International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 04, April 2019, pp. 324-331, Article ID: IJCIET_10_04_034
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=04
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication
Scopus Indexed
THE EFFECT OF CORRUPTION ON ASIAN
ECONOMIC GROWTH
Khubbi Abdillah
Economics Doctoral Program, Faculty of Economics and Business, Universitas Airlangga,
Indonesia
Rossanto Dwi Handoyo and Wasiaturrahma
Departement of Economics, Faculty of Economics and Business, Universitas Airlangga,
Indonesia
ABSTRACT
This study aims to analyze the correlation between corruptions with economic
growth in Asia. The data were analyzed using GMM panel regression during 20102017 period. The result of the analysis shows corruption positively affect economic
growth. High corruption rate inhibits the economic growth and economic growth will
facilitate the economic growth. Abuse of power through corruption practices inhibits
economic growth.
Keywords: Corruption, Economic Growth, GMM
Cite this Article: Khubbi Abdillah, Rossanto Dwi Handoyo and Wasiaturrahma, the
Effect of Corruption on Asian Economic Growth, International Journal of Civil
Engineering and Technology, 10(04), 2019, pp. 324-331
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=04
1. INTRODUCTION
The correlation between corruptions (institutional factor) with economic growth becomes an
interesting issues to analyze. Acemoglu and Robinson (2013) states institutional factor is an
important factor that determines success or failure of economic development in a country.
Institutional factor occurs as the result of government failure in allocating economic resources
optimally. Countries with established institution tend to have good economic performance.
On the contrary, countries with poor institution will have bad economic performance, such
as unsustainable economic growth, low productivity, high poverty rate, and low economic
prosperity caused by corruptive actions of the government officials, bad governance, unfair
democracy system, limited economic freedom, and so on. Economic growth tends to slow
down in countries that have poor institutional quality. Institutional quality in a country can be
seen from level of corruption (Mankiw, 2007).
http://www.iaeme.com/IJCIET/index.asp
324
editor@iaeme.com
Khubbi Abdillah, Rossanto Dwi Handoyo and Wasiaturrahma
In general, corruption is an illegal action. The development of a country can be achieved
through corruption-free governance, effective and efficient policies, and straightforward
bureaucracy. Study Lucic, Radisic, and Dobromirov (2016) find that corruption is a fact faced
by all the countries in the world. Effort to eliminate corruption depends on the characteristics
of each country, for example economic freedom, financial structure, government expenses, and
democracy level because there are countries with high corruption and high economic growth
rate and there are countries with high economic growth rate and low corruption (Chea, 2015).
Del Monte and Papagni (2001) suggest the policies to prevent corruption in improving local
public institution efficiency provides positive impulse on economic growth. Although many
local officials have been punished, policies to eliminate corruption crime are still needed to
monitor corruption in the government (Lui, 1996).
This study is important because issues of these research empirically still have not shown
consistent results. The institutional factor approach is based on potential economic leakage due
to corrupt behavior, isolated democracy or poor governance. This study contributes to
government to pay attention to the institutional aspects in encouraging sustainable economic
growth.
Based on the background above, the study complement the issues of influence of corruption
on economic growth. So far, there is no study that analyze the influence of corruption
(corruption perception index and control corruption) and control variables (democracy, rule of
law, political stability, investment, education, government consumption, and openness) on
economic growth using GMM method. This study also comprehences the perspective of Asian
regions which is using panel data with 40 Asian countries observed during 2010-2017 period.
2. LITERATURE REVIEW
Studies on the effect of corruption towards economic growth have been conducted with
different issues. Mauro (1995), Meon and Sekkat (2005), D’Amico (2015), Cieslik and Goczek
(2018) finds that corruption lowers investment and economic growth. Mo (2001) finds that
corruption reduces economic growth, the level of human capital and the share of private
investment. Corruption lowers economic growth and prevents business development.
Economic growth may increase if corruption can be minimized through comprehensive
bureaucratic reform and liberalization (Paksha Paul, 2010). The study conducted by Amin,
Ahmed, and Zaman (2013) suggests that corruption is a major factor constraining economic
development that proportionally burdens the poor and impedes the effectiveness of incoming
foreign investment and aid received by a country. Pulok and Ahmed (2017) finds that economic
growth increases by reducing corruption through institutional reform and raising public
awareness of the dangers of corruption. The study of Nwogu and Ijirshar (2016) states that
Corruption has a negative effect on economic growth and becomes a bad culture.
