARCH, are estimated and tested against each other using full sample and rolling windows estimation.

Suggested Citation

  • Felix Chan & Dora Marinova & Michael McAleer, 2004. "Modelling the asymmetric volatility of anti-pollution patents in the USA," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(2), pages 179-197, February.
    • Handle: RePEc:spr:scient:v:59:y:2004:i:2:d:10.1023_b:scie.0000018527.22276.10
    DOI: 10.1023/B:SCIE.0000018527.22276.10
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    References listed on IDEAS

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    1. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
    2. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
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    4. Ling, Shiqing & McAleer, Michael, 2002. "NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS," Econometric Theory, Cambridge University Press, vol. 18(3), pages 722-729, June.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. World Bank, 2001. "Making Sustainable Commitments : An Environment Strategy for the World Bank," World Bank Publications - Books, The World Bank Group, number 13985.
    7. Jeantheau, Thierry, 1998. "Strong Consistency Of Estimators For Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 14(1), pages 70-86, February.
    8. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    9. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Wang, Qizhen, 2019. "Multifractal characterization of air polluted time series in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 167-180.

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