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Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets

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  • Kihwan Kim

    ()
    (Rutgers University)

  • Norman Swanson

    ()
    (Rutgers University)

Abstract

In this chapter, we discuss the use of mixed frequency models and diffusion index approximation methods in the context of prediction. In particular, select recent specification and estimation methods are outlined, and an empirical illustration is provided wherein U.S. unemployment forecasts are constructed using both classical principal components based diffusion indexes as well as using a combination of diffusion indexes and factors formed using small mixed frequency datasets. Preliminary evidence that mixed frequency based forecasting models yield improvements over standard fixed frequency models is presented.

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Bibliographic Info

Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 201315.

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Length: 20 pages
Date of creation: 16 Jul 2013
Date of revision:
Handle: RePEc:rut:rutres:201315

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Keywords: forecasting; diffusion index; mixed frequency; recursive estimation; Kalman filter;

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