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Observed high-frequency prices are contaminated with liquidity costs or market microstructure noise. Using such data, we derive a new asset return variance estimator inspired by the market microstructure literature to explicitly model the noise and remove it from observed returns before estimating their variance.

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

The authors study the implications of fiscal policy behaviour for sovereign risk in a framework that determines a country’s fiscal limit, the point at which, for economic or political reasons, taxes and spending can no longer adjust to stabilize debt.

The paper explores the macroeconomic consequences of fiscal consolidations whose timing and composition - either tax- or spending-based - are uncertain.

Notwithstanding a resurgence in research on out-of-sample forecasts of the price of oil in recent years, there is one important approach to forecasting the real price of oil which has not been studied systematically to date.

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.

This special issue discusses tools used at Bank of Canada to conduct current analysis - the collection and analysis of a broad spectrum of information to form a view of current economic activity. This analysis is a key input into the Bank’s monetary policy decision-making process.