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Evaluating the OECD’s main economic indicators at anticipating recessions

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  • Máximo Camacho
  • Gonzalo Palmieri

Abstract

Using receiver operating characteristic (ROC) techniques, we evaluate the predictive content of the monthly main economic indicators (MEI) of the Organization for Economic Co‐operation and Development (OECD) for predicting both growth cycle and business cycle recessions at different horizons. From a sample that covers 123 indicators for 32 OECD countries as well as for Brazil, China, India, Indonesia, the Russian Federation, and South Africa, our results suggest that the OECD's MEI show a high overall performance in providing early signals of economic downturns worldwide, albeit they perform a bit better at anticipating business cycles than growth cycles. Although the performance for OECD and non‐OECD members is similar in terms of timeliness, the indicators are more accurate at anticipating recessions for OECD members. Finally, we find that some single indicators, such as interest rates, spreads, and credit indicators, perform even better than the composite leading indicators.

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  • Máximo Camacho & Gonzalo Palmieri, 2021. "Evaluating the OECD’s main economic indicators at anticipating recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 80-93, January.
  • Handle: RePEc:wly:jforec:v:40:y:2021:i:1:p:80-93
    DOI: 10.1002/for.2709
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    1. Gorr, Wilpen L. & Schneider, Matthew J., 2013. "Large-change forecast accuracy: Reanalysis of M3-Competition data using receiver operating characteristic analysis," International Journal of Forecasting, Elsevier, vol. 29(2), pages 274-281.
    2. 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.
    3. Drechsel, Katja & Scheufele, Rolf, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10/2010, Halle Institute for Economic Research (IWH).
    4. 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.
    5. Drehmann, Mathias & Juselius, Mikael, 2014. "Evaluating early warning indicators of banking crises: Satisfying policy requirements," International Journal of Forecasting, Elsevier, vol. 30(3), pages 759-780.
    6. Johann Burgstaller, 2002. "Are stock returns a leading indicator for real macroeconomic developments?," Economics working papers 2002-07, Department of Economics, Johannes Kepler University Linz, Austria.
    7. Qi, Min, 2001. "Predicting US recessions with leading indicators via neural network models," International Journal of Forecasting, Elsevier, vol. 17(3), pages 383-401.
    8. Pierre-Olivier Gourinchas & Maurice Obstfeld, 2012. "Stories of the Twentieth Century for the Twenty-First," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(1), pages 226-265, January.
    9. Kajal Lahiri & Liu Yang, 2018. "Confidence Bands for ROC Curves With Serially Dependent Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 115-130, January.
    10. Òscar Jordà & Moritz Schularick & Alan M Taylor, 2011. "Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 59(2), pages 340-378, June.
    11. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    12. James H. Stock & Mark W. Watson, 2003. "How did leading indicator forecasts perform during the 2001 recession?," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 89(Sum), pages 71-90.
    13. Robert H. McGuckin & Ataman Ozyildirim & Victor Zarnowitz, 2000. "The Composite Index of Leading Economic Indicators: How to Make it More Timely," Economics Program Working Papers 00-04, The Conference Board, Economics Program.
    14. Gad Levanon, 2010. "Evaluating and Comparing Leading and Coincident Economic Indicators," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 45(1), pages 16-27, January.
    15. Travis J. Berge, 2015. "Predicting Recessions with Leading Indicators: Model Averaging and Selection over the Business Cycle," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(6), pages 455-471, September.
    16. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    17. Camacho, Maximo & Perez-Quiros, Gabriel & Poncela, Pilar, 2018. "Markov-switching dynamic factor models in real time," International Journal of Forecasting, Elsevier, vol. 34(4), pages 598-611.
    18. Cohen, Jacqueline & Garman, Samuel & Gorr, Wilpen, 2009. "Empirical calibration of time series monitoring methods using receiver operating characteristic curves," International Journal of Forecasting, Elsevier, vol. 25(3), pages 484-497, July.
    19. 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.
    20. Davis, E Philip & Fagan, Gabriel, 1997. "Are Financial Spreads Useful Indicators of Future Inflation and Output Growth in EU Countries?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(6), pages 701-714, Nov.-Dec..
    21. Garcia-Ferrer, Antonio & Bujosa-Brun, Marcos, 2000. "Forecasting OECD industrial turning points using unobserved components models with business survey data," International Journal of Forecasting, Elsevier, vol. 16(2), pages 207-227.
    22. Marcellino, Massimiliano, 2006. "Leading Indicators," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 16, pages 879-960, Elsevier.
    23. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    24. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, March.
    25. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    26. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
    27. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
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    1. Alonso-Alvarez, Irma & Molina, Luis, 2023. "How to foresee crises? A new synthetic index of vulnerabilities for emerging economies," Economic Modelling, Elsevier, vol. 125(C).

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