IDEAS home Printed from https://ideas.repec.org/a/fip/fedder/y1994iqiip53-62.html

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

Author

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

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

  • Franklin D. Berger & Keith R. Phillips, 1994. "Solving the mystery of the disappearing January blip in state employment data," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q II, pages 53-62.
  • Handle: RePEc:fip:fedder:y:1994:i:qii:p:53-62
    as

    Download full text from publisher

    File URL: https://www.dallasfed.org/~/media/documents/research/er/1994/er9402d.pdf
    File Function: Full Text
    Download Restriction: no
    ---><---

    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. Franklin D. Berger & Keith R. Phillips, 1993. "Reassessing Texas employment growth," Southwest Economy, Federal Reserve Bank of Dallas, issue Jul, pages 1-3.
    3. 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.
    4. 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.
    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. Brave, Scott A. & Gascon, Charles & Kluender, William & Walstrum, Thomas, 2021. "Predicting benchmarked US state employment data in real time," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1261-1275.
    2. Thomas M. FULLERTON & Macie Z. SUBIA, 2017. "Metropolitan Business Cycle Analysis for Lubbock," Journal of Economics and Political Economy, EconSciences Journals, vol. 4(1), pages 33-52, March.
    3. Keith R. Phillips & Jianguo Wang, 2015. "Seasonal adjustment of state and metro ces jobs data," Working Papers 1505, Federal Reserve Bank of Dallas.
    4. Lori L. Taylor & Mine K. Yücel, 1996. "The interest rate sensitivity of Texas industry," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q II, pages 27-33.
    5. Phillips, Keith R. & Teng, Judy S., 2020. "Months for benchmark dominance: A new accuracy measure for state employment data," Economics Letters, Elsevier, vol. 187(C).

    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. Franklin D. Berger & Keith R. Phillips, 1994. "The disappearing January blip and other state employment mysteries," Working Papers 9403, Federal Reserve Bank of Dallas.
    2. Clements Michael P., 2012. "Forecasting U.S. Output Growth with Non-Linear Models in the Presence of Data Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-27, January.
    3. Hännikäinen Jari, 2017. "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    4. Michael P. Clements, 2014. "Anticipating Early Data Revisions to US GDP and the Effects of Releases on Equity Markets," ICMA Centre Discussion Papers in Finance icma-dp2014-06, Henley Business School, University of Reading.
    5. Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
    6. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    7. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz & Tyler Radler, 2018. "Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity," Finance and Economics Discussion Series 2018-005, Board of Governors of the Federal Reserve System (U.S.).
    8. Thomas A. Knetsch, 2005. "Evaluating the German Inventory Cycle Using Data from the Ifo Business Survey," Contributions to Economics, in: Jan-Egbert Sturm & Timo Wollmershäuser (ed.), Ifo Survey Data in Business Cycle and Monetary Policy Analysis, pages 61-92, Springer.
    9. repec:spo:wpmain:info:hdl:2441/2q9catktmn91sabau2l9qji1as is not listed on IDEAS
    10. Glenn D. Rudebusch, 2001. "Is The Fed Too Timid? Monetary Policy In An Uncertain World," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 203-217, May.
    11. KOMINE Takao & BAN Kanemi & KAWAGOE Masaaki & YOSHIDA Hiroshi, 2009. "What Have We Learned from a Survey of Japanese Professional Forecasters? Taking Stock of Four Years of ESP Forecast Experience," ESRI Discussion paper series 214, Economic and Social Research Institute (ESRI).
    12. Van Nieuwerburgh, Stijn & Veldkamp, Laura, 2006. "Learning asymmetries in real business cycles," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 753-772, May.
    13. Keith R. Phillips, 2004. "A new monthly index of the Texas business cycle," Working Papers 0401, Federal Reserve Bank of Dallas.
    14. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
    15. S. Boragan Aruoba, 2004. "Data Uncertainty in General Equilibrium," Computing in Economics and Finance 2004 131, Society for Computational Economics.
    16. Francisco Castro & Javier J. P√Ârez & Marta Rodr√Çguez-Vives, 2013. "Fiscal Data Revisions in Europe," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(6), pages 1187-1209, September.
    17. Ducoudré, Bruno & Hubert, Paul & Tabarly, Guilhem, 2020. "The state-dependence of output revisions," Economics Letters, Elsevier, vol. 192(C).
    18. Watson, Mark W, 1993. "Measures of Fit for Calibrated Models," Journal of Political Economy, University of Chicago Press, vol. 101(6), pages 1011-1041, December.
    19. Götz, Thomas B. & Hecq, Alain & Urbain, Jean-Pierre, 2016. "Combining forecasts from successive data vintages: An application to U.S. growth," International Journal of Forecasting, Elsevier, vol. 32(1), pages 61-74.
    20. Clements, Michael P., 2012. "Do professional forecasters pay attention to data releases?," International Journal of Forecasting, Elsevier, vol. 28(2), pages 297-308.
    21. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.

    More about this item

    Keywords

    ;

    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:fip:fedder:y:1994:i:qii:p:53-62. See general information about how to correct material in RePEc.

    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: Amy Chapman (email available below). General contact details of provider: https://edirc.repec.org/data/frbdaus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.