Economics
What is the level of spatial autocorrelation of the green economy? The case study of voivodships in Poland
Name and surname of author:
Pawel Dziekanski, Lukasz Poplawski, Jozef Glova
Keywords:
Green economy, spatial differentiation, province, spatial autocorrelation measure, local Moran’s coefficient, global Moran’s coefficient, synthetic measure
DOI (& full text):
Anotation:
In an era of resource scarcity, climate change, and environmental degradation, the growth of a green economy necessitates a new course for socio-economic development that successfully pursues sustainable development objectives. Among other things, variables related to demographics, the environment, technology, the economy, and society all contribute to its polarisation. The aim of the study is to understand what factors influence the development of the green economy in the various provinces of Poland, and how these factors may be related to each other in a spatial context. The selection of factors from 2010 to 2020 was the availability of Statistics Poland records. The study offers a spatial analysis of Poland’s green economy in its provinces in 2010, 2019, and 2020. Spatial autocorrelation was found using spatial statistical methods, and the geographical pattern of the green economy’s formation was shown. These analyses used measures of spatial autocorrelation, which allowed for the identification of spatial relationships of a particular characteristic throughout the whole research region and the connection between a particular place and nearby locations. Due to a combination of natural and geographic features, as well as the impact of socio-economic factors, each province in the nation has a unique economic climate, which determines its level of development and standard of life.
In an era of resource scarcity, climate change, and environmental degradation, the growth of a green economy necessitates a new course for socio-economic development that successfully pursues sustainable development objectives. Among other things, variables related to demographics, the environment, technology, the economy, and society all contribute to its polarisation. The aim of the study is to understand what factors influence the development of the green economy in the various provinces of Poland, and how these factors may be related to each other in a spatial context. The selection of factors from 2010 to 2020 was the availability of Statistics Poland records. The study offers a spatial analysis of Poland’s green economy in its provinces in 2010, 2019, and 2020. Spatial autocorrelation was found using spatial statistical methods, and the geographical pattern of the green economy’s formation was shown. These analyses used measures of spatial autocorrelation, which allowed for the identification of spatial relationships of a particular characteristic throughout the whole research region and the connection between a particular place and nearby locations. Due to a combination of natural and geographic features, as well as the impact of socio-economic factors, each province in the nation has a unique economic climate, which determines its level of development and standard of life.
APA Style Citation:
Dziekanski, P., Poplawski, L., & Glova, J. (2025). What is the level of spatial autocorrelation of the green economy? The case study of voivodships in Poland. E&M Economics and Management, 28(2), 25–48. https://doi.org/10.15240/tul/001/2025-2-002