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Softer US jobs data could prompt Fed to shift to earlier rate cuts next year - CIBC
Key Takeaways (30s Read)
Softness in the US labor market may prompt earlier rate cuts by the Fed.
CIBC notes that the latest employment figures reflect a further softening in the US labor market. While non-farm payrolls rose by 64k in November, this followed a sharp decline of 105k in October, effectively erasing previous gains seen in September. Additionally, the three-month average job growth has cooled to 22k, and the unemployment rate edged up to 4.6%. This signals ongoing softening in the labor market.
Conversely, the October retail sales control group showed a 0.8% increase, indicating that consumer demand remains relatively robust. This mixed picture could lead Fed policymakers, who were at odds at the last meeting, to reassess their position, increasing the chances of earlier rate cuts in 2026.
The new voting members on the FOMC will include Beth Hammack (Cleveland Fed), Anna Paulson (Philadelphia Fed), Lorie Logan (Dallas Fed), and Neel Kashkari (Minneapolis Fed), while dissidents Goolsbee and Schmid will rotate out. Hammack and Logan may be similarly inclined, potentially more hawkish. However, the cooling labor market could undermine their resolve, and CIBC suggests that the case for maintaining rates may weaken, raising the likelihood for earlier easing by the Fed in 2026.
AI Analyst
AI Opinion
"The latest US labor market data indicates more fragility in economic stability than previously thought. The slowdown in employment growth amid robust consumer demand presents a confusing narrative that could significantly impact future monetary policy decisions. Notably, the shift in voting members may alter the hawkish stance observed recently, and the cooling labor market could bolster the case for earlier rate cuts. However, changes in the members with conflicting views do not necessarily guarantee abrupt policy shifts. Investors should monitor the Fed's actions closely and formulate strategies based on labor market and consumer behavior dynamics."
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