Robust thresholding for Diffusion Index forecast

Vu Le, Qing Wang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


In this paper we propose a new methodology in improving the Diffusion Index forecasting model (Stock and Watson, 2002a, 2002b) using hard thresholding with robust KVB statistic for regression hypothesis tests (Kiefer et al., 2000). The new method yields promising results in the context of long forecasting horizons and existence of serial correlation. Numerical comparison indicates that the proposed methodology can improve upon the existing hard thresholding methods and outperform the soft thresholding methods (Bai and Ng, 2008) when applied to a real data set that forecasts eight macroeconomic variables in the United States.

Original languageEnglish (US)
Pages (from-to)52-56
Number of pages5
JournalEconomics Letters
Issue number1
StatePublished - Oct 2014

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics


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