JOURNAL ARTICLE
Spatial wage curve and the role of external factors over time.
Published In: Economics of Transition & Institutional Change, 2025, v. 33, n. 2. P. 413 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Majchrowska, Aleksandra; Broniatowska, Paulina 3 of 3
Abstract
This study attempts to answer the question of how strongly the situation in local and neighbouring labour markets affects the level of wages in the local labour market. To answer it we use the wage curve concept. We estimate the wage curve that includes spatial effects and check the stability of the relationships over time. We concentrate on 380 local labour markets in Poland. The research period covers 2005–2021, and spatial panel models are used. Our estimates confirm the existence of the statistically significant and negative relationship between average wages and the situation in the local labour market in Poland with an estimated elasticity of −0.06. Moreover, we confirm the existence of the spatial wage curve in Poland in the 2005–2021 period. Both direct (local) and indirect (spatial) effects are statistically significant and negative on average in the analysed period. The total effects of unemployment rate wages vary from −0.06 to −0.08 depending on the spatial matrix used. Additionally, our research indicates several macroeconomic and institutional factors which are important in shaping wages. Lastly, we find that the elasticity of wages with respect to the unemployment rate is not stable over time. The relationship between unemployment and average wages has strongly weakened. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Economics of Transition & Institutional Change. 2025/04, Vol. 33, Issue 2, p413
- Document Type:Article
- Subject Area:Economics
- Publication Date:2025
- ISSN:2577-6975
- DOI:10.1111/ecot.12432
- Accession Number:183953916
- Copyright Statement:Copyright of Economics of Transition & Institutional Change is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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