IDEAS home Printed from https://ideas.repec.org/p/nbr/nberte/0201.html
   My bibliography  Save this paper

Asymptotically Median Unbiased Estimation of Coefficient Variance in a Time Varying Parameter Model

Author

Listed:
  • James H. Stock
  • Mark W. Watson

Abstract

This paper considers the estimation of the variance of coefficients in time varying parameter models with stationary regressors. The maximum likelihood estimator has large point mass at zero. We therefore develop asymptotically median unbiased estimators and confidence intervals by inverting median functions of regression-based parameter stability test statistics, computed under the constant-parameter null. These estimators have good asymptotic relative efficiencies for small to moderate amounts of parameter variability. We apply these results to an unobserved components model of trend growth in postwar U.S. GDP: the MLE implies that there has been no change in the trend rate, while the upper range of the median-unbiased point estimates imply that the annual trend growth rate has fallen by 0.7 percentage points over the postwar period.

Suggested Citation

  • James H. Stock & Mark W. Watson, 1996. "Asymptotically Median Unbiased Estimation of Coefficient Variance in a Time Varying Parameter Model," NBER Technical Working Papers 0201, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0201
    Note: ME
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/t0201.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alexander H. Sarris, 1973. "A Bayesian Approach To Estimation Of Time-Varying Regression Coefficients," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 2, number 4, pages 501-523, National Bureau of Economic Research, Inc.
    2. Saikkonen, Pentti & Luukkonen, Ritva, 1993. "Point Optimal Tests for Testing the Order of Differencing in ARIMA Models," Econometric Theory, Cambridge University Press, vol. 9(3), pages 343-362, June.
    3. Shephard, Neil, 1993. "Distribution of the ML Estimator of an MA(1) and a local level model," Econometric Theory, Cambridge University Press, vol. 9(3), pages 377-401, June.
    4. Cooley, Thomas F & Prescott, Edward C, 1973. "Tests of an Adaptive Regression Model," The Review of Economics and Statistics, MIT Press, vol. 55(2), pages 248-256, May.
    5. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    6. Cooley, Thomas F & Prescott, Edward C, 1973. "An Adaptive Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 364-371, June.
    7. Busetti, Fabio & Harvey, Andrew, 2008. "Testing For Trend," Econometric Theory, Cambridge University Press, vol. 24(1), pages 72-87, February.
    8. Sargan, J D & Bhargava, Alok, 1983. "Maximum Likelihood Estimation of Regression Models with First Order Moving Average Errors When the Root Lies on the Unit Circle," Econometrica, Econometric Society, vol. 51(3), pages 799-820, May.
    9. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    10. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, vol. 44(1), pages 167-184, January.
    11. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    12. Thomas S. Shively, 1988. "An Exact Test For A Stochastic Coefficient In A Time Series Regression Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(1), pages 81-88, January.
    13. N. G. Shephard & A. C. Harvey, 1990. "On The Probability Of Estimating A Deterministic Component In The Local Level Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(4), pages 339-347, July.
    14. Andrews, Donald W. K. & Lee, Inpyo & Ploberger, Werner, 1996. "Optimal changepoint tests for normal linear regression," Journal of Econometrics, Elsevier, vol. 70(1), pages 9-38, January.
    15. Chow, Gregory C., 1984. "Random and changing coefficient models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 21, pages 1213-1245, Elsevier.
    16. Davis, Richard A. & Dunsmuir, William T.M., 1996. "Maximum Likelihood Estimation for MA(1) Processes with a Root on or near the Unit Circle," Econometric Theory, Cambridge University Press, vol. 12(1), pages 1-29, March.
    17. Hansen, Bruce E, 2002. "Tests for Parameter Instability in Regressions with I(1) Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 45-59, January.
    18. Pantula, Sastry G, 1991. "Asymptotic Distributions of Unit-Root Tests When the Process Is Nearly Stationary," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 63-71, January.
    19. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michael T. Kiley, 2020. "What Can the Data Tell Us about the Equilibrium Real Interest Rate?," International Journal of Central Banking, International Journal of Central Banking, vol. 16(3), pages 181-209, June.
    2. Ian Dew-Becker & Robert J. Gordon, 2005. "Where Did Productivity Growth Go? Inflation Dynamics and the Distribution of Income," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 36(2), pages 67-150.
    3. Schalck, Christophe & Chenavaz, Régis, 2015. "Oil commodity returns and macroeconomic factors: A time-varying approach," Research in International Business and Finance, Elsevier, vol. 33(C), pages 290-303.
