Law imposes substantive constraints on dismissal (WoL, V2)
| Quick info | |
|---|---|
| Data type | Numeric |
| Scale | Metric |
| Value labels | not applicable |
| Technical name | labor_dism_constr_subst |
| Category | Labour and labour market |
| Label | Law imposes substantive constraints on dismissal (WoL, V2) |
| Related indicators | |
Measures the strength of substantive employment protection.
Employees are existentially dependent on the income from their employment relationship, so termination of this by the employer also means the termination of the employee's ability to make a living. This is the reason for the special significance of protection against dismissal.
Substantive employment protection draws boundaries regarding the reasons for which an employee can be dismissed. The more the decision to dismiss an employee is removed from the employer's discretion, the higher the level of protection. The level of protection is highest when employees can only be dismissed for serious misconduct, and it is thus in their hands to prevent dismissal by acting in accordance with the contract.
This variable is derived and minimally modified from the CBR Labour Regulation Index Dataset (‘CBR-LRI’), which provides data on employment law across 117 countries spanning the years from (in most instances) 1970 to 2022, with the exception of post-socialist countries (refer to Adams et al. 2017, 2023). The current CBR-LRI data points were reviewed, and any discrepancies in values were adjusted in accordance with the WoL coding rules. Additionally, data points from before 1970 or equivalent timeframes for former Soviet bloc countries were included (cf. Fechner/Carlino 2025). In addition to the 115 countries with populations exceeding 500,000 as classified by CBR-LRI, 37 more countries have been included (cf. Fechner/Carlino 2025). Core differences concerning the original CBR-LRI data:
- The CBR Labour Regulation Index Dataset was developed by analysing legal provisions, collective agreements (if generally binding or containing national standards) and pertinent court rulings, sourced from secondary materials, national legal databases, and ILO NATLEX data (cf. Adams et al. 2017, 2023). WoL exclusively codes statutory law, resulting in modifications to outcomes that include collective agreements and court decisions that define entitlements.
Variable S.11 in the Worlds of Labour (WoL) SPE template - originally CBR-LRI variable 20.
Coding rules
Equals 1 if dismissal is only permissible for serious misconduct or fault of the employee. Equals 0.67 if dismissal is lawful according to a wider range of legitimate reasons (misconduct, lack of capability, redundancy, etc.). Equals 0.33 if dismissal is permissible if it is ‘just’ or ‘fair’ as defined by case law. Equals 0 if employment is at will (i.e., no-cause dismissal is normally permissible). Scope for gradations between 0 and 1 to reflect changes in the strength of the statutory law.
For detailed coding rules, please consult Fechner/Carlino 2025.
Bibliographic info
Citation: Fechner, Heiner and Marina Carlino (2025). Worlds of Labour (WoL) Leximetric Dataset. University of Bremen.
Related publications: Adams, Zoe, Bhumika Billa, Louise Bishop, Simon Deakin and Tvisha Shroff (2023). CBR Labour Regulation Index (Dataset of 117 Countries, 1970-2022) - Codes and Sources. Centre for Business Research, University of Cambridge. at: https://doi.org/10.17863/CAM.9130.2
Carlino, Marina, Fechner, Heiner, and Schäfer, Andrea (2025). Using leximetrics for coding legal segmentation in employment law: The development and potential of the Worlds of Labour database. In I. Dingeldey, H. Fechner, & U. Mückenberger (Eds.), Constructing Worlds of Labour. Coverage and Generosity of Labour Law as Outcomes of Regulatory Social Policy. Palgrave Macmillan. pp.53-83
Deakin, Simon, Johna Armour and Mathias Siems (2023). CBR Leximetric Datasets [Updated 2023]. Apollo - University of Cambridge Repository. https://doi.org/10.17863/CAM.9130.2
Dingeldey, Irene, Heiner Fechner, Jean-Yves Gerlitz, Jenny Hahs, Ulrich Mückenberger, Worlds of Labour: Introducing the Standard-Setting, Privileging and Equalising Typology as a Measure of Legal Segmentation in Labour Law, Industrial Law Journal, Volume 51, Issue 3, September 2022, Pages 560–597, https://doi.org/10.1093/indlaw/dwab016
Fechner, Heiner, and Marina Carlino (2025). Coding Legal Segmentation in Employment Law. The Worlds of Labour (WoL) Dataset. SFB 1342 Technical Paper Series, 22. Bremen: SFB 1342. https://doi.org/10.26092/elib/4191
Misc
Project manager(s): Responsible for data coding: Heiner Fechner (2018-2025), Marina Carlino (2022-2025).
Responsible for data editing, description (WESIS) and entry: Heiner Fechner (2025), Andrea Schäfer (2021-2025), Jenny Hahs (2018-21), Jean-Yves Gerlitz (2018-20).
Principal Investigators: Irene Dingeldey, Ulrich Mückenberger.
Student assistants (alphabetical ordering): Max Anders, Julia Bode, Jessica Bonn, Daniel Euler, Jan-Christopher Floren, Maxime Fischer, Jennifer Götte, Eliko Hagen, Désirée Hoppe, Irina Kyburz, Alexandra Kojnow, Tarek Mahmalat, Karolin Meyer, Oguz Mermut, Johanna Nold, Tanusha Pali, Gerrit Pantel, Johannes Ramsauer, Max Sudhoff, Kristina Walter, Caroline Zambiasi.
Data release: Version 0.001: Initial release December 2025.
Revisions: No revisions yet.
This is the first version of the dataset of the thoroughly revised Version 2 WoL template; for the first time, all variables including those originally stemming from CBR-LRI have been coded/revised under WoL criteria. A preliminary version with compiled data (CBR-LRI and WoL) has been published in WeSIS marked by "CBR-LRI-based" and "WoL, V1".
Sources
Own coding, partially based on coding by CBR-LRI.
Fechner, Heiner, and Marina Carlino (2025). Coding Legal Segmentation in Employment Law. The Worlds of Labour (WoL) Dataset. SFB 1342 Technical Paper Series, 22. Bremen: SFB 1342. https://doi.org/10.26092/elib/4191
Partially identical (after revision by WoL) with the original CBR-LRI coding, to be found in:
Deakin, Simon, Johna Armour and Mathias Siems (2023). CBR Leximetric Datasets [Updated 2023]. Apollo - University of Cambridge Repository. https://doi.org/10.17863/CAM.9130.2
