Can public intervention improve local public sector economic performance? The analysis of Special Economic Zones in Poland

Katarzyna Kopczewska

doi:10.2478/ceej-2019-0019

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Can public intervention improve local public sector economic performance? The analysis of Special Economic Zones in Poland

Central European Economic Journal

Volume 6 (2019): Issue 53 (January 2019)

By: Katarzyna Kopczewska

Open Access

|Jun 2020

Figures & Tables

The expected direct and indirect effects of SEZ. *Source*: The author.

Expected changes in density distributions under global shift, divergence and convergence. *Source*: Kopczewska (2014).

Location of SEZ in comparison with non-SEZ business locations in 2016. *Note:* Firms *per capita* in intervals 0–0.1–0.15–0.20–0.5–0.75, from light to dark grey; SEZ are given with circles. *Source*: The author. The location of SEZ from MR (2017), the density of business from Central Statistical Office www.stat.gov.pl.

Panel plots for selected groups of NTS5 units. *Source*: The author’s results, estimated in R.

Density distributions of 3-year average data in time spans: 1995–1997 and 2014–2016. *Source*: The author’s results, estimated in R.

Table A1

Summary statistics

Variable	Year	Urban NTS5, no SEZ	Rural and mixed NTS5, no SEZ	Seats of NTS4 authorities, no SEZ	Urban NTS with SEZ	Rural and mixed NTS5 with SEZ	Seats of NTS4 authorities with SEZ
Public investments per capita	1995	403.01	283.21	301.00	359.49	397.02	303.20
	2005	477.10	399.78	355.03	357.10	508.80	462.50
	2015	562.01	573.53	523.73	491.96	671.12	574.01
Own revenues per capita	1995	1,323.31	706.38	817.77	959.60	1,113.19	937.29
	2005	2,299.77	1,285.73	1,758.46	1,859.01	1,825.00	2,122.48
	2015	3,659.58	2,250.30	2,911.66	3,053.13	3,062.19	3,432.31
PIT revenues per capita	1995	312.86	227.43	242.79	265.13	248.52	255.70
	2005	447.29	201.19	387.97	379.16	249.47	470.69
	2015	769.64	433.52	682.69	684.79	533.43	803.61
Firms per inhabitant in productive age	1995	0.11	0.05	0.09	0.09	0.06	0.10
	2005	0.18	0.10	0.15	0.15	0.11	0.16
	2015	0.22	0.11	0.17	0.16	0.13	0.18
Unemployment rate	1995	NaN	NaN	NaN	NaN	NaN	NaN
	2005	12.71	13.63	13.01	14.91	14.20	12.22
	2015	6.87	7.69	7.84	7.65	7.49	6.79
Share of population in productive age	1995	0.59	0.55	0.59	0.60	0.56	0.60
	2005	0.64	0.61	0.64	0.65	0.63	0.65
	2015	0.63	0.63	0.63	0.63	0.64	0.63

[i] Source: The author’s results.

