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Recent research suggests that quantitative easing (QE) may affect a broad range of asset prices through a portfolio balance channel. Using novel security-level holding data of individual US mutual funds, we establish evidence that portfolio rebalancing occurred both within and across funds.

In this paper, the authors survey some of the recent techniques proposed in the literature to measure the trend component of output or potential output. Given the reported shortcomings of mechanical filters and univariate approaches to estimate potential output, the paper focusses on three simple multivariate methodologies: the multivariate Beveridge-Nelson methodology (MBN), Cochrane's methodology (CO), and the structural VAR methodology with long-run restrictions applied to output (LRRO).

The author reviews the theoretical and empirical literature to examine the traditional perception that the following trade-off exists between economic efficiency and stability in the banking system: a competitive banking system is more efficient and therefore important to growth, but market power is necessary for stability in the banking system.

Deputy Governor Timothy Lane discusses the benefits and challenges of international capital mobility.

The good forecasting performance of factor models has been well documented in the literature. While many studies focus on a very limited set of variables (typically GDP and inflation), this study evaluates forecasting performance at disaggregated levels to examine the source of the improved forecasting accuracy, relative to a simple autoregressive model. We use the latest revision of over 100 U.S. time series over the period 1974-2009 (monthly and quarterly data).

This article focuses on the role that loans backed by housing collateral play in amplifying housing booms and, more generally, procyclicality in the housing market. The author uses a model developed to include borrower and lender households, as well as a housing market, to examine the impact that altering the loan-to-value ratio (either permanently or countercyclically) might have on the volatility of house prices and mortgage debt.

We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

During and after the Great Recession of 2008–09, conventional monetary policy in the United States and many other advanced economies was constrained by the effective lower bound (ELB) on nominal interest rates. Several central banks implemented large-scale asset purchase (LSAP) programs, more commonly known as quantitative easing or QE, to provide additional monetary stimulus.

This article focuses on a quantitative method to identify financial system vulnerabilities, specifically, an imbalance indicator model (IIM) and its application to Canada. An IIM identifies potential vulnerabilities in a financial system by comparing current economic and financial data with data from periods leading up to past episodes of financial stress. It complements other sources of information - including market intelligence and regular monitoring of the economy - that policy-makers use to assess vulnerabilities.

Improving the conduct of monetary policy is unlikely to be the main motivation for central banks to issue a central bank digital currency (CBDC). While some argue that a CBDC could allow more complex transfer schemes or the ability to break below the zero lower bound, we find these benefits might be small or difficult to realize in practice.