Browse research

This paper examines the business cycle linkages that propagate industry-specific business cycle shocks throughout the economy in a way that (sometimes) generates aggregated cycles. The transmission of sectoral business cycles is modelled through a multivariate Markov-switching model, which is estimated by Gibbs sampling.

The answer as to whether there are gains from pooling real-time oil price forecasts depends on the objective. The approach of combining five of the leading forecasting models with equal weights dominates the strategy of selecting one model and using it for all horizons up to two years.

This paper discusses how central banking is evolving in light of recent experience, with particular emphasis on the incorporation of uncertainty into policy decision-making.

The U.S. Federal Reserve responded to the great recession by reducing policy rates to the effective lower bound. In order to provide further monetary stimulus, they subsequently conducted large-scale asset purchases, quadrupling their balance sheet in the process.

A measure of the neutral policy interest rate can be used to gauge the stance of monetary policy. We define the neutral rate as the real policy rate consistent with output at its potential level and inflation equal to target after the effects of all cyclical shocks have dissipated.

Using the prices of crude oil futures contracts, we construct the term structure of crude oil convenience yields out to one-year maturity. The crude oil convenience yield can be interpreted as the interest rate, denominated in barrels of oil, for borrowing a single barrel of oil, and it measures the value of storing crude oil over the borrowing period.

This paper conducts a real-time, out-of-sample analysis of the forecasting power of various aggregate financial intermediaries’ balance sheets to a wide range of economic activity measures in the United States.

Guided by a macroeconomic model in which non-energy commodity prices are endogenously determined, we apply a new factor-based identification strategy to decompose the historical sources of changes in commodity prices and global economic activity.

The authors describe the key features of a new large-scale Canadian macroeconomic forecasting model developed over the past two years at the Bank of Canada.

In this paper, the authors develop a new tool to improve the short-term forecasting of real GDP growth in the euro area and Japan. This new tool, which uses unrestricted mixed-data sampling (U-MIDAS) regressions, allows an evaluation of the usefulness of a wide range of indicators in predicting short-term real GDP growth.