Mortgage Rate Intelligence & Market Updates

Banks must extract useful signals of a potential borrower’s quality from a large set of possibly informative characteristics when making lending decisions. A model that speaks to how banks specialize in lending to an industry in order to better extract signals from data can potentially be applied to a number of real-world scenarios. In this post, we apply lessons from such a model to a topic of timely relevance in economics: job market recommendation letters. Institutions looking to hire new economists must evaluate PhD applicants based on limited and often noisy signals of future performance, including letters of recommendation from these applicants’ advisors or co-authors. Using insights from our model, we argue that the value of these letters depends on who reads them.

Why does the banking industry remain prone to large and costly disruptions despite being so heavily regulated? Is there a need for more regulation, less regulation, or simply different regulation? Our recent Staff Report combines insights from academic research in economics, finance, and accounting to provide a deeper understanding of the challenges involved in designing and implementing bank regulation, as well as opportunities for future exploration. This post focuses on the regulation of bank capital, but the ideas are applicable more broadly.

This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since September 2025. To summarize, growth in 2025 is expected to be stronger than in September due to a lower projected path of the policy rate, as well as higher productivity. Inflation projections are higher in 2025 because of cost-push shocks, which capture the effects of tariffs. The model’s predictions for the short-run real natural rate of interest (or r*) in 2025 have decreased relative to September.

Following the recent passage of legislation in the U.S., payment stablecoins seem to be on the brink of wider-scale adoption and explosive growth in market capitalization. In this post, we contend that the driving factor is not their proximity to digital cash instruments, but rather how they are transferred—via global, open-access, peer-to-peer systems, or “permissionless blockchains,” for short.

There has been a lot of interest in firms’ pricing decisions in the past few years—both during the inflation surge of 2021-23 and in the more recent rounds of tariff increases. In this post, we let firms speak for themselves about what factors they consider when adjusting prices in response to various shocks. The analysis is based on an ongoing research project, joint with the Atlanta and Cleveland Federal Reserve Banks, on how businesses set prices and the extent of passthrough of cost increases. In particular, we leverage the qualitative portion of the study based on open-ended interviews with senior decision-makers on how they approach pricing decisions in their firms. Rather than a uniform approach, a very nuanced picture emerges of businesses trying to balance competing objectives while keeping an eye on demand conditions for their products as well as on their direct competitors’ behavior in the market.

A 2012 Liberty Street Economics post noted that U.S. monetary policy exhibits a surprising degree of seasonal behavior: over the 1987-2008 period, the Federal Reserve was much more likely to lower interest rates (or abstain from raising rates) in the first month of each quarter than in the two subsequent months. Thirteen years later, we revisit that analysis to investigate whether the seasonal pattern in monetary policy still holds today, in the wake of a rate hiking cycle, a pandemic, a surge in inflation, and a second round of rate hikes. We find that the pattern has indeed continued; however, unlike in the earlier sample period, it can be completely explained by the timing of the FOMC calendar.

In a previous post, we documented how, over the past five decades, the typical U.S. bank has evolved from an entity mainly focused on deposit taking and loan making to a more diversified conglomerate also incorporating a variety of nonbank activities. In this post, we show that an important driver of the evolution of this new organizational form is the desire of banks to efficiently manage liquidity needs.

 
In light of the rapid growth of nonbank financial institutions (NBFIs), many have argued that bank-led financial intermediation is on the decline, based on the traditional notion that banks operate to take in deposits and make loans. However, we argue that deposit-taking and loan-making have not accurately characterized U.S. banking operations in recent decades. Instead, as we propose in this post, absent regulatory restrictions, banks naturally expand their boundaries to include NBFI subsidiaries. A significant component of the growth of NBFIs has in fact taken place inside the boundaries of banking firms.  

In 2025, the Federal Reserve has cut interest rates, trade policy has shifted abruptly, and economic policy uncertainty has increased. How have these developments affected the functioning of the key U.S. Treasury securities market? In this post, we return to some familiar metrics to assess the recent behavior of Treasury market liquidity. We find that liquidity briefly worsened around the April 2025 tariff announcements but that its relation to Treasury volatility has been similar to what it was in the past.