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Can We Improve upon Preliminary Estimates of Payroll Employment Growth?

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  • Neumark, David
  • Wascher, William L

Abstract

We explore the feasibility of improving upon the preliminary estimates of payroll employment growth from the U.S. Bureau of Labor Statistics by predicting subsequent revisions to these estimates, using the preliminary estimates themselves and other information available concurrently. Results of statistical tests suggest that the preliminary estimates can be improved upon; that is, they are not "efficient forecasts" of the revised estimates. The improvement of preliminary estimates as indicators of estimates of employment growth following annual benchmarks is particularly large; the unanticipated component of the revision based on the annual benchmarks is reduced by more than 22 percent.

Suggested Citation

  • 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.
  • Handle: RePEc:bes:jnlbes:v:9:y:1991:i:2:p:197-205
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    Cited by:

    1. Phillips, Keith R. & Nordlund, James, 2012. "The efficiency of the benchmark revisions to the current employment statistics (CES) data," Economics Letters, Elsevier, vol. 115(3), pages 431-434.
    2. 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.
    3. Tomaz Cajner & Leland Crane & Ryan 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.).
    4. Franklin D. Berger & Keith R. Phillips, 1994. "The disappearing January blip and other state employment mysteries," Working Papers 9403, Federal Reserve Bank of Dallas.

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