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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.

We introduce a history of macroprudential policy (MPP) events in Canada since the 1980s. We document the short-run effects of MPP announcements on market-based measures of systemic risk and find that MPPs can influence the market’s perception of large banks’ resilience.

Changes in the term premium can reflect uncertainty about inflation, growth and monetary policy. Understanding the key factors that influence the term premium is important when central banks make decisions about monetary policy. In this paper, we derive the real term premium from the nominal term premium in Canada.

Changes in domestic interest rates affect the value of the Canadian dollar less than changes in the risk premium do. These variations often occur when a broad shift in risk sentiment occurs in global markets. Ultimately, the value of the currency reflects long-term, slow-moving features of the economies.

I study the welfare consequences of regulations on high-cost consumer credit in the United States and find that borrowing limits have distributional impacts on households with self-control issues.

We analyze micro-level data from the Canadian Survey of Consumer Expectations through the lens of a heterogeneous-expectations model to study how inflation expectations form over the business cycle. We provide new insights into how households form expectations, documenting that forecasting behaviours, attention and noise in beliefs vary across socio-demographic groups and correlate with views about monetary policy.

This paper provides an extensive evaluation of the performance of quantile vector autoregression (QVAR) to forecast macroeconomic risk. Generally, QVAR outperforms standard benchmark models. Moreover, QVAR and QVAR augmented with factors perform equally well. Both are adequate for modeling macroeconomic risks.

We find that individuals who require help performing banking tasks or who are reluctant to adopt technology avoid digital payment systems they expect to lack usability. Addressing these issues through standard accessibility practices, live assistance and thoughtful interface design can enhance user interaction and trust.

I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values.

We model non-bank entry into fixed-income markets and state-dependent liquidity. Non-bank financial institutions improve liquidity more during normal times than in stress. Banks may become less reliable to marginal clients, exacerbating the difference in liquidity between normal and stressed times. Central bank lending during stress may limit this harmful division.