Poli Roukova
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Poli Roukova has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Aleksandra Ravnachka
Institute for Population and Human Studies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
1 shared publication - Boris Kazakov
National Institute of Geophysics, Geodesy, and Geography-Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
1 shared publication - Dessislava Poleganova
National Institute of Geophysics, Geodesy, and Geography-Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
1 shared publication - Marina Raykova
Department of Geography, National Institute of Geophysics, Geodesy and Geography, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 3, 1113 Sofia, Bulgaria
1 shared publication - Nadezhda Ilieva
National Institute of Geophysics, Geodesy, and Geography-Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
1 shared publication - Velimira Stoyanova
National Institute of Geophysics, Geodesy, and Geography-Bulgarian Academy of Sciences (NIGGG-BAS), 1113 Sofia, Bulgaria
1 shared publication
Latest Publications
- Open Access
Spatial Disparities in the Bulgarian Labour Market: A Multivariate and Spatial Autocorrelation Analysis (2021–2024)
The transformation of the labour market is a significant challenge for sustainable regional development, especially in countries with pronounced socioeconomic inequalities. This study aims to analyse the spatial disparities in the Bulgarian labour market at the regional level (NUTS 3, districts) for the period of 2021–2024, combining descriptive spatial analysis, multidimensional cluster analysis, and Local Indicator of Spatial Association (Local Moran’s I-LISA). The analysis is based on three key indicators: employment rates, unemployment rates, and the relative wage index, calculated against the national average. The results of the descriptive analysis reveal clear spatial imbalances, with low labour income persisting in many districts despite relatively high employment rates. The cluster analysis identifies four types of labour markets with specific socioeconomic profiles, confirming that the spatial disparities are a result of specific combinations of indicators and economic specialisation at the regional level. The LISA analysis further reveals the existence of spatially stable cores of vulnerability and local spatial anomalies that highlight the importance of regional context and spatial proximity. The results indicate the need for a spatially differentiated approach in regional policies in line with the objectives of SDG8, SDG10, the European Pillar of Social Rights, and the EU’s cohesion policy.
Open AccessSpatial Disparities in the Bulgarian Labour Market: A Multivariate and Spatial Autocorrelation Analysis (2021–2024)
The transformation of the labour market is a significant challenge for sustainable regional development, especially in countries with pronounced socioeconomic inequalities. This study aims to analyse the spatial disparities in the Bulgarian labour market at the regional level (NUTS 3, districts) for the period of 2021–2024, combining descriptive spatial analysis, multidimensional cluster analysis, and Local Indicator of Spatial Association (Local Moran’s I-LISA). The analysis is based on three key indicators: employment rates, unemployment rates, and the relative wage index, calculated against the national average. The results of the descriptive analysis reveal clear spatial imbalances, with low labour income persisting in many districts despite relatively high employment rates. The cluster analysis identifies four types of labour markets with specific socioeconomic profiles, confirming that the spatial disparities are a result of specific combinations of indicators and economic specialisation at the regional level. The LISA analysis further reveals the existence of spatially stable cores of vulnerability and local spatial anomalies that highlight the importance of regional context and spatial proximity. The results indicate the need for a spatially differentiated approach in regional policies in line with the objectives of SDG8, SDG10, the European Pillar of Social Rights, and the EU’s cohesion policy.