Testing for a Unit Root in Noncausal Autoregressive Models

Pentti Saikkonen and Rickard Sandberg

Journal of Time Series Analysis, 2016, vol. 37, issue 1, 99-125

Abstract: type="main" xml:id="jtsa12141-abs-0001"> This work develops maximum likelihood-based unit root tests in the noncausal autoregressive (NCAR) model with a non-Gaussian error term formulated by Lanne and Saikkonen (2011, Journal of Time Series Econometrics 3, Issue 3, Article 2). Finite-sample properties of the tests are examined via Monte Carlo simulations. The results show that the size properties of the tests are satisfactory and that clear power gains against stationary NCAR alternatives can be achieved in comparison with available alternative tests. In an empirical application to a Finnish interest rate series, evidence in favour of an NCAR model with leptokurtic errors is found.

Date: 2016
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Working Paper: Testing for a unit root in noncausal autoregressive models (2013)
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