Core Viewpoint - The upcoming annual benchmark revision of non-farm payroll (NFP) data by the U.S. Bureau of Labor Statistics (BLS) is expected to reveal a significant downward adjustment of employment figures, potentially by 550,000 to 800,000 jobs, which could impact market confidence and lead to a 50 basis point rate cut by the Federal Reserve [1] Group 1: Reasons for Data Revision - The primary reasons for the anticipated downward revision include the distortion of the birth-death model, which overestimates job creation from new businesses, and a significant reduction in illegal immigration, leading to an overestimation of the labor force [1][2] - Estimates suggest that these biases may result in an overstatement of actual employment by 40,000 to 70,000 jobs per month, accumulating to 550,000 to 800,000 jobs annually [1][2] Group 2: Employment Data Analysis - Goldman Sachs indicates that the BLS's birth-death model is a major source of employment data distortion, as it relies on estimations rather than actual business registration or tax data, making it prone to systematic overestimation [2] - The Quarterly Census of Employment and Wages (QCEW) and Business Dynamics Statistics (BDM) are considered more reliable benchmarks for employment data, as they are based on actual unemployment insurance records [2][3] Group 3: Employment Trends and Signals - From early 2024, established companies are reportedly adding only 25,000 jobs per month, while the BLS estimates new companies contribute over 100,000 jobs monthly, a discrepancy highlighted by BDM data [3] - To maintain a balanced labor market, a reasonable level of non-farm employment should be around 170,000 jobs per month, with 100,000 from natural growth and 70,000 from model overestimations [3] Group 4: Additional Indicators of Data Issues - Goldman Sachs identifies five additional signals indicating the employment data may be inflated, including a decrease in illegal immigration, seasonal adjustment model inaccuracies, historical patterns of data revisions during economic slowdowns, discrepancies in healthcare employment growth compared to ADP data, and potential overestimations in household surveys regarding population and employment growth [4][5][6][7][8][9]