Mortgage Rate Intelligence & Market Updates

Why do some entrepreneurs drive economic growth while others do not? This piece discusses new work that studies entrepreneurs using a comprehensive dataset from Denmark. We study who becomes an entrepreneur, along with their hiring and business decisions, and find that a distinct minority are “transformative.” These individuals, who generate disproportionate productivity gains, tend to have high IQ scores, be well-educated, and hire technical (R&D) workers. The data support the idea of productivity growth being driven by the symbiotic relationship between transformative entrepreneurs and R&D workers. For policymakers, the lesson is that when an economy has more R&D workers and transformative entrepreneurs, they sustain higher long-run productivity growth.

Each year brings a new set of economic challenges: In 2025, major areas of focus included tariffs and trade tensions, as well as the financial pressures facing younger adults. New York Fed economists contributed insightful research on both topics—and readers took notice. In fact, all five of the year’s most-read posts on Liberty Street Economics analyzed aspects of these issues. Read on to see how the restoration of student loan data to credit reports affected borrowers’ credit scores, whether the costs of a college degree are still worth it, how businesses are responding to higher tariffs, and why the U.S. runs a trade deficit.

Call Reports are regulatory filings in which commercial banks report their assets, liabilities, income, and other information. They are one of the most-used data sources in banking and finance. In this post, we describe a new dataset made available on the Federal Reserve Bank of New York’s website that contains time-consistent balance sheets and income statements for commercial banks in the United States from 1959 to 2025.

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.