Abstract
We perform Monte Carlo simulations to study the effect of increasing the frequency of observations and data span on the Johansen (J Econ Dyn Control 12(2–3):231–254, 1988; Likelihood-based inference in cointegrated vector autoregressive models, Oxford University Press, Oxford, 1995) maximum likelihood cointegration testing approach, as well as on the bootstrap and wild bootstrap implementations of the method developed by Cavaliere et al. (Econometrica 80(4):1721–1740, 2012; Econ Rev 33(5–6):606– 650, 2014). Considering systems with three and four variables, we find that when both the data span and the frequency vary, the power of the tests depend more on the sample length. We illustrate our findings by investigating th existence of long-run equilibrium relationships among four indicators prices of coffee.
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Notes
It is likely that changes over time in the structure and regulation of the coffee market may have caused structural breaks. The effect of temporal aggregation on such breaks is left as a topic for further research though.
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We are grateful to two anonymous referees for their detailed comments and suggestions. The usual disclaimer applies.
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Otero, J., Panagiotidis, T. & Papapanagiotou, G. Multivariate Cointegration and Temporal Aggregation: Some Further Simulation Results. Comput Econ 59, 59–70 (2022). https://doi.org/10.1007/s10614-020-10062-w
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DOI: https://doi.org/10.1007/s10614-020-10062-w