MEMORANDUM
TO: Investment Committee
FROM: Senior Economist
DATE: May 15, 2026
RE: Federal Reserve District Research Briefing
I have reviewed the latest research cycle from the Fed districts. While several entries were null, there is a clear thematic concentration on the structural integration of AI and the fragility of the consumer balance sheet.
1. [NY] Do Job Postings Show Early Labor-Market Effects of AI?
This research seeks empirical evidence of AI-driven shifts in labor demand via real-time job posting data. For our models, this is critical for determining if AI is currently acting as a labor-augmenting force or a labor-displacing one, which directly impacts our long-term unemployment and wage-growth forecasts.
2. [RIC] Productivity Growth and Monetary Policy in the 1990s
By revisiting the 1990s productivity boom, the Richmond Fed is drawing a parallel to the current AI trajectory to guide FOMC thinking. This suggests the Fed is considering whether a productivity surge could allow for higher nominal growth without triggering inflation, potentially raising the "neutral rate" (r*) and the long-term ceiling for equity valuations.
3. [STL] Mind the Gap: AI Adoption in Europe and the US
This analysis highlights the divergence in AI implementation speeds between the US and EU. A widening productivity gap would likely strengthen the USD and create a structural divergence in GDP growth rates, favoring US-based tech equities over European counterparts.
4. [NY] Federal Student Loan Defaults Return After Pandemic Pause
The return of student loan defaults amidst a slight rise in total household debt ($18.8 trillion) signals a weakening of the consumer's financial cushion. This increases the risk of a "consumption cliff" if labor market conditions soften, limiting the Fed's room to maintain restrictive rates.
5. [STL] Firm-Worker Matches: Experience or Inspection Goods?
This theoretical look at how firms value worker experience versus "inspection" (testing/vetting) is highly relevant in an AI-disrupted market. If the "value" of traditional experience is declining relative to new technical competencies, we should expect higher frictional unemployment and increased labor churn.
Synthesis:
The Fed is currently preoccupied with whether AI will trigger a 1990s-style productivity miracle that offsets inflationary pressures and boosts growth. However, this optimism is balanced against emerging cracks in household credit, suggesting a precarious transition period for the US consumer.
The paper investigates whether generative AI tools are influencing labor demand by analyzing U.S. job postings. It utilizes occupational AI exposure measures to identify early shifts in hiring patterns.
As generative AI tools become more widely used, a key issue is the technology’s impact on labor demand. Where might we find evidence of that impact? In this post, we examine whether early evidence of AI’s effect on the labor market appears in firms’ job postings. We combine an occupational measure of AI exposure with detailed U.S. job-posting data from Lightcast, which aggregates listings from company career pages, national and local job boards, and job-listing aggregators. Using this data, we test whether postings for AI-exposed occupations declined disproportionately since the release of Cha
Household debt increased to $18.8 trillion in 2026:Q1, driven by rises in mortgage, HELOC, and auto balances. The data highlights a return of student loan defaults following the expiration of pandemic-era pauses.
During 2026:Q1, household debt balances increased slightly, by $18 billion, to reach $18.8 trillion, according to the latest Quarterly Report on Household Debt and Credit from the New York Fed’s Center for Microeconomic Data. Amid upticks in mortgage, HELOC, and auto balances and a seasonal decline in credit card balances, student loan balances remained unchanged. However, the share of student loan balances past due increased, nearing pre-pandemic levels at just over 10 percent. In this post, we focus on which borrowers entered default on their federal student loans over the past two quarters.
The paper examines the relationship between productivity growth and monetary policy decisions during the 1990s. It specifically analyzes how productivity gains influence FOMC deliberations and draws parallels to the potential impact of artificial intelligence on trend growth.
With the potential of artificial intelligence to raise trend productivity growth, it is illuminating to revisit Al Broaddus' contributions to late 1990s FOMC discussions.
The research examines the nature of firm-worker matching, analyzing whether worker quality is determined by accumulated experience or through a screening process. It explores the implications for labor market efficiency and hiring frictions.
This study compares the rate and depth of AI adoption between European and United States economies. It analyzes the structural and regulatory drivers that create a gap in technological integration.
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