IDEAS home Printed from https://ideas.repec.org/p/cfm/wpaper/1520.html
   My bibliography  Save this paper

Predictable Recoveries

Author

Listed:
  • Xiaoming Cai

    (Tongji University)

  • Wouter Den Haan

    (London School of Economics
    Centre for Macroeconomics (CFM)
    Centre for Economic Policy Research (CEPR))

  • Jonathan Pinder

    (London School of Economics
    Centre for Macroeconomics (CFM))

Abstract

Should an unexpected change in real GMP of x% lead to an x% change in the forecasts of future GNP? The answer could be no even if GNP is a random walk. We show that US economic downturns often go together with changes in long-term GNP forecasts that are substantially smaller than the initial drop. But not always! Essential for our results is that GNP forecasts are not based on a univariate time series model, which is not uncommon. Our alternative forecasts are based on a simple multivariate representation of GNP's expenditure components.

Suggested Citation

  • Xiaoming Cai & Wouter Den Haan & Jonathan Pinder, 2015. "Predictable Recoveries," Discussion Papers 1520, Centre for Macroeconomics (CFM).
  • Handle: RePEc:cfm:wpaper:1520
    as

    Download full text from publisher

    File URL: http://www.centreformacroeconomics.ac.uk/Discussion-Papers/2015/CFMDP2015-20-Paper.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2013. "News, Noise, and Fluctuations: An Empirical Exploration," American Economic Review, American Economic Association, vol. 103(7), pages 3045-3070, December.
    2. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
    3. Wouter J. Den Haan & Steven W. Sumner & Guy M. Yamashiro, 2011. "Bank Loan Components and the Time‐varying Effects of Monetary Policy Shocks," Economica, London School of Economics and Political Science, vol. 78(312), pages 593-617, October.
    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. Xiaoming Cai & Wouter J. Den Haan & Jonathan Pinder, 2016. "Predictable Recoveries," Economica, London School of Economics and Political Science, vol. 83(330), pages 307-337, April.
    2. Cai, Xiaoming & Den Haan, Wouter J. & Pinder, Jonathan, 2015. "Predictable recoveries," LSE Research Online Documents on Economics 86289, London School of Economics and Political Science, LSE Library.
    3. Den Haan, Wouter & Cai, Xiaoming & Pinder, Jonathan, 2015. "Predictable Recoveries," CEPR Discussion Papers 10815, C.E.P.R. Discussion Papers.
    4. Cai, Xiaoming & Den Haan, Wouter J. & Pinder, Jonathan, 2016. "Predictable recoveries," LSE Research Online Documents on Economics 65188, London School of Economics and Political Science, LSE Library.
    5. Den Haan, Wouter & Cai, Xiaoming, 2009. "Predicting recoveries and the importance of using enough information," CEPR Discussion Papers 7508, C.E.P.R. Discussion Papers.
    6. John Barkoulas & Christopher Baum & Mustafa Caglayan, 1999. "Fractional monetary dynamics," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1393-1400.
    7. Jan Babecký & Fabrizio Coricelli & Roman Horváth, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(2), pages 102-127, June.
    8. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," LIDAM Discussion Papers CORE 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Michelacci, Claudio & Zaffaroni, Paolo, 2000. "(Fractional) beta convergence," Journal of Monetary Economics, Elsevier, vol. 45(1), pages 129-153, February.
    10. Di Bella, Gabriel & Grigoli, Francesco, 2019. "Optimism, pessimism, and short-term fluctuations," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 79-96.
    11. Gil-Alana, L.A., 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, Elsevier, vol. 15(1), pages 28-48.
    12. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Modelling squared returns using a SETAR model with long-memory dynamics," Economics Letters, Elsevier, vol. 86(2), pages 237-243, February.
    13. Claudio, Morana & Giacomo, Sbrana, 2017. "Temperature anomalies, radiative forcing and ENSO," Working Papers 361, University of Milano-Bicocca, Department of Economics, revised 10 Feb 2017.
    14. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    15. Eric Hillebrand & Marcelo C. Medeiros, 2016. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 23-41, January.
    16. A. M. M. Shahiduzzaman Quoreshi & Reaz Uddin & Naushad Mamode Khan, 2019. "Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework," JRFM, MDPI, vol. 12(2), pages 1-13, April.
    17. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
    18. Claudio, Morana & Giacomo, Sbrana, 2017. "Some Financial Implications of Global Warming: An Empirical Assessment," Working Papers 377, University of Milano-Bicocca, Department of Economics, revised 25 Dec 2017.
    19. Jean-Philippe Gervais, 2011. "Disentangling nonlinearities in the long- and short-run price relationships: an application to the US hog/pork supply chain," Applied Economics, Taylor & Francis Journals, vol. 43(12), pages 1497-1510.
    20. Maria Kalli & Jim Griffin, 2015. "Flexible Modeling of Dependence in Volatility Processes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 102-113, January.

    More about this item

    Keywords

    Forecasting; Unit Root; Business Cycles;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:cfm:wpaper:1520. 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: Helen Power (email available below). General contact details of provider: https://edirc.repec.org/data/cmlseuk.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.