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Does linearity in the dynamics of inflation gap and unemployment rate matter?


  • Roque Montero


This paper tests the hypothesis of linearity against a specific form of nonlinearity in the Data Generating Process (DGP) of the unemployment rate and the difference between the inflation rate (CPI and CPIX1) and the inflation target. The test is performed over each variable using time series models. Under the null hypothesis, the DGP has a linear representation (AR model) and under the alternative, a non linear specification (SETAR model). Unlike traditional ARIMA models, these models allow the endogenous variable to have different regimes across time. The main results are: it is not possible to reject linearity in the deviation of inflation from the inflation target. During the last twenty years, inflation has converged smoothly to the target without any regime switching. Finally, strong evidence is found against linearity in the unemployment rate. On the contrary, it fluctuates with high probability between states or regimes through time.

Suggested Citation

  • Roque Montero, 2011. "Does linearity in the dynamics of inflation gap and unemployment rate matter?," Working Papers Central Bank of Chile 614, Central Bank of Chile.
  • Handle: RePEc:chb:bcchwp:614

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    References listed on IDEAS

    1. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    2. 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.
    3. Hansen, Bruce E, 1999. " Testing for Linearity," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 551-576, December.
    4. Javier García - Cicco & Roque Montero, 2011. "Modeling Copper Price: A Regime-Switching Approach," Working Papers Central Bank of Chile 613, Central Bank of Chile.
    5. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.
    6. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    7. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
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    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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