IDEAS home Printed from https://ideas.repec.org/a/fip/fedfer/y1991ifallp31-40.html
   My bibliography  Save this article

Recession probability indexes: a survey

Author

Listed:
  • Chan Guk Huh

Abstract

No abstract is available for this item.

Suggested Citation

  • Chan Guk Huh, 1991. "Recession probability indexes: a survey," Economic Review, Federal Reserve Bank of San Francisco, issue Fall, pages 31-40.
    • Handle: RePEc:fip:fedfer:y:1991:i:fall:p:31-40
    as

    Download full text from publisher

    File URL: http://www.frbsf.org/publications/economics/review/1991/91-4_31-40.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ben S. Bernanke, 1990. "On the predictive power of interest rates and interest rate spreads," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 51-68.
    2. Olivier J. Blanchard & Mark W. Watson, 1986. "Are Business Cycles All Alike?," NBER Chapters, in: The American Business Cycle: Continuity and Change, pages 123-180, National Bureau of Economic Research, Inc.
    3. 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.
    4. Kenneth M. Emery & Evan F. Koenig, 1991. "Misleading indicators? Using the composite leading indicators to predict cyclical turning points," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Jul, pages 1-14.
    5. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
    6. William Roberds, 1988. "A quarterly Bayesian VAR model of the US economy," FRB Atlanta Working Paper 88-2, Federal Reserve Bank of Atlanta.
    7. Neftici, Salih N., 1982. "Optimal prediction of cyclical downturns," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 225-241, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andrew J. Filardo, 1999. "How reliable are recession prediction models?," Economic Review, Federal Reserve Bank of Kansas City, vol. 84(Q II), pages 35-55.

    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. Marco Del Negro, 2001. "Turn, turn, turn: Predicting turning points in economic activity," Economic Review, Federal Reserve Bank of Atlanta, vol. 86(Q2), pages 1-12.
    2. Duo Qin, 2010. "Econometric Studies of Business Cycles in the History of Econometrics," Working Papers 669, Queen Mary University of London, School of Economics and Finance.
    3. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
    4. Layton, Allan P., 1996. "Dating and predicting phase changes in the U.S. business cycle," International Journal of Forecasting, Elsevier, vol. 12(3), pages 417-428, September.
    5. Franck Sédillot, 2001. "La pente des taux contient-elle de l'information sur l'activité économique future ?," Economie & Prévision, La Documentation Française, vol. 147(1), pages 141-157.
    6. Christopher A. Sims, 1993. "A Nine-Variable Probabilistic Macroeconomic Forecasting Model," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 179-212, National Bureau of Economic Research, Inc.
    7. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    8. Wilbur John Coleman & Christian Gilles & Pamela Labadie, 1993. "Discount window borrowing and liquidity," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
    9. Mendoza, Liu & Morales, Daniel, 2013. "Construyendo un índice coincidente de recesión: Una aplicación para la economía peruana," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 26, pages 81-100.
    10. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    11. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
    12. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    13. Ben S. Bernanke & Ilian Mihov, 1998. "Measuring Monetary Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 869-902.
    14. Kenneth N. Kuttner, 1993. "Credit conditions and external finance: interpreting the behavior of financial flows and interest rate spreads," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
    15. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    16. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
    17. Beatriz C. Galvao, Ana, 2002. "Can non-linear time series models generate US business cycle asymmetric shape?," Economics Letters, Elsevier, vol. 77(2), pages 187-194, October.
    18. Croushore, Dean & Evans, Charles L., 2006. "Data revisions and the identification of monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1135-1160, September.
    19. Fernando H.P.S Mendes & João Frois Caldeira & Guilherme Valle Moura, 2019. "Duration-dependent Markov-switching model: an empirical study for the Brazilian business cycle," Economics Bulletin, AccessEcon, vol. 39(1), pages 676-685.
    20. George Athanasopoulos & Heather M. Anderson & Farshid Vahid, 2007. "Nonlinear autoregressive leading indicator models of output in G-7 countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 63-87.

    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:fip:fedfer:y:1991:i:fall:p:31-40. 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: Federal Reserve Bank of San Francisco Research Library (email available below). General contact details of provider: https://edirc.repec.org/data/frbsfus.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.