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A Comparison of Alternative Instrumental Variables Estimators of a Dynamic Linear Model

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  • West, Kenneth D
  • Wilcox, David 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.

Suggested Citation

  • West, Kenneth D & Wilcox, David W, 1996. "A Comparison of Alternative Instrumental Variables Estimators of a Dynamic Linear Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 281-293, July.
  • Handle: RePEc:bes:jnlbes:v:14:y:1996:i:3:p:281-93
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Hansen, Lars Peter, 1985. "A method for calculating bounds on the asymptotic covariance matrices of generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 203-238.
    3. Epstein, Larry G & Zin, Stanley E, 1991. "Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: An Empirical Analysis," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 263-286, April.
    4. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    5. Blanchard, Olivier J. & Melino, Angelo, 1986. "The cyclical behavior of prices and quantities: The case of the automobile market," Journal of Monetary Economics, Elsevier, vol. 17(3), pages 379-407, May.
    6. Ramey, Valerie A, 1991. "Nonconvex Costs and the Behavior of Inventories," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 306-334, April.
    7. Kenneth D. West & David W. Wilcox, 1993. "Some evidence on finite sample behavior of an instrumental variables estimator of the linear quadratic inventory model," Finance and Economics Discussion Series 93-29, Board of Governors of the Federal Reserve System (U.S.).
    8. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    9. Hansen, Lars Peter & Singleton, Kenneth J, 1996. "Efficient Estimation of Linear Asset-Pricing Models with Moving Average Errors," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 53-68, January.
    10. West, Kenneth D, 1986. "A Variance Bounds Test of the Linear Quadratic Inventory Model," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 374-401, April.
    11. West, Kenneth D., 1997. "Another heteroskedasticity- and autocorrelation-consistent covariance matrix estimator," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 171-191.
    12. Kenneth D. West, 1993. "Inventory Models," NBER Technical Working Papers 0143, National Bureau of Economic Research, Inc.
    13. Eichenbaum, Martin, 1989. "Some Empirical Evidence on the Production Level and Production Cost Smoothing Models of Inventory Investment," American Economic Review, American Economic Association, vol. 79(4), pages 853-864, September.
    14. Rotemberg, Julio J, 1984. "Interpreting the Statistical Failures of Some Rational Expectations Macroeconomic Models," American Economic Review, American Economic Association, vol. 74(2), pages 188-193, May.
    15. Tauchen, George, 1986. "Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained from Financial Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 397-416, October.
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    Citations

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    Cited by:

    1. West, Kenneth D., 1997. "Another heteroskedasticity- and autocorrelation-consistent covariance matrix estimator," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 171-191.
    2. 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.
    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. Stanislav Anatolyev, 2007. "Optimal Instruments In Time Series: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 143-173, February.
    5. Sophocles Mavroeidis, 2006. "Testing the New Keynesian Phillips Curve Without Assuming Identification," Working Papers 2006-13, Brown University, Department of Economics.
    6. Kenneth D. West, 1993. "Inventory Models," NBER Technical Working Papers 0143, National Bureau of Economic Research, Inc.
    7. 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.
    8. 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.
    9. West, K.D., 1997. "On Optimal Instrumental Variables Estimation of Time Series Models," Working papers 9717, Wisconsin Madison - Social Systems.
    10. 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.
    11. 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.
    12. Arellano, Manuel, 2016. "Modelling optimal instrumental variables for dynamic panel data models," Research in Economics, Elsevier, vol. 70(2), pages 238-261.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. David Mandy & Sandor Fridli, 2004. "Exact FGLS Asymptotics for MA Errors," Working Papers 0405, Department of Economics, University of Missouri, revised 16 Dec 2004.
    18. Kuersteiner, Guido M., 2012. "Kernel-weighted GMM estimators for linear time series models," Journal of Econometrics, Elsevier, vol. 170(2), pages 399-421.
    19. Adrian Pagan, 2007. "Weak Instruments: A Guide to the Literature," NCER Working Paper Series 13, National Centre for Econometric Research.

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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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