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Internal Economics Training

Advanced Forecasting Methods (Self-Financed)

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Session No.: IT 19.10

Location: Washington, D.C., United States New location

Date: September 9-11, 2019 (2 days) New dates

Primary Language: English

    Target Audience

    Officials, primarily in ministries of finance, economy, and planning, or in central banks.

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    Qualifications

    It is required that candidates have an advanced degree in economics, strong analytical skills, and a very good knowledge of English. Courses will be conducted in English with no interpretation.

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    Course Description

    This course introduces participants to a variety of advanced topics and approaches in economic forecasting. The course starts off by emphasizing the importance of grounding forecasts in the economic objectives of the forecasting analysis, as represented by the forecaster’s loss function. Often the difference between good and bad forecasting approaches hinges on how they deal with changes to the underlying data generating process. The course therefore next addresses the consequences of model instability on forecasting performance and discusses strategies for dealing with such instability, using empirical illustrations from macroeconomics and finance.

    The second part of the course covers forecast evaluation, forecast comparisons, and monitoring of forecasting performance. Professor Timmermann will discuss which properties an optimal forecast should have and describe methods for evaluating whether a given forecast is efficient. Searching across multiple models for a good forecasting model can, if not treated properly, introduce data mining biases, and ways to handle this problem will be discussed. Next, Professor Timmermann will introduce methods for comparing the predictive accuracy of competing forecasts in situations with a pair of alternative forecasts as well as in settings with large numbers of forecasts. He will analyze how real-time monitoring of competing models’ forecasting performance has the potential to improve upon the forecasting performance of individual models.

    Point forecasts do not reveal the uncertainty surrounding a given forecast and so many economic institutions have moved on to report interval and density (probability distribution) forecasts. The third part of the course introduces methods for generating these types of forecasts, covering both univariate and multivariate approaches. Finally, Professor Timmermann will discuss how to evaluate the accuracy of interval and density forecasts.

    Target Audience: Economists interested in applying advanced forecasting techniques. A recommended prerequisite is an introductory, one year graduate sequence in econometrics.

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    Important Note for Internal Economics Training Courses

    Internal Economics Training (IT) courses are self-financed. The IMF will not charge officials for attending courses. However, all travel, insurance, hotel, and living costs will need to be covered by the agency sponsoring the participants.

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