Table A2

P-value of Wilcoxon paired and unpaired tests for similarity of distributions

Firms per inhabitant
	sub10	sub20	sub30	sub40	sub50	sub60	sub1	sub2	sub3	sub4	sub5	sub6
sub10	1	0	0.27	0.5	0	0.74	0	0.85	0	0	0.04	0
sub20	0	1	0	0	0	0	0	0	0	0	0	0
sub30	0.27	0	1	0.6	0	0.09	0	0.06	0	0	0	0
sub40	0.5	0	0.6	1	0	0.13	0	0.21	0	0	0	0
sub50	0	0	0	0	1	0	0	0	0	0	0	0
sub60	0.74	0	0.09	0.13	0	1	0	0.86	0	0	0	0
sub1	0	0	0	0	0	0	1	0	0.2	0.26	0	0.79
sub2	0.85	0	0.06	0.21	0	0.86	0	1	0	0	0	0
sub3	0	0	0	0	0	0	0.2	0	1	0.5	0	0.09
sub4	0	0	0	0	0	0	0.26	0	0.5	1	0	0.1
sub5	0.04	0	0	0	0	0	0	0	0	0	1	0
sub6	0	0	0	0	0	0	0.79	0	0.09	0.1	0	1
PIT revenues per capita
	sub10	sub20	sub30	sub40	sub50	sub60	sub1	sub2	sub3	sub4	sub5	sub6
sub10	1	0	0	0.3	0	0.08	0	0	0	0	0	0
sub20	0	1	0	0	0	0	0	0	0	0	0	0
sub30	0	0	1	0.04	0.94	0.01	0	0	0	0	0	0
sub40	0.3	0	0.04	1	0.03	0.61	0	0	0	0	0	0
sub50	0	0	0.94	0.03	1	0.01	0	0	0	0	0	0
sub60	0.08	0	0.01	0.61	0.01	1	0	0	0	0	0	0
sub1	0	0	0	0	0	0	1	0	0.39	0.95	0	0.02
sub2	0	0	0	0	0	0	0	1	0	0	0	0
sub3	0	0	0	0	0	0	0.39	0	1	0.62	0	0
sub4	0	0	0	0	0	0	0.95	0	0.62	1	0	0.06
sub5	0	0	0	0	0	0	0	0	0	0	1	0
sub6	0	0	0	0	0	0	0.02	0	0	0.06	0	1
Own revenues per capita
	sub10	sub20	sub30	sub40	sub50	sub60	sub1	sub2	sub3	sub4	sub5	sub6
sub10	1	0	0	0.35	0	0.08	0	0	0	0	0	0
sub20	0	1	0	0	0	0	0	0	0	0	0	0
sub30	0	0	1	0.11	0.01	0	0	0	0	0	0	0
sub40	0.35	0	0.11	1	0.01	0.88	0	0	0	0	0	0
sub50	0	0	0.01	0.01	1	0	0	0	0	0	0	0
sub60	0.08	0	0	0.88	0	1	0	0	0	0	0	0
sub1	0	0	0	0	0	0	1	0	0	0.44	0	0.83
sub2	0	0	0	0	0	0	0	1	0	0	0	0
sub3	0	0	0	0	0	0	0	0	1	0.05	0.01	0
sub4	0	0	0	0	0	0	0.44	0	0.05	1	0	0.36
sub5	0	0	0	0	0	0	0	0	0.01	0	1	0
sub6	0	0	0	0	0	0	0.83	0	0	0.36	0	1
Public investment per capita
	sub10	sub20	sub30	sub40	sub50	sub60	sub1	sub2	sub3	sub4	sub5	sub6
sub10	1	0.06	0.13	0.98	0.38	0.39	0	0	0.15	0.32	0	0
sub20	0.06	1	0.77	0.18	0.07	0.05	0	0	0	0.01	0	0
sub30	0.13	0.77	1	0.23	0.3	0.18	0	0	0	0.02	0	0
sub40	0.98	0.18	0.23	1	0.45	0.5	0.04	0.03	0.3	0.5	0	0.03
sub50	0.38	0.07	0.3	0.45	1	0.88	0	0	0	0.07	0	0
sub60	0.39	0.05	0.18	0.5	0.88	1	0	0	0	0.04	0	0
sub1	0	0	0	0.04	0	0	1	0.54	0.07	0.28	0.33	0.83
sub2	0	0	0	0.03	0	0	0.54	1	0.02	0.36	0	0.66
sub3	0.15	0	0	0.3	0	0	0.07	0.02	1	0.96	0	0.03
sub4	0.32	0.01	0.02	0.5	0.07	0.04	0.28	0.36	0.96	1	0.05	0.3
sub5	0	0	0	0	0	0	0.33	0	0	0.05	1	0.05
sub6	0	0	0	0.03	0	0	0.83	0.66	0.03	0.3	0.05	1
Unemployment rate
	sub10	sub20	sub30	sub40	sub50	sub60	sub1	sub2	sub3	sub4	sub5	sub6
sub10	1	0.1	0.25	0.07	0.01	0.78	0	0	0	0	0	0
sub20	0.1	1	0.42	0.19	0.02	0	0	0	0	0	0	0
sub30	0.25	0.42	1	0.08	0.01	0.11	0	0	0	0	0	0
sub40	0.07	0.19	0.08	1	0.56	0.02	0	0	0	0	0	0
sub50	0.01	0.02	0.01	0.56	1	0	0	0	0	0	0	0
sub60	0.78	0	0.11	0.02	0	1	0	0	0	0	0	0
sub1	0	0	0	0	0	0	1	0.02	0.01	0.2	0.13	0.67
sub2	0	0	0	0	0	0	0.02	1	0.33	0.89	0.4	0
sub3	0	0	0	0	0	0	0.01	0.33	1	0.85	0.19	0
sub4	0	0	0	0	0	0	0.2	0.89	0.85	1	0.69	0.17
sub5	0	0	0	0	0	0	0.13	0.4	0.19	0.69	1	0.07
sub6	0	0	0	0	0	0	0.67	0	0	0.17	0.07	1
Share of population in productive age
	sub10	sub20	sub30	sub40	sub50	sub60	sub1	sub2	sub3	sub4	sub5	sub6
sub10	1	0	0.14	0.36	0	0.09	0	0	0	0	0	0
sub20	0	1	0	0	0	0	0	0	0	0	0	0
sub30	0.14	0	1	0.05	0	0	0	0	0	0	0	0
sub40	0.36	0	0.05	1	0	0.72	0	0	0	0	0	0
sub50	0	0	0	0	1	0	0	0	0	0	0	0
sub60	0.09	0	0	0.72	0	1	0	0	0	0	0	0
sub1	0	0	0	0	0	0	1	0.61	0.22	0.73	0	0.22
sub2	0	0	0	0	0	0	0.61	1	0	0.47	0	0
sub3	0	0	0	0	0	0	0.22	0	1	0.76	0	0.82
sub4	0	0	0	0	0	0	0.73	0.47	0.76	1	0.01	0.68
sub5	0	0	0	0	0	0	0	0	0	0.01	1	0
sub6	0	0	0	0	0	0	0.22	0	0.82	0.68	0	1

