Annual leave entitlements
| Quick info | |
|---|---|
| Data type | Numeric |
| Scale | Metric |
| Value labels | not applicable |
| Technical name | labor_ann_lea_ent |
| Category | Labour and labour market |
| Label | Annual leave entitlements |
| Related indicators | |
This variable measures the normal length of annual paid leave guaranteed by (statutory) law or collective agreement. The same score is given for laws and for collective agreements which are de facto binding on most of the workforce (as in the case of systems which have extension legislation for collective agreements). The normalised scale ranges from 0 to 1 (0 = 0 days and 1 = 30 days). Paid vacation is essential for employees to protect their health and participate in social and cultural life. Public holidays and entitlements based on seniority (length of service with the company) are not included.
Coding rules
The score is normalised on a 0-1 scale, with a leave entitlement of 30 days equivalent to a score of 1 (see Adams et al. 2023).
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There is a break in the time series due to coverage of legal text:
- 1880-1969 [1880-1979/89 [see 1]] + 35 additional countries [see 2]: Values based on statutory law only.
- 1970-2022 [1980-2022 [see 3]]: Values - based on law or collective agreement - which have been extracted from CBR Leximetric Datasets (see Deakin et al 2023).
- 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://www.repository.cam.ac.uk/handle/1810/263766.2
- 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
- Responsible for data editing and entry: Andrea Schäfer (2021-2025), Jenny Hahs (2018-21), Jean-Yves Gerlitz (2018-20)
- Responsible for data coding: Heiner Fechner (2018-2025), Marina Carlino (2022-2025)
- Principal Investigator: 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
- Version 0.001: Initial release
- Version 0.002: Updated with files from CBR-LRI 2023 v2*
- The sources used for the WoL values can be found as a variable called 'source' when you download the data. Further information is available via the country templates published in GESIS data archive in december 2024.
- 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://www.repository.cam.ac.uk/handle/1810/263766.2
The comparability of the values over time is therefore limited.
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[1] Applies to the following countries: Namibia, Zimbabwe.
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[2] Applies to all countries not covered by CBR Leximetric Datasets (see Deakin et al 2023): Albania, Benin, Bosnia/Herzegovina, Burkina Faso, Burundi, Central African Republic, Chad, Congo, El Salvador, Eritrea, Gambia, Guatemala, Guinea, Hong Kong, Haiti, Iraq, Jamaica, Kuwait, Laos, Lebanon, Liberia, Libya, Madagascar, Malawi, Mauritania, Mozambique, Nepal, Niger, North Korea, Papua New Guinea, Sierra Leone, Somalia, South Sudan, Tajikistan, Togo, Trinidad and Tobago, Turkmenistan and Uzbekistan for all times points available.
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[3] Applies to the following countries: (1991-2022) Armenia, Azerbaijan, Belarus, Croatia, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Macedonia, Moldova, Serbia, Slovenia, Ukraine; (1990-2022) Bulgaria, Czech Republic, Hungary, Latvia, Lithuania, Namibia, Poland, Romania, Vietnam; (1992/3/5-2022) Cambodia, Russia, Slovakia, Yemen; (1980/6-2022) China, United Arab Emirates, Zimbabwe; (2006-2022) Montenegro. St. Lucia and Malta are not included in the data.
Important note: The values of the variables are based on values stored in extensive Excel tables. In addition to the values, the legal excerpts and sources of these excerpts are also documented there. The values in the Excel tables differ (depending on the version) from the values in the WESIS database. This applies in particular to the values of variables that are based on the original CBR-LRI data. The reason for this difference is a different range of data material used for coding (see break in series) and different legal interpretations by the coders.
Bibliographic info
Citation: Carlino, Marina, Irene Dingeldey, Heiner Fechner, Ulrich Mückenberger and Andrea Schäfer (2024). WoL Leximetric Datasets [Updated 2024]. University of Bremen.
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