Why You Should Take The Jobs Number With A Grain of Salt

Courtesy of Lee Adler of the Wall Street Examiner

This post is an excerpt of a report posted on October 3, 2012.

Given its larger sample size and use of actual payrolls, the ADP employment estimate is probably a more accurate guide to actual employment trends than is the BLS data. However, the market pays little attention to the ADP data, and focuses almost exclusively on the BLS data. Unfortunately the BLS data is also subject to large annual revisions, called benchmarking, based on collection of actual employment data from unemployment tax returns. The BLS just released a preliminary benchmark revision for the period from April 2011 to March 2012, adding 386,000 jobs. As a result it will also restate the figures not only for that year, but for the period from April to August, revising them up. This does not include the annual backward revisions of the seasonally adjusted data every year for 5 years following the date of the release.

In any given month, the BLS data cannot be trusted to give an accurate picture of employment trends. The government says that that sampling error is in the range of +/- 100,000. This does not include non-sampling error that may be due to other factors. That degree of uncertainty can result in a huge difference to the market. A beat or miss of 50,000 or less versus the consensus often moves the market.

Finally, there’ s the seasonal adjustment problem. Virtually everybody uses seasonally adjusted data because it smooths the month to month and quarter to quarter variations in the data. This results in an abstract data plot that often creates a misleading picture of the the trend. The current month’s seasonally adjusted number isn’t even finalized until 5 years after the release date because the government is constantly trying to adjust the number to more closely and accurately represent the trend of the actual data based on subsequent data. From the BLS monthly press release:

For both the household and establishment surveys, a concurrent seasonal adjustment methodology is used in which new seasonal factors are calculated each month using all relevant data, up to and including the data for the current month. In the household survey, new seasonal factors are used to adjust only the current month’s data. In the establishment survey, however, new seasonal factors are used each month to adjust the three most recent monthly estimates. The prior 2 months are routinely revised to incorporate additional sample reports and recalculated seasonal adjustment factors. In both surveys, 5-year revisions to historical data are made once a year.

Given the unknown impact of non-payroll factors in the withholding tax data and the capricious nature of BLS survey data, perhaps the best measure of employment trends is the weekly unemployment claims data collected by the Labor Department’s Employment and Training Administration. It does not give the whole picture in that it only shows those filing for unemployment, but as a measure of the trend, it is certainly the most accurate and most timely. It consists of an actual count, is available virtually in real time, and the data is reported on both an actual, not seasonally adjusted (NSA) basis and a seasonally adjusted (SA) basis, enabling us to clearly distinguish just how misleading the SA data is. The actual NSA data has shown a steady trend of improvement at a relatively constant rate for the past two years. I will post an update of the charts and data on Thursday.

The market isn’t known for its rationality, but investor and media focus on the monthly headline payrolls number is a little insane given the problems inherent in the data. Both the withholding tax data, even though it includes some uncertainty, and the weekly claims data, reflect at least steady growth in jobs.

Read Downtrend In Claims, Uptrend in Withholding, Suggest Blowout Jobs Number As Stocks Bubble

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