TESTING FOR LINEARITY IN REGRESSIONS WITH I(1) PROCESSES (2016)
Author: Yoichi Arai
Abstract
We propose a
generalized version of the RESET test for linearity in regressions with I(1) processes
against various nonlinear alternatives and no cointegration. The proposed test
statistic for linearity is given by the Wald statistic and its limiting
distribution under the null hypothesis is shown to be a x² distribution with a
"leads and lags" estimation technique. We show that the test is
consistent against a class of nonlinear alternatives and no cointegration.
Finite-sample simulations show that the empirical size is close to the nominal
one and the test succeeds in detecting both nonlinearity and no cointegration.
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