Maximum duration of fixed-term contracts (WoL, V2)
| Quick info | |
|---|---|
| Data type | Numeric |
| Scale | Metric |
| Value labels | not applicable |
| Technical name | labor_equity_fix_dura |
| Category | Labour and labour market |
| Label | Maximum duration of fixed-term contracts (WoL, V2) |
| Related indicators |
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The variable measures the maximum duration of temporary employment relationships, and thus the potential for circumventing employment protection legislation with regard to the maximum duration.
The possibility of long-term precarious employment and consequently the lack of protection of those affected depends largely on whether and to what extent the use of fixed-term contracts is limited in time – at least as far as the alternative of permanent employment is concerned. From the employee's perspective it is ideal to be able to decide when the employment relationship ends and not to be at the mercy of the employer from day one. At most, a maximum limit of a few months for seasonal jobs leaves the protection against dismissal largely untouched. If the maximum limit is more than a year, from the employee's perspective there is a not insignificant increase in precariousness, which, with a maximum limit of 10 years, is equivalent to an absence of protection against dismissal. The coding values are set up accordingly.
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 E.10 in the Worlds of Labour (WoL) SPE template - originally CBR-LRI variable 6.
Coding rules
Measures the maximum cumulative duration of fixed-term contracts permitted by statutory law before the employment is deemed to be permanent. The score is normalised from 0 to 1, with higher values indicating a lower permitted duration. The score equals 1 if the maximum limit is less than 1 year and 0 if it is 10 years or more or if there is no legal limit.
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
