Spatio‑temporal Modelling of the Influence of the Number of Business Entities in Selected Urban Centres on Unemployment in the Kujawsko‑Pomorskie Voivodeship

Abstract

<jats:p>The paper presents the analysis of the spatial and spatio‑temporal tendencies and dependence in matters related to the situation in the labour market of the Kujawsko‑Pomorskie Voivodeship across municipalities in the period of 2004–2015. The aim of the investigation is to verify whether, in the presence of the dependence, investing (through a growing number of enterprises) in the development of selected urban centres with a high level of unemployment can significantly reduce the unemployment rate in the whole province. The assessment of the situation in the labour market for each of the municipalities is made with the use of two characteristics, i.e. the share of registered unemployed persons in the number of the working age population and the number of business entities per 10,000 working age population. From the methodological point of view, the values of the variables are treated as realisations of spatial and spatio‑temporal stochastic processes. The spatial and spatio‑temporal tendencies and dependence were investigated using the concept of spatial and spatio‑temporal trends and spatial autocorrelation. Additionally, spatial autoregressive models for individual processes and spatial models of the dependence of unemployment on the number of business entities, for each year of the investigated period, were estimated and verified. The specification of spatio‑temporal models of unemployment, including the model which takes into consideration spatial shifts and time lags of the dependence, was carried out. The models were used for simulating the level of unemployment in the province assuming some growth in the number of business entities in selected urban centres.</jats:p>

Economic convergence in the European Union at the regional level with particular attention to the impact of the COVID-19 pandemic – a spatio-temporal approach

“…Moreover, β 1 ,β 2 ,β 3 are the structural parameters of the model, and ε i,t is defined as above. In turn, w ij,t are elements of the block matrix of spatio-temporal connections, which is expressed as (Szulc and Jankiewicz, 2018):…”