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The effectiveness of monetary policy depends, to a large extent, on market expectations of its future actions. In a standard New Keynesian business-cycle model with rational expectations, systematic monetary policy reduces the variance of inflation and the output gap by at least two-thirds.

The Survey of Professional Forecasters (SPF) has had vast influence on research related to better understanding expectation formation and the behaviour of macroeconomic agents. Inflation expectations, in particular, have received a great deal of attention, since they play a crucial role in determining real interest rates, the expectations-augmented Phillips curve and monetary policy.

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.

The recent financial crisis and subsequent recession have spurred great interest in the sources of unemployment fluctuations. Previous studies predominantly assume a single economy-wide labour market, and therefore abstract from differences across sectorspecific labour markets in the economy.

This report provides a detailed technical description of an updated version of the Terms-of-Trade Economic Model (ToTEM II), which replaced ToTEM (Murchison and Rennison 2006) in June 2011 as the Bank of Canada’s quarterly projection model for Canada.

In this paper, the authors propose a measure of underlying inflation for Canada obtained from estimating a monthly factor model on individual components of the CPI. This measure, labelled the common component of CPI, has intuitive appeal and a number of interesting features.

The U.S. Energy Information Administration regularly publishes short-term forecasts of the price of crude oil.

Canada’s Short-Term Indicator (CSI) is a new model that exploits the information content of 32 indicators to produce daily updates to forecasts of quarterly real GDP growth. The model is a data-intensive, judgment-free approach to short-term forecasting. While CSI’s forecasts at the start of the quarter are not very accurate, the model’s accuracy increases appreciably as more information becomes available. CSI is the latest addition to a wide range of models and information sources that the Bank of Canada uses, combined with expert judgment, to produce its short-term forecasts.

This article examines whether combining forecasts of real GDP from different models can improve forecast accuracy and considers which model-combination methods provide the best performance. In line with previous literature, the authors find that combining forecasts generally improves forecast accuracy relative to various benchmarks. Unlike several previous studies, however, they find that, rather than assigning equal weights to each model, unequal weighting based on the past forecast performance of models tends to improve accuracy when forecasts across models are substantially different.

The Bank of Canada uses several short-term forecasting models for the monitoring of key foreign economies - the United States, the euro area, Japan and China. The design of the forecasting models used for each region is influenced by the level of detail required, as well as the timeliness and volatility of data. Forecasts from different models are typically combined to mitigate model uncertainty, and judgment is applied to the model forecasts to incorporate information that is not directly reflected in the most recent indicators.