风暴中的美国劳工统计局

Core Viewpoint - The July CPI data in the U.S. shows a year-on-year increase of 2.7%, lower than the expected 2.8%, while the core CPI rose by 3.1%, exceeding the forecast of 3% [1][2]. Group 1: Data Collection and Credibility Issues - The recent CPI data is considered a critical indicator of the impact of new tariff policies on consumer spending and may directly influence the Federal Reserve's interest rate decisions in September [3]. - The Bureau of Labor Statistics (BLS) has reduced its sampling range for CPI data collection, halting price collection in certain cities and temporarily suspending about 15% of price samples across 72 other survey areas [3][6]. - The BLS claims that the overall inflation rate statistics should remain largely unchanged, but the reduced sampling may increase monthly price volatility in the affected areas [7][9]. Group 2: Internal Challenges at BLS - The BLS faces significant internal challenges due to personnel shortages and budget cuts, with approximately 15% of its workforce lost since the beginning of the year [9][10]. - The Trump administration's budget proposal includes an 8% cut to the BLS budget for the fiscal year 2026, exacerbating the agency's difficulties [11]. - The disbandment of advisory committees has further complicated BLS operations, leading to concerns about the reliability of government economic data [11][12]. Group 3: Data Generation Process - The CPI data generation involves collecting around 100,000 price samples monthly from various cities, which has been compromised due to reduced sampling and increased reliance on estimation methods [14][18]. - The BLS has had to rely more on "different unit" imputation methods, which are less accurate, to fill in gaps caused by missing data [15][18]. Group 4: Implications of Data Credibility - The credibility of the CPI data is under scrutiny, with concerns that the reduced sampling and increased reliance on estimations may lead to inaccuracies, particularly in regional and item-specific indices [19][21]. - Experts warn that the erosion of data quality could mislead the Federal Reserve in its monetary policy decisions, affecting interest rate adjustments and welfare programs tied to inflation indices [27][28]. - The potential decline in data reliability may undermine public trust in economic policies and the effectiveness of macroeconomic management [30][31].