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420 Results

The Impact of Unemployment Insurance and Unsecured Credit on Business Cycles

Staff working paper 2023-22 Michael Irwin
This paper studies how unsecured consumer credit impacts the extent to which unemployment insurance (UI) policies smooth aggregate consumption fluctuations over the business cycle. Using a general equilibrium real business cycle model, I find that unsecured credit amplifies the extent to which UI smooths cyclical consumption fluctuations.

Third-Country Effects of U.S. Immigration Policy

Staff working paper 2023-60 Agostina Brinatti, Xing Guo
We study how the tightening of US immigration policy affects the Canadian economy and American workers. After the reduction in H-1B visa admissions in 2017, more immigrants came to Canada, and Canadian firms expanded their employment, sales and exports. The close trade link between the United States and Canada dampens the benefit American workers derive from this policy change.

The Financial Origins of Non-fundamental Risk

Staff working paper 2022-4 Sushant Acharya, Keshav Dogra, Sanjay Singh
We explore the idea that the financial sector can be a source of non-fundamental risk to the rest of the economy. We also consider whether policy can be used to reduce this risk—either by increasing the supply of publicly backed safe assets or by reducing the demand for safe assets.

Monetary Policy Tradeoffs Between Financial Stability and Price Stability

Staff working paper 2016-49 Malik Shukayev, Alexander Ueberfeldt
We analyze the impact of interest rate policy on financial stability in an environment where banks can experience runs on their short-term liabilities, forcing them to sell assets at fire-sale prices.

Inflation vs Inclusion: Stabilization Policy in the Wake of the Pandemic

Staff working paper 2026-13 Felipe Alves, Giovanni L. Violante
As the economy emerges from a crisis, macroeconomic policy confronts a dilemma: a protracted stimulus can foster a more inclusive labor market recovery, yet risks igniting inflation that ultimately undermines workers’ welfare through real income erosion. This tension amplifies in the presence of the ZLB and aggregate capacity constraints. We embed this insight into a quantitative model of the US economy.

Bank Market Power and Central Bank Digital Currency: Theory and Quantitative Assessment

We show that issuing a deposit-like central bank digital currency (CBDC) with a proper interest rate would encourage banks to pay higher interest to keep their customers. Banks would then attract more deposits and offer more loans. Hence, a CBDC would not necessarily crowd out private banking.

Measuring Systemic Risk Across Financial Market Infrastructures

Staff working paper 2016-10 Fuchun Li, Héctor Pérez Saiz
We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant.

Foreign Exchange Fixings and Returns Around the Clock

Staff working paper 2021-48 Ingomar Krohn, Philippe Mueller, Paul Whelan
We document a new empirical finding in the foreign exchange market: currency returns show systematic reversals around the benchmark fixings. Specifically, the US dollar, on average, appreciates in the hours before fixes and depreciates after fixes.

Central Bank Digital Currency and Banking: Macroeconomic Benefits of a Cash-Like Design

Staff working paper 2021-63 Jonathan Chiu, Mohammad Davoodalhosseini
Should a CBDC be more like cash or bank deposits? An interest-bearing, cash-like CBDC not only makes payments more efficient but also increases total demand. This has positive effects on other transactions, inducing more deposit taking and lending and, thus, bank intermediation.

Differentiable, Filter Free Bayesian Estimation of DSGE Models Using Mixture Density Networks

Staff working paper 2025-3 Chris Naubert
I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values.
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