Team,
I have reviewed the latest research cycle from the Federal Reserve districts. While some entries were incomplete, there are several high-signal papers that impact our current valuation models and risk assessments. Here are the most analytically significant takeaways:
1. [NY] Bank Failures: The Roles of Solvency and Liquidity
This research disentangles whether systemic failures are driven by fundamental insolvency or liquidity runs. For our portfolio, this is critical for assessing the "contagion risk" in regional banking; if failures are liquidity-driven, Fed discount window efficacy is the key metric; if solvency-driven, we need to brace for deeper haircuts.
2. [NY] The R*–Labor Share Nexus
The paper links the decline in the natural rate of interest (R) to the shrinking labor share of national income. This suggests that long-term neutral rates are structurally tied to income distribution, meaning we cannot view R in a vacuum—shifts in labor bargaining power will directly influence the long-term floor for Treasury yields.
3. [NY] Use of Gen AI in the Workplace and the Value of Access to Training
This study quantifies the productivity gap created by disparate access to AI training. From a macro perspective, this indicates that AI-driven productivity gains may be unevenly distributed, potentially creating a "K-shaped" corporate earnings recovery based on how aggressively firms upskill their workforce.
4. [RIC] Reserve Demand Estimation: A Proposal
This technical proposal aims to refine how the Fed estimates the demand for reserves. While granular, this matters for our liquidity forecasting; a change in how the Fed views reserve demand could signal a shift in the pace of Quantitative Tightening (QT) or the timing of a pivot to a new floor system.
5. [STL] An Empirical Analysis of the Cost of Borrowing
This analysis provides fresh data on the transmission of monetary policy to the end-borrower. It is essential for our forecasting of consumer spending and CAPEX, as it reveals whether the "higher for longer" regime is hitting the real economy as intensely as the headline Fed Funds rate suggests.
Synthesis: The current research suggests a shift toward understanding structural "floors"—whether in the form of R*, reserve demand, or AI productivity. We should move away from transitory models and begin pricing in these long-term structural shifts in labor and liquidity.
The paper examines the primary drivers of bank failures, arguing that insolvency is typically the root cause rather than liquidity runs. It suggests that while bank runs accelerate failure, they are often symptoms of underlying insolvency.
Do banks fail because of runs or because they become insolvent? Answering this question is central to understanding financial crises and designing effective financial stability policies. Long-run historical evidence reveals that the root cause of bank failures is usually insolvency. The importance of bank runs is somewhat overstated. Runs matter, but in most cases they trigger or accelerate failure at already weak banks, rather than cause otherwise sound banks to fail.
The paper proposes a model to analyze the simultaneous decline of the natural rate of interest (R*) and the labor share of income. It argues that these two macroeconomic trends are fundamentally linked rather than isolated phenomena.
Over the past quarter century, the U.S. economy has experienced significant declines in both the labor share of income and the natural rate of interest, referred to as R*. Existing research has largely analyzed these two developments in isolation. In this post, we provide a simple model that captures the joint evolution of the labor share and R*, which we call the R*–labor share nexus. Our key finding is that structural changes affecting R* also influence the evolution of the labor share, and thereby wages and prices. This highlights a potentially important channel, absent from many macroecono
This study examines the integration of generative AI in the workplace, focusing on tool accessibility and productivity gains. It highlights the significant value workers place on specialized training to utilize these technologies effectively.
The rapid spread of generative AI (AI) tools is reshaping the workplace at a remarkable rate. Yet relatively little is known about whether workers have access to these tools, how the tools affect workers’ daily productivity, and how much workers value the training needed to use the tools effectively. In this post, we shed light on these issues by drawing on supplemental questions in the November 2025 Survey of Consumer Expectations (SCE), fielded to a representative sample of the U.S. population. We find that adoption of AI tools at work is heterogeneous, that a sizable share of workers see AI
The author presents a new methodology for estimating reserve demand to enhance the precision of monetary policy implementation. The proposal aims to resolve practical difficulties inherent in current estimation techniques.
Reserve-demand estimation is central to monetary policy implementation but tricky in practice. This discusses a proposal that could improve it.
The analysis evaluates the effectiveness of export promotion strategies in reducing trade deficits. It specifically highlights the historical role of the Export-Import Bank in shaping US trade policy.
A post looks at the role of the Export-Import Bank, which in years past has played an effective role in US trade policy.
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The paper provides an empirical investigation into the determinants and trends of borrowing costs. It analyzes the factors influencing the pricing of credit across different market segments.
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