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The authors examine how the use of extreme value theory yields collateral requirements that are robust to extreme fluctuations in the market price of the asset used as collateral.

We study how the distribution of information supply by the news media affects the macroeconomy. We find that media coverage focuses particularly on the largest firms, and that firms’ equity financing and investment increase after media coverage. But these equity and investment responses are largest among small, rarely covered firms. Our quantitative studies highlight that the aggregate effects of media coverage depend crucially on how that coverage is allocated.

Over the past year, Canada’s economy has outperformed the economies of virtually all the other major industrial countries.

The exponential family, relative entropy, and distortion are methods of transforming probability distributions. We establish a link between those methods, focusing on the relation between relative entropy and distortion.

At the time of the November 2000 Monetary Policy Report, although signs of the anticipated slowing of the U.S. economy were becoming apparent, the momentum of the global economy was considered strong.

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.

In our analysis of the US productivity slowdown in the 1970s and 2000s, we find that a significant portion of this deceleration can be attributed to a lack of improvement in allocative efficiency across sectors. Our analysis further identifies increased sector-level volatility as a major contributor to this lack of improvement in allocative efficiency.

In the April Monetary Policy Report, the Bank noted that inflation was well above its 2 per cent target and that short-term inflation expectations had edged up.

The year that just passed posed many challenges for all Canadians. The slowdown in the global economy became more pronounced as the year went on, and this affected households, businesses, and governments alike. The tragedy of 11 September compounded the economic difficulties and issues facing us all. Through this period of rapidly changing circumstances, the Bank met its responsibilities by responding quickly and vigorously to events in order to underpin confidence and support the economy.

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.