On the other hand, the negative correlation between corruption and economic growth was
indicated by the study conducted by Huang (2016) analyzing the correlation between
corruption and economic growth in Asian Pacific countries. The findings of this study
suggested that corruption did not significantly affect economic growth in 13 Asian Pacific
countries, except China and South Korea which showed that the increasing economic growth
entailed increasing corruption. This finding confirms grease the wheel hypothesis perceiving
corruption as “the lubricant of development”. The finding of the study indicates that most of
Asian Pacific countries do not effectively implement anti-corruption policy to enhance its
economic development. Mallik and Saha (2016) found that corruption negatively affects
economic growth. They found that corrupt country stimulates its economic growth by
cutting/reducing red tapes (i.e. regulations, procedures, and rules).
http://www.iaeme.com/IJCIET/index.asp
325
editor@iaeme.com
The Effect of Corruption on Asian Economic Growth
3. DATA AND METHODOLOGY
The data used in this study are secondary data and panel data. This study used annual data of
40 Asian countries from 2010-2017 period. Several countries, namely North Korea, Syria,
Pakistan, Myanmar, Macau, Maldives, Iran, Iraq, and Brunei Darussalam were excluded from
this study due to data limitation. The data were obtained from World Development Indicators,
Worldwide Governance Indicators, Transparency International, and The Economist
Intelligence Unit. The measurement used in this study was ratio stated in the unit of decimals
and index.
Table 1
Data Sources
Source
Transparency
International (2018)
The Economist
Intelligence Unit (2018)
WDI (2018)
WGI (2018)
Definition
Corruption Perception
Index
Variable
Democracy Index
Democracy
GDP per capita growth
(annual %)
Logarithm Natural of
GDP per capita
(constant 2010)
Net inflows foreign
direct investment (% of
GDP)
General final
consumption
expenditure (% of
GDP)
School enrollment,
secondary (% gross)
Trade (% of GDP)
Governance Indicators
Corruption
Economic Growth
Ln Initial GDPt-1
Foreign Direct
Investment
Government
Consumption
Education
Openness
Control Corruption
Political stability
Rule of law
Source: own information
This study adopted technique of analysis proposed by Cieslik and Goczek (2018) analyzing
control corruption and FDI on economic growth by using panel data. The analysis technique
used in this study was dynamic panel model. Panel data can substantially reduce the omitted
variable problem or ignore the relevant variables (Gujarati, 2009). There are many economic
behaviors expressed from the use of lag dependent variables as the regressor which causes
endogeneity issue so that if the model is estimated using fixed effects approach and random
effects approach the resulted estimators will be biased and inconsistent (Verbeek, 2008). In
order to solve this issue, Arellano and Bond (1991) proposed method of moment approach, or
commonly known as Generalized Method of Moment (GMM).
The econometric equation used in this study can be formulated as:
𝑌𝑖𝑡 = 𝛽0 + 𝛽1𝑙𝑛𝑌𝑖, 𝑡 − 1 + 𝛽2𝐶𝐶𝑖𝑡 + 𝛽3𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑖𝑡 𝜈𝑖 + 𝜏𝑡 + 𝜀𝑖𝑡
http://www.iaeme.com/IJCIET/index.asp
326
editor@iaeme.com
(1)
Khubbi Abdillah, Rossanto Dwi Handoyo and Wasiaturrahma
𝑌𝑖𝑡 = 𝛽0 + 𝛽1𝑙𝑛𝑌𝑖, 𝑡 − 1 + 𝛽2𝐼𝑃𝐶𝑖𝑡 + 𝛽3𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑖𝑡 + 𝜈𝑖 + 𝜏𝑡 + 𝜀𝑖𝑡
Where:
Yit
lnYi,t-1
CCit
IPCit
Controlit
νi
τt
εit
i
t
(2)
= GDP per capita growth
= Lag initial GDP per capita growth
= Control Corruption
= Corruption Perception Index
= Control variables
= Cross-section specific effect
= Periode-specific effect common to all regions
= Error term
= Country (cross-section)
= Year
4. FINDING AND DISCUSSION
TURKMENISTAN
RRC
LAOS
MONGOLIA
INDIA
UZBEKISTAN
KAMBOJA
BANGLADESH
TURKI GEORGIA
BHUTAN
VIETNAM
SRILANKA
TAJIKIZTANFILIPINA
INDONESIA
SINGAPURA
ARMENIA
MALAYSIA
THAILAND
NEPAL
KAZAHSTAN
KORSEL
HONGKONG
KIRGIZTAN
PAKISTAN
ISRAEL UEA
JEPANG
ARAB
SAUDI
BAHRAIN
AZERBAIJAN
QATAR
SIPRUS
LEBANON
YORDANIA
OMAN
TIMOR LESTE KUWAIT
-10
-5
0
5
10
The Asian continent is divided based on geographical location into five regions, namely West
Asia, South Asia, Central Asia, Southeast Asia, and East Asia. Figure 1 shows that the average
corruption perception index in most Asian countries has a score below 50. This shows that
there are still many countries in Asia with high corruption rates. Almost all middle and low
income countries have problems with high corruption. Countries with a low category of
corruption are dominated by high-income countries. This can be seen from the value of the
corruption perception index above 49. The country with the highest corruption perception index
score is owned by Singapore at 87, followed by Hong Kong and Japan at 78 and 75
respectively. However, there are some high-income countries with high corruption, namely
Bahrain, Saudi Arabia, and Kuwait which are in fact West Asian countries. Then, middle and
lower income countries categorized as low corruption are Bhutan and Georgia. The higher the
corruption perception index score, indicates that the state has a low level of corruption, and
vice versa.
