Econometric Methodology Ii : Strengthening Time Series Analysis
This article reviews some of the recent methodology developed for the analysis of time series data stressing that the statistical properties of the individual series need to be analysed to avoid spurious regressions. A convergence of econometric methodology is entertained with specific focus on cointegration and error correction models which allows the testing of long run relationships between variables and allows for a more dynamic structure than some of the previous models that appear in the literature. An example of this is the commonly used partial adjustment model in supply analysis which is nested in the less restrictive error correction model. Tests can be performed on the validity of these restrictions. These models have a wide application in agricultural economic analysis.
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- Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
- Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
- Mosconi, Rocco & Giannini, Carlo, 1992. "Non-causality in Cointegrated Systems: Representation Estimation and Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 399-417, August.
- Banerjee, Anindya & Dolado, Juan J. & Galbraith, John W. & Hendry, David, 1993. "Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data," OUP Catalogue, Oxford University Press, number 9780198288107, December.
- Hall, Stephen G & Milne, Alistair, 1994. "The Relevance of P-Star Analysis to UK Monetary Policy," Economic Journal, Royal Economic Society, vol. 104(424), pages 597-604, May.
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