IDEAS home Printed from https://ideas.repec.org/p/aah/create/2013-14.html
   My bibliography  Save this paper

Forecasting US Recessions: The Role of Sentiments

Author

Listed:
  • Charlotte Christiansen

    () (Aarhus University and CREATES)

  • Jonas Nygaard Eriksen

    () (Aarhus University and CREATES)

  • Stig V. Møller

    () (Aarhus University and CREATES)

Abstract

We examine sentiment variables as new predictors for US recessions. We combine sentiment variables with either classical recession predictors or with common factors based on a large panel of macroeconomic and ?nancial variables. Sentiment variables hold vast predictive power for US recessions in excess of both the classical recession predictors and the common factors. The strong importance of the sentiment variables is documented both in-sample and out-of-sample.

Suggested Citation

  • Charlotte Christiansen & Jonas Nygaard Eriksen & Stig V. Møller, 2013. "Forecasting US Recessions: The Role of Sentiments," CREATES Research Papers 2013-14, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2013-14
    as

    Download full text from publisher

    File URL: ftp://ftp.econ.au.dk/creates/rp/13/rp13_14.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.
    2. Matsusaka, John G & Sbordone, Argia M, 1995. "Consumer Confidence and Economic Fluctuations," Economic Inquiry, Western Economic Association International, vol. 33(2), pages 296-318, April.
    3. Arturo Estrella & Mary R. Trubin, 2006. "The yield curve as a leading indicator: some practical issues," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 12(Jul).
    4. Henri Nyberg, 2010. "Dynamic probit models and financial variables in recession forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 215-230.
    5. Sydney C. Ludvigson, 2004. "Consumer Confidence and Consumer Spending," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 29-50, Spring.
    6. Travis J. Berge & Òscar Jordà, 2011. "Evaluating the Classification of Economic Activity into Recessions and Expansions," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 246-277, April.
    7. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    8. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    9. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    10. 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.
    11. Marcelle Chauvet & Simon Potter, 2005. "Forecasting recessions using the yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 77-103.
    12. Carroll, Christopher D & Fuhrer, Jeffrey C & Wilcox, David W, 1994. "Does Consumer Sentiment Forecast Household Spending? If So, Why?," American Economic Review, American Economic Association, vol. 84(5), pages 1397-1408, December.
    13. Jason Bram & Sydney Ludvigson, 1998. "Does consumer confidence forecast household expenditure? a sentiment index horse race," Economic Policy Review, Federal Reserve Bank of New York, issue Jun, pages 59-78.
    14. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
    15. Schrimpf, Andreas & Wang, Qingwei, 2010. "A reappraisal of the leading indicator properties of the yield curve under structural instability," International Journal of Forecasting, Elsevier, vol. 26(4), pages 836-857, October.
    16. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
    17. George A. Akerlof, 2009. "How Human Psychology Drives the Economy and Why It Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1175-1175.
    18. Michael J. Dueker, 1997. "Strengthening the case for the yield curve as a predictor of U.S. recessions," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 41-51.
    19. 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.
    20. Banerjee, Anindya & Marcellino, Massimiliano, 2006. "Are there any reliable leading indicators for US inflation and GDP growth?," International Journal of Forecasting, Elsevier, vol. 22(1), pages 137-151.
    21. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    22. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    23. Startz, Richard, 2008. "Binomial Autoregressive Moving Average Models With an Application to U.S. Recessions," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 1-8, January.
    24. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    25. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
    26. 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.
    27. Batchelor, Roy & Dua, Pami, 1998. "Improving macro-economic forecasts: The role of consumer confidence," International Journal of Forecasting, Elsevier, vol. 14(1), pages 71-81, March.
    28. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier.
    29. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    30. 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.
