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Risk-management systems in financial institutions have come under increasing scrutiny in light of the current financial crisis, resulting in calls for improvements and an increased role for regulators. Yet such objectives miss the intricacy at the heart of the risk-management process. This article outlines the complexity inherent in any modern risk-management system, which arises because there are shortcuts in the theoretical models that risk managers need to be aware of, as well as the difficulties in sensible calibration of model parameters. The author suggests that prudential regulation of such systems should focus on failures within the financial firm and in the market interactions between firms and reviews possible strategies that can improve the performance of risk management and microprudential regulatory practice.

We analyze the value proposition and limitations of decentralized finance (DeFi). Based on a distributed ledger and smart contracts, DeFi can guarantee the execution of financial contracts, potentially lowering the costs of intermediation and improving financial inclusion.

We study how input-output networks affect the speed of technology adoption. In particular, we model the decision to adopt the programming language Python 3 by software packages. Python 3 provides advanced features but is not backward compatible with Python 2, which implies it comes with adoption costs.

Carbon dioxide emissions have been commonly modelled as rising and falling with total output. Yet many factors, such as energy-efficiency improvements and shifts to cleaner energy, can break this relationship. We evaluate these factors using US data and find that changes in energy efficiency of consumption goods explain a significant proportion of emissions fluctuations. This finding also implies that models that omit energy efficiency likely overestimate the trade-off between environmental protection and economic performance.

The initiatives reviewed by the author were undertaken to ensure a liquid and well-functioning market for Government of Canada securities in light of the significant shift in the government's financial position. They include changes made in 1998 by the Bank of Canada and the government to the rules governing auctions and to the Bank's surveillance of the auction process, changes to the treasury bill and bond programs, and implementation of a pilot buyback program for Government of Canada marketable bonds. In addition, the Investment Dealers Association of Canada adopted a code of conduct for the secondary market. These initiatives were well received by the market and appear to have had a positive impact. The Bank and the government are, however, continuing their search for ways to maintain and enhance the efficiency of this market.

Average hourly real wage series from the Labor Productivity and Costs (LPC) program and the Current Employment Statistics (CES) program have evolved very differently over the past decades.

How might one simulate a million realistic income paths and compute their statistical moments in under a second? Using CUDA-based methods to estimate the Canadian earnings process, I find that the distribution of labour income growth is sharply peaked with heavy tails—similar to that in the United States.

Forecasts of the price of crude oil play a significant role in the conduct of monetary policy, especially for commodity producers such as Canada. This article presents a range of recently developed forecasting models that, when pooled together, can generate, on average, more accurate forecasts of the price of oil than the oil futures curve. It also illustrates how policy-makers can evaluate the risks associated with the baseline oil price forecast and how they can determine the causes of past oil price fluctuations.

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.