IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2016-251.html
   My bibliography  Save this paper

Financial Information and Macroeconomic Forecasts

Author

Listed:
  • Sophia Chen
  • Mr. Romain Ranciere

Abstract

We study the forecasting power of financial variables for macroeconomic variables for 62 countries between 1980 and 2013. We find that financial variables such as credit growth, stock prices and house prices have considerable predictive power for macroeconomic variables at one to four quarters horizons. A forecasting model with financial variables outperforms the World Economic Outlook (WEO) forecasts in up to 85 percent of our sample countries at the four quarters horizon. We also find that cross-country panel models produce more accurate out-of-sample forecasts than individual country models.

Suggested Citation

  • Sophia Chen & Mr. Romain Ranciere, 2016. "Financial Information and Macroeconomic Forecasts," IMF Working Papers 2016/251, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2016/251
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=44496
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Loayza, Norman V. & Ranciere, Romain, 2006. "Financial Development, Financial Fragility, and Growth," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(4), pages 1051-1076, June.
    2. Edward E. Leamer, 2007. "Housing is the business cycle," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 149-233.
    3. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    4. Ranciere, Romain & Tornell, Aaron & Westermann, Frank, 2006. "Decomposing the effects of financial liberalization: Crises vs. growth," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3331-3348, December.
    5. Bernanke, Ben & Gertler, Mark & Gilchrist, Simon, 1996. "The Financial Accelerator and the Flight to Quality," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 1-15, February.
    6. Hoogstrate, Andre J & Palm, Franz C & Pfann, Gerard A, 2000. "Pooling in Dynamic Panel-Data Models: An Application to Forecasting GDP Growth Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 274-283, July.
    7. Moritz Schularick & Alan M. Taylor, 2012. "Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008," American Economic Review, American Economic Association, vol. 102(2), pages 1029-1061, April.
    8. Martin Schneider & Aaron Tornell, 2004. "Balance Sheet Effects, Bailout Guarantees and Financial Crises," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(3), pages 883-913.
    9. Thomas Philippon, 2009. "The Bond Market's q," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(3), pages 1011-1056.
    10. 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.
    11. Barro, Robert J, 1990. "The Stock Market and Investment," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 115-131.
    12. Chetan Dave & Scott J. Dressler & Lei Zhang, 2013. "The Bank Lending Channel: A FAVAR Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(8), pages 1705-1720, December.
    13. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
    14. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    15. Yannick Kalantzis, 2015. "Financial Fragility in Small Open Economies: Firm Balance Sheets and the Sectoral Structure," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(3), pages 1194-1222.
    16. Bernanke, Ben & Gertler, Mark, 1989. "Agency Costs, Net Worth, and Business Fluctuations," American Economic Review, American Economic Association, vol. 79(1), pages 14-31, March.
    17. Garcia-Ferrer, Antonio, et al, 1987. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 53-67, January.
    18. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
    19. Stijn Claessens & M. Ayhan Kose & Marco E. Terrones, 2009. "What happens during recessions, crunches and busts? [Business cycles for G-7 and European countries]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 24(60), pages 653-700.
    20. Romain Rancière & Aaron Tornell & Frank Westermann, 2006. "Decomposing the Effects of Finncial Liberalization: Growth vs. Crises," Post-Print halshs-00754116, HAL.
    21. Helene Rey, 2013. "Dilemma not trilemma: the global cycle and monetary policy independence," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 1-2.
    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. Zivile Zekaite & Gabe de Bondt & Elke Hahn, 2017. "Alice: A New Inflation Monitoring Tool," EcoMod2017 10414, EcoMod.
    2. Paccagnini, Alessia, 2019. "Did financial factors matter during the Great Recession?," Economics Letters, Elsevier, vol. 174(C), pages 26-30.
    3. Shi, Qi & Li, Bin, 2022. "Further evidence on financial information and economic activity forecasts in the United States," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    4. Yan Carrière-Swallow & José Marzluf, 2023. "Macrofinancial Causes of Optimism in Growth Forecasts," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 509-537, June.
    5. Imran Hussain Shaha & Simón Sosvilla-Rivero, 2017. "Seeking price and macroeconomic stabilisation in the euro area: The role of house prices and stock prices," Working Papers del Instituto Complutense de Estudios Internacionales 1707, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
    6. Olga Bespalova & Mrs. Marina V Rousset, 2019. "Macrofinancial Linkages and Growth at Risk in the Dominican Republic," IMF Working Papers 2019/246, International Monetary Fund.
    7. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    8. Nicolas Chatelais & Menzie Chinn & Arthur Stalla-Bourdillon, 2022. "Macroeconomic Forecasting Using Filtered Signals from a Stock Market Cross Section," Working papers 903, Banque de France.
    9. María Paula Bonel & Daniel J. Aromí, 2021. "Assessing GDP forecasts from autoregressive models: the impact of model complexity and training dataset," Asociación Argentina de Economía Política: Working Papers 4440, Asociación Argentina de Economía Política.
    10. de Bondt, Gabe J. & Hahn, Elke & Zekaite, Zivile, 2021. "ALICE: Composite leading indicators for euro area inflation cycles," International Journal of Forecasting, Elsevier, vol. 37(2), pages 687-707.
    11. Lukasz Mach & Dariusz Zmarzly & Ireneusz Dabrowski & Pawel Fracz, 2020. "Comparison on Subannual Seasonality of Building Construction in European Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 241-257.
    12. Qu, Li, 2021. "A new approach to estimating earnings forecasting models: Robust regression MM-estimation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1011-1030.
    13. Jack Fosten & Shaoni Nandi, 2023. "Nowcasting from cross‐sectionally dependent panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 898-919, September.
    14. Periklis Gogas & Theophilos Papadimitriou & Emmanouil Sofianos, 2022. "Forecasting unemployment in the euro area with machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 551-566, April.

