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In this paper, we argue that differences in the cost structures across sectors play an important role in firms’ decisions to adjust their prices. We develop a menu-cost model of pricing in which retail firms intermediate trade between producers and consumers.

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).

Dion examines the evolution of Canadian productivity since the mid-1990s, using the United States as a benchmark. During this period, trend productivity growth in Canada remained modest, whereas the U.S. witnessed a strong resurgence. Among the factors identified as potential root causes of Canada's lower productivity performance are a lower investment in information and communications technology, reallocation and adjustment costs associated with large relative price movements, and a weak demand for innovation.

Central banks face considerable uncertainty when conducting monetary policy. The COVID-19 pandemic brought this issue back to the forefront of policy discussions. We draw from academic literature to review key sources of uncertainty and how they affect the conduct of monetary policy.

We model non-bank entry into fixed-income markets and state-dependent liquidity. Non-bank financial institutions improve liquidity more during normal times than in stress. Banks may become less reliable to marginal clients, exacerbating the difference in liquidity between normal and stressed times. Central bank lending during stress may limit this harmful division.

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.

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.

One of the most important factors that must be considered if countries are thinking about lowering the target level of inflation much below 2 per cent is the zero interest bound. Targeting inflation rates that are too low, the authors note, may restrict the ability of monetary policy to respond to economic shocks by limiting the amount by which interest rates can be eased.

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.