E37 - Forecasting and Simulation: Models and Applications
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Nowcasting BRIC+M in Real Time
Emerging-market economies have become increasingly important in driving global GDP growth over the past 10 to 15 years. This has made timely and accurate assessment of current and future economic activity in emerging markets important for policy-makers not only in these countries but also in advanced economies. -
Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data
This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes – Bayesian (static) model averaging and dynamic model averaging – so as to explicitly reflect the objective of forecasting a discrete outcome. -
Integrating Uncertainty and Monetary Policy-Making: A Practitioner’s Perspective
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. -
Predicting Financial Stress Events: A Signal Extraction Approach
The objective of this paper is to propose an early warning system that can predict the likelihood of the occurrence of financial stress events within a given period of time. To achieve this goal, the signal extraction approach proposed by Kaminsky, Lizondo and Reinhart (1998) is used to monitor the evolution of a number of economic indicators that tend to exhibit an unusual behaviour in the periods preceding a financial stress event. -
Analyzing and Forecasting the Canadian Economy through the LENS Model
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. -
Forecasting Short-Term Real GDP Growth in the Euro Area and Japan Using Unrestricted MIDAS Regressions
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. -
Perceived Inflation Persistence
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. -
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.