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Misclassification-Errors-Adjusted Sahm Rule for Early Identification of Economic Recession

Author

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  • Feng, Shuaizhang

    (Shanghai University of Finance and Economics)

  • Sun, Jiandong

    (Jinan University)

Abstract

Accurate identification of economic recessions in a timely fashion is a major macroeconomic challenge. The most successful early detector of recessions, the Sahm rule, relies on changes in unemployment rates, and is thus subject to measurement errors in the U.S. labor force statuses based on survey data. We propose a novel misclassification-error-adjusted Sahm recession indicator and provide empirically-based optimal threshold values. Using historical data, we show that the adjusted Sahm rule offers earlier identification of economic recessions. Based on the newly released U.S. unemployment rate in March 2020, our adjusted Sahm rule diagnoses the U.S. economy is already in recession, while the original Sahm rule does not.

Suggested Citation

  • Feng, Shuaizhang & Sun, Jiandong, 2020. "Misclassification-Errors-Adjusted Sahm Rule for Early Identification of Economic Recession," IZA Discussion Papers 13168, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp13168
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    References listed on IDEAS

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    1. Shuaizhang Feng & Yingyao Hu, 2013. "Misclassification Errors and the Underestimation of the US Unemployment Rate," American Economic Review, American Economic Association, vol. 103(2), pages 1054-1070, April.
    2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    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. Ruilin Tian & Gang Shen, 2019. "Predictive power of Markovian models: Evidence from US recession forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(6), pages 525-551, September.
    5. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    6. Lahiri, Kajal & Yang, Liu, 2015. "A further analysis of the conference board’s new Leading Economic Index," International Journal of Forecasting, Elsevier, vol. 31(2), pages 446-453.
    7. 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.
    8. Feng, Shuaizhang & Hu, Yingyao & Sun, Jiandong, 2018. "On the robustness of alternative unemployment measures," Economics Letters, Elsevier, vol. 166(C), pages 1-5.
    9. 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.
    10. Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
    11. Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    12. Tao Chen & Erin Pik Ki So & Liang Wu & Isabel Kit Ming Yan, 2015. "The 2007–2008 U.S. Recession: What Did The Real-Time Google Trends Data Tell The United States?," Contemporary Economic Policy, Western Economic Association International, vol. 33(2), pages 395-403, April.
    13. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    14. 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.
    15. Arturo Estrella, 2005. "Why Does the Yield Curve Predict Output and Inflation?," Economic Journal, Royal Economic Society, vol. 115(505), pages 722-744, July.
    16. 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.
    17. Abowd, John M & Zellner, Arnold, 1985. "Estimating Gross Labor-Force Flows," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 254-283, June.
    18. Poterba, James M & Summers, Lawrence H, 1986. "Reporting Errors and Labor Market Dynamics," Econometrica, Econometric Society, vol. 54(6), pages 1319-1338, November.
    19. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    20. Levanon, Gad & Manini, Jean-Claude & Ozyildirim, Ataman & Schaitkin, Brian & Tanchua, Jennelyn, 2015. "Using financial indicators to predict turning points in the business cycle: The case of the leading economic index for the United States," International Journal of Forecasting, Elsevier, vol. 31(2), pages 426-445.
    21. Rudebusch, Glenn D. & Williams, John C., 2009. "Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 492-503.
    22. Jeremy J. Nalewaik, 2012. "Estimating Probabilities of Recession in Real Time Using GDP and GDI," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 235-253, February.
    23. 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.
    24. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
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    Cited by:

    1. Blanchflower, David G. & Bryson, Alex, 2021. "The Economics of Walking About and Predicting Unemployment," GLO Discussion Paper Series 922, Global Labor Organization (GLO).
    2. Blanchflower, David G. & Bryson, Alex, 2023. "Labour Market Expectations and Unemployment in Europe," IZA Discussion Papers 15905, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    misclassification errors; Sahm rule; economic recession; unemployment rate;
    All these keywords.

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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