IDEAS home Printed from
   My bibliography  Save this paper

Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process


  • Dong Jin Lee

    (University of Connecticut)


This paper considers parameter instability tests in conditional quantile models. I suggest tests for quantile parameter instability based on the asymptotically optimal tests of Lee (2008) both in parametric and semiparametric set-up. In parametric models, Komunjer (2005)'s tick-exponential family of distributions is used as the underlying distribution, in which the test has asymptotically correct sizes even when the error distribution is misspecified. I apply our test statistic to various quantile models of the U.S. inflation process such as Phillips curve, P-star model, and autoregressive models. The test result shows an evidence of parameter instability in most quantile levels of all models. The semiparametric test rejects the stability even in more recent period with moderate economic volatility. Phillips curve model and autoregressive model have asymmetric test results across quantile levels, implying the asymmetric response of inflation to economic shocks.

Suggested Citation

  • Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
  • Handle: RePEc:uct:uconnp:2009-26

    Download full text from publisher

    File URL:
    File Function: Full text
    Download Restriction: no

    References listed on IDEAS

    1. Komunjer, Ivana, 2005. "Quasi-maximum likelihood estimation for conditional quantiles," Journal of Econometrics, Elsevier, vol. 128(1), pages 137-164, September.
    2. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    3. Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
    4. Lance J. Bachmeier & Norman R. Swanson, 2005. "Predicting Inflation: Does The Quantity Theory Help?," Economic Inquiry, Western Economic Association International, vol. 43(3), pages 570-585, July.
    5. Ippei Fujiwara & Maiko Koga, 2002. "A Statistical Forecasting Method for Inflation Forecasting," Bank of Japan Working Paper Series Research and Statistics D, Bank of Japan.
    6. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    7. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-1310, November.
    8. Marco Vega, 2004. "Policy Makers Priors and Inflation Density Forecasts," Econometrics 0403005, EconWPA.
    9. James W. Taylor & Derek W. Bunn, 1999. "A Quantile Regression Approach to Generating Prediction Intervals," Management Science, INFORMS, vol. 45(2), pages 225-237, February.
    10. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    11. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.
    12. Thompson, Patrick A & Miller, Robert B, 1986. "Sampling the Future: A Bayesian Approach to Forecasting from Univariate Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 427-436, October.
    13. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    14. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
    15. Arturo Estrella & Jeffrey C. Fuhrer, 2003. "Monetary Policy Shifts and the Stability of Monetary Policy Models," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 94-104, February.
    16. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    17. J. Jouini & M. Boutahar, 2003. "Structural breaks in the U.S. inflation process: a further investigation," Applied Economics Letters, Taylor & Francis Journals, vol. 10(15), pages 985-988.
    18. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
    19. Koenker, Roger & Park, Beum J., 1996. "An interior point algorithm for nonlinear quantile regression," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 265-283.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Quantile Model; optimal test; parameter instability; Phillips curve; inflation;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:uct:uconnp:2009-26. 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: (Mark McConnel). 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.

    If CitEc recognized a 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.

    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.