-15
YAMAN
20
40
Source: own calculation
60
CPI
GDPCap
GDPCap
GDPCap
80
100
GDPCap
GDPCap
Fitted values
Figure 1 Correlation Corruption and Economic Growth
Based on the analysis of dynamic panel used in this study, Table 2 below shows p-value of
Hansen test on Asia exceeds significance value 10% indicating that there is no rejection on H0.
http://www.iaeme.com/IJCIET/index.asp
327
editor@iaeme.com
The Effect of Corruption on Asian Economic Growth
Therefore, all variables in this study is valid and the equation model is robust. The result of
Hansen test also indicates goodness of fit in the equation model.
Table 2 also shows the result of examination to identify the occurrence of auto-correlation
to eliminate biases happening in the equation model, as indicated by p-value AR (2) higher
than 10% indicating that there is no rejection on H0 and there is no auto-correlation in the
model. Hence, the estimator used in this model is “xtabond2” proposed by Arellano and Bond
(1991).
Table 2
The Growth Model
Variable
Ln Initial GDPt-1
Control Corruption
Model I
Twostep System GMM
-6,053*
(1,078)
4,129*
(1,636)
Corruption Perception Index
Democracy Index
Foreign Direct Investment
Education
Openness
Government Consumption
0,102*
(0,033)
0,271*
(0,051)
-0,006
(0,007)
-0,072
(0,056)
Government Consumption^2
Political Stability
Rule of Law
Wald test
Number of time series
Number of cross-section
Number of groups
number of instruments
Hansen test
Test for Residual AR (1)
Test for Residual AR (2)
1,739**
(0,764)
-1,995
(1,830)
1699,99*
7
40
36
28
0,734
0,148
0,316
Model II
Twostep System GMM
-10,199*
(1,337)
0,151*
(0,054)
4,201*
(0,628)
-0,012*
(0,628)
0,292*
(0,034)
0,034*
(0,009)
2,022*
(0,573)
-0,045*
(0,012)
742,66*
7
40
36
30
0,917
0,198
0,848
Note: *, **, are significant at 1% and 5 %
From Table 2 it can be seen that all initial variables of GDP per capita are significant at 1%
level. This means that initial GDP per capita has a significant effect on economic growth, and
http://www.iaeme.com/IJCIET/index.asp
328
editor@iaeme.com
Khubbi Abdillah, Rossanto Dwi Handoyo and Wasiaturrahma
the negative coefficient value in this variable indicates the convergence, where countries with
high initial GDP per capita tend to have lower economic growth rate. The convergent economic
growth rate confirms neoclassic growth theory (Barro and Sala-i-Martin, 1992). It means poor
countries have a tendency to be able to catch up from rich countries. If economic growth in a
country is convergent, then poorer countries can catch up the richer countries and reducing the
income gap between rich countries and poor countries every year. In long term, the
convergence economic growth of a country will be improved to steady state economic growth.
