IDEAS home Printed from https://ideas.repec.org/p/chb/bcchwp/614.html
   My bibliography  Save this paper

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

Author

Listed:
  • Roque Montero

Abstract

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
    as

    Download full text from publisher

    File URL: https://www.bcentral.cl/documents/33528/133326/DTBC_614.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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. repec:bla:jecsur:v:13:y:1999:i:5:p:551-76 is not listed on IDEAS
    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. Rómulo Chumacero E., 2004. "Forecasting Chilean Industrial Production and Sales With Automated Procedures," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 7(3), pages 47-56, December.
    6. 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.
    7. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    8. Hansen,B.E., 1999. "Testing for linearity," Working papers 7, Wisconsin Madison - Social Systems.
    9. 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.
    Full references (including those not matched with items on IDEAS)

    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. Singh, Tarlok, 2014. "On the regime-switching and asymmetric dynamics of economic growth in the OECD countries," Research in Economics, Elsevier, vol. 68(2), pages 169-192.
    2. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    3. Lanouar Charfeddine & Dominique Guegan, 2008. "Is it possible to discriminate between different switching regressions models? An empirical investigation," Post-Print halshs-00368358, HAL.
    4. Ihle, Rico & von Cramon-Taubadel, Stephan, 2008. "A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37603, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    5. Gerson Nhapulo & João Nicolau, 2017. "Assessing Nonlinear Dynamics of Central Bank Reaction Function: The Case of Mozambique," South African Journal of Economics, Economic Society of South Africa, vol. 85(1), pages 28-51, March.
    6. Gabriel Vasco J. & Alexandre Fernando & Bação Pedro, 2008. "The Consumption-Wealth Ratio under Asymmetric Adjustment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(4), pages 1-32, December.
    7. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro," Documents de travail du Centre d'Economie de la Sorbonne 09053, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2002. "Estimation and model selection based inference in single and multiple threshold models," Journal of Econometrics, Elsevier, vol. 110(2), pages 319-352, October.
    9. Kulaksizoglu, Tamer & Kulaksizoglu, Sebnem, 2009. "The U.S. Excess Money Growth and Inflation Relation in the Long-Run: A Nonlinear Analysis," MPRA Paper 23780, University Library of Munich, Germany.
    10. Gross, Marco & Binder, Michael, 2013. "Regime-switching global vector autoregressive models," Working Paper Series 1569, European Central Bank.
    11. Franc Klaassen, 2005. "Long Swings in Exchange Rates: Are They Really in the Data?," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 87-95, January.
    12. Trenkler, Carsten & Wolf, Nikolaus, 2005. "Economic integration across borders: The Polish interwar economy 1921–1937," European Review of Economic History, Cambridge University Press, vol. 9(2), pages 199-231, August.
    13. Kim, Chang-Jin & Morley, James C. & Nelson, Charles R., 2001. "Does an intertemporal tradeoff between risk and return explain mean reversion in stock prices?," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 403-426, September.
    14. Philip Kostov & John Lingard, 2004. "Regime-switching Vector Error Correction Model (VECM) analysis of UK meat consumption," Econometrics 0409007, University Library of Munich, Germany.
    15. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    16. Lanouar Charfeddine & Dominique Guegan, 2008. "Is it possible to discriminate between different switching regressions models? An empirical investigation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00368358, HAL.
    17. de Morais, Igor Alexandre C. & Portugal, Marcelo Savino, 2005. "A Markov Switching Model for the Brazilian Demand for Imports: Analyzing the Import Substitution Process in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 25(2), November.
    18. Andreas A. Andrikopoulos & Dimitrios C. Gkountanis, 2011. "Issues and Models in Applied Econometrics: A partial survey," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 9(2), pages 107-165.
    19. Gray, Stephen F., 1996. "Modeling the conditional distribution of interest rates as a regime-switching process," Journal of Financial Economics, Elsevier, vol. 42(1), pages 27-62, September.
    20. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.

    More about this item

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:chb:bcchwp:614. 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: Alvaro Castillo (email available below). General contact details of provider: https://edirc.repec.org/data/bccgvcl.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.