Unit Root in Unemployment - New Evidence from Nonparametric Tests
We 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.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- G. William Schwert, 1988.
"Tests For Unit Roots: A Monte Carlo Investigation,"
NBER Technical Working Papers
0073, National Bureau of Economic Research, Inc.
- Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
- 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.
- Magnus Gustavsson & Par Osterholm, 2006. "Hysteresis and non-linearities in unemployment rates," Applied Economics Letters, Taylor & Francis Journals, vol. 13(9), pages 545-548.
- 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.
When requesting a correction, please mention this item's handle: RePEc:vie:viennp:0915. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Paper Administrator)
If references are entirely missing, you can add them using this form.