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I construct a weekly measure of real economic activity in Canada. Based on the work of Aruoba et al. (2009), the indicator is extracted as an unobserved component underlying the co-movement of four monthly observed real macroeconomic variables - employment, manufacturing sales, retail sales and GDP.

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 authors develop simple econometric models to analyze and forecast two components of the Bank of Canada commodity price index: the Bank of Canada non-energy (BCNE) commodity prices and the West Texas Intermediate crude oil price. They present different methodologies to identify transitory and permanent components of movements in these prices.

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).

The authors examine the Bank of Canada's overnight rate as a measure of monetary policy in vector autoregression (VAR) models. Since the time series of the Bank's current measure of the overnight rate begins only in 1971, the authors splice it to day loan rate observations to obtain a sufficiently long period of data.

Real rigidities that limit the responsiveness of real marginal cost to output are a key ingredient of sticky price models necessary to account for the dynamics of output and inflation. We argue here, in the spirit of Bils and Kahn (2000), that the behavior of marginal cost over the cycle is directly related to that of inventories, data on which is readily available.

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.

The COVID-19 pandemic has caused an atypical recession in which some sectors of the economy boomed and others collapsed. This required a unique fiscal policy reaction to both support firms and stimulate activity in sectors with slack. Was fiscal policy able to get where it was needed? Mostly, yes.

The household debt-to-disposable income ratio in Canada increased from 110 per cent in 1999 to 127 per cent in 2007. This increase has raised questions about the ability of households to service their increased debt if faced with a negative economic or socio-economic shock.

The research findings highlighted in this article suggest that firm-size differences play a significant role in explaining the productivity gap between Canada and the United States. The authors review factors that lead to a positive relationship between productivity and size and then look at Canadian evidence of this relationship at the firm level. They quantify the extent to which the change in Canadian productivity as well as the Canada-U.S. productivity differences can be accounted for by the change in the importance of large firms and identify several factors that play a role in determining average firm size and aggregate productivity.