Unit root in unemployment - new evidence from nonparametric tests
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Jürgen Holl & Robert M. Kunst, 2009. "Unit Root in Unemployment - New Evidence from Nonparametric Tests," Vienna Economics Papers 0915, University of Vienna, Department of Economics.
References listed on IDEAS
- 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.
- 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, July.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Luis A. Gil-Alana & Antonio Moreno & Seonghoon Cho, 2012.
"The Deaton paradox in a long memory context with structural breaks,"
Taylor & Francis Journals, vol. 44(25), pages 3309-3322, September.
- Luis A. Gil-Alana & Antonio Moreno & Seonghoon Cho, 2009. "The Deaton paradox in a long memory context with structural breaks," Faculty Working Papers 03/09, School of Economics and Business Administration, University of Navarra.
- Luis Alberiko Gil-Alana & Antonio Moreno & Seonghoon Cho, 2011. "The Deaton paradox in a long memory context with structural breaks," Post-Print hal-00711450, HAL.
More about this item
- 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; Diffusion Processes
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:apeclt:v:18:y:2011:i:6:p:509-512. 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: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/RAEL20 .