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Identification robust inference in cointegrating regressions

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  • Khalaf, Lynda
  • Urga, Giovanni

Abstract

In cointegrating regressions, estimators and test statistics are nuisance parameter dependent. This paper addresses this problem from an identification-robust perspective. Confidence sets for the long-run coefficient (denoted β) are proposed that invert LR-tests against an unrestricted or a cointegration-restricted alternative. For empirically relevant special cases, we provide analytical solutions to the inversion problem. A simulation study, imposing and relaxing strong exogeneity, analyzes our methods relative to standard Maximum Likelihood, Fully Modified and Dynamic OLS, and a stationarity-test based counterpart. In contrast with all the above, proposed methods have good size regardless of the identification status, and good power when β is identified.

Suggested Citation

  • Khalaf, Lynda & Urga, Giovanni, 2014. "Identification robust inference in cointegrating regressions," Journal of Econometrics, Elsevier, vol. 182(2), pages 385-396.
  • Handle: RePEc:eee:econom:v:182:y:2014:i:2:p:385-396
    DOI: 10.1016/j.jeconom.2014.06.001
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    Cited by:

    1. David H. Bernstein & Bent Nielsen, 2019. "Asymptotic Theory for Cointegration Analysis When the Cointegration Rank Is Deficient," Econometrics, MDPI, Open Access Journal, vol. 7(1), pages 1-24, January.
    2. Arize, Augustine C. & Malindretos, John & Ghosh, Dilip, 2015. "Purchasing power parity-symmetry and proportionality: Evidence from 116 countries," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 69-85.

    More about this item

    Keywords

    Cointegration; Weak identification; Bound test; Simulation-based inference;

    JEL classification:

    • 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
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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