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How can Surveys of Professional Forecasters (SPF) be used to improve inflation forecasts? By using US historical quarterly data on SPF forecasts, we provide better understanding of how we can use forecast disagreement to improve our own forecasts.

This paper proposes a novel asymptotic least-squares estimator of multi-country Gaussian dynamic term structure models that is easy to compute and asymptotically efficient, even when the number of countries is relatively large—a situation in which other recently proposed approaches lose their tractability.

We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a disaggregated industrial production series for the US economy. We identify unexpected changes in durable goods uncertainty as drivers of downturns, while unexpected hikes in non-durable goods uncertainty are expansionary.

Inflation can affect both the dispersion of commodity-specific price levels across locations (relative price variability, RPV) and the dispersion of inflation rates (relative inflation variability, RIV). Some menu-cost models and models of consumer search suggest that the RIV-inflation relationship could differ from the RPV-inflation relationship.

It has been a difficult year for capital markets professionals. The turmoil has deteriorated into a full-blown financial crisis. Most financial markets have experienced historic falls in prices, and some are strained to the point of closing.

The 2007–09 global financial crisis has led policy-makers around the world, including central banks, to refocus their efforts to promote financial stability. As part of this process, central banks became quite active in supporting financial stability in a variety of ways, such as publicly sharing their assessments of financial system vulnerabilities and risks and helping to strengthen regulation, supervision and macroprudential measures.

We provide an updated evaluation of the value of various measures of core inflation that could be used in the conduct of monetary policy. We find that the Bank of Canada’s current preferred measures of core inflation—CPI-trim, CPI-median and CPI-common—continue to outperform alternative core measures across a range of criteria.

Oil prices have declined sharply over the past three years. While both supply and demand factors played a role in the large oil price decline of 2014, global supply growth seems to have been the predominant force. The most important drivers were likely the surprising growth of US shale oil production, the output decisions of the Organization of the Petro-leum Exporting Countries and the weaker-than-expected global growth that followed the 2009 global financial crisis.

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.