Assessment and spatial diversity of the competitiveness of communes of the Swictokrzyskie province

The commune is the basic local government unit. Analysis the spatial disproportions in the competitiveness of poviats of the Swictokrzyskie Voivodship using a synthetic measure. Diversification of the measure of regional competitiveness of poviats.

Рубрика Экономика и экономическая теория
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Assessment and spatial diversity of the competitiveness of communes of the Swiзtokrzyskie province

Pawel Dziekanski, PhD, Institute of Law, Economics and Administration, Jan Kochanowski University in Kielce; Adrian Lipa, Scientific and Educational Consortium; Urszula Karpinska, Cooperative Bank in Kielce, Poland

The commune is the basic local government unit. It has a certain range of freedom in deciding on the path of development and property. The commune 's process of activity takes place in a space that is entirely filled by the natural and economic environment, and its specific, individual features of the economy, society and resources. The aim of the article is to analyze the spatial disproportions in the competitiveness of poviats of the Swiзtokrzyskie Voivodship using a synthetic measure. As the source material, data from the Regional Accounting Chamber (Kielce branch) and Local Database of the Central Statistical Office for 2009, 2011 and 2017 were used. The competitiveness of the local economy is largely dependent on the processes taking place in the so-called development centers and the availability of endogenous resources.

The center can get rich at the expense of peripheral areas (e.g. by attracting human capital). Wloszczowski, Kielecki and Buski poviats were high in the ranking. At the other end of the ranking were Pinczowski, Skarzyski, Kazimierski. The synthetic measure in 2017 rangedfrom 0.52 (Wloszczowski) to 0.73 (Kazimierksi), in 2009 0.53 (Staszowski) to 0.79 (Kazimierski) respectively. No position stability was observed in the ranking, the level of the indicator is influenced by: the economic nature of the unit and the function of the area (industrial, tourist, residential), economic potential, financial situation, natural environment and infrastructure. Therefore, the assessment should take into account local specificities in various structural and functional conditions.

Key words: competitiveness, synthetic measure, commune, Swiзtokrzyskie Province.

Оцінка та просторове різноманіття конкурентоспроможності комун у свєнтокшиському воєводстві

Джєканьський Павел, Доктор філософії, Факультет права, управління і менеджменту, Університет ім. Я. Кохановського; Ліпа Адріан, Науковий та освітній консорціум; Карпіньська Уршула, Кооперативний банк у Кєльце

Комуна є основною одиницею місцевого самоврядування. Вона має певний діапазон свободи у вирішенні шляху розвитку та власності. Процес діяльності громади відбувається в просторі, повністю заповненому природним та економічним середовищем та його специфічними, індивідуальними особливостями економіки, суспільства та ресурсів. Метою статті є аналіз просторових диспропорцій у конкурентоспроможності повітів Свентокшиського воєводства за допомогою синтетичного заходу. У якості вихідного матеріалу були використані дані Регіональної бухгалтерської палати (філія Кільце) та Місцевої бази даних Центрального статистичного управління за 2009, 2011 та 2017 роки. Конкурентоспроможність місцевої економіки значною мірою залежить від процесів, що відбуваються у так званих центрах розвитку, та наявності ендогенних ресурсів.

Центр може розбагатіти за рахунок периферійних районів (наприклад, за рахунок залучення людського капіталу). Висошевські, Кілецькі та Буські пов'язки були високими в рейтингу. На іншому кінці рейтингу опинилися Піньчовський, Скаржиський, Казімірський. Синтетичний захід 2017року становив від 0,52 (Wloszczowski) до 0,73 (Kazimierksi), 2009 року - від 0,53 (Staszowski) до 0,79 (Kazimierki) відповідно. Стабільності позицій у рейтингу не спостерігалось, на рівень показника впливають економічний характер одиниці та функція району (промисловий, туристичний, житловий), економічний потенціал, фінансове становище, природне середовище та інфраструктура. Тому оцінка повинна враховувати місцеві особливості в різних структурних та функційних умовах.

