by Thomas Wash | PDF
The federal government’s economic reports are a valuable resource — timely, comprehensive, and generally recognized as unbiased. However, the data’s accuracy is a growing concern and has been exacerbated by pandemic-related distortions that are still largely unaddressed. We have always triangulated our analysis of government data with private data and corporate reports to make sure that our understanding of economic trends is as accurate as possible. Today, the growing reliability issues in the federal data have made private data and corporate reports even more indispensable for informed decision-making.
The recent downward revisions to the nonfarm payrolls data have brought this issue into sharp focus. Last month, the Bureau of Labor Statistics (BLS) reported the largest two-month downward revision in the jobs data since 1968. While the estimate reductions were driven primarily by government job cuts, the downward revisions were broad-based across nearly all sectors. The sharp drop in estimated payrolls has cast doubt on the economy’s true strength, especially since the initial data coincided with the rollout of new tariffs.
Why Has the Data Become Less Reliable?
Downward revisions in the BLS payroll data are not unusual. Over the past five years, initial job figures have been revised downward by an average of 30,000 jobs per month in all but one year — a trend that shows no sign of reversing yet. The BLS’s Quarterly Census of Employment and Wages, which is less timely but more accurate, may ultimately reveal even lower job counts once benchmark revisions are complete.
The root of the problem lies in the BLS’s data collection process. Survey response rates have plummeted to 42% recently, down from 60% during the pandemic. With fewer responses, the agency increasingly relies on modeled estimates to generate its preliminary figures for monthly job growth. For the number of nonfarm payrolls in any given month, the initial estimate and the one released the next month can be seen as placeholders, with the third month’s release marking the final revision. In sum, the initial estimates often diverge sharply from the final numbers, especially during periods of economic uncertainty because they are based on incomplete, lagged data.
The slowdown in the BLS’s survey responses is driven by two key factors: persistent labor shortages and a post-pandemic surge in new businesses. Although the BLS has more staff than in 2020, the sheer volume of data requiring collection has exploded, fueled by record-breaking new business formations. While startups have been a major driver of job growth, collecting timely data from them remains challenging, particularly from newer firms unaccustomed to strict reporting deadlines. This often results in delays and inconsistent data.
Alternative Data Sources
To understand what’s going on in the economy, we look not just at government data, but also private reports. Key indicators like the S&P Global Purchasing Managers’ Index (PMI) and the Institute for Supply Management’s (ISM) Manufacturing Index provide insights into business sentiment. At the same time, consumer optimism surveys, such as those from the University of Michigan and The Conference Board, reveal household expectations. These surveys do more than track the labor market; they also shed light on price trends, future consumption, and investment spending.
That said, sentiment data can provide valuable early warnings of economic trouble, but it is not without flaws. Because they rely on people’s feelings at a specific point in time, responses can be subject to a “time period bias” or political biases unrelated to underlying economic fundamentals. This means that while changes in sentiment can signal trouble, they may also contain significant noise.
Other crucial sources we are paying attention to are the earnings reports of economic bellwethers. These companies, such as FedEx, Walmart, Caterpillar, and most recently Nvidia, have proven to be reliable barometers of the economy. When these firms report strong earnings and provide solid, financially supported feedback on their outlooks, it serves as a powerful indicator. Not only does this offer insight into the broader economy, but it also provides a more reliable assessment of market performance sustainability.
Similarly, financial indicators also have their flaws. Firms are generally reluctant to share very negative information, so their outlooks may be rosier than reality. Additionally, there is a size bias to the data from public firms as it primarily reflects the views of larger companies. Lastly, the data is backward-looking and may not account for unexpected changes in the future.
Conclusion
While the recent negative revisions to payroll data were an unpleasant surprise, we believe they reflect information lags rather than fundamentally “bad” data. We continue to pay close attention to government data, but we also rely heavily on alternative sources to inform our investment decisions. We remain cautiously optimistic about the economy, even with these troubling signs in the data. Our risk tolerance may increase as economic trends improve, but for now, we remain strategic with our investment allocations.