    4. Laurence Boone & Michel Juillard & Doug Laxton & Papa N'Diaye, 2002. "How Well Do Alternative Time-Varying Parameter Models of the NAIRU Help Policymakers Forecast Unemployment and Inflation in the OECD Countries?," Computing in Economics and Finance 2002 359, Society for Computational Economics.
    5. Moussa, Zakaria, 2010. "The Japanese Quantitative Easing Policy under Scrutiny: A Time-Varying Parameter Factor-Augmented VAR Model," MPRA Paper 29429, University Library of Munich, Germany.
    6. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
    7. Alberto Ronchi Neto & Osvaldo Candido, 2020. "Measuring the neutral real interest rate in Brazil: a semi-structural open economy framework," Empirical Economics, Springer, vol. 58(2), pages 651-667, February.
    8. Primiceri, Giorgio E. & van Rens, Thijs, 2009. "Heterogeneous life-cycle profiles, income risk and consumption inequality," Journal of Monetary Economics, Elsevier, vol. 56(1), pages 20-39, January.
    9. Mr. Papa M N'Diaye & Mr. Douglas Laxton, 2002. "Monetary Policy Credibility and the Unemployment-Inflation Tradeoff: Some Evidence From 17 Industrial Countries," IMF Working Papers 2002/220, International Monetary Fund.
    10. Massimiliano De Santis, 2005. "Movements in the Equity Premium: Evidence from a Bayesian Time-Varying VAR," Money Macro and Finance (MMF) Research Group Conference 2005 62, Money Macro and Finance Research Group.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    2. Feldstein, Martin & Stock, James H., 1996. "Measuring money growth when financial markets are changing," Journal of Monetary Economics, Elsevier, vol. 37(1), pages 3-27, February.
    3. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    4. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Birkbeck Working Papers in Economics and Finance 1409, Birkbeck, Department of Economics, Mathematics & Statistics.
    5. Li, Hong, 2008. "Estimation and testing of Euler equation models with time-varying reduced-form coefficients," Journal of Econometrics, Elsevier, vol. 142(1), pages 425-448, January.
    6. Yabe, Ryota, 2017. "Asymptotic distribution of the conditional-sum-of-squares estimator under moderate deviation from a unit root in MA(1)," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 220-226.
    7. Adom, Philip Kofi & Bekoe, William, 2013. "Modelling electricity demand in Ghana revisited: The role of policy regime changes," Energy Policy, Elsevier, vol. 61(C), pages 42-50.
    8. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    9. Ai Deng & Pierre Perron, 2006. "A comparison of alternative asymptotic frameworks to analyse a structural change in a linear time trend," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 423-447, November.
    10. Julian Ramajo & Miguel A. Marquez, 1998. "Structural change in regional economies: A varying coefficients econometric modeling approach," ERSA conference papers ersa98p189, European Regional Science Association.
    11. Bakhodir A Ergashev, 2004. "Sequential Detection of US Business Cycle Turning Points: Performances of Shiryayev-Roberts, CUSUM and EWMA Procedures," Econometrics 0402001, University Library of Munich, Germany, revised 16 Mar 2004.
    12. Tatsuma Wada & Pierre Perron, 2005. "Trend and Cycles: A New Approach and Explanations of Some Old Puzzles," Computing in Economics and Finance 2005 252, Society for Computational Economics.
    13. Douglas O. Staiger & James H. Stock & Mark W. Watson, 1997. "How Precise Are Estimates of the Natural Rate of Unemployment?," NBER Chapters, in: Reducing Inflation: Motivation and Strategy, pages 195-246, National Bureau of Economic Research, Inc.
    14. Min, Chung-ki, 1998. "A Gibbs sampling approach to estimation and prediction of time-varying-parameter models," Computational Statistics & Data Analysis, Elsevier, vol. 27(2), pages 171-194, April.
    15. Nyakabawo, Wendy & Miller, Stephen M. & Balcilar, Mehmet & Das, Sonali & Gupta, Rangan, 2015. "Temporal causality between house prices and output in the US: A bootstrap rolling-window approach," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 55-73.
    16. Filippo di Mauro & L. Vanessa Smith & Stephane Dees & M. Hashem Pesaran, 2007. "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 1-38.
    17. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2014. "Housing and the Great Depression," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2966-2981, August.
    18. Davide Pettenuzzo & Allan Timmermann, 2017. "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 183-201, April.
    19. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    20. Ramzi Issa & Robert Lafrance & John Murray, 2008. "The turning black tide: energy prices and the Canadian dollar," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(3), pages 737-759, August.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberte:0201. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.