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This paper studies the effects of a monetary policy expansion in the United States during times of high financial stress. The analysis is carried out by introducing a smooth transition factor model where the transition between states (“normal” and high financial stress) depends on a financial conditions index.

This article investigates the stability of Okun's law for Canada and the United States using a time varying parameter approach. Time variation is modeled as driftless random walks and is estimated using the median unbiased estimator approach developed by Stock and Watson (1998).

We develop an algorithm and run it on a hybrid quantum annealing solver to find an ordering of payments that reduces the amount of system liquidity necessary without substantially increasing payment delays.

We analyze the dynamic and heterogeneous responses of small-business loan performance to a monetary-policy shock using loan-level data in Canada. We find evidence of monetary policy transmission through the cash-flow channel and the aggregate demand channel as well as some, though limited, impact of collateral to discipline loan repayment.

Cyclical contractions are often referred to as inventory cycles, in part because movements in inventories can amplify cyclical fluctuations in output. An unanticipated slowing in demand generally leads to an unintended buildup of inventories: only with a lag do firms adjust production and their actual holding of inventories relative to the desired level.

Recent events in financial markets have underlined the importance of analyzing the link between the financial health of banks and real economic activity. This paper contributes to this analysis by constructing a dynamic general equilibrium model in which the balance sheet of banks affects the propagation of shocks.

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.

We present a two-stage model of mobile phone and mobile payment usage that controls for selectivity. This reveals unobserved factors that work against having a mobile phone and toward mobile paying. Therefore, people who are unable to acquire or choose not to own a mobile device might have unmet payment needs.

I present a structural econometric analysis supporting the hypothesis that money is still relevant for shaping inflation and output dynamics in the United States. In particular, I find that real money balance effects are quantitatively important, although smaller than they used to be in the early postwar period.

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.