Time Series Analysis, Cointegration, and Applications
AbstractThe 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 sub-field 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."
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Bibliographic InfoArticle provided by American Economic Association in its journal American Economic Review.
Volume (Year): 94 (2004)
Issue (Month): 3 (June)
Other versions of this item:
- Granger, Clive W.J., 2004. "Time Series Analysis, Cointegration, and Applications," University of California at San Diego, Economics Working Paper Series qt2nb9f668, Department of Economics, UC San Diego.
- Granger, Clive W. J., 2003. "Time Series Analysis, Cointegration, and Applications," Nobel Prize in Economics documents 2003-7, Nobel Prize Committee.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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