Małgorzata Markowska

The Influence of Upper Level NUTS on Lower Level Classification of EU Regions

The Nomenclature of Territorial Units for Statistics or Nomenclature of Units for Territorial Statistics (NUTS) is a geocode standard for referencing the subdivision of countries for statistical purposes. It covers the member states of the European Union. For each EU member country, a hierarchy of three levels is established by Eurostat. In 27 EU countries we have 97 regions at NUTS1, 271 regions at NUTS2 and 1,303 regions at NUTS3. They are subject of many statistical analysis involving clustering methods. Having a partition of units on a given level, we can ask the question, whether this partition has been influenced by the upper level division of Europe. For example, after finding groups of homogeneous levels of NUTS 2 regions we would like to know if the partition has been influenced by differences between countries. In the paper we propose a procedure for testing the statistical significance of influence of upper level units on a given partition. If there is no such influence, we can expect that the number of between-groups borders which are also country borders should have a proper probability distribution. A simulation procedure for finding this distribution and its critical values for testing significance is proposed in this paper. The real data analysis shown as an example deals with the innovativeness of German districts and the influence of government regions on innovation processes.

Ocena udziału sektorów w zróżnicowaniu struktur zatrudnienia w Warszawie i powiatach sąsiadujących w latach 2005–2014

The aim of the paper is the identification of differences in employment structure (from the point of view of shape and scale), in dynamic perspective, in Warsaw and neighbouring districts. Shares of agriculture, industry, trade, financial services and other services in difference between Warsaw city and the following districts: legionowski, minski, otwocki, wolominski, piaseczynski, pruszkowski and warszawski zachodni, have been evaluated. The analysis is based on data from the period of 2005–2014. Two statistical measures have been used: URij which enables to estimate the share of i-th element in dissimilarities of two structures with respect to size, and UKij with respect to shape. The results obtained make it possible to compare sectors in a district, or to compare districts for a given sector of economy. As far as the differences in the size of structure are concerned, Warsaw dominated, and the hierarchy of districts was very stable, except for piaseczynski district. In the analysis of the shape of employment structure we have found significantly higher shares of industry and agriculture in particular districts, as compared with Warsaw city. Changes in the influence of financial services appeared more random and were difficult to interpret. Our results advocate for separate consideration of size and shape while comparing structures.

Three-Way Clustering Problems in Regional Science

Three-way clustering problems have been considered since many years. They are popular specially in psychology and chemistry, but some of the propositions and methods are of more general nature. In regional science three-way data matrices consist of objects (regions), variables and time units (years). Asking which variables, in which regions and when, follow homogeneous pattern is meaningful. Three general approaches are proposed in the paper and different modes of standardization are discussed. The example on Eurostat data is also presented.

The Assessment Of Geographical Borders In Economic Research

Abstract The length of common border between two geographical units is frequently used as a basic weight in spatial analysis. The newest methodological propositions such as tests for hierarchical relations (Markowska et. al. 2014; Sokołowski et. al. 2013), regional spatial moving average and new spatial correlation coefficient (Markowska et. al. 2015) are using border lengths. In cited references new methods have been illustrated by analyses for EU NUTS2 regions. It is obvious that borders between regions belonging to different countries have different socio-economic impact than borders between regions lying in the same country. A new simple method for assesment the importance of borders is proposed in the paper. It is based on a chosen macroeconomic variable available at NUTS 2 level (e.g. GDP, infant mortality, Human Development Index). For neighboring regions bigger value is divided by smaller value giving the local importance of the given border. These measures of local border importance can be than average for borders within the same country and for borders for each pair of neighboring countries.

Dynamiczna klasyfikacja regionów UE ze względu na strukturę rynku pracy – pozycja regionów polskich

W pracy zaprezentowano wyniki dynamicznej klasyfikacji regionow Polski na tle regionow Unii Europejskiej szczebla NUTS 2 ze wzgledu na strukture zatrudnionych w trzech podstawowych sektorach gospodarki: rolnictwie, przemyśle i uslugach. Okres analizy obejmuje lata 2000–2012. W 2008 roku Europejska Klasyfikacja Dzialalności Gospodarczej zostala uaktualniona oraz zmieniona i dla tego roku istnieją dwa zestawy danych. Wykorzystano je do oszacowania rownan regresji, ktore w dalszej kolejności posluzyly do przeliczenia danych dla lat 2000–2007 na system uaktualniony. Podstawowa metoda badawcza to dynamiczna analiza skupien, w ktorej przedmiotem grupowania są obiekto-okresy (operacyjne jednostki taksonomiczne – OJT). To podejście umozliwia śledzenie zmian zarowno w czasie, jak i w przestrzeni oraz pozwala na zidentyfikowanie typowych struktur zatrudnienia. Istotna zmiana struktury zatrudnienia w regionie skutkuje przemieszczeniem sie tego regionu do innej grupy. Wyniki mogą byc analizowane na poziomie regionow, a takze na poziomie panstw. W ramach analizy skupien liczba grup jest identyfikowana przez ocene dendrogramu uzyskanego metodą Warda, natomiast ostateczny podzial dokonywany jest metodą k-średnich. Oceniana jest tez stabilnośc grup i ich zdolnośc przyciągania innych regionow.

Ocena zmian struktury pracujących w unijnych regionach szczebla NUTS 2 z wykorzystaniem miary Braya i Curtisa

The aim of the paper is the evaluation of the changes observed in the employment structure at the European regional space of NUTS 2 level. The employment structure is expressed in three elements: agriculture, industry and services. Data covers two overlapping periods: 2000–2008 and 2008–2012. This is because of the changes in Eurostat data bases imposed by the update of European Classification of Economic Activities introduced in 2008 to the original regulation from 1997. New activities were defined, mainly in the field of information services and technologies. In new system, information on enterprises and labour market and some definitions in high-tech industries and services are not fully comparable with the old one. This problem is discussed in the paper. The measure of structures diversity is the basic research method for the analysis presented in the paper. It makes it possible to identify the intensity of labour market changes in both time and space.The aim of the paper is the evaluation of the changes observed in the employment structure at the European regional space of NUTS 2 level. The employment structure is expressed in three elements: agriculture, industry and services. Data covers two overlapping periods: 2000–2008 and 2008–2012. This is because of the changes in Eurostat data bases imposed by the update of European Classification of Economic Activities introduced in 2008 to the original regulation from 1997. New activities were defined, mainly in the field of information services and technologies. In new system, information on enterprises and labour market and some definitions in high-tech industries and services are not fully comparable with the old one. This problem is discussed in the paper. The measure of structures diversity is the basic research method for the analysis presented in the paper. It makes it possible to identify the intensity of labour market changes in both time and space.

Taksonomia dynamiki zmian struktury zatrudnienia w nowoczesnym przemyśle i usługach, w regionach Unii Europejskiej

The objective of the study is to analyze changes of employment share in modern, high-tech services and industry in the European Union regions at NUTS 2 level. The data covering the period of 1999–2008 were used since they are relatively complete and comparable. The growth tendency, separately for each quality/property and for each region, was estimated. Trend coefficients were used as input variables for the purposes of cluster analysis. By applying Ward’s method identified was the number of regional clusters, which differ by the model of employment changes dynamics in the analyzed spheres. The ultimate division of regions in terms of dynamics was obtained by using the k-means method. The results of clustering were verified by applying one-way analysis of variance. Finally the models of dynamics typical for the distinguished clusters of regions were specified.