Odd Lots

Lots More on the Worsening State of the US Labor Market

November 7, 2025

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  • The absence of official Non-Farm Payrolls data due to a government shutdown is forcing reliance on alternative data sources like ADP and Challenger, which are currently presenting conflicting signals about the labor market's health. 
  • Guest Conor Sen argues that the labor market situation is serious and potentially underappreciated, suggesting that corporate America may soon stop hoarding labor, which could lead to a snowball effect of job losses as companies focus on cost-cutting. 
  • The perceived impact of AI on the labor market is currently more about corporate optics and budget allocation (cutting labor to fund AI investment) than direct technological displacement of workers. 

Segments

Podcast Anniversary and Data Absence
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(00:01:56)
  • Key Takeaway: The hosts celebrated the 10-year anniversary of Odd Lots while lamenting the lack of official jobs data due to a government shutdown.
  • Summary: The hosts marked the 10-year anniversary of the Odd Lots podcast, noting that the government shutdown prevented the release of the expected Non-Farm Payrolls report. They view the absence of official data as a significant hindrance to understanding the current confusing economic spot. The episode itself, titled “Lots More on the Worsening State of the US Labor Market,” serves as a substitute for the missing jobs report.
Critique of ADP Data
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(00:04:02)
  • Key Takeaway: ADP payroll data is often criticized because its estimates are frequently revised to align with the official BLS data months later, making its real-time predictive value questionable.
  • Summary: The speakers expressed a preference for the official jobs data over alternatives like ADP, noting that caring about ADP estimates is frustrating. The primary flaw cited is that ADP revisions often align with the final BLS figures long after the initial release, undermining its immediate utility. This highlights the general confusion between economic models (the map) and the actual economy (the territory).
Conflicting Labor Market Signals
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(00:05:30)
  • Key Takeaway: Conflicting alternative data points, such as record October layoff announcements versus steady initial claims, create uncertainty regarding the labor market’s true trajectory.
  • Summary: Challenger data indicated the worst month for layoffs in over 20 years, yet initial claims remained steady, confusing the overall picture. Cleveland Fed’s Hammock expressed greater concern over inflation than employment risks to the dual mandate, a view the guest, Conor Sen, opposes, seeing the labor market as a serious, underappreciated risk.
Labor Hoarding and Cyclical Tension
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(00:06:03)
  • Key Takeaway: The long period of low fires may end as companies realize they no longer need to hoard labor, potentially leading to a snowball effect of cost-cutting layoffs.
  • Summary: The low-fires labor market, sustained for 18 to 24 months, might be ending because companies no longer need to hoard workers given the availability of unemployed individuals for hiring. This realization could prompt widespread cost-cutting, causing the labor market to deteriorate over the next three to six months. This situation creates tension between the ‘contracted market’ (high 2022 wages) and the ‘spot market’ (lower current hiring rates).
Immigration’s Role in Labor Supply
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(00:10:52)
  • Key Takeaway: Reduced immigration lowers the break-even jobs growth rate required to maintain current conditions, and this population slowdown impacts demand across sectors like multifamily housing.
  • Summary: The break-even jobs growth rate is considered much lower due to reduced immigration, though supply can generate its own demand, as seen in housing. Reduced population growth translates to less need for job growth, which subsequently reduces the demand for signing new apartment leases, affecting sectors beyond direct employment.
AI’s Indirect Impact on Layoffs
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(00:12:05)
  • Key Takeaway: AI is contributing to labor cuts indirectly by forcing companies to reallocate budgets toward necessary AI investment and by creating a negative ‘vibe’ against hiring.
  • Summary: Companies facing cost constraints feel compelled to invest in AI, necessitating cuts elsewhere, with labor being an easy target. Furthermore, there is a perception that hiring aggressively signals a company does not understand or embrace the current AI trend. This dynamic is visible in the stock performance of fast-casual chains like Sweetgreen and Kava, suggesting consumer weakness is creeping up the income and age ladders.
Fed Policy and AI Economy
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(00:18:37)
  • Key Takeaway: The Fed is likely to remain cautious until forced by deteriorating data, as traditional monetary policy transmission mechanisms, like housing fixes from rate cuts, have not worked as expected.
  • Summary: The Fed is expected to wait for clear signals, anchored by the historically low unemployment rate, despite housing worsening despite rate cuts. The emergence of an AI-driven economy complicates monetary policy, as the Fed is not equipped to regulate the boom driven by entities like OpenAI or NVIDIA. This situation suggests the Fed may only play a role in the ‘cleanup’ phase rather than preventing the boom’s excesses.
Political Ramifications of AI
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(00:20:47)
  • Key Takeaway: The AI industry is likely to become politically ‘friendless’ by 2028, facing antagonism from both political sides due to job loss fears and electricity demands.
  • Summary: The politics surrounding AI are expected to become significant by 2028, with the industry potentially lacking strong political allies. While Democrats have long been critical of Big Tech, the Republican coalition, which relies on working-class voters, may find its interests misaligned with tech/VC interests regarding AI’s impact on jobs. This suggests an emerging ‘anti-AI’ lane in future political campaigning.