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Does the process of shrinking concern also small towns? lessons from Poland

Bartosz Bartosiewicz
Bartosz Bartosiewicz
, 
Agnieszka Kwiatek-Sołtys
Agnieszka Kwiatek-Sołtys
 und 
Sławomir Kurek
Sławomir Kurek
   | 26. Dez. 2019
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Online veröffentlicht: 26. Dez. 2019
Seitenbereich: 91 - 105
Eingereicht: 26. Juni 2019
DOI: https://doi.org/10.2478/quageo-2019-0039
© 2019 Bartosz Bartosiewicz, Agnieszka Kwiatek-Sołtys, Sławomir Kurek, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Fig. 1

Population growth in small towns and its components.
Population growth in small towns and its components.

Fig. 2

Demographic types of population according to Webb in small towns in Poland between 2002 and 2014.
Demographic types of population according to Webb in small towns in Poland between 2002 and 2014.

Fig. 3

Population dynamics in small towns between 2002 and 2014 (2002=100).
Population dynamics in small towns between 2002 and 2014 (2002=100).

Fig. 4

Types of small depopulating towns.
Types of small depopulating towns.

Fig. 5

Changes in the affiliation of depopulating small towns to the type of economic growth level (2002–2014). 1 – Świeradów Zdrój, 2 – Ścinawa, 3 – Strzegom, 4 – Ząbkowice Śląskie, 5 – Ziebice, 6 – Bogatynia, 7 – Poniatowa, 8 – Gozdnica, 9 – Małomice, 10 – Żychlin, 11 – Błaszki, 12 – Lipsko, 13 – Strzelce Opolskie, 14 – Wołczyn, 15 – Krapkowice, 16 – Dobrodzień, 17 – Paczków, 18 – Głuchołazy, 19 – Ozimek, 20 – Siematycze, 21 – Hel, 22 – Kazimierza Wielka, 23 – Ożarów, 24 – Działoszyce, 25 – Pieniężno, 26 – Korsze, 27 – Dąbrowa Białostocka, 28 – Sokółka, 29 – Węgliniec, 30 – Łapy.
Changes in the affiliation of depopulating small towns to the type of economic growth level (2002–2014). 1 – Świeradów Zdrój, 2 – Ścinawa, 3 – Strzegom, 4 – Ząbkowice Śląskie, 5 – Ziebice, 6 – Bogatynia, 7 – Poniatowa, 8 – Gozdnica, 9 – Małomice, 10 – Żychlin, 11 – Błaszki, 12 – Lipsko, 13 – Strzelce Opolskie, 14 – Wołczyn, 15 – Krapkowice, 16 – Dobrodzień, 17 – Paczków, 18 – Głuchołazy, 19 – Ozimek, 20 – Siematycze, 21 – Hel, 22 – Kazimierza Wielka, 23 – Ożarów, 24 – Działoszyce, 25 – Pieniężno, 26 – Korsze, 27 – Dąbrowa Białostocka, 28 – Sokółka, 29 – Węgliniec, 30 – Łapy.

Shrinking small towns in Poland: basic information.

Number of populationNumber of small townsNumber of shrinking small townsShare of shrinking small towns
up to 5,000320 (47%)11 (37%)3.4%
5,000–10,000177 (26%)10 (33%)5.6%
10,000–15,000107 (15.5%)2 (7%)1.9%
15,000–20,00079 (11.5%)7 (23%)8.9%
In total683304.4%

Affiliation of shrinking small towns to the appointed types of changes in the level of social and economic development (Table 4).

Type 2002
A–BłaszkiŚwieradów ZdrójStrzegom, Śląskie, Głuchołazy Ząbkowice
BDobrodzieńLipsko, Kazimierza Wielka, OżarówBogatynia, Wołczyn, SiemiatyczeZiębice, Strzelce Opolskie, Krapkowice, Paczków, Hel
CPoniatowa, Żychlin, Działoszyce, Pienięż- noWęgliniecOzimek–
DGozdnica, Korsze, Dąbrowa BiałostockaŚcinawa, Małomice, SokółkaŁapy–
DCBAType 2014

Values of part I and I of the indicator calculated with a shift-and-share analysis for the selected 5 shrinking small towns.

TownValues of part III of the method according to sectorsReal difference in the number of business entities in town between 2002 and 2014Hypothetical increase in the number of business entities – part I of the methodDifference be- tween real and hypothetical (part I) change in the number of business entitiesDifference between real and hypothetical (part I) change in the number of business entities
sector Isector IIsector IIIsector IV
Błaszki0.2−0.3−0.3−0.5−7228.360−100−354
Ożarów−0.2−0.3−0.3−0.5−11250.170−162−323
Żychlin0.2−0.2−0.2−0.4−9772.490−169−234
Sokółka−0.2−0.1−0.1−0.3−49168.633−218−129
Dobrodzień−0.20.0−0.2−0.1−439.420−43−110

The way of singling out 16 types of development levels of small towns in Poland between 2002 and 2014.

Type 2002
AIIIIIIIV
BVVIVIIVIII
CIXXXIXII
DXIIIXIVXVXVI
DCBAType 2014

Population dynamics in small towns between 1970 and 2014.

Population dynamics (base year = 100)1970–20141970–19781978–19881988–20022002–2014
102 and more544482570370179
98–102208333135190
over 98737234132268
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