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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.

It is a pleasure to be here in Winnipeg. Today, I intend to elaborate on elements of the Bank of Canada's economic outlook.

Motivated by the observation that survey expectations of stock returns are inconsistent with rational return expectations under real-world probabilities, we investigate whether alternative expectations hypotheses entertained in the literature on asset pricing are consistent with the survey evidence.

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.

Futures markets are a potentially valuable source of information about price expectations. Exploiting this information has proved difficult in practice, because time-varying risk premia often render the futures price a poor measure of the market expectation of the price of the underlying asset.

We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions.

Market power and pass-through of cost and demand shocks are studied in a market with free entry of heterogeneous firms and consumer mixed search. Equilibrium prices and markups are driven by variation in the elasticity of demand across firms. Improved conditions for buyers can either raise or lower market power.

Cash use is declining while contactless and mobile payments are on the rise.

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.

We construct a dataset on Federal Reserve and Bank of Canada non-rate announcement events to provide novel insights into how foreign and domestic monetary policy communications affect the financial markets of open economies. We find that Fed non-rate communications have a stronger impact on long-term interest rates and stock futures, while Bank of Canada communications are relatively more important for short-term interest rates and the exchange rate.