IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/0056.html
   My bibliography  Save this paper

Comparison of Robust and Varying Parameter Estimates of a Macroeconometric Model

Author

Listed:
  • Thomas F. Cooley

Abstract

Four estimators of econometric models are compared for predictive accuracy. Two estimators assume that the parameters of the equations are subject to variation over time. The first of these, the adaptive regression technique (ADR), assumes that the intercept varies overtime, while the other, a varying-parameter regression technique (VPR), assumes that all parameters may be subject to variation. The other two estimators are ordinary least squares (OLS) and a robust estimator that gives less weight to large residuals. The vehicle for these experiments is the econometric model developed by Ray Fair. The main conclusion is that varying parameter techniques appear promising for the estimation of econometric models. They are clearly superior in the present context for short term forecasts. Of the two varying parameter techniques considered, ADR is superior over longer prediction intervals.

Suggested Citation

  • Thomas F. Cooley, 1974. "Comparison of Robust and Varying Parameter Estimates of a Macroeconometric Model," NBER Working Papers 0056, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:0056
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w0056.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    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. 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.
    3. 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.
    4. Fair, Ray C, 1973. "A Comparison of Alternative Estimators of Macroeconomic Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 261-277, 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. Various, 1975. "Staff Reports on Research Under Way," NBER Chapters, in: Understanding Economic Change, pages 9-120, National Bureau of Economic Research, Inc.

    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. 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.
    2. 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.
    3. 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.
    4. repec:wrk:wrkemf:13 is not listed on IDEAS
    5. 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.
    6. 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.
    7. 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.
    8. Freebairn, John W. & Rausser, Gordon C., 1974. "Updating Parameter Estimates: A Least Squares Approach with an Application to the Inventory of Beef Cows," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 42(02), pages 1-17, June.
    9. Thomas F. Cooley & Steven J. DeCanio, 1974. "Varying-Parameter Supply Functions and the Sources of Economic Distress in American Agriculture, 1866-1914," NBER Working Papers 0057, National Bureau of Economic Research, Inc.
    10. 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.
    11. Arash Hadizadeh & Ahmad Jafari Samimi & Zahra Mila Elmi, 2013. "An Estimation of Seasonal GDP Gap in Iran: Application of Adaptive Least Squares Method," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 18(1), pages 157-177, winter.
    12. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    13. Schlicht, Ekkehart, 2006. "VC - A Method For Estimating Time-Varying Coefficients in Linear Models," Discussion Papers in Economics 61656, University of Munich, Department of Economics.
    14. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    15. 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.
    16. Faust, Jon & Rogers, John H. & Wang, Shing-Yi B. & Wright, Jonathan H., 2007. "The high-frequency response of exchange rates and interest rates to macroeconomic announcements," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1051-1068, May.
    17. Arrau, Patricio & De Gregorio, Jose & Reinhart, Carmen M. & Wickham, Peter, 1995. "The demand for money in developing countries: Assessing the role of financial innovation," Journal of Development Economics, Elsevier, vol. 46(2), pages 317-340, April.
    18. Rodríguez, Alejandro & Ruiz, Esther, 2012. "Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 62-74, January.
    19. Evans, George W. & Ramey, Garey, 2006. "Adaptive expectations, underparameterization and the Lucas critique," Journal of Monetary Economics, Elsevier, vol. 53(2), pages 249-264, March.
    20. Kwakwa, Paul Adjei, 2014. "Energy-growth nexus and energy demand in Ghana: A review of empirical studies," MPRA Paper 54971, University Library of Munich, Germany, revised 01 Apr 2014.
    21. Donald T. Sant, 1977. "Generalized Least Squares Applied to Time Varying Parameter Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 6, number 3, pages 301-314, National Bureau of Economic Research, Inc.

    More about this item

    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:nberwo:0056. 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.