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Relationship between rule of law and tax revenues: dynamic panel data analysis
Article | Year: 2022 | Pages: 403 - 419 | Volume: 46 | Issue: 3 Received: September 6, 2021 | Accepted: April 28, 2022 | Published online: August 29, 2022
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FULL ARTICLE
FIGURES & DATA
REFERENCES
CROSSMARK POLICY
METRICS
LICENCING
PDF
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Variables
|
Period
|
Frequency
|
Source
|
Symbol
|
|
Tax
Revenue (GDP %)
|
2002-2018
|
Annual
|
World Bank
|
TR
|
|
Rule
of Law
|
2002-2018
|
Annual
|
World Bank
|
RL
|
|
Import
(GDP %)
|
2002-2018
|
Annual
|
World Bank
|
ImGDP
|
|
GDP
Per Capita
|
2002-2018
|
Annual
|
World Bank
|
GDPPC
|
|
Agriculture
Sector (GDP %)
|
2002-2018
|
Annual
|
World Bank
|
Agri
|
|
Industry
(GDP %)
|
2002-2018
|
Annual
|
World Bank
|
Ind
|
|
Service
(GDP %)
|
2002-2018
|
Annual
|
World Bank
|
Ser
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Note: All with annual frequency, in 2002-2018 period, source World Bank. Source: Authors’ preparation.
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Variables
|
No. of observations
|
Mean
|
Std. Deviation
|
Minimum
|
Maximum
|
|
Tax
Revenue (GDP %)
|
1,003
|
18.67
|
5.75
|
7.03
|
48.56
|
|
Rule
of Law
|
1,003
|
64.50
|
26.81
|
4
|
100
|
|
Import
(GDP %)
|
1,003
|
50.90
|
27.81
|
11.25
|
208.33
|
|
GDP
Per Capita
|
1,003
|
22,675.04
|
23,677.72
|
474.94
|
111,968.3
|
|
Agriculture
Sector (GDP %)
|
1,003
|
5.90
|
6.24
|
0.0284
|
34.55
|
|
Industry
(GDP %)
|
1,003
|
25.23
|
5.93
|
9.88
|
45.09
|
|
Service
(GDP %)
|
1,003
|
59.02
|
8.25
|
35.02
|
79.33
|
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Variables/Tests
|
Breusch-Pagan
LM
|
Pesaran CD
|
|
TR
|
5711.564(0.000)
|
14.786(0.000)
|
|
RL
|
5557.867(0.000)
|
3.59 (0.0003)
|
|
ImGDP
|
9028.183
(0.000)
|
44.392(0.000)
|
|
GDPPC
|
17723.44(0.000)
|
110.6822(0.0000)
|
|
Agri
|
9371.135
(0.000)
|
63.469
(0.0000)
|
|
Service
|
9979.556(0.000)
|
51.36084(0.0000)
|
|
Indp
|
9439.447(0.0000)
|
42.49648(0.0000)
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Variables
|
Test
Statistic Value
|
Probability
|
|
TR
|
-4.11287
|
0.000
|
|
RL
|
-5.38299
|
0.000
|
|
ImGDP
|
-8.42850
|
0.000
|
|
GDPPC
|
-5.28732
|
0.000
|
|
Agri
|
-10.3820
|
0.000
|
|
Service
|
-5.27322
|
0.000
|
|
Indp
|
-5.82446
|
0.000
|
|
Dependent
Variable: TRit
|
|
|
Independent
Variables
|
(1)
|
(2)
|
(3)
|
|
TRit-1
|
-0.0409***
(0.006580)
|
-0.0786***
(0.005999)
|
-0.076729***
(0.007228)
|
|
RLit
|
0.0672***
(0.002716)
|
0.0650***
(0.002504)
|
0.0666***
(0.001732)
|
|
ImGDPit
|
-0.296***
(0.017728)
|
-0.3291***
(0.019130)
|
-0.3376***
(0.013551)
|
|
Agriit
|
-0.4495***
(0.013394)
|
-0.4807***
(0.02472)
|
-0.4505
(0.021178)
|
|
Serviceit
|
-.0.3197***
(0.011396)
|
-0.3538***
(0.01706)
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-0.3311***
(0.015736)
|
|
Indpit
|
|
0.2133***
(0.014250)
|
|
|
RLit×KUKit
|
|
|
3.84E-06***
(3.97E-07)
|
|
RLit×GDPPCit
|
|
|
-0.000374***
(3.44E-05)
|
|
GDPPCit
|
-0.0409***
(0.006580)
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-0.0786***
(0.005999)
|
-0.076729***
(0.007228)
|
|
Sargan
Test
|
53.23329
(0.42)
|
54.3208
(0.38)
|
54.30157
(1.000)
|
|
AR(1)
|
(0.044)
|
(0.045)
|
(0.0038)
|
|
AR
(2)
|
(0.777)
|
(0.842)
|
0.2255
|
Note: *** shows that the variables are statistically significant at the 1% significance level. The instrumental variables used in the model based on the probability values of the Sargan Test are valid. Furthermore, contrary to the expectations, there is no autocorrelation problem in the model according to the AR (2) probability value. Source: Authors’ calculation.
|
Countries
=>20.000 $
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Australia,
Austria, Belgium, Cyprus, Czechia, Denmark, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Israel, Italy, Luxemburg, Netherland, Norway,
Portugal, Singapore, Slovenia, Spain, Sweden, Switzerland, United Kingdom
|
|
Countries
<20.000 $
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Argentina,
Belarus, Bhutan, Brazil, Bulgaria, Burkina, Cambodia, Costa Rica, Cote d’Ivoire,
El Salvador, Estonia, Georgia, Guatemala, Jamaica, Jordan, Latvia, Lebanon,
Lithuania, Croatia Mauritius, Moldova, Morocco, Nicaragua, Peru, Philippines,
Poland, Romania, Russia, Slovakia, South Africa, Sri Lanka, Thailand, Ukraine,
Zambia
|
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September, 2022
III/2022 |
