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Using the Purchasing Managers' Index to assess the economy's strength and the likely direction of monetary policy

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  • Evan F. Koenig

Abstract

When economists are concerned that the economy may be about to change direction, one of the indicators to which they give special scrutiny is the Purchasing Managers’ Index (PMI), released monthly by the Institute for Supply Management. This article discusses the construction and interpretation of the PMI and presents evidence of its usefulness as an indicator of growth in the manufacturing sector and the economy as a whole, and as a predictor of changes in Federal Reserve policy. PMI values above 47 generally signal expansion in manufacturing, while the critical value for positive GDP growth is around 40. Over the past fifteen years, PMI values above 52.5 have tended to be associated with rising short-term interest rates.> When economists are concerned that the economy may be about to change direction, one of the indicators to which they give special scrutiny is the Purchasing Managers’ Index (PMI), released monthly by the Institute for Supply Management. This article discusses the construction and interpretation of the PMI and presents evidence of its usefulness as an indicator of growth in the manufacturing sector and the economy as a whole, and as a predictor of changes in Federal Reserve policy. PMI values above 47 generally signal expansion in manufacturing, while the critical value for positive GDP growth is around 40. Over the past fifteen years, PMI values above 52.5 have tended to be associated with rising short-term interest rates.>

Suggested Citation

  • 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.
  • Handle: RePEc:fip:fedder:y:2002:n:v.1no.6
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    File URL: http://dallasfed.org/assets/documents/research/efpr/v01_n06_a01.pdf
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    References listed on IDEAS

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    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    3. Balke, Nathan S & Petersen, D'Ann, 2002. "How Well Does the Beige Book Reflect Economic Activity? Evaluating Qualitative Information Quantitatively," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 114-136, February.
    4. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    5. Ethan S. Harris, 1991. "Tracking the economy with the purchasing managers' index," Research Paper 9124, Federal Reserve Bank of New York.
    6. Ethan S. Harris, 1991. "Tracking the economy with the purchasing managers' index," Quarterly Review, Federal Reserve Bank of New York, issue Aut, pages 61-69.
    7. Stephen K. McNees, 1986. "Modeling the Fed: a forward- looking monetary policy reaction function," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 3-8.
    8. R. Mark Rogers, 1992. "Forecasting industrial production: purchasing managers' versus production-worker hours data," Economic Review, Federal Reserve Bank of Atlanta, issue Jan, pages 25-36.
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    Cited by:

    1. Claudia Godbout & Marco J. Lombardi, 2012. "Short-Term Forecasting of the Japanese Economy Using Factor Models," Staff Working Papers 12-7, Bank of Canada.
    2. van den Hauwe, Sjoerd & Paap, Richard & van Dijk, Dick, 2013. "Bayesian forecasting of federal funds target rate decisions," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 19-40.
    3. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, pages 644-658.
    4. Gabe de Bondt, 2012. "Nowcasting: Trust the Purchasing Managers’ Index or wait for the flash GDP estimate?," EcoMod2012 3896, EcoMod.
    5. Daragh Clancy, 2013. "Output Gap Estimation Uncertainty: Extracting the TFP Cycle Using an Aggregated PMI Series," The Economic and Social Review, Economic and Social Studies, vol. 44(1), pages 1-18.
    6. 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.
    7. Schnatz, Bernd & D'Agostino, Antonello, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
    8. Valentina Aprigliano, 2011. "The relationship between the PMI and the Italian index of industrial production and the impact of the latest economic crisis," Temi di discussione (Economic working papers) 820, Bank of Italy, Economic Research and International Relations Area.
    9. Khundrakpam, Jeevan Kumar & George, Asish Thomas, 2012. "An Empirical Analysis of the Relationship between WPI and PMI-Manufacturing Price Indices in India," MPRA Paper 50929, University Library of Munich, Germany.
    10. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
    11. Claudia Godbout & Jocelyn Jacob, 2010. "Le pouvoir de prévision des indices PMI," Discussion Papers 10-3, Bank of Canada.
    12. Tsuchiya, Yoichi, 2014. "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 599-618.
    13. repec:ecb:ecbwps:20111428 is not listed on IDEAS

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