[i] Note: Similar distributions (p > 0.05) were highlighted in red, diagonal elements not for interpretation in grey.

[ii] sub10-sub60 for period 1995–1997 (unemployment 2003–2005), sub1–sub6 for period 2014–2016.

[iii] sub10, sub1: urban municipalities, no authorities’ seats, no SEZ.

[iv] sub20, sub2: rural and mixed municipalities, no authorities’ seats, no SEZ.

[v] sub30, sub3: municipalities with seats of authorities, no SEZ.

[vi] sub40, sub4: urban municipalities, no authorities’ seats, with SEZ.

[vii] Sub50, sub5: rural and mixed municipalities, no authorities’ seats, with SEZ.

[viii] sub60, sub6: municipalities with seats of authorities, with SEZ.

[ix] Source: The author’s results.

References

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Articles in this issue

DOI: https://doi.org/10.2478/ceej-2019-0019 | Journal eISSN: 2543-6821 | Journal ISSN: 2544-9001

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Language: English

Page range: 221 - 245

Published on: Jun 6, 2020

Published by: Faculty of Economic Sciences, University of Warsaw

In partnership with: Paradigm Publishing Services

Keywords:

Special Economic Zones

JEL:

R12,

R53,

C21

Related subjects:

Business and economics,

Political economics,

Economic theory, systems and structures,

Microeconomics,

Macroeconomics,

Economic policy

© 2020 Katarzyna Kopczewska, published by Faculty of Economic Sciences, University of Warsaw
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 6 (2019): Issue 53 (January 2019)

Can public intervention improve local public sector economic performance? The analysis of Special Economic Zones in Poland

Figures & Tables

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Table A1

Table A2

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