    31. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    32. Evan F. Koenig, 2002. "Using the Purchasing Managers' Index to assess the economy's strength and the likely direction of monetary policy," Economic and Financial Policy Review, Federal Reserve Bank of Dallas.
    33. E. Philip Howrey, 2001. "The Predictive Power of the Index of Consumer Sentiment," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 32(1), pages 175-216.
    34. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
    35. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    36. 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.).
    37. Ng, Eric C.Y., 2012. "Forecasting US recessions with various risk factors and dynamic probit models," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 112-125.
    38. Heikki Kauppi, 2008. "Yield-Curve Based Probit Models for Forecasting U.S. Recessions: Stability and Dynamics," Discussion Papers 31, Aboa Centre for Economics.
    39. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    40. Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, vol. 74(4), pages 1133-1150, July.
    41. Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March.
    42. Estrella, Arturo, 1998. "A New Measure of Fit for Equations with Dichotomous Dependent Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 198-205, April.
    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. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    2. Martin M. Andreasen & Tom Engsted & Stig V. Møller & Magnus Sander, 2016. "Bond Market Asymmetries across Recessions and Expansions: New Evidence on Risk Premia," CREATES Research Papers 2016-26, Department of Economics and Business Economics, Aarhus University.
    3. repec:spr:soinre:v:133:y:2017:i:2:d:10.1007_s11205-016-1376-4 is not listed on IDEAS
    4. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics.
    5. Baris Soybilgen, 2017. "Identifying Us Business Cycle Regimes Using Factor Augmented Neural Network Models," Working Papers 1703, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    6. Rachidi Kotchoni & Dalibor Stevanovic, 2016. "Forecasting U.S. Recessions and Economic Activity," CIRANO Working Papers 2016s-36, CIRANO.
    7. Byrne, Joseph P & Lorusso, Marco & Xu, Bing, 2017. "Oil Prices and Informational Frictions: The Time-Varying Impact of Fundamentals and Expectations," MPRA Paper 80668, University Library of Munich, Germany.
    8. repec:wly:jforec:v:36:y:2017:i:5:p:469-482 is not listed on IDEAS
    9. Baghestani, Hamid, 2016. "Do gasoline prices asymmetrically affect US consumers’ economic outlook?," Energy Economics, Elsevier, vol. 55(C), pages 247-252.
    10. Beetsma, Roel & Furtuna, Oana & Giuliodori, Massimo, 2017. "Revenue- versus spending-based consolidation plans: the role of follow-up," CEPR Discussion Papers 12133, C.E.P.R. Discussion Papers.
    11. Pönkä, Harri, 2017. "Sentiment and sign predictability of stock returns," MPRA Paper 81861, University Library of Munich, Germany.
    12. Fornaro, Paolo, 2015. "Forecasting U.S. Recessions with a Large Set of Predictors," MPRA Paper 62973, University Library of Munich, Germany.
    13. Kevin Moran & Simplice Aime Nono, 2016. "Using Confidence Data to Forecast the Canadian Business Cycle," Cahiers de recherche 1606, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    14. Tsung-Hsien Michael Lee & Wenjuan Chen, 2015. "Is There an Asymmetric Impact of Housing on Output?," SFB 649 Discussion Papers SFB649DP2015-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Baghestani, Hamid & AbuAl-Foul, Bassam M., 2017. "Comparing Federal Reserve, Blue Chip, and time series forecasts of US output growth," Journal of Economics and Business, Elsevier, vol. 89(C), pages 47-56.
    16. Caglayan, Mustafa & Xu, Bing, 2016. "Sentiment volatility and bank lending behavior," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 107-120.
    17. Anna Pestova, 2015. "Leading Indicators of the Business Cycle: Dynamic Logit Models for OECD Countries and Russia," HSE Working papers WP BRP 94/EC/2015, National Research University Higher School of Economics.
    18. Harri Ponka, 2017. "The Role of Credit in Predicting US Recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 469-482, August.

    More about this item

    Keywords

    Business cycles; Forecasting; Factor analysis; Probit model; Sentiment variables;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • 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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:aah:create:2013-14. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://www.econ.au.dk/afn/ .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.