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1831 Results

Grasping De(centralized) Fi(nance) Through the Lens of Economic Theory

Staff Working Paper 2022-43 Jonathan Chiu, Charles M. Kahn, Thorsten Koeppl
We analyze the value proposition and limitations of decentralized finance (DeFi). Based on a distributed ledger and smart contracts, DeFi can guarantee the execution of financial contracts, potentially lowering the costs of intermediation and improving financial inclusion.

Examining recent revisions to CPI-common

Staff Analytical Note 2022-15 Elyse Sullivan
Unusually large revisions to CPI-common in recent months stem from increased common movements across consumer price index components amid broad inflationary pressures. With recent revisions, CPI-common is more closely aligned with the Bank of Canada’s other two preferred measures of core inflation. However, caution is necessary when interpreting real-time estimates of CPI-common in the current environment.

Archetypes for a retail CBDC

Staff Analytical Note 2022-14 Sriram Darbha
A variety of technology designs could support retail central bank digital currency (CBDC) systems. We develop five archetypes of CBDC systems, outline their characteristics and discuss their trade-offs. This work serves as a framework to analyze and compare different designs, independent of vendor, platform and implementation.

Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model

Technical Report No. 122 Gabriel Bruneau, Thibaut Duprey, Ruben Hipp
We present a new corporate default model, one of the building blocks of the Bank of Canada’s bank stress-testing infrastructure. The model is used to forecast corporate loan losses of the Canadian banking sector under stress.

Harnessing the benefit of state-contingent forward guidance

Staff Analytical Note 2022-13 Vivian Chu, Yang Zhang
A low level of the neutral rate of interest increases the likelihood that a central bank’s policy rate will reach its effective lower bound (ELB) in future economic downturns. In a low neutral rate environment, using an extended monetary policy toolkit including forward guidance helps address the ELB challenge. Using the Bank’s Terms-of-Trade Economic Model, we assess the benefits and limitations of a state-contingent forward guidance implemented within a flexible inflation targeting framework.

Behavioral Learning Equilibria in New Keynesian Models

Staff Working Paper 2022-42 Cars Hommes, Kostas Mavromatis, Tolga Özden, Mei Zhu
We introduce behavioral learning equilibria (BLE) into DSGE models with boundedly rational agents using simple but optimal first order autoregressive forecasting rules. The Smets-Wouters DSGE model with BLE is estimated and fits well with inflation survey expectations. As a policy application, we show that learning requires a lower degree of interest rate smoothing.

How does the Bank of Canada’s balance sheet impact the banking system?

Staff Analytical Note 2022-12 Daniel Bolduc, Brad Howell, Grahame Johnson
We examine how changes in the Bank of Canada’s balance sheet impact the banking system. Quantitative easing contributed to an increase in the size of the banking system’s balance sheet and an improvement in bank liquidity coverage ratios. Quantitative tightening is expected to partially reverse these impacts. The banking system will have to adjust its liquidity management strategy in response.

Looking Through Supply Shocks versus Controlling Inflation Expectations: Understanding the Central Bank Dilemma

Staff Working Paper 2022-41 Paul Beaudry, Thomas J. Carter, Amartya Lahiri
Why might central banks want to look through supply-driven inflation sometimes and pivot away at other times? When does a change in monetary policy stance help anchor expectations? In this paper we present a simple environment that helps clarify these issues by offering an optimal policy perspective on recent central bank behaviour.

Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models

Staff Discussion Paper 2022-19 James Younker
This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models.
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