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Although the concept of monetary policy lag has historical roots deep in the monetary economics literature, relatively little attention has been paid to the idea. In this paper, we build on Svensson's (1997) inflation targeting framework by explicitly taking into account the lagged effect of monetary policy and characterize the optimal monetary policy reaction function both in the absence and in the presence of the zero lower bound on the nominal interest rate.

One of the central lessons learned from the Great Depression was that adjusting government spending each year to balance the budget increases the volatility of output.

The increasing importance of risk management in payment systems has led to the development of an array of sophisticated tools designed to mitigate tail risk in these systems. In this paper, we use extreme value theory methods to quantify the level of tail risk in the Canadian retail payment system (ACSS) for the period from 2002 to 2015.

The premium on “on-the-run” Treasuries is an anomaly. I explain it using a model in which primary dealers hold inventories of Treasuries. I use the model to analyze the effects of granting access to central bank facilities.

In this paper, we build a dynamic stochastic general-equilibrium model with housing and household debt, and compare the effectiveness of monetary policy, housing-related fiscal policy, and macroprudential regulations in reducing household indebtedness.

The Canadian Financial Monitor (CFM) survey uses non-probability sampling for data collection, so selection bias is likely. We outline methods for obtaining survey weights and discuss the conditions necessary for these weights to eliminate selection bias. We obtain calibration weights for the 2018 and 2019 online CFM samples.

We model the behavior of dealers in Over-the-Counter (OTC) derivatives markets where a small number of dealers trade with a continuum of heterogeneous clients (hedgers). Imperfect competition and (endogenous) default induce a familiar trade-off between competition and risk.

This article reviews selected papers that use machine learning for economics research and policy analysis. Our review highlights when machine learning is used in economics, the commonly preferred models and how those models are used.

This paper studies the efficiency of financial intermediation through securitization in a model with heterogeneous investment projects and asymmetric information about the quality of securitized assets. I show that when retaining part of the risk, the issuer of securitized assets may credibly signal its quality.

We study consumer cash inventory behavior by developing a dynamic model of forward-looking consumers and estimating structural parameters of the model using detailed consumer survey data. Consumers facing holding and withdrawal costs solve a discrete-time continuous-control dynamic programming problem to optimally use cash at the point of sale.