    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. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    2. Okimoto, Tatsuyoshi & Takaoka, Sumiko, 2022. "The credit spread curve distribution and economic fluctuations in Japan," Journal of International Money and Finance, Elsevier, vol. 122(C).
    3. Borsi, Mihály Tamás, 2018. "Credit contractions and unemployment," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 573-593.
    4. Okimoto, Tatsuyoshi & Takaoka, Sumiko, 2017. "The term structure of credit spreads and business cycle in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 45(C), pages 27-36.
    5. Lyócsa, Štefan & Výrost, Tomáš & Plíhal, Tomáš, 2021. "A tale of tails : New evidence on the growth-return nexus," Finance Research Letters, Elsevier, vol. 38(C).
    6. Guender, Alfred V, 2018. "Credit prices vs. credit quantities as predictors of economic activity in Europe: Which tell a better story?," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 380-399.
    7. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    8. Stijn Claessens & M Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: a survey," BIS Working Papers 676, Bank for International Settlements.
    9. Yépez, Carlos A., 2018. "Financial intermediation and real estate prices impact on business cycles: A Bayesian analysis," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 138-160.
    10. Douglas Sutherland & Peter Hoeller, 2012. "Debt and Macroeconomic Stability: An Overview of the Literature and Some Empirics," OECD Economics Department Working Papers 1006, OECD Publishing.
    11. Mercè Sala-Rios & Teresa Torres-Solé & Mariona Farré-Perdiguer, 2016. "Credit and business cycles’ relationship: evidence from Spain," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 15(3), pages 149-171, December.
    12. Cremers, Martijn & Fleckenstein, Matthias & Gandhi, Priyank, 2021. "Treasury yield implied volatility and real activity," Journal of Financial Economics, Elsevier, vol. 140(2), pages 412-435.
    13. Thomas Flavin & Ekaterini Panopoulou & Theologos Pantelidis, 2009. "Forecasting growth and inflation in an enlarged euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 405-425.
    14. Dieckelmann, Daniel, 2021. "Market sentiment, financial fragility, and economic activity: The role of corporate securities issuance," Discussion Papers 2021/6, Free University Berlin, School of Business & Economics.
    15. Christiansen, Charlotte & Eriksen, Jonas Nygaard & Møller, Stig Vinther, 2014. "Forecasting US recessions: The role of sentiment," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 459-468.
    16. Helbling, Thomas & Huidrom, Raju & Kose, M. Ayhan & Otrok, Christopher, 2011. "Do credit shocks matter? A global perspective," European Economic Review, Elsevier, vol. 55(3), pages 340-353, April.
    17. 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.
    18. Hélène Rey, 2016. "International Channels of Transmission of Monetary Policy and the Mundellian Trilemma," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(1), pages 6-35, May.
    19. Gilchrist, Simon & Yankov, Vladimir & Zakrajsek, Egon, 2009. "Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 471-493, May.
    20. David López-Salido & Jeremy C. Stein & Egon Zakrajšek, 2017. "Credit-Market Sentiment and the Business Cycle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1373-1426.

    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:imf:imfwpa:2016/251. 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: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.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.