IDEAS home Printed from https://ideas.repec.org/a/spr/jqecon/v17y2019i2d10.1007_s40953-019-00162-2.html
   My bibliography  Save this article

A Recursive Monte Carlo Study of Structural-Break Sensitivity of Adjustment Coefficients in Cointegrated VAR Systems

Author

Listed:
  • Takamitsu Kurita

    (Fukuoka University)

Abstract

This paper studies the sensitivity of adjustment coefficients to various structural breaks in a cointegrated vector autoregressive system. A Monte Carlo simulation study is conducted in a recursive manner to examine fluctuations of finite-sample estimates of the coefficients. The study reveals the wide-ranging influences of breaks on the estimates, which can give rise to inference for spurious time-varying adjustment coefficients, although the underlying true coefficients are stable and time-invariant. It is thus advisable to be cautious about seemingly time-varying adjustment coefficients when analyzing time series data subject to structural breaks.

Suggested Citation

  • Takamitsu Kurita, 2019. "A Recursive Monte Carlo Study of Structural-Break Sensitivity of Adjustment Coefficients in Cointegrated VAR Systems," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 251-270, June.
    • Handle: RePEc:spr:jqecon:v:17:y:2019:i:2:d:10.1007_s40953-019-00162-2
    DOI: 10.1007/s40953-019-00162-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40953-019-00162-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40953-019-00162-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David F. Hendry & Jurgen A. Doornik, 1997. "The Implications for Econometric Modelling of Forecast Failure," Scottish Journal of Political Economy, Scottish Economic Society, vol. 44(4), pages 437-461, September.
    2. repec:bla:jecsur:v:12:y:1998:i:5:p:533-72 is not listed on IDEAS
    3. Hendry, David F. & Massmann, Michael, 2007. "Co-Breaking: Recent Advances and a Synopsis of the Literature," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 33-51, January.
    4. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
    5. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
    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. Takamitsu Kurita & B. Nielsen, 2018. "Partial cointegrated vector autoregressive models with structural breaks in deterministic terms," Economics Papers 2018-W03, Economics Group, Nuffield College, University of Oxford.
    2. Takamitsu Kurita & Bent Nielsen, 2019. "Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms," Econometrics, MDPI, vol. 7(4), pages 1-35, October.
    3. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    4. Kosei Fukuda, 2011. "Cointegration rank switching model: an application to forecasting interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(5), pages 509-522, August.
    5. Kurita, Takamitsu, 2020. "Likelihood-based tests for parameter constancy in I(2) CVAR models with an application to fixed-term deposit data," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    6. Castle, Jennifer L. & Kurita, Takamitsu, 2024. "Stability between cryptocurrency prices and the term structure," Journal of Economic Dynamics and Control, Elsevier, vol. 165(C).
    7. Carlomagno, Guillermo, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Carsten Trenkler*, 2005. "The Effects of Ignoring Level Shifts on Systems Cointegration Tests," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 89(3), pages 281-301, August.
    9. Rodríguez-Caballero, Carlos Vladimir & Ventosa-Santaulària, Daniel, 2017. "Energy-growth long-term relationship under structural breaks. Evidence from Canada, 17 Latin American economies and the USA," Energy Economics, Elsevier, vol. 61(C), pages 121-134.
    10. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    11. Takamitsu Kurita & Mototsugu Shintani, 2023. "Johansen Test with Fourier-Type Smooth Nonlinear Trends in Cointegrating Relations," CIRJE F-Series CIRJE-F-1216, CIRJE, Faculty of Economics, University of Tokyo.
    12. Vijay Kumar Vishwakarma, 2021. "Long-run drivers and integration in interprovincial Canadian housing price relations," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 16(1), pages 22-40, November.
    13. Miller, Stephen M. & Martins, Luis Filipe & Gupta, Rangan, 2019. "A Time-Varying Approach Of The Us Welfare Cost Of Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 775-797, March.
    14. Gadea, María Dolores & Kaabia, Monia Ben & Sabaté, Marcela, 2009. "Exchange rate regimes and prices: The cases of Italy, Spain and the United Kingdom (1874-1998)," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 477-489, July.
    15. Lusine Lusinyan & John Thornton, 2011. "Unit roots, structural breaks and cointegration in the UK public finances, 1750-2004," Applied Economics, Taylor & Francis Journals, vol. 43(20), pages 2583-2592.
    16. Peia, Oana & Roszbach, Kasper, 2015. "Finance and growth: Time series evidence on causality," Journal of Financial Stability, Elsevier, vol. 19(C), pages 105-118.
    17. Salah A. Nusair & Naser I. Abumustafa, 2012. "Recursive Cointegration Analysis of Purchasing Power Parity: An Application to Asian Countries," The American Economist, Sage Publications, vol. 57(2), pages 196-209, November.
    18. Johansen, Søren & Nielsen, Morten Ørregaard, 2018. "The cointegrated vector autoregressive model with general deterministic terms," Journal of Econometrics, Elsevier, vol. 202(2), pages 214-229.
    19. Gunnar Bårdsen & Stan Hurn & Zoë Mchugh, 2007. "Modelling Wages and Prices in Australia," The Economic Record, The Economic Society of Australia, vol. 83(261), pages 143-158, June.
    20. Salah A. Nusair & Khalid M. Kisswani, 2015. "Asian Real Exchange Rates And Oil Prices: A Cointegration Analysis Under Structural Breaks," Bulletin of Economic Research, Wiley Blackwell, vol. 67(S1), pages 1-25, December.

    More about this item

    Keywords

    Cointegrated vector autoregressive systems; Adjustment coefficients; Sensitivity; Structural breaks; Spurious time-varying parameters; Recursive Monte Carlo experiments;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

    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:spr:jqecon:v:17:y:2019:i:2:d:10.1007_s40953-019-00162-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.