Skip to main content
SpringerLink
Log in

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

  • Published:
Scientometrics Aims and scope Submit manuscript

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.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Berndt, E. K., B. H. Hall, R. E. Hall, J. A. Hausman (1974), Estimation and inference in nonlinear structural models, Annals of Economic and Social Measurement, 3: 653-665.

    Google Scholar 

  • Boussama, F. (2000), Asymptotic normality for the quasi-maximum likelihood estimator of a GARCH model, Comptes Rendus de l'Académie des Sciences, Série I, 331: 81-84.

    Article  MATH  MathSciNet  Google Scholar 

  • Bollerslev, T. (1986), Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31: 307-327.

    Article  MATH  MathSciNet  Google Scholar 

  • Bollerslev, T., J. M. Wooldridge (1992), Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances, Econometric Reviews, 11: 143-173.

    MATH  MathSciNet  Google Scholar 

  • Dunn, S., J. A. Peterson (Eds) (2001), Hydrogen Futures: Towards a Sustainable Energy System, Worldwatch Institute, Washington DC.

    Google Scholar 

  • Elie, L., T. Jeantheau (1995), Consistency in heteroskedastic models, Comptes Rendus de l'Académie des Sciences, Série I, 320: 1255-1258.

    MATH  MathSciNet  Google Scholar 

  • Engle, R. F. (1982), Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 50: 987-1007.

    Article  MATH  MathSciNet  Google Scholar 

  • Glosten, L., R. Jagannathan, D. Runkle (1992), On the relation between the expected value and volatility of nominal excess returns on stocks, Journal of Finance, 46: 1779-1801.

    Google Scholar 

  • Jeantheau, T. (1998), Strong consistency of estimators for multivariate ARCH models, Econometric Theory, 14: 70-86.

    Article  MathSciNet  Google Scholar 

  • Ling, S., W. K. Li (1997), On fractionally integrated autoregressive moving-average models with conditional heteroskedasticity, Journal of the American Statistical Association, 92: 1184-1194.

    Article  MATH  MathSciNet  Google Scholar 

  • Ling, S., M. McAleer (2000), Testing GARCH versus E-GARCH, In: W.-S. Chan, W. K. Li, H. Tong (Eds), Statistics and Finance: An Interface, Imperial College Press, London, pp. 226-242.

    Google Scholar 

  • Ling, S., M. McAleer (2002a), Necessary and sufficient moment conditions for the GARCH(r,s) and asymmetric power GARCH(r,s) models, Econometric Theory, 18: 722-729.

    Article  MATH  MathSciNet  Google Scholar 

  • Ling, S., M. McAleer (2002b), Stationarity and the existence of moments of a family of GARCH processes, Journal of Econometrics, 106: 109-117.

    Article  MATH  MathSciNet  Google Scholar 

  • Ling, S., M. McAleer (2003), Asymptotic theory for a vector ARMA-GARCH model, Econometric Theory, 19: 278-308.

    MathSciNet  Google Scholar 

  • Marinova, D., M. McAleer (2003a), Nanotechnology strength indicators: International rankings based on US Patents, Nanotechnology, 14: R1-R7.

    Article  Google Scholar 

  • Marinova, D., M. McAleer (2003b), Modelling trends and volatility in ecological patents in the USA, Environmental Modelling and Software, 18(3): 195-203.

    Article  Google Scholar 

  • McAleer, M., F. Chan, D. Marinova (to appear), An econometric analysis of asymmetric volatility: Theory and application to patents, paper presented to the Australasian Meeting of the Econometric Society, Brisbane, July 2002, Journal of Econometrics.

  • Nelson, D. B. (1991), Conditional heteroskedasticity in asset returns: A new approach, Econometrica, 59: 347-370.

    Article  MATH  MathSciNet  Google Scholar 

  • Phillips, P. C. B., P. Perron (1988), Testing for a unit root in time series regression, Biometrika, 75(2):335-346.

    Article  MATH  MathSciNet  Google Scholar 

  • Shephard, N. (1996), Statistical aspects of ARCH and stochastic volatility, In: O. E. Barndorff-Nielsen, D. R. Cox, D. V. Hinkley (Eds), Statistical Models in Econometrics, Finance and Other Fields, Chapman & Hall, London, pp. 1-67.

    Google Scholar 

  • World Bank (2001), Making Sustainable Commitments: An Environment Strategy for the World Bank, Washington DC.

Download references

Author information

Authors and Affiliations

  1. Department of Economics, University of Western Australia Crawley, WA (, Australia

    Felix Chan & Michael McAleer

  2. Institute for Sustainability and Technology Policy, Murdoch University Murdoch, WA, 6150, Australia

    Dora Marinova

Authors
  1. Felix Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dora Marinova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael McAleer
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chan, F., Marinova, D. & McAleer, M. Modelling the asymmetric volatility of anti-pollution patents in the USA. Scientometrics 59, 179–197 (2004). https://doi.org/10.1023/B:SCIE.0000018527.22276.10

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:SCIE.0000018527.22276.10

Keywords

Search

Navigation