A Reduced Rank Regression Approach to Coincident and Leading Indexes Building∗
نویسنده
چکیده
This paper proposes a new methodology to build composite coincident and leading indexes. Based on a formal definition that requires that the first differences of the leading index is the best linear predictor of the first differences of the coincident index, 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. JEL classification: C32
منابع مشابه
A Reduced Rank Regression Approach to Coincident and Leading Indexes Building a Reduced Rank Regression Approach to Coincident and Leading Indexes Building
This paper proposes a reduced rank regression framework for constructing coincident and leading indexes. Based on a formal definition that requires that the first differences of the leading index are the best linear predictor of the first differences of the coincident index, it is shown that the notion of polynomial serial correlation common features can be used to build these composite variabl...
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