Corruption Perception Index (CPI) variable shows significance at 1% with coefficient
0,151. This means that corruption positively affects economic growth. The higher CPI score
indicates how free a country from corruption, means the positive value on the CPI coefficient
indicates that the higher the corruption perception index score will encourage economic
growth. 1% increase in CPI will boost economic growth by 0,151 percent. The hypothesis is
based on the studies carried out by Cieslik and Goczek (2018), Nwogu and Ijirshar (2016),
D’Amico (2015), Pulok and Ahmed (2017), Amin, Ahmed, and Zaman (2013), Paksha Paul
(2010), Meon and Sekkat (2005), Mo (2001), Mauro (1995), empirically proving that
corruption hampers economic growth, Meanwhile, Huang (2016), Mallik and Saha (2016)
found that corruption enhanced economic growth.
The result of control corruption variable estimation shows significance at 1% with 4,129
coefficient, indicating that control corruption significantly affects the economic growth. The
increasing of control corruption by 1% will higher the economic growth rate by 4,129 percent.
The positive coefficient of control corruption shows the higher the control corruption, the
higher the economic growth. This finding supports the previous studies conducted by Cieslik
and Goczek (2018).
The result of estimation on the control variables in model I indicates that foreign direct
investment, education, and political stability have significant and positive correlation to the
economic growth. This finding is in accordance with the result of studies conducted by Cieslik
and Goczek (2018). While other variable, rule of law have not significant and negative effect
on economic growth. The sign variable is not as expected. The negative coefficient of rule of
law variable signifies crime and poor quality of law. The finding of this study agrees the finding
of Ishola Mobalaji and Omoteso (2009).
The result of estimation on the control variables in model II indicates that democracy index,
education, and openness have significant and positive correlation to the economic growth.
While other variable, government consumption have significant and negative effect on
economic growth. This finding is in accordance with the result of studies conducted by Cieslik
and Goczek (2018) and Barro (2003).
5. CONCLUSION
Higher corruption perception index indicates how far a country free from corruption. But,
control corruption measures how far the government officials to abuse their power the personal
gain. In the Asian region, sand the wheels hypothesis happens, in which a low level of
corruption can increase economic growth. The hyphothesis implies that corruption is
considered harmful and may cause high cost economy. Abuse of power through corruption
practices inhibits economic growth.
The more democratic a country mean that the improvement of freedom for its citizen to
make their own decisions and improving their participation in the development. The positive
value of democracy index coefficient signifies that higher democracy provides more positive
effect on economic growth. The finding suggests that most Asian countries have implemented
http://www.iaeme.com/IJCIET/index.asp
329
editor@iaeme.com
The Effect of Corruption on Asian Economic Growth
democratic governance. As the consequence, power is fully in people’s hand. The strong
democracy can improve economic growth.
The higher education level of a country will have a positive impact on economic growth.
Every country attempts to improve education of its citizens in order to improve its human
capital. Higher human capital owned by a country becomes an asset of the country to carry out
economic development because high number of educated labor is very important to support
economic growth.
Some countries in Asia have implemented free trade by removing trade barriers, such as
tariff, quota limitation, removing business limitations to improve efficiency and reducing
transaction cost, and high competition. Higher openness trade indicates how far a country
implements free market by facilitating business and will enhance economic growth through the
implementation of economic liberalization.
Government consumption is negatively related to economic growth. Initially, government
consumption through the construction of highways will increase economic growth in a country.
However, when it passes the optimal point of government consumption it causes economic
growth to decline. The high tax rate imposed by government will have a negative impact on
the decline in people’s purchasing power.
This finding implies that stable political condition will support economic growth. This
means every action taken by government that tends to be far from regulations and legal
certainty will lead to worse economic growth response. Many regulations favor the interest of
certain group above public interest. Law enforcement is carried out selectively, gentle on elites
and harsh on the poor. The worse law enforcement implemented by a country will negatively
affect the economic growth.
Policy recommendation that suggest are law system and ownership rights protection and
the absence of investment limitation. Then, good political system and democratic reign will
stimulate economic growth in a long term,. In addition, monitoring and law enforcement of
corrupt behavior needed to reduce leakage of national income.
REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
Acemoglu, D., & Robinson, J. A. (2013). Why nations fail: The origins of power,
prosperity, and poverty: Broadway Business.
Amin, M., Ahmed, A., & Zaman, K. (2013). The relationship between corruption and
economic growth in Pakistan – Looking Beyound the Incumbent. Oeconomics of
Knowledge, 5(3), 21.
Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo
evidence and an application to employment equations. The review of economic studies,
58(2), 277-297.
Barro, R. J., & Sala-i-Martin, X. (1992). Convergence. Journal of political Economy,
100(2), 223-251.
Barro, R. J. (1996). Democracy and growth. Journal of economic growth, 1(1), 1-27.
