IDEAS home Printed from https://ideas.repec.org/p/ecm/wc2000/1654.html
   My bibliography  Save this paper

Econometric Evaluation of Rational Belief Models

Author

Listed:
  • Sergei Morozov

    (Stanford University)

Abstract

The paper proposes a method for construction, estimation, and testing the Rational Beliefs (RB) models. RB models, due to Kurz, 1994, allow agents' beliefs to differ from the Rational Expectations (RE), but require that beliefs cannot be contradicted by past data. By implication, RB and RE must agree in strictly stationary worlds, while a disagreement is allowed in non-stationary setting. The estimation method involves sample counterparts to the conditional and unconditional moment restrictions formed from the Euler equations and rationality conditions. In essence, the method deduces systems of conditional beliefs consistent with the conditional moment restriction posed by the Euler equations. Consistent test statistics then discriminates the rationality from non-rationality. The attractive features are (i) the estimation and testing procedures are implemented without solving explicitly for RB equilibria, (ii) learning is permitted, and (iii) both the econometrician and the economic agents are put on the ``equal footing'' in the sense of Muth, 1961 and ``down to earth''. Under flexible regularity conditions, the test statistics are shown to converge in distribution to the continuous functionals of generalized Brownian bridges, whose coordinates are projections on the space of moment functions that are used to phrase the rationality conditions. As a result, the limit distributions are non-standard or standard, depending on whether the test statistic is itself a function of finite-dimensional projection or a functional of the whole process, respectively. The resampling and simulation methods allow for valid approximation of either distribution. A simple estimated model of aggregate consumption and stock market behavior, populated by investors with rational beliefs, points to the variation in agents' sentiments as a dominant source of asset price volatility.

Suggested Citation

  • Sergei Morozov, 2000. "Econometric Evaluation of Rational Belief Models," Econometric Society World Congress 2000 Contributed Papers 1654, Econometric Society.
  • Handle: RePEc:ecm:wc2000:1654
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/RePEc/es2000/1654.pdf
    File Function: main text
    Download Restriction: no

    References listed on IDEAS

    as
    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    2. Peel, David & Davidson, James, 1998. "A non-linear error correction mechanism based on the bilinear model1," Economics Letters, Elsevier, vol. 58(2), pages 165-170, February.
    3. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, vol. 59(2), pages 283-306, March.
    4. repec:bla:restud:v:57:y:1990:i:1:p:99-125 is not listed on IDEAS
    5. Hansen, Bruce E, 1992. "Consistent Covariance Matrix Estimation for Dependent Heterogeneous Processes," Econometrica, Econometric Society, vol. 60(4), pages 967-972, July.
    6. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    7. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", pages 125-132.
    8. Granger, C W J & Lee, T H, 1989. "Investigation of Production, Sales and Inventory Relationships Using Multicointegration and Non-symmetric Error Correction Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 145-159, Supplemen.
    9. Hansen, Bruce E., 1992. "Efficient estimation and testing of cointegrating vectors in the presence of deterministic trends," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 87-121.
    10. repec:cup:etheor:v:11:y:1995:i:5:p:888-911 is not listed on IDEAS
    11. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    12. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    13. Robert M. De Jong & James Davidson, 2000. "Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices," Econometrica, Econometric Society, vol. 68(2), pages 407-424, March.
    14. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    15. Phillips, Peter C B & Ouliaris, S, 1990. "Asymptotic Properties of Residual Based Tests for Cointegration," Econometrica, Econometric Society, vol. 58(1), pages 165-193, January.
    16. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    17. Saikkonen, Pentti, 1995. "Problems with the Asymptotic Theory of Maximum Likelihood Estimation in Integrated and Cointegrated Systems," Econometric Theory, Cambridge University Press, vol. 11(05), pages 888-911, October.
    18. de Jong, Robert M., 2001. "Nonlinear estimation using estimated cointegrating relations," Journal of Econometrics, Elsevier, vol. 101(1), pages 109-122, March.
    Full references (including those not matched with items on IDEAS)

    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:ecm:wc2000:1654. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/essssea.html .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.