IDEAS home Printed from
   My bibliography  Save this paper

Empirical likelihood-based inference in linear errors-in-covariables models with validation data


  • Wang, Qihua
  • Rao, J. N. K.


Linear errors-in-covariables models are considered, assuming the availability of independent validation data on the covariables in addition to primary data on the response variable and surrogate covariables. We first develop an estimated empirical log-likelihood with the help of validation data and prove that its asymptotic distribution is that of a weighted sum of independent standard x random variables with unknown weights. By estimating the unknown weights consistently, an estimated empirical likelihood confidence region on the regression parameter vector is constructed. We also suggest an adjusted empirical log-likelihood and prove that its asymptotic distribution is a standard X To avoid estimating the unknown weights or the adjustment factor, we propose a partially smoothed bootstrap empirical log- likelihood to construct a confidence region which has asymptotically correct coverage probability. A simulation study is conducted to compare the proposed methods with a normal approximation based method in term of coverage accuracy and average length of the confidence interval.

Suggested Citation

  • Wang, Qihua & Rao, J. N. K., 2001. "Empirical likelihood-based inference in linear errors-in-covariables models with validation data," SFB 373 Discussion Papers 2001,64, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:200164

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Hafner, Christian M. & Herwartz, Helmut, 2001. "Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis," Journal of Empirical Finance, Elsevier, vol. 8(1), pages 1-34, March.
    2. Lumsdaine, Robin L, 1996. "Consistency and Asymptotic Normality of the Quasi-maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models," Econometrica, Econometric Society, vol. 64(3), pages 575-596, May.
    3. Shinn-Juh Lin & Jian Yang, 1999. "Testing Shifts in Financial Models with Conditional Heteroskedasticity: An Empirical Distribution Function Approach," Research Paper Series 30, Quantitative Finance Research Centre, University of Technology, Sydney.
    4. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    5. Lastrapes, William D, 1989. "Exchange Rate Volatility and U.S. Monetary Policy: An ARCH Application," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 21(1), pages 66-77, February.
    6. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    7. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    8. Jin-Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32.
    9. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    10. Takatoshi Ito & Tokuo Iwaisako, 1996. "Explaining Asset Bubbles in Japan," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 14(1), pages 143-193, July.
    11. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    12. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    13. Harris, Lawrence, 1989. " S&P 500 Cash Stock Price Volatilities," Journal of Finance, American Finance Association, vol. 44(5), pages 1155-1175, December.
    Full references (including those not matched with items on IDEAS)


    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:zbw:sfb373:200164. 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: (ZBW - German National Library of Economics). General contact details of provider: .

    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.