Barro, R. J. (2003). Determinants of economic growth in a panel of countries. Annals of
economics and finance, 4, 231-274.
Chea, C. C. (2015). Empirical Studies: Corruption and Economic Growth. American
Journal of Economics, 5(2), 183-188.
Cieślik, A., & Goczek, Ł. (2018). Control of corruption, international investment, and
economic growth–Evidence from panel data. World Development, 103, 323-335.
D'Amico, N. (2015). Corruption and Economic Growth in China: An Emirical Analysis.
Del Monte, A, & Papagni, E. (2001). Public expenditure, corruption, and economic growth:
the case of Italy. European journal of political economy, 17(1), 1-16.
http://www.iaeme.com/IJCIET/index.asp
330
editor@iaeme.com
Khubbi Abdillah, Rossanto Dwi Handoyo and Wasiaturrahma
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
[27]
[28]
[29]
Doppelhofer, G., & Miller, R. I. (2004). Determinants of long-term growth: A Bayesian
averaging of classical estimates (BACE) approach. American economic review, 94(4), 813835.
Gujarati, D. N. (2009). Basic econometrics: Tata McGraw-Hill Education.
Huang, C.-J. (2016). Is corruption bad for economic growth? Evidence from Asia-Pacific
countries. The North American Journal of Economics and Finance, 35, 247-256.
Huynh, K. P., & Jacho-Chávez, D. T. (2009). Growth and governance: A nonparametric
analysis. Journal of Comparative Economics, 37(1), 121-143.
Ishola Mobolaji, H., & Omoteso, K. (2009). Corruption and economic growth in some
selected transitional economies. Social Responsibility Journal, 5(1), 70-82.
Lučić, D., Radišić, M., & Dobromirov, D. (2016). Causality between corruption and the
level of GDP. Economic research-Ekonomska istraživanja, 29(1), 360-379.
Lui, F. T. (1996). Three aspects of corruption. Contemporary Economic Policy, 14(3), 2629.
Mallik, G., & Saha, S. (2016). Corruption and growth: a complex relationship. International
Journal of Development Issues, 15(2), 113-129.
Mauro, P. (1995). Corruption and growth. The quarterly journal of economics, 110(3), 681712.
Méon, P.-G., & Sekkat, K. (2005). Does corruption grease or sand the wheels of growth?
Public choice, 122(1-2), 69-97.
Nwogu, J. A., & Ijirshar, V. U. (2016). The Impact of Corruption on Economic Growth and
Cultural Values in Nigeria: A Need for Value Re-orientation. International Journal of
Economics & Management Sciences, Volume 6 (1), 1-7. doi: 10.4172/2162-6359.1000388
Omoteso, K., & Ishola Mobolaji, H. (2014). Corruption, governance and economic growth
in Sub-Saharan Africa: a need for the prioritisation of reform policies. Social Responsibility
Journal, 10(2), 316-330.
Paksha Paul, B. (2010). Does corruption foster growth in Bangladesh? International Journal
of Development Issues, 9(3), 246-262.
Pulok, M. H., & Ahmed, M. U. (2017). Does corruption matter for economic development?
Long run evidence from Bangladesh. International Journal of Social Economics, 44(3),
350-361.
Mankiw, N. G. (2007). Macroeconomics (t. Edition Ed.). New York and Basingstoke:
Worth Publishers.
Mo, P. H. (2001). Corruption and economic growth. Journal of Comparative Economics,
29(1), 66-79.
Rachdi, H., & Saidi, H. (2015). Democracy and Economic Growth: Evidence in MENA
Countries. Procedia-Social and Behavioral Sciences, 191, 616-621.
Salahodjaev, R. (2015). Democracy and economic growth: The role of intelligence in crosscountry regressions. Intelligence, 50, 228-234.
The Economist Intelligence Unit. (2018). Democracy Index 2010 – 2017. from
https://infographics.economist.com/2018/DemocracyIndex/
[30]
Transparency International. (2018). Corruption Perception Index 2010 - 2017. from
https://www.transparency.org/country
[31]
[32]
Verbeek, M. (2008). A guide to modern econometrics: John Wiley & Sons.
World Bank. (2018a). Agregate Indicators of Governance 2010 - 2017 from
http://info.worldbank.org/governance/wgi/#home
[33]
World Bank. (2018c). World Development Indicators Database Online from
https://data.worldbank.org/country
http://www.iaeme.com/IJCIET/index.asp
331
editor@iaeme.com