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Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data
This paper combines information from two sources of U.S. private payroll employment to increase the accuracy of real-time measurement of the labor market. The sources are the Current Employment Statistics (CES) from BLS and microdata from the payroll processing firm ADP. We briefly describe the ADP-derived data series, compare it to the BLS data, and describe an exercise that benchmarks the data series to an employment census. The CES and the ADP employment data are each derived from roughly equal-sized samples. We argue that combining CES and ADP data series reduces the measurement error ...
From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending
Access to timely information on consumer spending is important to economic policymakers. The Census Bureau's monthly retail trade survey is a primary source for monitoring consumer spending nationally, but it is not well suited to study localized or short-lived economic shocks. Moreover, lags in the publication of the Census estimates and subsequent, sometimes large, revisions diminish its usefulness for real-time analysis. Expanding the Census survey to include higher frequencies and subnational detail would be costly and would add substantially to respondent burden. We take an alternative ...
Tracking Labor Market Developments during the COVID-19 Pandemic: A Preliminary Assessment
Many traditional official statistics are not suitable for measuring high-frequency developments that evolve over the course of weeks, not months. In this paper, we track the labor market effects of the COVID-19 pandemic with weekly payroll employment series based on microdata from ADP. These data are available essentially in real-time, and allow us to track both aggregate and industry effects. Cumulative losses in paid employment through April 4 are currently estimated at 18 million; just during the two weeks between March 14 and March 28 the U.S. economy lost about 13 million paid jobs. ...
Technological Innovation and Discrimination in Household Finance
Technology has changed how discrimination manifests itself in financial services. Replacing human discretion with algorithms in decision-making roles reduces taste-based discrimination, and new modeling techniques have expanded access to financial services to households who were previously excluded from these markets. However, algorithms can exhibit bias from human involvement in the development process, and their opacity and complexity can facilitate statistical discrimination inconsistent with antidiscrimination laws in several aspects of financial services provision, including advertising, ...
Exploring the use of anonymized consumer credit information to estimate economic conditions: an application of big data
The emergence of high-frequency administrative data and other big data offers an opportunity for improvements to economic forecasting models. This paper considers the potential advantages and limitations of using information contained in anonymized consumer credit reports for improving estimates of current and future economic conditions for various geographic areas and demographic markets. Aggregate consumer credit information is found to be correlated with macroeconomic variables such as gross domestic product, retail sales, and employment and can serve as leading indicators such that lagged ...