Difference between revisions of "Legally mandated notice period (CBR-LRI)"
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Revision as of 16:40, 22 July 2021
| Quick info | |
|---|---|
| Data type | Numeric |
| Scale | Metric |
| Value labels |
normalised scale ranging from 0 to 1 |
| Technical name | labor_dis_not_per |
| Category | [[Labour and labour market]] |
| Label | Legally mandated notice period |
| Related indicators | |
This CBR-LRI indicator measures the length of notice, in weeks, that has to be given to a worker with 3 years’ employment.
Coding rules
The CBR-LRI is a leximetric dataset on employment protection. It quantifies the strength of protection expressed in labour law and functional equivalents such as administrative regulation and collective agreements (see Adams et al. 2017). The scale of the indicator was normalised so that "0" corresponds to 0 weeks and "1" to 12 weeks. For country-specific information see Adams, Bishop and Deakin (2016).
Bibliographic info
Citation:- Adams, Zoe, Parisa Bastani, Louise Bishop, and Simon Deakin. 2017. "The CBR-LRI Dataset: Methods, Properties and Potential of Leximetric Coding of Labour Law." International Journal of Comparative Labour Law and Industrial Relations 33 (1): 59–91. http://kluwerlawonline.com/abstract.php?area=Journals&id=IJCL2017004
- Adams, Zoe, Louise Bishop, and Simon Deakin. 2016. CBR Labour Regulation Index (Dataset of 117 Countries). Cambridge: Centre for Business Research. https://www.repository.cam.ac.uk/bitstream/handle/1810/263766/CBR_LRI_Dataset_Codebook_Methodology_2017_pdf.pdf?sequence=16&isAllowed=y
- Deakin, Simon, Jonas Malmberg, and Prabirjit Sarkar. 2014. "How do labour laws affect unemployment and the labour share of national income? The experience of six OECD countries, 1970-2010". International Labour Review 153 (1): 1-27. https://onlinelibrary.wiley.com/doi/epdf/10.1111/j.1564-913X.2014.00195.x
Misc
Project manager(s):- Jean-Yves Gerlitz
- Andrea Schäfer
- No revisions yet
Sources
- Deakin, Simon, John Armour, and Mathias Siems. 2017. "CBR Leximetric Datasets [updated] [Dataset]". https://doi.org/10.17863/CAM.9130
