[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/fth/pensta/4-96-3.html
   My bibliography  Save this paper

An introduction to stochastic Unit Root Processes

Author

Listed:
  • Granger, E.J.
  • Swanson, N.R.
Abstract
A class of nonlinear processes which have a root that is not constant, but is stochastic, and varying around unity is introduced. Th eprocess can be stationary for some periods, and mildly explosive for others.

Suggested Citation

  • Granger, E.J. & Swanson, N.R., 1996. "An introduction to stochastic Unit Root Processes," Papers 4-96-3, Pennsylvania State - Department of Economics.
    • Handle: RePEc:fth:pensta:4-96-3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 971-987, December.
    2. C. W. J. Granger & Jeff Hallman, 1991. "Nonlinear Transformations Of Integrated Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 12(3), pages 207-224, May.
    3. Gonzalo, Jesus & Granger, Clive W J, 1995. "Estimation of Common Long-Memory Components in Cointegrated Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 27-35, January.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Granger, Clive W J, 1993. "What Are We Learning about the Long-Run?," Economic Journal, Royal Economic Society, vol. 103(417), pages 307-317, March.
    6. Laroque, Guy & Salanie, Bernard, 1994. "Estimating the canonical disequilibrium model : Asymptotic theory and finite sample properties," Journal of Econometrics, Elsevier, vol. 62(2), pages 165-210, June.
    7. Mohsen Pourahmadi, 1986. "On Stationarity Of The Solution Of A Doubly Stochastic Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(2), pages 123-131, March.
    8. Engle, R. F. & Granger, C. W. J. (ed.), 1991. "Long-Run Economic Relationships: Readings in Cointegration," OUP Catalogue, Oxford University Press, number 9780198283393.
    9. Deborah A. Guyton & Nien‐Fan Zhang & Robert V. Foutz, 1986. "A Random Parameter Process For Modeling And Forecasting Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(2), pages 105-115, March.
    10. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    11. Leybourne, S J & McCabe, B P M & Tremayne, A R, 1996. "Can Economic Time Series Be Differenced to Stationarity?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 435-446, October.
    12. Mohsen Pourahmadi, 1988. "STATIONARITY OF THE SOLUTION OF Xt= AtXt‐1+εt AND ANALYSIS OF NON‐GAUSSIAN DEPENDENT RANDOM VARIABLES," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(3), pages 225-239, May.
    13. Barr Rosenberg, 1973. "The Analysis of a Cross Section of Time Series by Stochastically Convergent Parameter Regression," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 2, number 4, pages 399-428, National Bureau of Economic Research, Inc.
    14. McCabe,B.P.M. & Tremayne,A.R., 1995. "Testing a Time-Series for Difference Stationarity," Cambridge Working Papers in Economics 9420, Faculty of Economics, University of Cambridge.
    15. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    16. Franses, Philip Hans, 1994. "A multivariate approach to modeling univariate seasonal time series," Journal of Econometrics, Elsevier, vol. 63(1), pages 133-151, July.
    17. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
    18. Osborn, Denise R, 1988. "Seasonality and Habit Persistence in a Life Cycle Model of Consumptio n," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(4), pages 255-266, October-D.
    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. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, September.
    2. Wu, Jyh-Lin & Chen, Show-Lin, 2001. "Nominal exchange-rate prediction: evidence from a nonlinear approach," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 521-532, August.
    3. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    4. Pär Österholm, 2005. "The Taylor Rule: A Spurious Regression?," Bulletin of Economic Research, Wiley Blackwell, vol. 57(3), pages 217-247, July.
    5. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    6. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    7. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    8. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    9. Bardsen, Gunnar & Eitrheim, Oyvind & Jansen, Eilev S. & Nymoen, Ragnar, 2005. "The Econometrics of Macroeconomic Modelling," OUP Catalogue, Oxford University Press, number 9780199246502.
    10. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November.
    11. Marcel Gorenflo, 2013. "Futures price dynamics of CO 2 emission allowances," Empirical Economics, Springer, vol. 45(3), pages 1025-1047, December.
    12. Norman R. Swanson, 2010. "Further Developments in the Study of Cointegrated Variables," Journal of Financial Econometrics, Oxford University Press, vol. 8(2), pages 187-190, spring.
    13. Khurshid Kiani & Terry Kastens, 2008. "Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 383-406, November.
    14. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    15. Krishna, Kala & Ozyildirim, Ataman & Swanson, Norman R., 2003. "Trade, investment and growth: nexus, analysis and prognosis," Journal of Development Economics, Elsevier, vol. 70(2), pages 479-499, April.
    16. Hassler Uwe, 2001. "Wealth and Consumption. A Multicointegrated Model for the Unified Germany / Vermögen und Konsum. Ein multikointegriertes Modell für das vereinigte Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 221(1), pages 32-44, February.
    17. Jan J J Groen & Clare Lombardelli, 2004. "Real exchange rates and the relative prices of non-traded and traded goods: an empirical analysis," Bank of England working papers 223, Bank of England.
    18. Grace, M. F. & J. L. Hotchkiss, 1993. "External Impacts on the Property-Liability Insurance Cycle," Working Papers 020, Risk and Insurance Archive, revised Feb 1995.
    19. Janine Aron & John Muellbauer, 2000. "Personal and Corporate Saving in South Africa," The World Bank Economic Review, World Bank, vol. 14(3), pages 509-544, September.
    20. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.

    More about this item

    Keywords

    UNIT ROOTS; ECONOMETRICS; COINTEGRATION;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:fth:pensta:4-96-3. 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: Thomas Krichel (email available below). General contact details of provider: https://edirc.repec.org/data/depsuus.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.