If the old axiom “information is power” holds true, then the opposite—that is, the lack of comprehensive, unbiased, accurate information—will ultimately result in weakness. This is the crossroads we face in light of recent reports of underfunded, understaffed, and potentially compromised collection of government economic data.
Over recent months, we have regularly witnessed mostly under-the-radar announcements of the gradual degradation of the U.S. Bureau of Labor Statistics (BLS) economic data collection. Recent changes include the suspension of Consumer Price Index (CPI) data collection in certain U.S. cities, the discontinued calculation and publication of approximately 350 indices of the Producer Price Index (PPI), disbanding of technical advisory committees, and even discussions of changing how gross domestic product is reported in anticipation of a lackluster report of economic growth.
Two primary harms can arise from having less-than-accurate economic data. First, it creates an uneven playing field where those with excessive resources may believe they can acquire superior, proprietary data—data that is unlikely to be genuinely accurate or comprehensive. Second, it creates a "rosy bias," driven by the natural human tendency to interpret data in a more optimistic way than reality warrants. This inherent optimism in data interpretation is detrimental to institutions and the country as a whole, preventing an honest assessment of actual conditions. We saw this play out in the last election, when American voters rejected reports of moderating inflation and low unemployment based on their own lived experiences.
At the Ludwig Institute for Shared Economic Prosperity, we have long advocated for the inclusion of more-responsive and real-world-reflective metrics as yardsticks for measuring economic performance, but this requires more analysis—not less. The reliance on less accurate, incomplete, and less-transparent data will ultimately result in misinformed economic policy.
While those who fail to study history may be doomed to repeat it, those who study and rely on grossly errant economic data may very well doom the economy.