Ключові слова: Конкурентоспроможність, синтетичний захід, комуна, Свєнтокшиське воєводство.

Оценка и пространственное многообразие конкурентоспособности коммун в свентокшиском воєводстве

Джеканьский Павел, Доктор философии, Факультет права, управления и менеджмента, Университет им. Я. Кохановського; Липа Адриан, Науковий и образовательный консорцуум; Карпиньска Уршула, Кооперативный банк в Кельце

Коммуна является основной единицей местного самоуправления. Она обладает определенной степенью свободы при выборе пути развития и собственности. Процесс деятельности коммуны происходит в пространстве, которое полностью заполнено природной и экономической средой и ее специфическими индивидуальными особенностями экономики, общества и ресурсов. Целью статьи является анализ пространственных диспропорций в конкурентоспособности повятов Свентокшиского воеводства с использованием синтетической меры. В качестве исходного материала использовались данные из Региональной Счетной палаты (Кельцкий филиал) и Локальной базы данных Центрального статистического управления за 2009, 2011 и 2017 гг. Конкурентоспособность местной экономики в значительной степени зависит от процессов, происходящих в так называемых центры развития и наличие эндогенных ресурсов.

Центр может разбогатеть за счет периферийных районов (например, путем привлечения человеческого капитала). Wloszczowski, Кельце и Буски повяты были высокими в рейтинге. На другом конце рейтинга были Пиньчув, Скаржиски, Казимеж. Синтетический показатель в 2017 году варьировался от 0,52 (Влоцлавек) до 0,73 (Казимеж), в 2009 году - 0,53 (Сташовский) до 0,79 (Казимеж) соответственно. Стабильности позиции в рейтинге не наблюдалось, на уровень индикатора влияют: экономический характер объекта и функции района (промышленный, туристический, жилой), экономический потенциал, финансовое положение, природная среда и инфраструктура. Поэтому при оценке следует учитывать местные особенности в различных структурных и функциональных условиях.

Ключевые слова: Конкурентоспособность, синтетическая мера, коммуна, Свентокшишское воеводство

commune poviat voivodship competitiveness

Introduction

The commune is the basic local government unit. Has a certain range of freedom in deciding on the path of development, property. It implements the scope of public tasks, in particular in the aspect of technical infrastructure, social infrastructure, protection and public security as well as spatial and ecological order Ustawa z dnia 8 marca 1990 r. o samorzqdzie gminnym (Dz. U. z 2001 r. Nr 142, poz. 1591 z pфzn. zm.); K. Podgфrski, 1991, Ustawowa regulacja zadan gminy jako jednostki samorzqdu terytorialnego, ST, nr 11-12, p. 21.. The environment and the economy form a network of interconnections in which tasks are carried out. Endogenous resources, acting for the benefit of the community, are interdependent and should be considered together J. Zaucha, 2012, Synteza aktualnego stanu wiedzy dotyczqcej rozwoju sustensywnego i spфjnosci terytorialnej w planowaniu przestrzennym (analiza dokumentфw UE, BSR i PL), [In:] Planowanie przestrzenne w rozwoju zrфwnowazonym, Inspiracje Projektu EcoRegion, czзsc I, UG, Gdansk; A. Zakrzewska-Pфltorak, 2011, Zasoby endogeniczne jako czynnik rozwoju lokalnego i regionalnego. Studium przypadkфw wybranych gmin wojewфdztwa dolnoslqskiego, Prace Naukowe Uniwersytetu Ekonomicznego we Wroclawiu, nr 152, p. 579-588.. Today, communes have become the subjects of economic processes. They pursue the interests of given communities, taking into account local resources. Their actions depend on both endogenous and exogenous factors. The commune's process of activity takes place in a space that is fully filled by the natural and economic environment, and its specific, individual features of the economy, society and resources D. Rynio, 2013, Ksztaltowanie nowej polityki regionalnej Polski w warunkach globalizacji i integracji, Monografie i Opracowania Uniwersytetu Ekonomicznego we Wroclawiu, nr 240, p. 357..

