IDEAS home Printed from https://ideas.repec.org/p/zbw/glodps/523.html
   My bibliography  Save this paper

Misclassification-errors-adjusted Sahm Rule for Early Identification of Economic Recession

Author

Listed:
  • Feng, Shuaizhang
  • Sun, Jiandong

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 in- dicator 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," GLO Discussion Paper Series 523, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:523
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/215887/1/GLO-DP-0523.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Feng, Shuaizhang & Hu, Yingyao & Sun, Jiandong, 2018. "On the robustness of alternative unemployment measures," Economics Letters, Elsevier, vol. 166(C), pages 1-5.
    7. Giannone, Domenico & Reichlin, Lucrezia & 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Arturo Estrella, 2005. "Why Does the Yield Curve Predict Output and Inflation?," Economic Journal, Royal Economic Society, vol. 115(505), pages 722-744, July.
    22. 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.
    23. Poterba, James M & Summers, Lawrence H, 1986. "Reporting Errors and Labor Market Dynamics," Econometrica, Econometric Society, vol. 54(6), pages 1319-1338, November.
    24. 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.
    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. Blanchflower, David G. & Bryson, Alex, 2021. "The Economics of Walking About and Predicting Unemployment," GLO Discussion Paper Series 922, Global Labor Organization (GLO).

    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. Sun, Jiandong & Feng, Shuaizhang & Hu, Yingyao, 2021. "Misclassification errors in labor force statuses and the early identification of economic recessions," Journal of Asian Economics, Elsevier, vol. 75(C).
    2. 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).
    3. Shuaizhang Feng & Jiandong Sun, 2020. "Misclassification-Errors-Adjusted Sahm Rule for Early Identification of Economic Recession," Working Papers 2020-029, Human Capital and Economic Opportunity Working Group.
    4. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    5. Aastveit, Knut Are & Anundsen, André K. & Herstad, Eyo I., 2019. "Residential investment and recession predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1790-1799.
    6. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2012. "The yield curve and the macro-economy across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1950-1970.
    7. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    8. Vasilios Plakandaras & Juncal Cunado & Rangan Gupta & Mark E. Wohar, 2016. "Do Leading Indicators Forecast U.S. Recessions? A Nonlinear Re-Evaluation Using Historical Data," Working Papers 201685, University of Pretoria, Department of Economics.
    9. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    10. Raúl Ibarra-Ramírez, 2021. "The Yield Curve as a Predictor of Economic Activity in Mexico: The Role of the Term Premium," Working Papers 2021-07, Banco de México.
    11. Fernandez-Perez, Adrian & Fernández-Rodríguez, Fernando & Sosvilla-Rivero, Simón, 2014. "The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 21-33.
    12. Davig, Troy & Hall, Aaron Smalter, 2019. "Recession forecasting using Bayesian classification," International Journal of Forecasting, Elsevier, vol. 35(3), pages 848-867.
    13. Christiansen, Charlotte, 2013. "Predicting severe simultaneous recessions using yield spreads as leading indicators," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1032-1043.
    14. Bellégo, C. & Ferrara, L., 2012. "Macro-financial linkages and business cycles: A factor-augmented probit approach," Economic Modelling, Elsevier, vol. 29(5), pages 1793-1797.
    15. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.
    16. Cyrille Lenoel & Garry Young, 2020. "Real-time turning point indicators: Review of current international practices," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-05, Economic Statistics Centre of Excellence (ESCoE).
    17. Pirschel, Inske, 2016. "Forecasting euro area recessions in real-time," Kiel Working Papers 2020, Kiel Institute for the World Economy (IfW Kiel).
    18. Bellégo, C. & Ferrara, L., 2009. "Forecasting Euro-area recessions using time-varying binary response models for financial," Working papers 259, Banque de France.
    19. Leo Krippner & Leif Anders Thorsrud, 2009. "Forecasting New Zealand's economic growth using yield curve information," Reserve Bank of New Zealand Discussion Paper Series DP2009/18, Reserve Bank of New Zealand.
    20. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.

    More about this item

    Keywords

    Economic recession; Sahm rule; Misclassification errors; Unemployment rate;
    All these keywords.

    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:zbw:glodps:523. 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: https://edirc.repec.org/data/glabode.html .

    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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/glabode.html .

    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.