Time Series Analysis, Cointegration, and Applications

Time Series Analysis, Cointegration, and Applications By CLIVE W. J. GRANGER* The two prize winners in Economics this year would describe themselves as “Econometricians,” so I thought that I should start by explaining that term. One can begin with the ancient subject of Mathematics which is largely concerned with the discovery of relationships between deterministic variables using a rigorous argument. (A deterministic variable is one whose value is known with certainty.) However, by the middle of the last millennium it became clear that some objects were not deterministic, they had to be described with the use of probabilities, so that Mathematics grew a substantial subfield known as “Statistics.” This later became involved with the analysis of data and a number of methods have been developed for data having what may be called “standard properties.” However, in some areas of application, the data that they generated were found to be not standard, and so special sub-subfields needed to be developed. For example, Biology produced Biometrics, Psychology gave us Psychometrics, and Economics produced Econometrics. There are many types of economic data, but the type considered by Robert Engle and myself is known as time series. Consider the measurement of unemployment rates which is an important measure http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Economic Review American Economic Association

Time Series Analysis, Cointegration, and Applications

American Economic Review, Volume 94 (3) – Jun 1, 2004

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Publisher
American Economic Association
Copyright
Copyright © 2004 by the American Economic Association
Subject
Articles
ISSN
0002-8282
DOI
10.1257/0002828041464669
Publisher site
See Article on Publisher Site

Abstract

By CLIVE W. J. GRANGER* The two prize winners in Economics this year would describe themselves as “Econometricians,” so I thought that I should start by explaining that term. One can begin with the ancient subject of Mathematics which is largely concerned with the discovery of relationships between deterministic variables using a rigorous argument. (A deterministic variable is one whose value is known with certainty.) However, by the middle of the last millennium it became clear that some objects were not deterministic, they had to be described with the use of probabilities, so that Mathematics grew a substantial subfield known as “Statistics.” This later became involved with the analysis of data and a number of methods have been developed for data having what may be called “standard properties.” However, in some areas of application, the data that they generated were found to be not standard, and so special sub-subfields needed to be developed. For example, Biology produced Biometrics, Psychology gave us Psychometrics, and Economics produced Econometrics. There are many types of economic data, but the type considered by Robert Engle and myself is known as time series. Consider the measurement of unemployment rates which is an important measure

Journal

American Economic ReviewAmerican Economic Association

Published: Jun 1, 2004

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