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Solving the mystery of the disappearing January blip in state employment data

Author

Listed:
  • Keith R. Phillips
  • Franklin D. Berger

    (University of California Davis)

Abstract

Frank Berger and Keith Phillips propose a new two-step method of seasonally adjusting state Current Employment Statistics (CES) data produced by the Bureau of Labor Statistics (BLS). This method, first proposed in the July/August 1993 issue of Southwest Economy, recently was adopted by the BLS to seasonally adjust the broadest industry groupings of the state employment series. With this new adjustment procedure, the state employment data should be smoother and better reflect trend-cycle movements than if a more traditional seasonal adjustment method were used. ; The article finds that forty-six states suffer a break in their seasonal pattern toward the end of the data series. The authors explain the reason for the break and describe a procedure to adjust for it. Although the BLS is currently using this procedure for states at the broadest level of industry detail, analysts who want to seasonally adjust the state employment data at a finer level of industry detail should find the authors' description of the process useful. Also, analysts who seek to seasonally adjust the CES data for metropolitan areas may find the two-step method helpful.

Suggested Citation

  • Keith R. Phillips & Franklin D. Berger, 1994. "Solving the mystery of the disappearing January blip in state employment data," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue qii, pages 53-62.
  • Handle: RePEc:fip:fedder:y:1994:i:qii:p:53-62
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    File URL: http://www.dallasfed.org/assets/documents/research/er/1994/er9402d.pdf
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    References listed on IDEAS

    as
    1. Evan F. Koenig & Kenneth M. Emery, 1994. "Why The Composite Index Of Leading Indicators Does Not Lead," Contemporary Economic Policy, Western Economic Association International, vol. 12(1), pages 52-66, January.
    2. Neumark, David & Wascher, William L, 1991. "Can We Improve upon Preliminary Estimates of Payroll Employment Growth?," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 197-205, April.
    3. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    4. Franklin D. Berger & Keith R. Phillips, 1993. "Reassessing Texas employment growth," Southwest Economy, Federal Reserve Bank of Dallas, issue jul, pages 1-3.
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    Cited by:

    1. William Kluender & Charles S. Gascon & Scott A. Brave & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Real Time," Working Papers 2019-037, Federal Reserve Bank of St. Louis, revised 29 Nov 2019.
    2. Thomas M. FULLERTON & Macie Z. SUBIA, 2017. "Metropolitan Business Cycle Analysis for Lubbock," Journal of Economics and Political Economy, KSP Journals, vol. 4(1), pages 33-52, March.
    3. Mine K. Ycel & Lori L. Taylor, 1996. "The interest rate sensitivity of Texas industry," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue qii, pages 27-33.
    4. Keith R. Phillips & Jianguo Wang, 2015. "Seasonal adjustment of state and metro ces jobs data," Working Papers 1505, Federal Reserve Bank of Dallas.

    More about this item

    Keywords

    Employment (Economic theory);

    Statistics

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