Building the region's competitiveness requires stimulating its various determinants (environmental, social and economic). The activity of these units is focused on the use of available endogenous resources J.J. Parysek, 2001, Podstawy gospodarki lokalnej, Wyd. Nauk. Uniwersytetu Adama Mickiewicza, Poznan., e.g. raw materials, economic, social and natural capital, finances and human resources W. Kisiala, B. Stзpinski (ed.), 2013, Rola obszarфw metropolitalnych w polityce regionalnej i rozwoju regionalnym, Wydawnictwo UE w Poznaniu, Poznan.. The competitive advantage of municipalities is not determined by the region's ability to configure various tangible and intangible resources, as a result of which new values are created T. Markowski, D. Stawasz (ed.), 2001, Ekonomiczne i srodowiskowe aspekty zarzqdzania rozwojem miast i regionфw, Lфdz, p. 91.. Competitiveness (development) of communes is a complex phenomenon, difficult to clearly and objectively assess from the point of view of the examined aspect of the structure, which cannot be measured and expressed by means of one feature F. Wysocki, 2010, Metody taksonomiczne w rozpoznawaniu typфw ekonomicznych rolnictwa i obszarфw wiejskich, Wydawnictwo Uniwersytetu Przyrodniczego w Poznaniu, Poznan.. The problem with assessing the operation of municipalities is the relatively large amount of information that creates information noise. It impedes the analyzes carried out, increases the research effort, and also makes it more difficult to make clear decisions. Support in the decisionmaking process can be the creation of synthetic measures with high information capacity or leaving those measures that have the greatest information value A. Adamczyk, D. Dawidowicz, 2016, Wartosc informacyjna wskaznikфw oceny kondycji finansowej jednostek samorzqdu terytorialnego, Ekonomiczne Problemy Uslug nr 125, p. 25-36..

Aim and research method

The aim of the article is to analyze the spatial disproportions in the competitiveness of poviats of the Swiзtokrzyskie Voivodship using a synthetic measure (a synthetic measure based on distance in real space with Euclidean metrics). As the source material, data from the Regional Accounting Chamber (Kielce branch) and Local Database of the Central Statistical Office for 2009, 2011 and 2017 were used.

In order to determine the measure of synthetic competitiveness, the following procedure was used P. Dziekanski, Spatial changes and assessment of the financial condition of local government units in the context of the income structure [In:] Formankova S., International Conference on Management (ICoM), Trends of Management in the Contemporary Society (Peer-Reviewed Conference Proceedings), Brno 2016, Publisher: Mendelova univerzita v Brnй.:

1. The variables describing competitiveness were selected. The ones with low spatial variability and high correlation of variables were removed from the set of variables (according to the inverted matrix method) A. Malina, 2004, Wielowymiarowa analiza przestrzennego zrфznicowania struktury gospodarki Polski wedlug wojewфdztw, Wyd. Akademii Ekonomicznej w Krakowie, Krakфw, p. 96-97..

2. The variables were subjected to the zero unitarisation procedure using the following formulas:

where: S-stimulant, D-destimulant; i=1, 2...n; j=1, 2...n, xij - means the value of the j-t feature for the tested unit, max - the maximum value of the j-t feature, min - the minimum value of the j-t featureP. Dziekanski, 2016, Spatial Differentiation of the Financial Condition of the Swiзtokrzyskie Voivodship Counties, Barometr Regionalny, Tom 14 nr 3; E. Mioduchowska-Jaroszewicz, 2013, Metody i kierunki oceny kondycji finansowej jednostek samorzqdфw terytorialnych, ZN US, nr 786, Finansowe, Ubezpieczenia, nr 64/2. p. 127-140; K. Kukula, 2000, Metoda unitaryzacji zerowanej, PWN, Warszawa; A. Mlodak, 2006, Analiza taksonomiczna w statystyce regionalnej, Difin, Warszawa..

