We analyze the sizes of standard cointegration tests applied to data subject to linear interpolation, discovering evidence of substantial size distortions induced by the interpolation. We propose modifications to these tests to effectively eliminate size distortions from such tests conducted on data interpolated from end-of-period sampled low-frequency series. Our results generally do not support linear interpolation when alternatives such as aggregation or mixed-frequency-modified tests are possible.
The authors are grateful to Peter Phillips, an anonymous referee, and other participants of the 2013 Advances in Econometrics Conference in Honor of Peter Phillips for useful comments. The first author acknowledges support of a Marie Curie FP7-PEOPLE-2010-IIF grant.
Ghysels, E. and Isaac Miller, J. (2014), "On the Size Distortion from Linearly Interpolating Low-frequency Series for Cointegration Tests", Essays in Honor of Peter C. B. Phillips (Advances in Econometrics, Vol. 33), Emerald Group Publishing Limited, Bingley, pp. 93-122. https://doi.org/10.1108/S0731-905320140000033004
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