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Pennsylvania Convention Center, 201-B
American Economic Association
What Can We Learn from Private Sector Data About the Labor Market?
Saturday, Jan. 6, 2018 8:00 AM - 10:00 AM
- Chair: Erik Hurst, University of Chicago
Rent Sharing Within Firms
AbstractThis paper estimates the degree to which rent sharing occurs among different types of workers within the same firms. Bertrand and Mullainathan (2001) have found that executive compensation tends to be positively correlated with observable forms of luck and that this relationship appears to be particularly strong at companies that have relatively weak forms of governance. Using micro data from ADP and profit shocks due to commodity prices and minimum wage hikes, we will analyze the degree to which rents are shared across workers in different wage categories within firms, and across firms.
Using ADP Payroll Microdata to Measure Aggregate Labor Market Activity
AbstractWe show that high frequency private payroll microdata can help forecast labor market conditions. Payroll employment is perhaps the most reliable real-time indicator of business cycles and it is therefore closely followed by policymakers, academia, and financial markets. Government statistical agencies have long served as the primary source of information on labor markets 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 ADP, which processes payrolls for about one fifth of U.S. private sector employment. We evaluate the efficacy of these data to create new statistics that complement existing government measurements. 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 possible with existing data sources. We evaluate whether the indexes complement the official employment statistics and then test whether the information contained in the high-frequency and timely estimates of employment assist in forecasting current employment. The large sample size of ADP data—similar in terms of private employment to the BLS CES sample—implies potentially high informational value of these data and our results strongly confirm this conjecture. The timeliness and frequency of the ADP payroll microdata substantially improves forecast accuracy of both current month employment and revisions to the BLS CES data. Importantly, augmenting publically produced information on employment with the ADP payroll microdata substantially improves our understanding of the cyclical state of the economy.
Aging and the Productivity Puzzle
AbstractResearch on the effect of an aging population on economic growth has tended to focus on labor force participation and the dependency ratio, and the limited work that has examined the effect of aging on productivity remains inconclusive. This analysis contributes to the aging and productivity literature and finds a negative effect of aging on productivity using both state-industry aggregate data and matched employer-employee micro-data. The aggregate data show a clear relationship between an older workforce and lower productivity at the state-industry level, in both cross-section and panel models. The results are confirmed using employer-employee linked data from private sector human resource company ADP that show having older coworkers reduces an individual’s wages. Robustness tests include ZIP-3 fixed effects and firm fixed effects for a sample of large nationwide firms. The results suggest that between a quarter and full percentage point of the slowing in productivity growth in recent years may be due to aging, an effect that is likely to persist for the next decade
- J0 - General
- J2 - Demand and Supply of Labor