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The Bank of Canada maintains regular contact with financial institutions as part of the information-gathering process that feeds into the larger set of information used to arrive at its monetary policy decision. Since 1999, the Bank has been conducting a quarterly survey of the business-lending practices of major Canadian financial institutions. Analysis of the information collected shows that it is correlated with future growth in both credit and business investment. This article focuses on how the survey is conducted and describes the construction of the summary statistics, highlighting the key statistical relationships in the historical survey data.

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.

In this article, the authors build on the framework used in the Bank of Canada's Financial System Review to assess the evolution of household indebtedness and financial vulnerabilities in response to changing economic conditions. To achieve this, they first compare two microdata sets generated by Ipsos Reid's Canadian Financial Monitor and Statistics Canada's Survey of Financial Security. They find that the surveys are broadly comparable, despite methodological differences. This enables them to use the combined information content for the identification of the threshold value of the debt-service ratio (DSR). The article then presents an innovative framework that uses household-level microdata to simulate changes in the distribution of the DSR under various stress scenarios. The authors show how this framework can be used by analyzing the effects of two different scenarios on the distribution of the debt-service ratio and the impact on vulnerable households. This tool will enable researchers to refine their analyses of current risks to the financial health of Canadian households. The article concludes with comments on future directions for refining the Bank's analyses of household sector risk.

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.

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.

This paper contributes to the debate on the magnitude of exchange rate elasticities by providing a set of price and quantity elasticities for 51 advanced and emerging-market economies. Specifically, for each of these countries we report the elasticity of trade prices and trade quantities on both the export and on the import sides, as well as the reaction of the trade balance.

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.

Many reports and analyses interpret the release of new economic data based on the headline surprise—for instance, total inflation, real GDP growth and the unemployment rate. However, we find that headline news alone cannot adequately explain the responses of market prices to new information. Rather, market prices react more strongly, on average, to non-headline news such as the composition of GDP growth, quality of jobs created and revisions to past data. Thus, tracking the impact of non-headline information released on the news day is crucial in analyzing how markets interpret and react to new economic data.

This paper proposes a method for estimating the joint distribution of two or more variables when only their marginal distributions and the distribution of their aggregates are observed. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure.