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This paper presents a new testing method for the scapegoat model of exchange rates that aims to tighten the link between the theory on scapegoats and its empirical implementation. This new testing method consists of a number of steps.

We use Canadian data to examine how monetary policy affects house prices and the consumer price index for rent through exogenous changes in the mortgage interest rates. It finds that the price and rent impacts operate through various channels and that these impacts vary by region.

We document an increase in deviations from short-term covered interest rate parity (CIP) in the first half of 2015. Since the Swiss National Bank’s (SNB) decision to abandon its minimum exchange rate policy, both the magnitude and volatility of deviations from CIP have increased across several currency pairs. The effect is particularly pronounced for pairs involving the Swiss franc.

Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data.

This paper relaxes the Bayesian Nash equilibrium (BNE) assumption commonly imposed in empirical discrete choice games with incomplete information. Instead of assuming that players have unbiased/correct expectations, my model treats a player’s belief about the behavior of other players as an unrestricted unknown function. I study the joint identification of belief and payoff functions.

We show how participants in Canada’s new high-value payment system save liquidity by exploiting the new gridlock resolution arrangement. The findings have important implications for the design of these systems and shed light on financial institutions’ liquidity preference.

This paper quantifies tail risks in the outlooks for Canadian inflation and real GDP growth by estimating their conditional distributions at a daily frequency. We show that the tail risk probabilities derived from the conditional distributions accurately reflect realized outcomes during the sample period from 2002 to 2022.

We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information.

Models with default options are hard to solve. We propose an extension of the endogenous grid method that solves default risk models more efficiently and accurately.

This paper studies the testable implication of players’ collusive or cooperative behaviour in a binary choice game with complete information. I illustrate the implementation of this test by revisiting the entry game between Walmart and Kmart.