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25 Results

Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.

Bootstrapping Mean Squared Errors of Robust Small-Area Estimators: Application to the Method-of-Payments Data

Staff Working Paper 2018-28 Valéry Dongmo Jiongo, Pierre Nguimkeu
This paper proposes a new bootstrap procedure for mean squared errors of robust small-area estimators. We formally prove the asymptotic validity of the proposed bootstrap method and examine its finite sample performance through Monte Carlo simulations.

State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models

Staff Working Paper 2018-14 Luis Uzeda
Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood.

Asymmetric Risks to the Economic Outlook Arising from Financial System Vulnerabilities

Staff Analytical Note 2018-6 Thibaut Duprey
When financial system vulnerabilities are elevated, they can give rise to asymmetric risks to the economic outlook. To illustrate this, I consider the economic outlook presented in the Bank of Canada’s October 2017 Monetary Policy Report in the context of two key financial system vulnerabilities: high levels of household indebtedness and housing market imbalances.

Bootstrap Tests of Mean-Variance Efficiency with Multiple Portfolio Groupings

Staff Working Paper 2014-51 Sermin Gungor, Richard Luger
We propose double bootstrap methods to test the mean-variance efficiency hypothesis when multiple portfolio groupings of the test assets are considered jointly rather than individually.

Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances

Staff Working Paper 2013-16 Sermin Gungor, Richard Luger
We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances.

A Framework to Assess Vulnerabilities Arising from Household Indebtedness Using Microdata

Staff Discussion Paper 2012-3 Ramdane Djoudad
Rising levels of household indebtedness have created concerns about the vulnerabilities of households to adverse economic shocks and the impact on financial stability. To assess these risks, the author presents a formal stress-testing framework that uses microdata to simulate how various economic shocks affect the distribution of the debt-service ratio (DSR) for the household sector.

What Matters in Determining Capital Surcharges for Systemically Important Financial Institutions?

Staff Discussion Paper 2011-9 Céline Gauthier, Toni Gravelle, Xuezhi Liu, Moez Souissi
One way of internalizing the externalities that each individual bank imposes on the rest of the financial system is to impose capital surcharges on them in line with their systemic importance.
Content Type(s): Staff research, Staff discussion papers Topic(s): Financial system regulation and policies JEL Code(s): C, C1, C15, C8, C81, E, E4, E44, G, G0, G01, G2, G21

Understanding Systemic Risk: The Trade-Offs between Capital, Short-Term Funding and Liquid Asset Holdings

Staff Working Paper 2010-29 Céline Gauthier, Zhongfang He, Moez Souissi
We offer a multi-period systemic risk assessment framework with which to assess recent liquidity and capital regulatory requirement proposals in a holistic way.
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