We gathered data series of GDP per capita, K and H, from the World Bank indicators (World Bank 2023). Good governance indicators obtained from World Governance Indicators (WGI) research (World Bank 2023). E-government indexes are from UN E-Government Survey (2022). The estimation period is 2003-2021 and 20 Middle East and North African countries are considered.
6-1 EGDI
EGDI is a weighted average of three normalized scores on three most important dimensions of e-government, namely: (1) scope and quality of online services (Online Service Index, OSI), (2) development status of telecommunication infrastructure (Telecommunication Infrastructure Index, TII), and (3) inherent human capital (Human Capital Index, HCI). Each of these indices is a composite measure that can be extracted and analyzed independently (table 1).
Table1. Sub-Indexes of EGDI (three most important dimensions of e-government)
Sub-Indexes
|
Index
|
(i) Adult literacy rate
(ii) The combined primary, secondary and tertiary gross enrolment ratio
(iii) Expected years of
schooling
(iv) Average years of schooling
|
Human Capital
|
(i) Estimated internet users per 100 inhabitants
(ii) Number of main fixed telephone lines per 100 inhabitants
(iii) Number of mobile subscribers per 100 inhabitants; (iv) number of wireless broadband subscriptions per 100 inhabitants
(v) Number of fixed broadband subscriptions per 100 inhabitants
|
Telecommunication Infrastructure (TII)
|
scale and quality of online services
|
Online Service Index
|
EGDI = 1/3 (OSI normalized + TII normalized + HCI normalized)
6-2 Good Governance
According to World Bank Development Research Group, 6 sub-indexes describe good governance. We can see definition of these indicators in table 2.
Table2. Sub-Indexes of Good Governance
Index
|
Definition
|
Control of Corruption
|
Perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests.
|
Government Effectiveness
|
Perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies.
|
Political Stability and Absence of Violence/Terrorism
|
Measures perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism.
|
Regulatory Quality
|
Perceptions of the ability of the government to formulate and implement sound policies and regulations that permits and promotes private sector development.
|
Rule of Law
|
Perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence.
|
Voice and Accountability
|
perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media.
|
For all indexes, estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.
6-3 Outcome variables
First considering descriptive statistics in table 3 show that Malt is a country with maximum human capital, e-government, and good governance in the region. On the other hand, Qatar has the maximum value of GDP Per capita and capital stock per worker between 20 countries in research. Through Table 3, we can see the critical question: Is there a chance that the difference in income may depend on the difference in the quality of government and apply of ICT in governance as e-government?
Table3. Summery Descriptive Variables
Variable
|
Obs
|
Mean
|
Std.Dev.
|
Min
|
Max
|
|
366
|
32883.64
|
25435.21
|
2557.070
(Syrian 2020)
|
98989.99
(Qatar 2011)
|
k
|
380
|
10245.44
|
10661.34
|
171.7970
(Djibouti 2019)
|
76922.08
(Qatar 2004)
|
h
|
380
|
7.69E-05
|
0.000144
|
2.40E-06
(Egypt 2010)
|
0.000659
(Malt 2004)
|
egdi
|
380
|
0.490421
|
0.182001
|
0.110000
(Libya 2006)
|
0.890000
(Malt 2021)
|
gov
|
|
-1.641534
|
4.328546
|
-10.63177
(Yemen 2021)
|
6.555153
(Malt 2008)
|
Before estimating the model, stationary test is essential for avoiding spurious regression. Some variables in the model are stationary in level, but EGDI and good governance are not stationary. Non- stationary variables are stationary with the first difference, (table 4). For long run relation, we need to conduct co-integration test. Results in table 5 indicate that null hypothesis is rejected. Then there is a long run relation among variables with 95% confidence.
Table4. Stationary Test
Variable
|
ADF Unit Root Statistics
|
P-Value
|
Stationary Level
|
GDPpc
|
457.086
|
0.0000
|
I(0)
|
k
|
771.070
|
0.0000
|
I(0)
|
h
|
73.5600
|
0.0010
|
I(0)
|
egdi
|
193.889
|
0.0000
|
I(1)
|
gov
|
193.591
|
0.0000
|
I (1)
|
Table5. Padroni (Engle Granger Based) Co-integration Test
Statistics
|
P-value
|
33.51352
|
0.0000
|
We can see estimation results in table 6 including k, h, egdi, gov, and lagged dependent variable. The effect of e-government and good governance on GDP per capita is positive and meaningful. On the other hand, lagged dependent variable, human capital and physical capital have a positive effect on the dependent variable that is consistent with the literature.
Table6. PCSE Analysis Results
|
Dependent Variable:
|
|
|
Independent Variables
|
Coefficient
|
T-Statistics
|
P-Value
|
(-1)
|
0.942331
|
3265.812
|
0.0000
|
k
|
0.036122
|
136.7185
|
0.0000
|
h
|
681046.0
|
20.32497
|
0.0000
|
egdi
|
923.4209
|
72.55846
|
0.0000
|
gov
|
151.3007
|
287.6728
|
0.0000
|
Number of observation
|
310
|
|
|
|
.99
|
|
|
Arenallo-Bond Test for AR(1), (P-Value)
|
0.9357
|
|
|
Arenallo-Bond Test for AR(2), (P-Value)
|
0.9638
|
|
|
Sargan Test, (P-Value)
|
0.9999
|
|
|
Wald Test, (P-Value)
|
0.0000
|
|
|
- According to Wald test with λ^2 distribution null hypothesis rejected, and so validity of coefficients approves in 95% confidence.
- Sargan test has λ^2 distribution with freedom degree equal to over-identifying restrictions. P-value for Sargan test is more than 0.05. This means there is no correlation between instrument variables and residuals, so results are valid.
- AR (1) and AR (2) reject autocorrelation.