IDEAS home Printed from https://ideas.repec.org/a/pal/buseco/v51y2016i4d10.1057_s11369-016-0017-x.html
   My bibliography  Save this article

Is Predicting Recessions Enough?

Author

Listed:
  • Azhar Iqbal

    (Wells Farge Securities)

  • John Silvia

    (Wells Farge Securities)

Abstract

We propose an ordered probit framework to simultaneously predict the probabilities of recession, weaker recovery, and stronger recovery. Our approach helps identify (a) whether the next phase is a recession, (b) when the recovery period starts, and (c) whether the recovery would be a weak or strong one compared to historical standards. We believe our approach would help policy makers decide when would be appropriate to (1) start expansionary policies (higher probabilities of recession), (2) continue expansionary policies (higher probabilities of weaker recovery), or (3) turn to neutral/contractionary policies (higher probabilities of stronger recovery). The ordered probit model shows the probabilities of recession staying above 50 percent during all five recessions in our simulated out-of-sample analysis of 1980:Q1–2016:Q1. The probabilities of weaker recovery are consistent with actual periods of below trend growth. Based on 2016:Q1 data, the model suggests a meaningfully higher chance of continuing below trend growth. One key result is that the probability of weaker growth has been persistently higher than the other two scenarios for the past several years. These higher probabilities of weak growth are consistent with the accommodative monetary policy stance of the past eight years.

Suggested Citation

  • Azhar Iqbal & John Silvia, 2016. "Is Predicting Recessions Enough?," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 51(4), pages 248-259, October.
  • Handle: RePEc:pal:buseco:v:51:y:2016:i:4:d:10.1057_s11369-016-0017-x
    DOI: 10.1057/s11369-016-0017-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s11369-016-0017-x
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s11369-016-0017-x?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. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992. "An ordered probit analysis of transaction stock prices," Journal of Financial Economics, Elsevier, vol. 31(3), pages 319-379, June.
    2. John Silvia & Azhar Iqbal, 2015. "An Ordered Probit Approach to Predicting the Probability of Inflation/Deflation," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 50(1), pages 12-19, January.
    3. Jonathan H. Wright, 2006. "The yield curve and predicting recessions," Finance and Economics Discussion Series 2006-07, Board of Governors of the Federal Reserve System (U.S.).
    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. Mark Vitner & Azhar Iqbal, 2019. "What is going right in manufacturing?," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 54(2), pages 114-121, April.
    2. Gjerde, Kathy Paulson & Prescott, Peter & Rice, Jennifer, 2019. "The Impact of State Fiscal Policy on States' Resilience Entering the Great Recession," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 49(1), January.
    3. Prescott, Peter & Gjerde, Kathy Paulson, 2022. "The Impact of State Fiscal Policy on States’ Resilience During the Great Recession," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 52(1), January.

    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. Azhar Iqbal & John E. Silvia, 2016. "Does Deflation Threaten the Global Economy?," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 16(2), pages 189-212, June.
    2. Aslanidis, Nektarios & Christiansen, Charlotte, 2012. "Smooth transition patterns in the realized stock–bond correlation," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 454-464.
    3. Hong, Harrison & Rady, Sven, 2002. "Strategic trading and learning about liquidity," Journal of Financial Markets, Elsevier, vol. 5(4), pages 419-450, October.
    4. Richard K. Lyons, 1996. "Foreign Exchange Volume: Sound and Fury Signifying Nothing?," NBER Chapters, in: The Microstructure of Foreign Exchange Markets, pages 183-208, National Bureau of Economic Research, Inc.
    5. Gerhard, Frank & Hess, Dieter & Pohlmeier, Winfried, 1998. "What a Difference a Day Makes: On the Common Market Microstructure of Trading Days," CoFE Discussion Papers 98/01, University of Konstanz, Center of Finance and Econometrics (CoFE).
    6. Hasbrouck, Joel, 1996. "Order characteristics and stock price evolution An application to program trading," Journal of Financial Economics, Elsevier, vol. 41(1), pages 129-149, May.
    7. Bernhardt, Dan & Hughson, Eric, 2002. "Intraday trade in dealership markets," European Economic Review, Elsevier, vol. 46(9), pages 1697-1732, October.
    8. Dimitrakopoulos, Stefanos & Tsionas, Mike, 2019. "Ordinal-response GARCH models for transaction data: A forecasting exercise," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1273-1287.
    9. Huang, Roger D. & Ting, Christopher, 2008. "A functional approach to the price impact of stock trades and the implied true price," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 1-16, January.
    10. Alexander, Gordon J. & Peterson, Mark A., 2007. "An analysis of trade-size clustering and its relation to stealth trading," Journal of Financial Economics, Elsevier, vol. 84(2), pages 435-471, May.
    11. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    12. Jun Muranaga, 1999. "Dynamics of Market Liquidity of Japanese Stocks: An Analysis of Tick-by-Tick Data of the Tokyo Stock Exchange," CGFS Papers chapters, in: Bank for International Settlements (ed.), Market Liquidity: Research Findings and Selected Policy Implications, volume 11, pages 1-25, Bank for International Settlements.
    13. de Jong, Frank & Nijman, Theo & Roell, Ailsa, 1996. "Price effects of trading and components of the bid-ask spread on the Paris Bourse," Journal of Empirical Finance, Elsevier, vol. 3(2), pages 193-213, June.
    14. Antunes, António & Bonfim, Diana & Monteiro, Nuno & Rodrigues, Paulo M.M., 2018. "Forecasting banking crises with dynamic panel probit models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 249-275.
    15. Hans Degryse & Frank Jong & Maarten Ravenswaaij & Gunther Wuyts, 2005. "Aggressive Orders and the Resiliency of a Limit Order Market," Review of Finance, Springer, vol. 9(2), pages 201-242, June.
    16. Angelo Ranaldo, 2002. "Market Dynamics Around Public Information Arrivals," FAME Research Paper Series rp45, International Center for Financial Asset Management and Engineering.
    17. repec:cty:dpaper:10.1080/14697680701881763 is not listed on IDEAS
    18. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 895-953, November.
    19. Degryse, Hans, 1999. "The total cost of trading Belgian shares: Brussels versus London," Journal of Banking & Finance, Elsevier, vol. 23(9), pages 1331-1355, September.
    20. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    21. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.

    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:pal:buseco:v:51:y:2016:i:4:d:10.1057_s11369-016-0017-x. 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.palgrave-journals.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.