C53 - Forecasting and Prediction Methods; Simulation Methods

• Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach

  Staff Working Paper 2013-28 Christiane Baumeister, Lutz Kilian

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

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, International topics JEL Code(s): C, C5, C53, E, E3, E32, Q, Q4, Q43

• Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis

  Staff Working Paper 2013-25 Christiane Baumeister, Lutz Kilian, Xiaoqing Zhou

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, International topics JEL Code(s): C, C5, C53, G, G1, G15, Q, Q4, Q43
• August 15, 2013

  CSI: A Model for Tracking Short-Term Growth in Canadian Real GDP

  Bank of Canada Review - Summer 2013 André Binette, Jae Chang

  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.

  Content Type(s): Publications, Bank of Canada Review articles Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C53, E, E1, E17, E3, E37
• August 15, 2013

  The Accuracy of Short-Term Forecast Combinations

  Bank of Canada Review - Summer 2013 Eleonora Granziera, Corinne Luu, Pierre St-Amant

  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.

  Content Type(s): Publications, Bank of Canada Review articles Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C52, C53, E, E3, E37
• August 15, 2013

  Big Data Analysis: The Next Frontier

  Bank of Canada Review - Summer 2013 Nii Ayi Armah

  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.

  Content Type(s): Publications, Bank of Canada Review articles Topic(s): Econometric and statistical methods, Monetary and financial indicators JEL Code(s): C, C5, C53, C6, C63, C8, C80

• What Central Bankers Need to Know about Forecasting Oil Prices

  Staff Working Paper 2013-15 Christiane Baumeister, Lutz Kilian

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, International topics JEL Code(s): C, C5, C53, E, E3, E32, Q, Q4, Q43

• Forecasting with Many Models: Model Confidence Sets and Forecast Combination

  Staff Working Paper 2013-11 Jon D. Samuels, Rodrigo Sekkel

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C53