3. A synthetic measure based on distance in real space was calculated with Euclidean metric according to the formula:

(3)

where: i=1, 2.N; j=1, 2., p (N is the number of objects (poviats), and p - number of features), zij - is the value of the j-th feature for the unit being tested F. Wysocki, 1996, Metody statystycznej analizy wielowymiarowej w rozpoznawaniu typфw struktury przestrzennej rolnictwa, Roczniki AR w Poznaniu, seria: Rozprawy Naukowe, z. 266, Poznan.. The synthetic measure allows measuring measured to the interval [0; 1]. A measure value of 0 means the maximum positive value of each stimulant tested M. Trojak, T. Tokarski (ed.), 2013, Statystyczna analiza przestrzennego zrфznicowania rozwoju ekonomicznego i spolecznego Polski, Wyd. UJ, Krakфw..

4. The studied area of rural communes in the Swiзtokrzyskie voivodship was divided into 4 quartile groups. The size of the indicator in the first group means a better unit, in the last one the weakest P. Dziekanski, A. Wyszkowski, 2018, Ocena przestrzennego zrфznicowania sytuacji finansowej gmin wojewфdztwa swiзtokrzyskiego z wykorzystaniem miary syntetycznej, Optimum. Economic Studies, nr 1 (91), p. 219-238; F. Wysocki, J. Lira, 2005, Statystyka opisowa, Wydawnictwo Uniwersytetu Przyrodniczego w Poznaniu, Poznan..

The essence of the region's competitiveness

K. Kucinski defines the competitiveness of the region as a resultant of possessed resources and their distribution, development to date, conscious activities of public authorities aiming at shaping the face of the region K. Kucinski, 1997, Konkurencyjnosc jako zagadnienie regionalne, IFGN, SGH, Warszawa, s. 1.. T. Markowski defines the competitiveness of regions in the objective sense, indicating that it is the ability of regions to meet the needs and demand for services and goods from local and global markets. This should provide regions with a sustainable income opportunity T. Markowski, Przedmiotowa i podmiotowa konkurencyjnosc regionфw [In:] T. Czyz, H. Rogacki (red.), Wspфlczesne problemy i koncepcje teoretyczne badan przestrzenno-ekonomicznych, z. 219, PAN KPZK, Warszawa 2005, p. 28-30.. In turn, A. Klasik treats the region's competitiveness as a result of the attractiveness of the service offer, the region's strengths, export strength, and productivity A. Klasik, 2002, Strategie regionalne. Formulowanie i wprowadzanie w zycie, AE, Katowice, p. 22-23..

The competitiveness of regions is their ability to produce sustainable growth in value added. It is based on the efficient and effective use of resources and management of economic processes in the regional economy. The element shaping competitiveness is the use of an appropriate combination of internal and external growth factors, directed among others to shape the region's attractiveness for foreign investors and to stimulate the creativity and aggressiveness of local investors J. Chqdzynski, A. Nowakowska, Z. Przygodzki, 2007, Region i jego rozwфj w warunkach globalizacji, Wyd. CeDeWu, Warszawa, p. 106..

The competitiveness of regions is determined by factors that can be classified as spatial, social and organizational. All competitiveness factors of the region fall into the category of development factors of the region W. Kosiedowski, 2008, Zarzqdzanie rozwojem regionalnym i lokalnym [In:] Gospodarka regionalna i lokalna, red. Z. Strzelecki, PWN, Warszawa, p. 232 i n.. It is shaped to the greatest extent by endogenous factors, otherwise known as local opportunities and development needs (demographic resources, infrastructure and economy). The features related to access and quality of individual factors from this group are important. Exogenous (external) factors refer to changes in macro-environment, which result, among others, from changing macroeconomic conditions, system changes in the state. An important factor is also the financial resources that are essential for the optimal functioning of local governments Z. Oplotnik, B. Brezovnik, 2004, Financing local government in Slovenia, Post-Communist Economies, Volume 16, Issue 4..

