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In recent years, the Bank has put renewed emphasis on analyzing monetary variables and on developing models that incorporate money as an active part of the transmission mechanism. In this article, Dinah Maclean describes how the monetary aggregates are used in the formulation of monetary policy analysis at the Bank, outlining the key tools and models used. The most important money-based model currently in use is the M1-VECM. In this model, deviations in the money supply from the long-term demand for money cause changes in inflation. The author briefly describes the "active-money" paradigm underlying this model and explains the key equations within it. Other simpler empirical models are also outlined, including single-equation indicator models for output based on the narrow aggregates, a neural network, and a model based on the broader aggregate M2++. A detailed technical annex provides details on model equations and coefficient values.

This paper quantifies the impact of hurricanes on seaborne international trade to the United States. Matching the timing of hurricane–trade route intersections with monthly U.S. port-level trade data, we isolate the unanticipated effects of a hurricane hitting a trade route using two separate identification schemes: an event study and a local projection.

The consumer price index (CPI) is the most commonly used measure to track changes in the overall level of prices. Since it departs from a true cost-of-living index, the CPI is subject to four types of measurement bias—commodity substitution, outlet substitution, new goods and quality adjustment. The author updates previous Bank of Canada estimates of measurement bias in the Canadian CPI by examining these four sources of potential bias. He finds the total measurement bias over the 2005–11 period to be about 0.5 percentage point per year, consistent with the Bank’s earlier findings. Slightly more than half of this bias is caused by the fixed nature of the CPI basket of goods and services.

Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.

I examine the impact of non-regulated lenders in the mortgage market using a dynamic stochastic general equilibrium (DSGE) model. My model features two types of financial intermediaries that differ in three ways: (i) only regulated intermediaries face a capital requirement, (ii) non-regulated intermediaries finance themselves by selling securities and cannot accept deposits, and (iii) non-regulated intermediaries face a more elastic demand.

Éric Chouinard and Graydon Paulin review the progress to date in implementing Basel III, the new framework of global regulatory standards for the banking sector developed by the Basel Committee on Banking Supervision. The report highlights the expected net benefits of implementing Basel III, as well as the challenges in ensuring international consistency in measuring the risk-weighted capital of banks. It includes a discussion on how implementing Basel III has affected the banking system in Canada and other important jurisdictions, and demonstrates the need for ongoing assessment of the effects on the financial system and the macroeconomy.

The U.S. recovery from the Great Recession has been slow relative to other postwar-era recoveries in the United States. Encouraged by loose lending standards in the pre-crisis period, U.S. households took on unsustainable amounts of debt, making them vulnerable to adverse shocks. Subsequently, a considerable drop in asset prices forced households to repair their balance sheets. While there has been progress in household deleveraging, the government sector now needs to delever, which will restrain growth over the next few years.

Severe disruptions in the financial markets, as observed during the 2008 global financial crisis or the COVID-19 pandemic, can impair the stability of the entire financial system and worsen macroeconomic downturns.

This paper presents a model of strategic buyer-seller networks with information exchange between sellers. Prior to engaging in bargaining with buyers, sellers can share access to buyers for a negotiated transfer. We study how this information exchange affects overall market prices, volumes and welfare, given different initial market conditions and information sharing rules.