Diffusion index model specification and estimation using mixed frequency datasets

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this chapter, we discuss the use of mixed frequency models and diffusion index approximation methods in the context of prediction. In particular, 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 and 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.

Original languageEnglish (US)
Title of host publicationRecent Advances in Estimating Nonlinear Models
Subtitle of host publicationWith Applications in Economics and Finance
PublisherSpringer New York
Pages15-31
Number of pages17
ISBN (Electronic)9781461480600
ISBN (Print)1461480590, 9781461480594
DOIs
StatePublished - May 1 2013

All Science Journal Classification (ASJC) codes

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

Keywords

  • Diffusion index
  • Forecasting
  • Kalman filter
  • Mixed frequency
  • Recursive estimation

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