Applied Dynamic Factor Analysis for Macroeconomic Forecasting
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The use of dynamic factor analysis in statistical modeling has broad utility across an array of applications. This paper presents a novel hierachical structure suited to a particular class of predictive problems - those which necessitate the aggregation of numerous forecasts in the presence of substantial data missingness and a need for systematic dimensionality reduction. The model hierarchy is presented in the context of the prediction of U.S. Nonfarm Payrolls, a well-known economic statistic, though can be generally applied for any context exhibiting an analagous data structure.
CitationEastman, William (2018). Applied Dynamic Factor Analysis for Macroeconomic Forecasting. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/17525.
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