Abstract
AbstractThis article compares the predictive ability of the factor models of Stock and Watson (2002a) and Forni, Hallin, Lippi and Reichlin (2005) using a ‘large’ panel of macroeconomic variables of the United States. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar exercises in the literature. Our main conclusion is that with the dataset at hand the two methods have a similar performance and produce highly collinear forecasts.
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