Numerical recipes: the art of scientific computing
Numerical recipes: the art of scientific computing
Forecasting the US unemployment rate
Computational Statistics & Data Analysis - Special issue: Computational econometrics
Estimation of fractional integration in the presence of data noise
Computational Statistics & Data Analysis
Multivariate modelling of long memory processes with common components
Computational Statistics & Data Analysis
Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH
Computational Statistics & Data Analysis
Multiscale spectral analysis for detecting short and long range change points in time series
Computational Statistics & Data Analysis
Type I and type II fractional Brownian motions: A reconsideration
Computational Statistics & Data Analysis
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A general procedure for fractional integration and structural breaks at unknown points in time is used, which allows for different orders of integration and deterministic components in each subsample. First, the procedure is extended to the non-linear case, and it is shown by means of Monte Carlo experiments to perform well in a non-linear environment. Second, it is applied to test for a single break in the unemployment rate in the US, the UK and Japan. The results shed some light on the empirical relevance of alternative unemployment theories for these countries. Specifically, a structuralist interpretation appears more appropriate for the US and Japan, whilst a hysteresis model accounts better for the UK experience (and also for the Japanese one in the second subsample). These findings are interpreted in terms of structural instability in labour markets with different features.