The basis of the regions' competitiveness is the high efficiency of the local economy. It ensures that the public enjoys a high and growing standard of living and a high employment rate. Regions often do not form a compact whole, and their elements develop at different rates and with different intensities. The consequence of this is the process of flow of resources from local to central centers. On the one hand, the captain is looking for areas with a higher rate of return, lower investment risk, an efficient institutional environment and highly qualified employees. On the other hand, a qualified workforce migrates in search of employment, ensuring better conditions for development T. Kudlacz, 2001, Rozwoj regionalny Polski lat 90. - ocena dominujqcych procesфw oraz spodziewanych tendencji [In:] Polityka regionalna panstwa posrфd uwiklan instytucjonalno-regulacyjnych, red. Szomburg J., IBnGR, Gdansk, p. 30; T. Markowski, 2001, Stymulowanie i regulowanie konkurencyjnosci w swietle procesфw globalizacji gospodarki, Samorzqd Terytorialny, nr 3, p. 30..

The multidimensionality of the functioning of local government units is demonstrated by the directions of action and the benefits achieved in the spatial, social, economic aspects, etc. The scope and effectiveness of the influence of local authorities on local and regional development are determined by income and expenditure instruments. They can be used by local authorities depending on the division of competences and powers between government and local institutions L. Patrzalek, 2010, Finanse samorzqdu terytorialnego a koncepcje rozwoju lokalnego i regionalnego, Prace Naukowe Uniwersytetu Ekonomicznego we Wroclawiu 112, Finanse publiczne, p. 549-556. These activities are usually focused around goals, among which should be distinguished long-term development, increase in income of residents and the budget, development of entrepreneurship P. Dziekanski, 2018, Ocena efektywnosci funkcjonowania gmin wojewфdztwa swiзtokrzyskiego w swietle ekonomii instytucjonalnej (analiza wielowymiarowa), Uniwersytet Jana Kochanowskiego w Kielcach, Kielce.

Intra-regional diversification of the competitiveness of poviats of the Swiзtokrzyskie Voivodship

The Swiзtokrzyskie Voivodship belongs to the ecologically cleanest areas of Poland. The region has an industrial and agricultural character with a high concentration of industry sectors related to the production and processing of metals, mining and processing of mineral resources and the production of foodstuffs.

The main industries of the Swiзtokrzyskie region are: metallurgical (Ostrowiec Swiзtokrzyski), metal (Skarzysko-Kamienna), machine (Starachowice), building materials (Kielce), ceramic, foundry (Konskie), food (Pinczфw, Kielce). The economy of the Swiзtokrzyskie region is based on the mining industry in the field of building materials (limestone, dolomite, marl, gypsum, sandstone), thanks to which the voivodship became the capital of Polish construction. The agricultural south is the base for the production of organic food (table 1). M.A. Jфzwiak, M. Jфzwiak, M. Strzyz, 2010, Predyspozycje naturalne regionu swiзtokrzyskiego do rozwoju turystyki, Krajobraz a Turystyka, Prace Komisji Krajobrazu Kulturowego Nr 14, Komisja Krajobrazu Kulturowego PTG, Sosnowiec.

Table 1. Characteristics of selected areas (poviats) of the Swiзtokrzyskie Voivodeship

Poviats

Characteristic

Kielce

Food and construction industry

Kielecki

Mining and processing industry for mineral raw materials, food production

Konecki

Foundry, construction, trade, hotel industry, transport

Ostrowiecki

Iron metallurgy, trade, services

Skarzyski

Metal industry, agriculture, trade and services, construction

Starachowicki

Machine and metal industry

Buski

Agriculture (vegetables, orchards), agrotourism, spas

Jзdrzejowski

Agriculture, agrotourism, agri-food processing

Kazimierski

Agriculture, construction, trade, services

Opatowski

Agriculture, agrotourism, industry (cement), dairy

Pinczowski

Agriculture, trade, services, mining industry

Sandomierski

Agriculture (gardening, orchards), agrotourism, industry (glassworks)

Staszowski

Agriculture, trade, services

Wloszczowski

Agriculture, trade, services, recreation

Zrфdlo: Bury P., Dziekanski P., 2013, Ocena kondycji finansowej powiatфw wojewфdztwa swiзtokrzyskiego w latach 20072011 za pomocq wskaznika syntetycznego, s. 220-248 [w:] Czynniki zmian zjawisk regionalnych, V Jurcak, P. Dziekanski (red.), Czynniki zmian zjawisk regionalnych, Wyd. WSBiP Ostrowiec Sw., Ostrowiec Sw.

