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 maximum likelihood (ML) estimators, establishes the relative rates of convergence of the ML estimators of the short-run and the long-run parameters, and derives their asymptotic distribution; 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 InfoPaper provided by Edinburgh School of Economics, University of Edinburgh in its series ESE Discussion Papers with number 44.
Date of creation: Apr 2004
Date of revision:
Cointegration; identification; testing non-linear restrictions; consistency; asymptotic distribution; Almost Ideal Demand Systems;
Other versions of this item:
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-04-25 (All new papers)
- NEP-ECM-2004-04-25 (Econometrics)
- NEP-ETS-2004-04-25 (Econometric Time Series)
- NEP-MIC-2004-04-25 (Microeconomics)
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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