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Vector Error Correction Models with Stationary and Nonstationary Variables

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  • Pu Chen

    (Melbourne Institute of Technology, Australia)

Abstract

Vector Error Correction Models (VECM) have become a standard tool in empirical economics for analyzing nonstationary time series data because they integrate two key concepts in economics: equilibrium and dynamic adjustment in a single model. The current standard VECM procedure is limited to time series data with the same degree of integration, i.e., all I(1) variables. However, empirical studies often involve time series data with different de‐grees of integration, necessitating the simultaneous handling of I(1) and I(0) time series. This paper extends the standard VECM to accommodate mixed I(1) and I(0) variables. The conditions for the mixed VECM are derived, and consequently, we present a test and estimation for the mixed VECM.

Suggested Citation

  • Pu Chen, 2024. "Vector Error Correction Models with Stationary and Nonstationary Variables," Economic Analysis Letters, Anser Press, vol. 3(2), pages 34-47, June.
    • Handle: RePEc:bba:j00004:v:3:y:2024:i:2:p:34-47:d:299
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    References listed on IDEAS

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    6. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
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