Wykorzystanie narzędzi statystyki przestrzennej do identyfikacji kluczowych ośrodków rozwoju województwa kujawsko-pomorskiego

Müller-Frączek, Iwona; Pietrzak, Michał Bernard

doi:10.12775/aunc_econ.2008.016

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…Moran's I usually varies between -1 and +1, and its positive values signal clustering spatial dependence effects of neighbouring communes with similar values, while the negative ones suggest checkerboard patterns of spatial heterogeneity. Close to zero values of the statistic indicate no spatial effects for the variable of interest (Müller-Frączek, Pietrzak, 2008). The global statistic shows the strength and direction of spatial autocorrelation, but it is by definition global: covering all communes and averaging all local effects in the studied area.…”

Section: Sources and Methodsmentioning

confidence: 99%

Spatial Autocorrelation of Communes’ Income Potential in Selected Metropolitan Areas

Kozera

Głowicka-Wołoszyn²

2017

Folia Oeconomica

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A commune’s own income potential, indicative of financial self‑sufficiency, underpins the ability of its government to foster local growth. Accurate recognition of the potential levels necessary for improvement of development policies requires that, apart from considering communes’ own potential, neighbouring communes’ potential should be taken into account, especially if the neighbours are large urban centres of substantial demographic and economic capacity. This article aims to examine spatial autocorrelation of income potential of metropolitan communes of Warsaw, Poznań, Wrocław, and Cracow metro areas in 2014. The study draws on data published by the Central Statistical Office in the Local Data Bank and uses the R programme packages, such as spdep, maptools, and shapefiles for calculations.

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Section: Sources and Methodsmentioning

confidence: 99%

Spatial Autocorrelation of Communes’ Income Potential in Selected Metropolitan Areas

Kozera

Głowicka-Wołoszyn²

2017

Folia Oeconomica

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“…Wyniki tego typu prac opublikowali m.in. : Kołodziejczak i Kossowski (2016), Müller-Frączek i Pietrzak (2008, Pośpiech (2015), Pośpiech i Mastalerz-Kodzis (2018), Sikora (2009), Szczuciński (2019) oraz Wilk i in. (2015).…”

Section: Wprowadzenieunclassified

The use of spatial statistics in the analysis of salaries at poviat level in Poland

Ręklewski

2022

Wiadomości Statystyczne. The Polish Statistician

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The spatial differentiation of salaries is the subject of many scientific studies, both theoretical and empirical. One of the factors determining remuneration in Poland is the structure and type of business activity, specific for a given region and depending on its poviats (counties) in terms of the level of the average gross monthly salary by means of spatial autocorrelation statistical methods. The analysed statistical data for 2010–2019 come from the Local Data Bank (Bank Danych Lokalnych – BDL) of Statistics Poland. Global and local measures were used in the analysis. The calculation of the global parameters of spatial autocorrelation was based on the I Moran and C Geary statistics, while the Ii Moran statistic, which belongs to local spatial indicators from the LISA group (Local Indicators of Spatial Association), was used to identify the local autocorrelation. The statistical significance of the global statistics was verified by means of a randomisation approach based on theoretical moments. The I Moran and C Geary global statistics indicated a significant (very weak or weak) and positive spatial autocorrelation between poviats in terms of the level of average gross monthly salaries in 2010–2019, which shows the existence of spatial poviat structures of similar values, i.e. clusters with high or low values of average salaries. The increase in I Moran’s statistics and the growth of the C Geary in the analysed period indicate a decrease in the differentiation of average monthly salaries between poviats, thus signifying an increase in the dependence of spatial autocorrelation. The analysis of the results of the obtained local statistics allowed the determination of clusters of similar poviats in Poland, e.g. Mazowiecki, Pomorski and Śląski. Furthermore, the results of the analysis indicated the presence of outlier poviats.

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“…Miary te należą do grupy statystyk przestrzennych pozwalających na identyfikację grup jednostek o podobnej sytuacji, w tym do identyfikacji ośrodków kluczowych np. [Müller-Frączek, Pietrzak 2008]. Do ustalenia wartości statystyk wykorzystano macierz sąsiedztwa pierwszego rzędu standaryzowaną rzędami do jedności.…”

Section: Metodyka Oceny Potencjału Dochodowego Gmin Z Wykorzystaniem Klasyfikacji Z Medianą I Analizy Przestrzennejunclassified

Classification of Municipalities by the Amount and Structure of Budget Revenues

Bal-Domańska¹

2018

PRACE NAUKOWE UNIWERSYTETU EKONOMICZNEGO WE WROCŁAWIU

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Streszczenie: Struktura dochodów gmin stanowi jeden z elementów oceny ich samodzielności finansowej, a co za tym idzie − zdolności do wykonywana zadań lokalnych wynikających z potrzeb i ze specyfiki danego obszaru i społeczności. W artykule wykorzystano dwie metody identyfikacji klas gmin, które umożliwiły ocenę zróżnicowania modeli dochodowych i ich przestrzenną charakterystykę − klasyfikację z medianą oraz statystyki przestrzenne I Morana. Pozwoliły one na wskazanie klas gmin o podobnej strukturze dochodów z wyróżnieniem trzech podstawowych grup wpływów (dochody własne, subwencje ogólne i dotacje celowe). Analizą objęto budżety gmin (z wyłączeniem miast na prawach powiatu) w 2016 r. Z przeprowadzonej analizy wynika, że tendencja do tworzenia skupisk sąsiadujących gmin o podobnym poziomie wpływów w przypadku dochodów ogółem i własnych jest niewielka i dotyczy jedynie wybranych lokalizacji o wysokim potencjale gospodarczym, jak m.in. okolice dużych miast.Słowa kluczowe: struktura dochodów gmin, klasyfikacja z medianą, statystyki przestrzenne. Summary:The structure of municipal revenues is one of the elements of their financial independence assessment, and thus their ability to implement a wide range of local tasks resulting from the needs and specificity of a particular area and community. Two methods of identifying municipal classes were used in the article, which allowed assessing the diversity of revenue models and their spatial characteristics. The applied methods are the median based classification and the Global Moran's I statistics. They allowed to indicate municipal classes presenting a similar revenue structure with distinction of three basic groups of receipts (own revenues, general subsidies and earmarked subsidies). The analysis was carried out in 2016 and covered municipal budgets (excluding cities with poviat status). The analysis shows that the tendency for creating clusters of neighbouring municipalities featuring a similar level of revenues in terms of total and own revenues is small and concerns only selected locations with high economic potential, such as e.g. the vicinity of large cities.

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Wykorzystanie narzędzi statystyki przestrzennej do identyfikacji kluczowych ośrodków rozwoju województwa kujawsko-pomorskiego

Cited by 5 publications

References 2 publications

Spatial Autocorrelation of Communes’ Income Potential in Selected Metropolitan Areas

Spatial Autocorrelation of Communes’ Income Potential in Selected Metropolitan Areas

The use of spatial statistics in the analysis of salaries at poviat level in Poland

Classification of Municipalities by the Amount and Structure of Budget Revenues

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