# Singular value decomposition in cointegration analysis: a note regarding the difference stationary series

Singular value decomposition in cointegration analysis: a note regarding the difference... Many methods and techniques have been developed gradually to compute cointegration vectors. We present here a comparatively simple method for computing the matrix of cointegrating vectors, by applying singular value decomposition. With this method, one can easily accommodate in the cointegrating vectors any deterministic factors, such as a dummy, apart from the constant term and the trend. Besides the errors corresponding to the finally selected cointegrating vector have the property of minimum variance. It is noted that this procedure is not mentioned in the relevant literature. Additionally, a sequential technique is introduced, for determining the order of integration for a given series. With this procedure one can directly detect whether the differencing process produces a stationary series or not, since it seems to be a common belief that differencing a variable (one or more times) we will always get a stationary series [Harris, R.: Using Cointegration Analysis in Econometric Modelling. Prentice Hall, London (1995)]. It will be seen that this is not necessarily the case. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

# Singular value decomposition in cointegration analysis: a note regarding the difference stationary series

, Volume 42 (5) – Aug 3, 2007
12 pages

/lp/springer_journal/singular-value-decomposition-in-cointegration-analysis-a-note-kPbDfAlEaO
Publisher
Springer Journals
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-007-9120-4
Publisher site
See Article on Publisher Site

### Abstract

Many methods and techniques have been developed gradually to compute cointegration vectors. We present here a comparatively simple method for computing the matrix of cointegrating vectors, by applying singular value decomposition. With this method, one can easily accommodate in the cointegrating vectors any deterministic factors, such as a dummy, apart from the constant term and the trend. Besides the errors corresponding to the finally selected cointegrating vector have the property of minimum variance. It is noted that this procedure is not mentioned in the relevant literature. Additionally, a sequential technique is introduced, for determining the order of integration for a given series. With this procedure one can directly detect whether the differencing process produces a stationary series or not, since it seems to be a common belief that differencing a variable (one or more times) we will always get a stationary series [Harris, R.: Using Cointegration Analysis in Econometric Modelling. Prentice Hall, London (1995)]. It will be seen that this is not necessarily the case.

### Journal

Quality & QuantitySpringer Journals

Published: Aug 3, 2007

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