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Long-Run Structural Modelling

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  • M. Hashem Pesaran
  • Yongcheol Shin

Abstract

The 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.

Suggested Citation

  • M. Hashem Pesaran & Yongcheol Shin, 2002. "Long-Run Structural Modelling," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 49-87.
  • Handle: RePEc:taf:emetrv:v:21:y:2002:i:1:p:49-87
    DOI: 10.1081/ETC-120008724
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    References listed on IDEAS

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    More about this item

    Keywords

    Cointegration; Identification; QMLE; Consistency; Asymptotic distribution; testing non-linear restrictions; Almost Ideal Demand Systems; JEL Classifications: C1; C3; D1; E1;
    All these keywords.

    JEL classification:

    • 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

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