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317 Results

Fiscal Stimulus and Skill Accumulation over the Life Cycle

Staff working paper 2023-9 Laure Simon
Using micro data from the U.S. Consumer Expenditure Survey and Current Population Survey, I document that government spending shocks affect individuals differently over the life cycle.
November 20, 2018

Choosing the Best Monetary Policy Framework for Canada

Remarks Carolyn A. Wilkins McGill University Max Bell School of Public Policy Montréal, Quebec
Senior Deputy Governor Carolyn A. Wilkins discusses public policy issues around monetary policy frameworks and how those issues have become more complex in the post-global financial crisis world.

Sectoral Uncertainty

Staff working paper 2022-38 Efrem Castelnuovo, Kerem Tuzcuoglu, Luis Uzeda
We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a disaggregated industrial production series for the US economy. We identify unexpected changes in durable goods uncertainty as drivers of downturns, while unexpected hikes in non-durable goods uncertainty are expansionary.

Predictive Density Combination Using a Tree-Based Synthesis Function

This paper studies non-parametric combinations of density forecasts. We introduce a regression tree-based approach that allows combination weights to vary on the features of the densities, time-trends or economic indicators. In two empirical applications, we show the benefits of this approach in terms of improved forecast accuracy and interpretability.

What Fed Funds Futures Tell Us About Monetary Policy Uncertainty

Staff working paper 2016-61 Jean-Sébastien Fontaine
The uncertainty around future changes to the Federal Reserve target rate varies over time. In our results, the main driver of uncertainty is a “path” factor signaling information about future policy actions, which is filtered from federal funds futures data.

A Macroeconomic Model of an Epidemic with Silent Transmission and Endogenous Self-isolation

Staff working paper 2020-50 Antonio Diez de los Rios
We study the interaction between epidemics and economic decisions in a model that has silent transmission of the virus. We find that rational behaviour strongly diminishes the severity of the epidemic but worsens the economic recession. We also find that the detection and isolation of not only symptomatic individuals but also those who are infected and asymptomatic or mildly symptomatic can reduce the severity of the recession caused by the pandemic.

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.

Do Monetary Policy Shocks Affect the Neutral Rate of Interest?

Staff working paper 2026-6 Danilo Leiva-Leon, Rodrigo Sekkel, Luis Uzeda
Can monetary policy influence the neutral real interest rate (r-star)? Using a new statistical model, we show that interest rate hikes tend to lower r-star and long-run growth, but that monetary policy explains only a small share of the long-run decline in r-star.

Unintended Consequences of the Home Affordable Refinance Program

Staff working paper 2024-11 Phoebe Tian, Chen Zheng
We investigate the unintended consequences of the Home Affordable Refinance Program (HARP). Originally designed to help borrowers refinance after the 2008–09 global financial crisis, HARP inadvertently strengthened the market power of incumbent lenders by creating a cost advantage for them. Despite a 2013 policy rectifying this cost advantage, we still find significant welfare losses for borrowers.

Estimating Large-Dimensional Connectedness Tables: The Great Moderation Through the Lens of Sectoral Spillovers

Staff working paper 2021-37 Felix Brunner, Ruben Hipp
Understanding the size of sectoral links is crucial to predicting the impact of a crisis on the whole economy. We show that statistical learning techniques substantially outperform traditional estimation techniques when measuring large networks of these links.
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