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Many central banks are considering issuing a central bank digital currency (CBDC). This would introduce a new policy tool—interest on CBDC. We investigate how this new tool would interact with traditional monetary policy tools, such as the interest on central bank reserves.

Cash gives users a high level of privacy when making payments, but the use of cash to make payments is declining. People increasingly use debit cards, credit cards or other methods to pay.

This paper develops a model of an economy where bank credit supports both productive investment and individual consumption smoothing in the face of idiosyncratic income risk. Bank credit is constrained by bank equity capital.

Proportional reduction is a common cartel practice in which cartel members reduce their output proportionately. We develop a method to quantify this reduction relative to a benchmark market equilibrium scenario and relate the reduction to the traditional conduct parameter.

This paper studies the relationship between bank holding company affiliation and the individual and systemic risk of banks. Using the 2005 hurricane season in the US as an exogenous shock to bank balance sheets, we show that banks that are part of a holding parent company are more resilient than independent banks.

We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

Statistical inference--both estimation and testing--for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student’s t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply “winsorization” to improve stability and finite-sample performance. Except for the degrees of-freedom parameter, closed-form expressions are available for all other parameters, extending Ahsan and Dufour (2019, 2021), thus eliminating the need for numerical optimization or initial values. We derive the estimators’ asymptotic distribution and show that, due to their analytical tractability, they support reliable, and even exact, simulation-based inference via Monte Carlo or bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models.

How do outcomes of monetary and fiscal stabilization policies at the zero lower bound change when decision makers have finite planning horizons in the economy? We explore the effects of limited foresight on policy tools and the interaction between monetary and fiscal policy.

How does the supply of nominal government debt affect the macroeconomy? To answer this question, we propose a portfolio-balance model of the yield curve in which inflation is determined through an interest rate rule.

We study optimal monetary policy in an analytically tractable Heterogeneous Agent New Keynesian model. In the model, the central bank has an incentive to reduce consumption inequality in addition to keeping economic activity at its efficient level and inflation stable.