Long-Run Structural Modelling
AbstractThe paper develops a general framework for identification, estimation, and hypothesis testing in cointegrated systems when the cointegrating coefficients are subject to (possibly) non-linear and cross-equation restrictions, obtained from economic theory or other relevant a priori information. It provides a proof of the consistency of the quasi maximum likelihood estimators (QMLE), establishes the relative rates of convergence of the QMLE of the short-run and the long-run parameters, and derives their asymptotic distributions; thus generalizing the results already available in the literature for the linear case. The paper also develops tests of the over-identifying (possibly) non-linear restrictions on the cointegrating vectors. The estimation and hypothesis testing procedures are applied to an Almost Ideal Demand System estimated on U.K. quarterly observations. Unlike many other studies of consumer demand this application does not treat relative prices and real per capita expenditures as exogenously given.
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Bibliographic InfoArticle provided by Taylor and Francis Journals in its journal Econometric Reviews.
Volume (Year): 21 (2002)
Issue (Month): 1 ()
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Web page: http://taylorandfrancis.metapress.com/link.asp?target=journal&id=107830
Other versions of this item:
- M Pesaran & Yongcheol Shin, 2004. "Long-Run Structural Modelling," ESE Discussion Papers 44, Edinburgh School of Economics, University of Edinburgh.
- Pesaran,H.M. & Shin,Y., 1995. "Long-Run Structural Modelling," Cambridge Working Papers in Economics 9419, Faculty of Economics, University of Cambridge.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- D1 - Microeconomics - - Household Behavior
- E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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