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Integrated Modiï¬ ed Least Squares Estimation and (Fixed-b) Inference for Systems of Cointegrating Multivariate Polynomial Regressions

Author

Listed:
  • Veldhuis, Sebastian

    (Department of Economics, University of Klagenfurt)

  • Wagner, Martin

    (Bank of Slovenia, Ljubljana and Institute for Advanced Studies, Vienna)

Abstract

We consider integrated modiï¬ ed least squares estimation for systems of cointegrating multivariate polynomial regressions, i. e., systems of regressions that include deterministic variables, integrated processes and products of these variables as regressors. The errors are allowed to be correlated across equations, over time and with the regressors. Since, under restrictions on the parameters or in case of non-identical regressors across equations, integrated modiï¬ ed OLS and GLS estimation do not, in general, coincide, we discuss in detail restricted integrated generalized least squares estimators and inference based upon them. Furthermore, we develop asymptotically pivotal ï¬ xed-b inference, available only in case of full design and for speciï¬ c hypotheses.

Suggested Citation

  • Veldhuis, Sebastian & Wagner, Martin, 2024. "Integrated Modiï¬ ed Least Squares Estimation and (Fixed-b) Inference for Systems of Cointegrating Multivariate Polynomial Regressions," IHS Working Paper Series 54, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihswps:number54
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    File URL: https://irihs.ihs.ac.at/id/eprint/6976
    File Function: First version, 2024
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    More about this item

    Keywords

    Integrated modiï¬ ed estimation; cointegrating multivariate polynomial regression; ï¬ xed-b inference; generalized least squares;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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