Bilgili, Faik (1998): Stationarity and cointegration tests: Comparison of Engle - Granger and Johansen methodologies. Published in: Journal of Faculty of Economics and Administrative Sciences, Erciyes University No. 13 (1998): pp. 131-141.
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Abstract
Engle-Granger methodology follows two-step estimations. The first step generates the residuals and the second step employs generated residuals to estimate a regression of first-differenced residuals on lagged residuals. Hence, any possible error from the first step will be carried into second step. The Johansen maximum likelihood methodology circumvents Engle-Granger methodology by estimating and testing for the presence of multiple cointegrating vectors through largest canonical correlations. The number of non-zero eigenvalues of Ψ of eq. 26 in the text will specify the number of cointegrating vectors. Some Monte Carlo evidence explores that Johansen procedure performs better than both single equation methods and alternative multivariate methods. In fact, evidence of this paper reveals, as well, that, as Engle-Granger yields some inconclusive outcome, the Johansen tests reach at least one cointegration relationship among variables for Canada, India, Italy, Japan, Turkey and the USA. Then, one may claim that Johansen methodology dominates the Engle- Granger methodology in cointegration analyses.
Item Type: | MPRA Paper |
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Original Title: | Stationarity and cointegration tests: Comparison of Engle - Granger and Johansen methodologies |
English Title: | Stationarity and cointegration tests: Comparison of Engle - Granger and Johansen methodologies |
Language: | English |
Keywords: | Stationarity, Cointegration, Engle-Granger methodology, Johansen methodology, Consumption |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C18 - Methodological Issues: General C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C29 - Other C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E21 - Consumption ; Saving ; Wealth |
Item ID: | 75967 |
Depositing User: | Faik Bilgili |
Date Deposited: | 04 Jan 2017 09:41 |
Last Modified: | 26 Sep 2019 14:58 |
References: | Dickey, David A. and Jansen W. Dennis, Thornton L, Daniel, "A Primer on Cointegration with an Application to Money and Income”, Federal Reserve Bank of St Louis, March/April, 1991. Enders, Walter, Applied Econometric Time Series, John Wiley & Sons, Inc., New York, 1995. Engle, R. and C. Granger, "Cointegration and Error Correction: Representation, Estimation, and Testing,” In Engle and Granger (eds.), Long Run Economic Readings in Cointegration, Oxford University Press, New York, 1991,81-113. Engle, R. and Yoo Sam, "Forecasting and Testing in Co-integrated Systems," In Engle and Granger (eds.), Long Run Economic Relationships. Readings in Cointegration, Oxford University Press, New York, 1991, 237-67. Granger, Clive, "Developments in The Study of Cointegrated Economic Variables," In Engle and Granger (eds.), Long Run Economic Relationships, Readings in Cointegration, Oxford University Press, New York, 1991,65-81. Granger, Clive and P. Newbold, "Spurious Regressions in Econometrics,” Journal of Econometrics, 2 (1974), 111-20. Hamilton, James D, Time Series Analysis, Princeton University Press, Princeton, New Jersey, 1994. Hargreaves, Colin, "A Review of Methods of Estimating Cointegrating Relationships,” In Colin P. Hargreaves (ed.), Nonstationary Time Series Analysis and Cointegration, Oxford University Press, New York, 1994, 87-133. Johansen, Soren, "Statistical Analysis of Cointegration Vectors," Journal of Economic Dynamics and Control, 12 (1988), 231-254. Johansen, S. and K. Juselius, "Maximum Likelihood Estimation and Inference on Cointegration with Application to the Demand for Money," Oxford Bulletin of Economics and Statistics, 52 (1990), 169-209. Phillips, Peter, "Understanding Spurious Regressions in Econometrics," Journal of Econometrics, 33 (1986), 311-40. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/75967 |