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Bayesian Unit Root Test for Panel Data

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  • Jitendra Kumar
  • Anoop Chaturvedi
  • Umme Afifa

Abstract

Present paper studies the panel data auto regressive (PAR) time series model for testing the unit root hypothesis. The posterior odds ratio (POR) is derived under appropriate prior assumptions and then empirical analysis is carried out for testing the unit root hypothesis of Net Asset Value of National Pension schemes (NPS) for different fund managers. The unit root hypothesis for the model with linear time trend and linear time trend with augmentation term is carried out. The estimated autoregressive coefficient is far away from one in case of linear time trend only so, testing is not executed but in consideration of augmentation term, it is close to one. Therefore, we performed the unit root hypothesis testing using the derived POR. In all cases unit root hypothesis is rejected therefore all NPS series are concluded trend stationary.

Suggested Citation

  • Jitendra Kumar & Anoop Chaturvedi & Umme Afifa, 2017. "Bayesian Unit Root Test for Panel Data," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 60(1), pages 74-95.
    • Handle: RePEc:eei:journl:v:60:y:2017:i:1:p:74-95
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    Keywords

    Panel data; Stationarity; Autoregressive time series; Unit root; Posterior odds ratio; New Pension Scheme; Net Asset Value.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other

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