Identifying Long-run Behaviour with Non-stationary Data
AbstractResults for the identification of non-linear models are used to support the traditional form of the order condition by sufficient conditions. The sufficient conditions reveal a two step procedure for firstly checking generic identification and then testing identifiability. This approach can be extended to sub-blocks of the system and it generalizes to non-linear restrictions. The procedure is applied to an empirical model of the exchange rate, which is identified by diagonalising the system.
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Bibliographic InfoPaper provided by Economics and Finance Section, School of Social Sciences, Brunel University in its series Economics and Finance Discussion Papers with number 98-01.
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Postal: Brunel University, Uxbridge, Middlesex UB8 3PH, UK
Other versions of this item:
- BAUWENS, Luc & HUNTER, John, 2000. "Identifying long-run behaviour with non-stationary data," CORE Discussion Papers 2000043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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- Hunter, J., 1990. "Cointegrating exogeneity," Economics Letters, Elsevier, vol. 34(1), pages 33-35, September.
- Ericsson, Neil R & Hendry, David F & Mizon, Grayham E, 1998.
"Exogeneity, Cointegration, and Economic Policy Analysis,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 16(4), pages 370-87, October.
- Neil R. Ericsson & David F. Hendry & Grayham E. Mizon, 1998. "Exogeneity, cointegration, and economic policy analysis," International Finance Discussion Papers 616, Board of Governors of the Federal Reserve System (U.S.).
- Johansen, Soren, 1995. "Identifying restrictions of linear equations with applications to simultaneous equations and cointegration," Journal of Econometrics, Elsevier, vol. 69(1), pages 111-132, September.
- Johansen, Soren, 1992.
"Testing weak exogeneity and the order of cointegration in UK money demand data,"
Journal of Policy Modeling,
Elsevier, vol. 14(3), pages 313-334, June.
- Johansen, S., 1991. "Testing Weak Exogeneity and the Order of Cointegration in UK Money Demand Data," Papers 78, Helsinki - Department of Economics.
- Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
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