Trump Administration Cuts Force BLS to Reduce Data Collection

The quality and accuracy of U.S. federal statistics have been declining for years, a trend that has been exacerbated by budget cuts and staff reductions under the Trump administration. The Bureau of Labor Statistics (BLS), a key federal agency responsible for collecting data on inflation, employment, and other economic indicators, has been particularly affected by these cutbacks.

Since taking office, the Trump administration has implemented a hiring freeze and proposed further budget cuts for government agencies, including the BLS. These measures have forced the agency to rely on less accurate data collection methods and to discontinue tracking inflation figures in certain cities. For instance, the BLS has stopped collecting data from Lincoln, Neb.; Provo, Utah; and Buffalo, N.Y., and has increasingly used "different-cell imputation" methods to estimate prices, which are less accurate than direct data collection.

The BLS collects data through field operators called enumerators, who gather information on products and services in physical stores. With fewer workers in the field, the agency has had to rely more heavily on estimates, which can lead to less accurate data. The BLS acknowledged that it makes reductions when current resources can no longer support the collection effort and will continue to evaluate survey operations.

Erica Groshen, a former BLS commissioner and current senior economics advisor at the Cornell University School of Industrial and Labor Relations, noted that the Trump administration's cuts add to decades of struggles faced by the BLS in maintaining accurate and detailed data. The agency's budget has decreased by about 20% in real terms since 2009, and it has faced political pressure and budget constraints.

Groshen emphasized that while the BLS strives to maintain accurate topline numbers, such as the overall Consumer Price Index (CPI), more granular data could be drastically scaled back. This could have significant implications for those who rely on this data, including Social Security beneficiaries, businesses, and the Federal Reserve. For example, a small error in the CPI could result in billions of dollars in overpayments or underpayments to Social Security beneficiaries.

Paul Donovan, chief economist at UBS Global Wealth Management, highlighted the potential risks for the Federal Reserve, which monitors CPI and employment numbers published by the BLS. Less accurate data could increase the chances of the Fed making policy errors, especially given its data-dependent approach.

Groshen concluded that the BLS will likely continue to reduce the scope of its operations to maintain the quality of headline numbers, but this comes at the cost of sacrificing the granularity of some statistics and programs that are useful for understanding economic changes. She described this as a choice to "fly more blindly," with a clouded windshield that could have been clearer.