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Fully Modified Estimation in Cointegrating Polynomial Regressions: Extensions and Monte Carlo Comparison

Author

Listed:
  • Yicong Lin

    (Vrije Universiteit Amsterdam)

  • Hanno Reuvers

    (Erasmus University Rotterdam)

Abstract

We study a set of fully modified (FM) estimators in multivariate cointegrating polynomial regressions. Such regressions allow for deterministic trends, stochastic trends, and integer powers of stochastic trends to enter the cointegrating relations. A new feasible generalized least squares estimator is proposed. Our estimator incorporates: (1) the inverse autocovariance matrix of multidimensional errors and (2) second-order bias corrections. The resulting estimator has the intuitive interpretation of applying a weighted least squares objective function to filtered data series. Moreover, the required second-order bias corrections are convenient byproducts of our approach and lead to a conventional asymptotic inference. Based on different FM estimators, multiple multivariate KPSS-type of tests for the null of cointegration are constructed. We then undertake a comprehensive Monte Carlo study to compare the performance of the FM estimators and the related tests. We find good performance of the proposed estimator and the implied test statistics for linear hypotheses and cointegration.

Suggested Citation

  • Yicong Lin & Hanno Reuvers, 2022. "Fully Modified Estimation in Cointegrating Polynomial Regressions: Extensions and Monte Carlo Comparison," Tinbergen Institute Discussion Papers 22-093/III, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20220093
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    References listed on IDEAS

    as
    1. Wagner, Martin & Hong, Seung Hyun, 2016. "Cointegrating Polynomial Regressions: Fully Modified Ols Estimation And Inference," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1289-1315, October.
    2. Choi, In & Saikkonen, Pentti, 2010. "Tests For Nonlinear Cointegration," Econometric Theory, Cambridge University Press, vol. 26(3), pages 682-709, June.
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    More about this item

    Keywords

    Cointegrating Polynomial Regression; Cointegration Testing; Fully Modified Estimation; 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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