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 Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2000043.
Date of creation: 00 Sep 2000
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Cointegration; Identiﬁcation; Identiﬁability; Order Condition; Sufficient Conditions.;
Other versions of this item:
- John Hunter, . "Identifying Long-run Behaviour with Non-stationary Data," Economics and Finance Discussion Papers 98-01, Economics and Finance Section, School of Social Sciences, Brunel University.
- 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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