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Interaction between Autocorrelation and Conditional Heteroscedasticity: A Random-Coefficient Approach

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Author Info

  • Bera, Anil K
  • Higgins, Matthew L
  • Lee, Sangkyu

Abstract

In applied econometrics, the authors tend to tackle specification problems one at a time rather than considering them jointly. This has serious consequences for statistical inference. One example of this is considering autocorrelation and autoregressive conditional heteroscedasticity separately. In this article, the authors consider a linear regression model with random coefficient autoregressive disturbances that provides a convenient framework to analyze autocorrelation and autoregressive conditional heteroscedasticity simultaneously. Their stationarity conditions and testing results reveal the strong interaction between autoregressive conditional heteroscedasticity and autocorrelation. An empirical example of testing the unbiasedness of experts' expectations of inflation demonstrates that neglecting conditional heteroscedasticity or misspecifying the autocorrelation structure might result in unreliable inference.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 10 (1992)
Issue (Month): 2 (April)
Pages: 133-42

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Handle: RePEc:bes:jnlbes:v:10:y:1992:i:2:p:133-42

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Cited by:
  1. Aknouche, Abdelhakim & Guerbyenne, Hafida, 2009. "On some probabilistic properties of double periodic AR models," Statistics & Probability Letters, Elsevier, vol. 79(3), pages 407-413, February.
  2. Furno, Marilena, 2001. "LAD estimation with random coefficient autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 36(4), pages 511-523, June.
  3. Marc Sáez & Robert M. Kunst, 1995. "ARCH patterns in cointegrated systems," Economics Working Papers 110, Department of Economics and Business, Universitat Pompeu Fabra.
  4. Stefan Mittnik & Marc Paolella & Svetlozar Rachev, 1998. "Unconditional and Conditional Distributional Models for the Nikkei Index," Asia-Pacific Financial Markets, Springer, vol. 5(2), pages 99-128, May.
  5. McDonald, A.David & Hurn, A.Stan, 1995. "Unobservable cyclical components in term premia of fixed-term financial instruments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 403-409.
  6. James D. Hamilton, 2008. "Macroeconomics and ARCH," NBER Working Papers 14151, National Bureau of Economic Research, Inc.
  7. Blake, Andrew P. & Kapetanios, George, 2007. "Testing for ARCH in the presence of nonlinearity of unknown form in the conditional mean," Journal of Econometrics, Elsevier, vol. 137(2), pages 472-488, April.
  8. Mohamed El Hedi Arouri & Shawkat Hammoudeh & Duc Khuong Nguyen & Amine Lahiani, 2013. "On the short- and long-run efficiency of energy and precious metal markets," Working Papers hal-00798036, HAL.
  9. Lumsdaine, Robin L. & Ng, Serena, 1999. "Testing for ARCH in the presence of a possibly misspecified conditional mean," Journal of Econometrics, Elsevier, vol. 93(2), pages 257-279, December.
  10. J. Peter Ferderer, 1999. "Credibility of the Interwar Gold Standard, Uncertainty, and the Great Depression," Macroeconomics 9907002, EconWPA.
  11. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, School of Economics and Management, University of Aarhus.
  12. Edmonds, Radcliffe Jr. & So, Jacky Y. C., 2004. "Is exchange rate volatility excessive? An ARCH and AR approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(1), pages 122-154, February.
  13. J. Peter Ferderer, 1994. "Credibility of the Interwar Gold Standard, Uncertainty, and the Great Depression," Economics Working Paper Archive wp_102, Levy Economics Institute.
  14. He, Changli & Teräsvirta, Timo, 2002. "An application of the analogy between vector ARCH and vector random coefficient autoregressive models," Working Paper Series in Economics and Finance 516, Stockholm School of Economics.
  15. H. Wong & W. Li, 2002. "Detecting and Diagnostic Checking Multivariate Conditional Heteroscedastic Time Series Models," Annals of the Institute of Statistical Mathematics, Springer, vol. 54(1), pages 45-59, March.
  16. Kyrtsou, Catherine, 2008. "Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6785-6789.
  17. De Arce Borda, R., 2004. "20 años de modelos ARCH: una visión de conjunto de las distintas variantes de la familia/20 Years of Arch Modelling: a Survey of Different Models in the Family," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 22, pages 27, Abril.
  18. Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2000. "Diagnosing and treating the fat tails in financial returns data," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 389-416, November.

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