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2166 Results

An Optimal Macroprudential Policy Mix for Segmented Credit Markets

Staff working paper 2021-31 Jelena Zivanovic
How can macroprudential policy and monetary policy stabilize segmented credit markets? Is there a trade-off between financial stability and price stability? I use a theoretical model to evaluate the performance of alternative policies and find the optimal mix of macroprudential and monetary policy in response to aggregate shocks.

The Political Impact of Immigration: Evidence from the United States

Staff working paper 2018-19 Anna Maria Mayda, Giovanni Peri, Walter Steingress
In this paper we study the impact of immigration to the United States on the vote for the Republican Party by analyzing county-level data on election outcomes between 1990 and 2010. Our main contribution is to separate the effect of high-skilled and low-skilled immigrants, by exploiting the different geography and timing of the inflows of these two groups of immigrants.

Estimating Discrete Choice Demand Models with Sparse Market-Product Shocks

Staff working paper 2025-10 Zhentong Lu, Kenichi Shimizu
We propose a novel approach to estimating consumer demand for differentiated products. We eliminate the need for instrumental variables by assuming demand shocks are sparse. Our empirical applications reveal strong evidence of sparsity in real-world datasets.

Assessing tariff pass-through to consumer prices in Canada: Lessons from 2018

Staff analytical note 2025-18 Alexander Lam
US trade protectionism is making the economic outlook increasingly uncertain. To assess how consumer prices may respond to tariffs, we examine a tariff episode from 2018 using detailed microdata and the synthetic control method.

From Stress to Strategy: How Banks Balance the Scales

Staff working paper 2026-26 Ruben Hipp, Javier Ojea Ferreiro
This paper develops a stress-testing framework in which banks strategically adjust their balance sheets in response to regulatory constraints and market conditions. Applied to Canada’s largest banks, it quantifies the effects of macroprudential policies on lending and identifies systemic vulnerabilities through reverse stress testing.

Managing GDP Tail Risk

Staff working paper 2020-3 Thibaut Duprey, Alexander Ueberfeldt
Models for macroeconomic forecasts do not usually take into account the risk of a crisis—that is, a sudden large decline in gross domestic product (GDP). However, policy-makers worry about such GDP tail risk because of its large social and economic costs.

Labor Market Shocks and Monetary Policy

Staff working paper 2023-52 Serdar Birinci, Fatih Karahan, Yusuf Mercan, Kurt See
We develop a heterogeneous-agent New Keynesian model featuring a frictional labor market with on-the-job search to quantitatively study the positive and normative implications of employer-to-employer transitions for inflation.

Trading on Long-term Information

Staff working paper 2020-20 Corey Garriott, Ryan Riordan
Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading.

How big is cash-futures basis trading in Canada’s government bond market?

Staff analytical note 2024-16 Andreas Uthemann, Rishi Vala
Cash-futures basis trading has grown alongside the Government of Canada bond futures market. We examine this growth over time in relation to Government of Canada bond and repurchase agreement markets and provide details on the type of market participants that engage in this type of trading activity.

Anonymous Credentials: Secret-Free and Quantum-Safe

Staff working paper 2023-50 Raza Ali Kazmi, Cyrus Minwalla
An anonymous credential mechanism is a set of protocols that allows users to obtain credentials from an organization and demonstrate ownership of these credentials without compromising users’ privacy. In this work, we construct the first secret-free and quantum-safe credential mechanism.
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