This paper proposes a nonlinear unit root test based on the artificial neural network-augmented Dickey-Fuller (ANN-ADF) test for testing hysteresis in unemployment. In this new unit root test, the linear, quadratic and cubic componentes of the neural network process are used to capture the nonlinearity in the time-series data. Fractional integration methods, based on linear and nonlinear trends are alo used in the paper. By considering five European countries such as France, Italy, Netherlands, Sweden and the United Kingdom, the empirical findings indicate that there is still hysteresis in these countries. Among batteries of unit root tests applied, both the ARNN-ADF and fractional integration tests fail to reject the hypothesis of unemployment hysteresis in all the countries.
A new unit root analysis for testing hysteresis in unemployment
Luis A. Gil-Alana
OlaOluwa Simon Yaya
Ahamuefula Ephraim Ogbonna
Oxford Bulletin of Economics and Statistics