The value of the synthetic measure allowed dividing the communes of the Swiзtokrzyskie Province into 4 groups. Small groups in time and space can be observed between the groups. Wloszczowski, Kielcki and Buski poviats were high in the ranking. At the other end of the ranking were Pinczowski, Skarzyski, Kazimierski. The synthetic measure in 2017 ranged from 0.52 (Wloszczowski poviat, best unit) to 0.73 (Kazimierski, the weakest unit), in 2009 0.53 (Staszowski) to 0.79 (Kazimierski) respectively.

Table 2. Quartile groups measures of synthetic competitiveness (OE) of poviats of the Swiзtokrzyskie voivodship in 2009, 2011, 2017

2009

2011

2017

A

Staszowski 0.53

staszowski 0.5

wloszczowski 0.52

kielecki 0.54

buski 0.55 j

зdrzejowski 0.55

B

kielecki 0.59

jзdrzejowski 0.62

Opatowski 0.62

buski 0.63

wloszczowski 0.58

kielecki 0.59

jзdrzejowski 0.6

buski 0.62

staszowski 0.56

konecki 0.57

sandomierski 0.63

C

wloszczowski 0.64

konecki 0.65

ostrowiecki 0.66

sandomierski 0.66

sandomierski 0.64

konecki 0.66

opatowski 0.64

starachowicki 0.64

ostrowiecki 0.66

D

pinczowski 0.72

starachowicki 0.74

skarzyski 0.75

kazimierski 0.79

ostrowiecki 0.68

pinczowski 0.68

opatowski 0.7

starachowicki 0.71

skarzyski 0.74

kazimierski 0.78

pinczowski 0.68

skarzyski 0.71

kazimierski 0.73

Source: own calculations of the authors based on the data from the Local Data Bank of Statistics Poland and Central Statistical Office

In the ranking, no position stability was observed, the level of the indicator is affected by: the economic nature of the unit and the function of the area (industrial, tourist, residential), economic potential, financial situation, natural environment and infrastructure (location rent). Therefore, the assessment should take into account local specificities in various structural and functional conditions.

Measures of spatial diversity indicate the relative stability of poviats in terms of competitiveness. In 2017, compared to 2009, the results show stability according to the standard deviation (0.07-0.07). The classic coefficient of variation (0.11-0.11) also indicates the stability of diversity. The values of the range 0.26 (2009) and 0.21 (2017) indicate slight changes in the area under study, a decrease in the diversity of poviats.

Table 3. Measures of diversification of the measure of synthetic competitiveness (OE) of poviats of the Swiзtokrzyskie Voivodship in 2009, 2011, 2017

2009

2011

2017

average

0,66

0,65

0,61

median

0,65

0,66

0,63

standard deviation

0,07

0,07

0,07

quarter (quartile) deviation

0,67

0,65

0,61

classic coefficient of variation

0,11

0,11

0,11

positional coefficient of variation

1,03

0,98

0,96

min

0,53

0,50

0,52

max

0,79

0,78

0,73

gap

0,26

0,28

0,21

quartile range

0,10

0,10

0,11

slant

0,18

-0,29

0,26

measure of concentration-kurtosis

-0,15

0,14

-1,31

The Pearson correlation coefficient between the value of the synthetic measure of development in 2009 and 2011 was - 0.893, in the case of the 2011-2017 relation - 0.856 (Figure 1). We observe convergence in the area of poviat competitiveness. It can be assumed that the spatial diversity of the studied area was quite stable, and the units reacted similarly to changes in the economy.

