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A Comparison of Alternative Instrumental Variables Estimators of Dynamic Linear Model

Author

Listed:
  • West, K.D.
  • Wilcox, D.W.

Abstract

Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, the authors compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional one (Hansen (1985)). They find that for some plausible data generating processes, the optimal one is distinctly more efficient asymptotically. Simulations indicate that, in samples of size typically available, asymptotic theory describes the distribution of the parameter estimates reasonably well but that test statistics sometimes are poorly sized.
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Suggested Citation

  • West, K.D. & Wilcox, D.W., 1994. "A Comparison of Alternative Instrumental Variables Estimators of Dynamic Linear Model," Working papers 9414, Wisconsin Madison - Social Systems.
    • Handle: RePEc:att:wimass:9414
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    Cited by:

    1. is not listed on IDEAS
    2. Joseph, Agnes S. & Kiviet, Jan F., 2005. "Viewing the relative efficiency of IV estimators in models with lagged and instantaneous feedbacks," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 417-444, April.
    3. West, Kenneth D, 2001. "On Optimal Instrumental Variables Estimation of Stationary Time Series Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1043-1050, November.
    4. West, Kenneth D., 1997. "Another heteroskedasticity- and autocorrelation-consistent covariance matrix estimator," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 171-191.
    5. Arellano, Manuel, 2016. "Modelling optimal instrumental variables for dynamic panel data models," Research in Economics, Elsevier, vol. 70(2), pages 238-261.
    6. West, Kenneth D & McCracken, Michael W, 1998. "Regression-Based Tests of Predictive Ability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 817-840, November.
    7. Hamilton, James D., 2002. "On the interpretation of cointegration in the linear-quadratic inventory model," Journal of Economic Dynamics and Control, Elsevier, vol. 26(12), pages 2037-2049, October.
    8. Ramey, Valerie A. & West, Kenneth D., 1999. "Inventories," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 13, pages 863-923, Elsevier.
    9. Tanja Krone & Casper J. Albers & Marieke E. Timmerman, 2017. "A comparative simulation study of AR(1) estimators in short time series," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(1), pages 1-21, January.
    10. Kenneth West & Ka-fu Wong & Stanislav Anatolyev, 2009. "Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 28(5), pages 441-467.
    11. Stanislav Anatolyev, 2007. "Optimal Instruments In Time Series: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 143-173, February.
    12. Liu, Wen-Hsien & Chung, Ching-Fan & Chang, Kuang-Liang, 2013. "Inventory change, capacity utilization and the semiconductor industry cycle," Economic Modelling, Elsevier, vol. 31(C), pages 119-127.
    13. Sophocles Mavroeidis, 2006. "Testing the New Keynesian Phillips Curve Without Assuming Identification," Working Papers 2006-13, Brown University, Department of Economics.
    14. David Mandy & Sandor Fridli, 2004. "Exact FGLS Asymptotics for MA Errors," Working Papers 0405, Department of Economics, University of Missouri, revised 16 Dec 2004.
    15. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
    16. Kenneth D. West, 1993. "Inventory Models," NBER Technical Working Papers 0143, National Bureau of Economic Research, Inc.
    17. Kuersteiner, Guido M., 2012. "Kernel-weighted GMM estimators for linear time series models," Journal of Econometrics, Elsevier, vol. 170(2), pages 399-421.
    18. Kiviet, Jan F. & Niemczyk, Jerzy, 2007. "The asymptotic and finite sample distributions of OLS and simple IV in simultaneous equations," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3296-3318, April.
    19. West, K.D., 1997. "On Optimal Instrumental Variables Estimation of Time Series Models," Working papers 9717, Wisconsin Madison - Social Systems.
    20. Adrian Pagan, 2007. "Weak Instruments: A Guide to the Literature," NCER Working Paper Series 13, National Centre for Econometric Research.

    More about this item

    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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