February employment

The ADP National Employment Report says the economy lost 20,000 private sector jobs in February. The ADP report seems to be a good proxy for private employment as it appears in the BLS report. For reasons given in the link above, the ADP numbers for February will not be affected by the blizzards in the way that the BLS data are. The data suggest to me that total employment growth in February was near zero (-20,000 plus whatever government employment growth there was). The BLS report should show a large negative number as a result of the blizzards. We're behind schedule here, people!

The construction of the ADP figures, described here, is interesting (in an incredibly techno-geeky kind of way). One reason the ADP numbers fit the BLS numbers so well is that they are benchmarked to the BLS numbers through a regression technique that I don't understand.

The BLS data (as currently reported) for growth of employment by industry is regressed on: (a) the matched-sample growth rates by industry based on the ADP data; (b) a weighted average of the historical average growth rates of employment in each cell based on QCEW data; (c) a weighted average of the historical average

growth rates of employment in each cell based on the ADP data; (d) lagged values of BLS estimates of growth of employment by industry; (e) initial unemployment claims filed during the week immediately before the week that includes the 12th of the month.

The regressions are estimated concurrently. The coefficient on term (b) above is restricted to unity. The coefficient on (c) is restricted to the negative of the coefficient on term (a). This method allows different trends of employment by size of payroll within industries, while assuming that the other industry-wide relationships implied by the regressions hold for all size classes within an industry. Inclusion of lagged employment in the regressions5 controls for shifting differences between the BLS sample and the ADP customer base, while inclusion of initial unemployment claims controls for differences in the definitions of employment used by BLS and ADP.

A level of employment is established in each cell by cumulating the predicted value of the matched sample growth rate in each cell forward and backwards from the most recently benchmarked March estimate of employment in that cell. Such referencing effectively weights the growth rates of the ADP data in each cell by

the observed distribution of employment by industry and size classification.

These levels are then summed to the aggregates by select industry and size of payroll that are shown in the summary table of the monthly report.

In addition, every year the ADP are revised when the BLS does its benchmark revisions. So the phenomenal fit of the ADP data (correlation of differences is 0.95) is by construction. I wonder how well the ADP figures predict the BLS figures before revisions, i.e. how closely is the -20,000 number reported for February correlated with the BLS number we get on Friday? Apparently Macroeconomic Advisors has studied this question, but I don't know what they found.

Bob is telling me that the seasonal adjustment factors that the BLS uses are probably skewed this winter because the weather has been much more severe than it has been in the past few years. (Basically, the BLS's seasonal adjustment procedure uses the last 5 or 6 years of data to net out seasonal effects. So if we had a mild Januaries in recent years, the January effect will be small. Then when we get socked by a bad January as happened this year, and employment declines as a result, the seasonal adjustment process only partially offsets that, interpreting the plunge as a bad economy rather than bad weather.) ADP uses the same seasonal adjustment procedure, so whatever ails the BLS data on that dimension will ail ADP data as well.