Difference between revisions of "Redundancy selection"

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<ul>
 
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<li>0 = employers don't have to follow priorty rules prior to dismissing for redundancy</li>
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<li>0 = employers does not have to follow priorty rules prior to dismissing for redundancy</li>
 
<li>1 = by law or binding collective agreement the employer must follow priority
 
<li>1 = by law or binding collective agreement the employer must follow priority
 
rules based on seniority, marital status, number or dependants, etc., prior to dismissing
 
rules based on seniority, marital status, number or dependants, etc., prior to dismissing

Revision as of 17:35, 12 March 2020

Quick info
Data type Numeric
Scale Metric
Value labels
  • 0 = employers does not have to follow priorty rules prior to dismissing for redundancy
  • 1 = by law or binding collective agreement the employer must follow priority rules based on seniority, marital status, number or dependants, etc., prior to dismissing for redundancy
  • quasi-metric scale; further gradations between 0 and 1 reflect changes in the strength of the law

Technical name labor_redund_select
Category Labour and labour market
Label Redundancy selection
Related indicators

This CBR-LRI indicator measures to what extent employers have to follow priority rules based on issues such as seniority, marital status, number of dependants etc. prior to a dismissal for redundancy.


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 ranges from "0" to "1" where "0" corresponds to not having to follow priority rules and "1" to having to follow priority rules prior to a dismissal for redundancy, and gradations between the two values reflect gradtions in the strength of law. For country-specific information see Adams, Bishop and Deakin (2016).


Bibliographic info

Citation:


Related publications:



Misc

Project manager(s):
  • Irene Dingeldey, Ulrich Mückenberger; research fellows: Heiner Fechner, Jean-Yves Gerlitz, Jenny Hahs


Data release:


Revisions:

Sources