Real Time Economic Data: Challenges and Opportunities
Saturday, Jan. 7, 2023 2:30 PM - 4:30 PM (CST)
- Chair: Stephanie Aaronson, Brookings Institution
The Importance of Blended Data: Measuring Employment at a Weekly Frequency
AbstractThe pandemic has demonstrated that timely, high-frequency data can provide pivotal economic insights in real time, allowing policymakers and businesses to quickly observe rapid changes in the economy. The elevation of nontraditional data has also highlighted the value of traditional products from statistical agencies given the need to benchmark and validate new data sources. We outline the transformation of a monthly employment indicator based on ADP payroll microdata into a weekly index, emphasizing the value of blending traditional and nontraditional data. We build off Cajner et al. (2018 and 2022) and construct weekly measures of both active (on payrolls) and paid (receiving a paycheck) employment. This new approach entails weekly seasonal adjustment and benchmarking to BLS aggregates at the industry level. The weekly series provides high-frequency insights while also facilitating easier comparison with monthly BLS payroll concepts than did prior work with ADP data. Additionally, we show that the difference between paid and active employment measures can be used as a proxy for temporary dislocation, an important factor in early pandemic labor markets. Finally, we document how the weekly employment indexes have fared during the pandemic jobs recovery, with particular interest in the benchmark revision to the publicly available data for the second half of 2021.
Measuring Business Trends and Outlook through a New Survey
AbstractThe Census Bureau’s new Business Trends and Outlook Survey (BTOS) provides timely information from businesses on their current trends and expectations over core concepts such as prices, employment, and revenue. BTOS collects qualitative information in order to produce extensive margins for core economic phenomena. BTOS results are representative of all single-location nonfarm businesses in the United States. We highlight sectoral differences in extensive margins of employment and prices using Finance and Insurance and Accommodation and Food Services as examples. We find businesses especially in Accommodation and Food Services anticipate future output price increases, possibly to accommodate rising current input prices.
Business Applications as Economic Indicators
AbstractHow are applications to start new businesses related to aggregate economic activity? This paper explores the properties of three monthly business application series from the U.S. Census Bureau’s Business Formation Statistics as economic indicators: all business applications, business applications that are relatively likely to turn into new employer businesses (“likely employers”), and the residual series -- business applications that have a relatively low rate of becoming
employers (“likely non-employers”). The analysis indicates that growth in applications for likely employers significantly leads total nonfarm employment growth and has a positive correlation with it, whereas growth in all applications and applications for likely non employers have weaker positive correlations and shorter leads. Furthermore, growth in applications for likely employers leads growth in nearly all of the monthly Principal Federal Economic Indicators (PFEI) included in this study. Impulse response functions from vector autoregression analysis indicate that growth of both total nonfarm employment and advance monthly sales in retail and food services have positive and long-lasting responses to innovations in growth of applications for likely employers. Overall, applications for likely employers appear to be a strong leading indicator of monthly PFEIs and aggregate economic activity, whereas applications for likely non-employers provide early information about changes in increasingly prevalent self-employment activity in the U.S. economy.
- C8 - Data Collection and Data Estimation Methodology; Computer Programs
- L2 - Firm Objectives, Organization, and Behavior