Unit Root in Unemployment - New Evidence from Nonparametric Tests
AbstractWe apply range unit-root tests to OECD unemployment rates and compare the results to conventional tests. By simulations, we nd that unemployment is represented adequately by a new nonlinear transformation of a serially-correlated I(1) process.
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Bibliographic InfoPaper provided by University of Vienna, Department of Economics in its series Vienna Economics Papers with number 0915.
Date of creation: Oct 2009
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Web page: http://www.univie.ac.at/vwl
Other versions of this item:
- Jurgen Holl & Robert Kunst, 2011. "Unit root in unemployment - new evidence from nonparametric tests," Applied Economics Letters, Taylor & Francis Journals, vol. 18(6), pages 509-512.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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- Schwert, G William, 1989.
"Tests for Unit Roots: A Monte Carlo Investigation,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 7(2), pages 147-59, April.
- Felipe Aparicio & Alvaro Escribano & Ana E. Sipols, 2006. "Range Unit-Root (RUR) Tests: Robust against Nonlinearities, Error Distributions, Structural Breaks and Outliers," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(4), pages 545-576, 07.
- Magnus Gustavsson & Par Osterholm, 2006. "Hysteresis and non-linearities in unemployment rates," Applied Economics Letters, Taylor & Francis Journals, vol. 13(9), pages 545-548.
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