C53 - Forecasting and Prediction Methods; Simulation Methods
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Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach
The U.S. Energy Information Administration regularly publishes short-term forecasts of the price of crude oil. -
Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis
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. -
August 15, 2013
CSI: A Model for Tracking Short-Term Growth in Canadian Real GDP
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. -
August 15, 2013
The Accuracy of Short-Term Forecast Combinations
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. -
August 15, 2013
Big Data Analysis: The Next Frontier
The formulation of monetary policy at the Bank of Canada relies on the analysis of a broad set of economic information. Greater availability of immediate and detailed information would improve real-time economic decision making. Technological advances have provided an opportunity to exploit “big data” - the vast amount of digital data from business transactions, social media and networked computers. Big data can be a complement to traditional information sources, offering fresh insight for the monitoring of economic activity and inflation. -
What Central Bankers Need to Know about Forecasting Oil Prices
Forecasts of the quarterly real price of oil are routinely used by international organizations and central banks worldwide in assessing the global and domestic economic outlook, yet little is known about how best to generate such forecasts. Our analysis breaks new ground in several dimensions. -
Forecasting with Many Models: Model Confidence Sets and Forecast Combination
A longstanding finding in the forecasting literature is that averaging forecasts from different models often improves upon forecasts based on a single model, with equal weight averaging working particularly well. This paper analyzes the effects of trimming the set of models prior to averaging. -
Short-Term Forecasting of the Japanese Economy Using Factor Models
While the usefulness of factor models has been acknowledged over recent years, little attention has been devoted to the forecasting power of these models for the Japanese economy. In this paper, we aim at assessing the relative performance of factor models over different samples, including the recent financial crisis. -
Real-Time Analysis of Oil Price Risks Using Forecast Scenarios
Recently, there has been increased interest in real-time forecasts of the real price of crude oil. Standard oil price forecasts based on reduced-form regressions or based on oil futures prices do not allow consumers of forecasts to explore how much the forecast would change relative to the baseline forecast under alternative scenarios about future oil demand and oil supply conditions.