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Production efficiency and financial stability do not necessarily go hand in hand. With heterogeneity in banks’ abilities to screen borrowers, the market for loans becomes segmented and a self-competition mechanism arises. When heterogeneity increases, the intensive and extensive margins have opposite effects.

This paper develops a travel-based metric to measure Canadians’ access to cash from automated banking machines (ABMs) and financial institution branches. We find that, overall, access to cash remained stable between 2019 and 2022. The total number of ABMs in Canada increased by 3.7% and the total number of branches decreased by 5.2% during that period.

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.

I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors.

Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.

This paper studies the effects of monetary policy shocks on firms’ participation in exporting. We develop a two-country dynamic stochastic general equilibrium model in which heterogeneous firms make forward-looking decisions on whether to participate in the export market and prices are staggered across firms and time.

Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.

Many emerging-market economies (EMEs) have significantly improved their macroeconomic fundamentals and undergone structural reforms since the Asian crisis. These developments have enhanced the composition of capital flows to EMEs through an improved debt structure, a larger share of capital flows as foreign direct investment, and greater access to international debt markets for corporations in EMEs. Structural changes in the global financial landscape have also increased capital flows, bringing economic and financial benefits to EMEs. During the recent financial crisis, however, the opening up of capital accounts and increased financial and trade linkages left many countries vulnerable to external disruptions. Countries with sound fundamentals have weathered the crisis relatively well. Policy-makers in EMEs need to implement policies that support capital flows and ensure that controls imposed to deal with detrimental outflows during periods of stress or rapid inflows are only temporary.

How wrong could policymakers be when using linearized solutions to their macroeconomic models instead of nonlinear global solutions?

We explore what drives transaction fees in the Bitcoin system and consider whether Bitcoin can remain tamper proof in the long run.