Geographic Concentration of the Healthcare Industry: �Macroeconomic Evidence from Polish Voivodeships
Scott W. Hegerty, Ph.D.
Professor of Economics, NEIU
Managing Across Borders in Times of Uncertainty: Sustainability and Digital Transformation
March 13, 2026
Main idea: Geographic Concentration
Is industry employment concentrated in certain areas?
Some industries are local (such as mining or fishing)
Others are concentrated in urban areas
Still more: Other factors (history, some kind of “push” or policy)
Able to measure empirically:� Concentration� Connection� Causes
Main idea: Geographic Concentration
This study: � Calculates and maps Location Quotients for Health and a few other sectors and subsectors within these
Measures spatial autocorrelation for 16 voivodeships
Estimates underlying factors via regression analysis
�
A few previous studies
Kowalski and Marcinkowski (Urban Planning Studies, 2012)� Cluster initiatives/ICT sector
Namyślak and Spallek (GeoJournal, 2022) Creative Clusters, regions
…a number of specific industries
Szczepaniak and Drożdż (2023) Food
Kocaj and Murzyn-Kupisz (2024) Clothing
Domaṅski and Gwosdz (2018) Automotive
�
Location Quotients
Employment data (Statistics Poland, h/t AM Kowalski)
19 sectors�73 subsectors
16 regions +2
R&D Expenditure
% Urban
Some Covariates, by Region
Spatial Autocorrelation
Between a value in each region and an average of neighbors
How to define a neighbor?
Here, “Queen contiguity” of order one (anything that touches)
Moran’s I:
Levels and/or spatial autocorrelation
Can have high connectivity or high levels of concentrations
or low connectivity/low levels
Can have significant spatial autocorrelation
or be relatively independent geographically.
🡪 Can have any combination of levels and autocorrelation
High LQ if > 1.25 Autocorrelation if p < 0.05
Location Quotients: Levels (Sectors)
Spatial Autocorrelation: Results
Only health–sector and two subsectors
Otherwise little spatial autocorrelation
Levels and/or spatial autocorrelation
Sectors:
Health: Low concentrations, but autocorrelated
Professional/Scientific/Technical and Information/Communication:� Some regions (Southern Poland) concentrated; not autocorrelated
Health Subsectors: More concentrated
Other Subsectors: Less concentrated?
Subsector LQs
Health/Social Services:� High LQs, East and West (Health):
(Also autocorrelated)
Others: Fewer voivodeships with concentrations
Overall
Health: Spatial autocorrelation for sector and both health subsectors� Low concentration levels at sector level
- More concentrations at subsector level
Others:
Not autocorrelated
Not much concentration at sector or subsector level
…Extend to all 19 sectors, 73 subsectors (future study)
Regression Analysis
Regular OLS to uncover drivers of regional LQs
DVs: LQs in Health (sector and subsectors)
Explanatory variables (source: GUS):
R&D/Innovation spending (2023)
Regional GDP
% Urban
Deaths (Circulatory system/cancer)
Number of doctors
Regression Results
Controlling for percent urban:
Health needs drive health spending, but only at the sector level
Number of doctors significant for sector and “healthcare subsector”
Conclusions
Difference between Health (/Social Services) sector and others�(lower LQs for sector, higher for subsectors), �more spatial autocorrelation)
Health needs (circulator-system deaths) worthy of further explorations
Extensions include more sectoral and regional analysis
Thank you!