Regression analysis allows you to create a linear model. When creating it, decide which variables will be the explained variable and which variables will be the explanatory one

Figure 1. Scatter chart of the ratio of synthetic competitiveness measures year to year by poviats Swiзtokrzyskie voivodship

Source: own calculations of the authors based on the data from the Local Data Bank of Statistics Poland and Central Statistical Office

The regression model describing the dependence of variables takes the form: f (OE competitiveness) = Z (employed in agriculture, employed in industry, entities entered in the register per 1000 population, persons conducting professional, scientific and technical activities per 1000 inhabitants, unemployment rate, total migration balance for permanent residence per 1000 inhabitants, sold production of industry per capita, investment outlays in enterprises per capita, gross value of fixed assets in enterprises per capita, poviat own income of poviats, poviat investment expenditure per capita, total forest land area).

The results of the regression analysis for the synthetic measure show that the presented regression model allows explaining R = 0.949 variable variations. The high values of the F statistics (52.31) and the corresponding level of probability p confirm the statistical significance of the linear model. The t-Student statistic value for the p parameter means that all parameters are statistically significant. The value of the determination coefficient (R2 =0,931) indicates a good fit of the regression model to the data (Table 5).

Table 4. KMNK estimation with dependent variable synthetic measure (OE)

Rate

Standard error

t-Student's

p-value

constant

1.34107

0.136661

9.813

<0.0001

***

working in agriculture

-0.523235

0.121484

-4.307

0.0002

***

working in industry

-0.398506

0.133569

-2.984

0.0059

***

persons conducting professional, scientific and technical activities per 1000 inhabitants

-0.00460970

0.000896491

-5.142

<0.0001

***

unemployment rate

0.00398883

0.000998886

3.993

0.0004

***

sold production of industry

-8.69723e-06

4.47916e-06

-1.942

0.0623

*

investment outlays in enterprises

-4.22669e-06

2.12659e-06

-1.988

0.0567

*

gross value of fixed assets

-1.39998e-06

3.38312e-07

-4.138

0.0003

***

poviat own revenues

-8.51890e-05

4.66759e-05

-1.825

0.0787

*

investment expenditure of poviats

-0.000166035

4.80431e-05

-3.456

0.0018

***

forest land area

-6.51252e-06

6.81284e-07

-9.559

<0.0001

***

Arithmetic mean of the dependent variable

0.642564

Standard deviation of the dependent variable

0.073188

Sum of residual squares

0.010340

Residual Standard Error

0.019217

Determining coefficient R- square

0.949200

Corrected R-square

0.931057

F(10, 28)

52.31795

P-value for the F test

1.92e-15

Logarithm of credibility

105.2496

Akaike information criterion

-188.4992

Bayesian information criterion

-170.2000

Hannan-Quinn information criterion

-181.9336

observations used 1-39

Source: own calculations of the authors based on the data from the Local Data Bank of Statistics Poland and Central Statistical Office

Summary

The competitiveness of the local economy is highly dependent on the processes taking place in the so-called development centers and the availability of endogenous resources. The center can get rich at the expense of peripheral areas (e.g. by attracting human capital).

The activities of poviats are of a multi-criteria category, their level of effectiveness is affected by location rents, finances, economic and infrastructural potential, natural resources, etc. A characteristic feature of them is the effect of leaching, e.g. human capital, social or economic potential.

The presented methods allow the identification of areas with a higher / lower level of performance effectiveness, and then programming their support from public funds under regional policy. It can be a helpful tool for local authorities assessing the accuracy of past decisions and the effectiveness of regional management instruments used in the past.

The value of the synthetic measure allowed dividing the communes of the Swiзtokrzyskie Province into 4 groups. Small groups in time and space can be observed between the groups. Wloszczowski, Kielcki and Buski poviats were high in the ranking. At the other end of the ranking were Pinczowski, Skarzyski, Kazimierski. The synthetic measure in 2017 ranged from 0.52 (Wloszczowski poviat, the best unit) to 0.73 (Kazimierski, the weakest unit), in 2009 0.53 (Staszowski) to 0.79 (Kazimierski) respectively.

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