Search

The intertemporal approach to the current account suggests modeling movements in the current account in a forward-looking, dynamic framework. In this framework, the current account reflects consumption smoothing of agents that lend and borrow from the rest of the world in the face of transitory shocks to income.

In this paper, we study the impact of Canada’s adoption of protectionist trade policy in 1879 on Canadian welfare. Under the National Policy the Canadian average weighted tariff increased from 14% to 21%. The conventional view is that this was a distortionary policy that negatively affected Canadian welfare.

Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

Diffusion functions in term-structure models are measures of uncertainty about future price movements and are directly related to the risk associated with holding financial securities. Correct specification of diffusion functions is crucial in pricing options and other derivative securities. In contrast to the standard parametric two-factor models, we propose a non-parametric two-factor term-structure model that […]

We build upon new developments in the international trade literature to construct a quantitative Ricardian framework similar to Caliendo and Parro (2015) to isolate and estimate the long-run economic impacts of tariff changes.

The present paper shows that, everything else equal, some transactions to transfer portfolio credit risk to third-party investors increase the insolvency risk of banks. This is particularly likely if a bank sells the senior tranche and retains a sufficiently large first-loss position.

We develop a production-network model to capture how decentralized finance (DeFi) has evolved across different sectors of financial services. The model allows us to measure the value added by different DeFi sectors and to study how the connections across the sectors influence token prices.

We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does.

Multi-stage production is widely recognized as an important feature of the modern global economy. This feature has been incorporated into many state-of-the-art quantitative trade models, and has been shown to deliver significant additional gains from international trade.

We develop a principal-agent model of cyber-attacking with fee-paying clients who delegate security decisions to financial platforms. We derive testable implications about clients’ vulnerability to cyber attacks and about the fees charged.