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Board of Governors of the Federal Reserve System (US)
Finance and Economics Discussion Series
Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity
Tomaz Cajner
Leland Crane
Ryan Decker
Adrian Hamins-Puertolas
Christopher J. Kurz
Tyler Radler
Abstract

We show that high-frequency private payroll microdata can help forecast labor market conditions. Payroll employment is perhaps the most reliable real-time indicator of the business cycle and is therefore closely followed by policymakers, academia, and financial markets. Government statistical agencies have long served as the primary suppliers of information on the labor market and will continue to do so for the foreseeable future. That said, sources of “big data” are becoming increasingly available through collaborations with private businesses engaged in commercial activities that record economic activity on a granular, frequent, and timely basis. One such data source is generated by the firm ADP, which processes payrolls for about one fifth of the U.S. private sector workforce. We evaluate the efficacy of these data to create new statistics that complement existing measures. In particular, we develop a set of weekly aggregate employment indexes from 2000 to 2017, which allows us to measure employment at a higher frequency than is currently possible. The extensive coverage of the ADP data—similar in terms of private employment to the BLS CES sample—implies potentially high information value of these data, and our results confirm this conjecture. Indeed, the timeliness and frequency of the ADP payroll microdata substantially improves forecast accuracy for both current-month employment and revisions to the BLS CES data.


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Tomaz Cajner & Leland Crane & Ryan Decker & Adrian Hamins-Puertolas & Christopher J. Kurz & Tyler Radler, Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity, Board of Governors of the Federal Reserve System (US), Finance and Economics Discussion Series 2018-005, 17 Jan 2018.
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Keywords: Consumption; saving; production; employment; and investment ; Labor supply and demand ; Forecasting
DOI: 10.17016/FEDS.2018.005
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