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GARCH-based identification and estimation of triangular systems

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Author Info
Todd Prono

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Abstract

Diagonal GARCH is shown to support identification of the triangular system and is argued as a higher moment analog to traditional exclusion restrictions used for determining suitable instruments. The estimator for this result is ML in the case where a distribution for the GARCH process is known and GMM otherwise. For the GMM estimator, an alternative weighting matrix is proposed.

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Paper provided by Federal Reserve Bank of Boston in its series Quantitative Analysis Unit Working Paper with number QAU08-4.

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Date of creation: 2008
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Handle: RePEc:fip:fedbqu:qau08-4

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Keywords: Time-series analysis;

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  1. Christian M. Hafner, 2003. "Fourth Moment Structure of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 1(1), pages 26-54.
  2. Sentana, Enrique & Fiorentini, Gabriele, 2001. "Identification, estimation and testing of conditionally heteroskedastic factor models," Journal of Econometrics, Elsevier, vol. 102(2), pages 143-164, June. [Downloadable!] (restricted)
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  3. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-27, July. [Downloadable!] (restricted)
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  4. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July. [Downloadable!] (restricted)
  5. Roberto Rigobon & Brian Sack, 2001. "Measuring the Reaction of Monetary Policy to the Stock Market," NBER Working Papers 8350, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July. [Downloadable!] (restricted)
  7. Roberto Rigobon, 2003. "Identification Through Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 777-792, 09. [Downloadable!] (restricted)
  8. Arthur Lewbel, 1997. "Constructing Instruments for Regressions with Measurement Error when no Additional Data are Available, with an Application to Patents and R&D," Econometrica, Econometric Society, vol. 65(5), pages 1201-1214, September.
  9. West, Kenneth D., 2002. "Efficient GMM estimation of weak AR processes," Economics Letters, Elsevier, vol. 75(3), pages 415-418, May. [Downloadable!] (restricted)
  10. Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245 Elsevier. [Downloadable!] (restricted)
  11. Garry Phillips & Emma Iglesias, 2004. "Simultaneous Equations and Weak Instruments under Conditionally Heteroscedastic Disturbances," Econometric Society 2004 Far Eastern Meetings 567, Econometric Society. [Downloadable!]
  12. Arthur Lewbel, 2003. "Using Heteroskedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Boston College Working Papers in Economics 587, Boston College Department of Economics, revised 27 Nov 2007. [Downloadable!]
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