A Reduced Rank Regression Approach to Coincident and Leading Indexes Building

• Autores: Gianluca Cubadda
• Localización: Oxford bulletin of economics and statistics, ISSN 0305-9049, Vol. 69, Nº. 2, 2007, págs. 271-292
• Idioma: inglés
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• Resumen

  • This paper proposes a reduced rank regression framework for constructing a coincident index (CI) and a leading index (LI). Based on a formal definition that requires that the first differences of the LI are the best linear predictor of the first differences of the CI, it is shown that the notion of polynomial serial correlation common features can be used to build these composite variables. Concepts and methods are illustrated by an empirical investigation of the US business cycle indicators.