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Can you do the wrong thing and still be right? Hypothesis testing in I(2) and near-I(2) cointegrated VARs

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  • Francesca Di Iorio
  • Stefano Fachin
  • Riccardo Lucchetti

Abstract

In this paper, we investigate the small-sample performance of LR tests on long-run coefficients in the I (2) model; we focus on a comparison between I (2) and near- I (2) data, i.e. I (1) data with a second root very close to unity, and report the results of some Monte Carlo experiments. With near- I (2) data, the finite-sample properties of the tests are (i) similar to those found with genuine I (2) data, (ii) systematically superior to those of the analogous tests constructed in the I (1) model, even if the latter is, in principle, correctly specified and the former is not. Therefore, there seems to be strong support to the idea that, in practice, modelling near- I (2) data using the I (2) model may be a good idea, despite the inherent misspecification.

Suggested Citation

  • Francesca Di Iorio & Stefano Fachin & Riccardo Lucchetti, 2016. "Can you do the wrong thing and still be right? Hypothesis testing in I(2) and near-I(2) cointegrated VARs," Applied Economics, Taylor & Francis Journals, vol. 48(38), pages 3665-3678, August.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:38:p:3665-3678
    DOI: 10.1080/00036846.2016.1142660
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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