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Do technological improvements mitigate the potential damages from extreme weather events? We show that hurricanes lower offshore oil production in the Gulf of Mexico and that stronger storms have larger impacts. Regulations enacted in 1980 that required improved offshore construction standards only modestly mitigated the production losses.

Why do BigTech platforms introduce payment services? We explore this using a model in which a monopoly platform faces a trade-off between the costs associated with privacy concerns and the revenue from data services. We then analyze the feedback effects between data and payments.

This paper examines household-level data from the Canadian Survey of Consumer Expectations (CSCE) to understand households’ expectations about price and wage inflation, how those expectations link to views about labour market conditions and the subsequent impact on households’ outlook for real spending growth.

How should central banks design monetary policy in stable times and during recessions? We run a horse race between five monetary policy frameworks in an experimental laboratory to assess how well the different approaches can manage the public’s expectations and stabilize the economy.

We develop a principal-agent model of cyber-attacking with fee-paying clients who delegate security decisions to financial platforms. We derive testable implications about clients’ vulnerability to cyber attacks and about the fees charged.

We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models.

This paper examines the cross-border spillovers from major economies’ quantitative easing (QE) policies to their trading partners. We concentrate on spillovers from the US to Canada during the zero lower bound period when QE policies were actively used.

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.

This paper evaluates the effectiveness of macroprudential policies when regulations are uneven across mortgage lender types. We look at credit tightening that results from macroprudential regulations and examine how much of it is counteracted by credit shifting to unregulated lenders. We also study the impact of monetary policy tightening when some lenders are unregulated.

We study economies where firms acquire capital in primary markets then retrade it in secondary markets after information on idiosyncratic productivity arrives. Our secondary markets incorporate bilateral trade with search, bargaining and liquidity frictions.