AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
T
IEF
1,002
-3,582
2,786
2,260
0,196
T
EFW
-0,407
-5,703
3,444
3,645
Hungary
IEF
66,100
62,700
67,600
2,476
0,523
EFW
72,000
65,600
73,600
3,765
T
IEF
-0,303
-2,326
4,321
2,615
0,067
T
EFW
0,486
-1,250
5,183
2,419
Poland
IEF
63,200
58,100
69,300
12,433
0,571
EFW
69,600
61,400
74,200
12,736
T
IEF
1,222
-5,016
4,809
7,789
0,005
T
EFW
1,140
-3,155
7,980
7,445
Slovak
Republic
IEF
67,200
59,000
70,000
11,196
0,829
EFW
74,200
62,000
76,300
17,648
T
IEF
0,073
-3,597
9,492
10,600
0,001
T
EFW
0,396
-2,252
9,209
8,620
Source: own calculation based on The Heritage Foundation
and Fraser Institute data
Both indices are linearly correlated in 13 countries (e.g.
Bulgaria, Romania, Slovak Republic), while this correlation can
be defined as great or even perfect.
Even the annual growth rate of indices is similar, considering the
median and distribution function.
3.1 The Importance of EFW in Economic Policy
Index evaluation of economic freedom provides only a
retrospective comprehensive status evaluation. If the evaluation
is applicable by decision making and tools of national economic
policy, the usefulness of information is low, the way of
monitoring and evaluating the economic freedom may be
considered deficient.
Figure 1 Time series of EFW in V4 countries
If the economic freedom is a consequence of the activity of
economic entities of the system and the system itself, as well as
of the conditions, then the analysis of the interrelationship
between the values of the economic freedom indicator and the
indicators that characterize the economic activity in a larger set
of countries or the examination of the correlation between the
historical values of the economic freedom indicator and the
indicators that characterize the economic activity in a particular
country are possible ways to monitor the economic freedom
(Table 2).
Table 2 Economic Freedom of World in the context of
macroeconomic characteristics
EU
(28)
Czech
Republic
Hungary
Poland
Slovak
Republic
EFW
7,53
7,30
7,42
7,45
GDP per inhabitant (€)
27
600,0
14 900,0
10 600,0
10
700,0
14 000,0
GDP growth rate (%)
1,6
2,7
4,0
3,3
2,6
Inflation (%)
0,8
2,5
3,4
0,5
-0,2
Export share to GDP (%)
42,7
82,5
88,7
47,6
91,8
Tax burden ( % GDP)
40,0
35,3
35,7
31,7
28,8
Gross public debt (% GDP)
86,7
42,2
75,7
50,2
53,6
Unemployment (%)
11,6
6,1
7,7
9,0
13,2
Source: based on the data of the World Development Indicators
2016 and Fraser Institute: Economic Freedom of the World
2016
Looking for linear correlation between the EFW index and the
single macroeconomic indicators (Table 3), we can assume that
heterogeneous composition of the EU caused zero hypothesis
confirmation. The EFW index linearly correlates with the public
debt in all V4 countries. If the index is rising, the public debt is
growing in the countries. The opposite happens in Slovakia. Tax
burden and inflation do not linearly correlate with the EFW
index.
Figure 2 Correlation of the EFW index and the selected
macroeconomic indicators in EU(28)
Table 1 Correlation of the EFW index and the selected
macroeconomic indicators
per GDP
Coeffici
ent
Tax
Burden
Export
GDP
growth
Public
debt
Inflation
Unemp
loyment
EU (28)
r
S
0,2941
-0,2000
0,3667
-0,4333
-0,0167
-0,5500
p-value
0,4055
0,5716
0,2997
0,2203
0,9624
0,1198
Czech
Republic
r
S
0,4202
0,8452
-0,2773
0,7866
0,0167
-0,2194
p-value
0,2347
0,0168
0,4328
0,0261
0,9622
0,5349
Hungary
r
S
-0,1688
0,8152
-0,0672
0,8320
-0,4346
0,6456
p-value
0,6331
0,0211
0,8492
0,0186
0,2190
0,0679
Poland
r
S
-0,4268
0,7615
-0,7667
0,7333
-0,2762
0,0669
p-value
0,2274
0,0312
0,0301
0,0381
0,4348
0,8498
Slovakia
r
S
0,2500
-0,2667
0,8667
-0,7500
0,3000
-0,7167
p-value
0,4795
0,4507
0,0142
0,0339
0,3961
0,0427
Source: author, processed according the World Bank data:
World Development Indicators 2016
We can monitor the same trend in V4 countries, as well as in the
EU by using linear correlation that does not depend on GDP or
inflation. The development of the EFW index can be compared
linearly with the V4 public debt.
The EFW index development can relate to the evolution of tax
burden, exports, public debt and unemployment, using
regression models. The EFW regression models with tax burden,
export, public debt, and unemployment can be considered as
high-availability models (Table 4).
Table 2 Regression models of the relation between the EFW
index and the chosen indicators
regression model
Model
CD
EU (28)
EFW = 1,8984*TAX BURDEN
0,9998
EFW = 1,85685*EXPORT
0,9905
EFW = 11,1443*GDP GROWTH
0,1261
EFW = 0,977635*PUBLIC DEBT
0,9771
EFW = 29,0017*INFLATION
0,8345
EFW = 7,9314*UNEMPLOYMENT
0,9783
Czech Republic
EFW = 2,16663*TAX BURDEN
0,9994
EFW = 1,03212*EXPORT
0,9924
EFW = 9,14372*GDP GROWTH
0,2216
EFW = 1,93148*PUBLIC DEBT
0,9724
EFW = 20,2795*INFLATION
0,6377
EFW = 11,1112*UNEMPLOYMENT
0,9795
Hungary
EFW = 1,89971*TAX BURDEN
0,9991
EFW = 0,880642*EXPORT
0,9969
EFW = 4,57347*GDP GROWTH
0,3811
EFW = 0,966551*PUBLIC DEBT
0,9957
EFW = 13,4875*INFLATION
0,7818
EFW = 7,57548*UNEMPLOYMENT
0,9745
Poland
EFW = 2,14441*TAX BURDEN
0,9971
EFW = 1,7154*EXPORT
0,9949
EFW = 14,963*GDP GROWTH
0,8095
EFW = 1,41182*PUBLIC DEBT
0,9964
EFW = 21,076*INFLATION
0,7572
EFW = 7,11111*UNEMPLOYMENT
0,9661
Slovakia
EFW = 2,55515*TAX BURDEN
0,9989
EFW = 0,884317*EXPORT
0,9903
EFW = 8,46*GDP GROWTH
0,4225
EFW = 1,70188*PUBLIC DEBT
0,9414
EFW = 21,8377*INFLATION
0,6831
EFW = 5,68731*UNEMPLOYMENT
0,9842
Source: authors, own calculation
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