The Impact of Control of Corruption, Human Development Index, and
Macroeconomics on Economic Growth Rates in Low-Middle Income
Countries
HERU WAHYUDI
Economic Development, Faculty of Economics and Business,
University of Lampung,
Jln. H. Komarudin, Rajabasa Raya, Rajabasa, Bandar Lampung,
INDONESIA
SURIPTO
Business Administration, Faculty of Social and Political Sciences,
University of Lampung,
Jln. H. Komarudin, Rajabasa Raya, Rajabasa, Bandar Lampung,
INDONESIA
FAKHRI RIZAL HUSAIN
Economic Development, Faculty of Economics and Business,
University of Lampung,
Puri Sejahtera Blok F No. 3, Hajimena, Natar, Lampung Selatan,
INDONESIA
WIDIA ANGGI PALUPI
Economic Development, Faculty of Economics and Business,
University of Lampung,
Landani House, Rajabasa, Rajabasa, Bandar Lampung,
INDONESIA
Abstract: - Economic growth is part of the indicators used in assessing economic performance and it also
becomes a benchmark for developing a country. Therefore, this study aims to determine the effect of control of
corruption, human development index, inflation, and exchange rate on economic growth in 15 low-middle-
income countries in Asia between 2016–2020. Furthermore, secondary data obtained from the World Bank in
the form of panel data were utilized and processed using the EViews 10 analysis tool. The results showed
control of corruption and the human development index had a positive and significant impact on the level of
economic growth in Asia's lower middle-income countries in 2016-2020. However, inflation and exchange
rates had a negative and significant impact on economic growth rates.
Key-Words: - Economic Growth, Control of Corruption, Human Development Index, Inflation, Exchange Rate
Received: November 2, 2022. Revised: April 13, 2023. Accepted: May 6, 2023. Published: May 15, 2023.
1 Introduction
A country tends to experience economic growth
when it is accompanied by an increase in individual
income. Economic growth is part of the indicators
used to examine and estimate economic
performance and it is also a benchmark in
developing a region, [1].
Asia's lower-middle-income countries are those
with low economic growth rates. This low income
impacts growth because one useful indicator to
determine a country's economic condition is the
Gross Domestic Product (GDP). The GDP functions
as the basis for making policy decisions when there
are problems at the macro level and it is also useful
for determining the level of growth and structure in
a country.
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Table 1. Average Gross Domestic Product of 15 Low-middle Income Countries in Asia 2016-2020
Country
2016
2017
2018
2019
2020
Average
Bangladesh
265,236.25
293,754.65
321,379.2
351,238.4
373,902.1
321,102.1
Cambodia
20,016.75
22,177.20
24,571.75
27,089.39
25,872.80
23,945.58
India
2,294,797.9
2,651,472.5
2,702,929.7
2,831,552.2
2,667,687.9
2,629,688.1
Indonesia
931,877.36
1,015,618.7
1,042,271.5
1,119,099.8
1,058,688.9
1,033,511.
Iran
457,954.61
486,630.15
330,991.59
291,362.92
231,547.57
359,697.37
Kyrgyzstan
6,813.09
7,702.93
8,271.11
8,871.03
7,780.87
7,887.81
Mongolia
11,181.35
11,480.85
13,178.09
14,206.36
13,312.98
12,671.93
Myanmar
60,291.74
61,449.39
67,144.73
68,697.76
78,930.26
67,302.77
Nepal
24,524.10
28,971.59
33,111.53
34,186.19
33,433.67
30,845.41
Pakistan
313,629.86
339,205.62
356,128.22
320,909.49
300,306.33
326,035.90
Philippines
318,626.76
328,480.87
346,842.09
376,823.28
361,751.12
346,504.82
Sri Langka
82,401.04
87,428.13
87,963.04
83,902.57
80,969.68
84,532.89
Tajikistan
6,992.39
7,536.44
7,765.01
8,300.78
8,134.00
7,745.73
Timor Leste
1,650.62
1,615.61
1,583.88
2,047.93
1,902.16
1,760.04
Vietnam
257,095.96
281,353.40
308,702.09
330,391.33
343,242.57
304,157.07
Source: World Bank
Based on the table above, the Asian lower-
middle-income countries fluctuated, especially in
2020 when the COVID-19 pandemic occurred, such
that the economic growth in most countries
experienced a significant decline. India had the
highest average GDP level of 2,629,688.16 million
USD compared to other countries. One factor
contributing to this high GDP is the improving
performance of the manufacturing and service
sectors. Meanwhile, Timor Leste had the lowest
average GDP of 1,760.04 million USD. The low
economy in East Timor was caused by the unstable
political conditions in the country.
High economic growth is required for countries
that fall into the lower middle-income category.
Also, increasing the classification of a country has a
positive impact, one of which is the interest of
investors to invest in the country, which indirectly
has an impact on development.
Economic growth is impacted by economic and
non-economic factors, [2]. One of the non-economic
factors that cause growth in per capita income is
institutional quality. This is one of the determining
factors in the state of the country's economy. Well-
managed resources can create good-quality
institutions. Meanwhile, deviations by the
government, through abuse of power for private or
group interests, can degenerate the state institutions'
quality. Economic growth will be more likely to
experience a slowdown when this quality is poor.
This quality can be noticed at the corruption level,
[3]. Corruption will result in inefficient use of
budget allocations. This inefficiency causes the
inability to achieve the desired budget, therefore,
leading to high costs. This results in the inability to
maximize capital expenditures sourced from the
total budget. Capital expenditure, which is a form of
government investment, will affect decreasing
output and result in a slowdown in economic
growth. Therefore, it is necessary to control
corruption to stabilize and increase the level of
economic growth. Control of corruption is an
important factor in economic growth, especially for
developing countries, [4].
Fig. 1: Relationship between Gross Domestic Product and Control of Corruption in 15 Asian Low-Middle-
Income Countries 2016-2020
Source: World Bank (data processed)
-1,5
-1
-0,5
0
0
1000000
2000000
3000000
Index
Million USD
GDP CC
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Based on the picture above, control of
corruption in 15 low-middle-income countries in
Asia is not optimal. This is one of the factors
causing low state income and limiting economic
growth. India is a country with a fairly good index
of control of corruption compared to others, which
affects its economic growth. Meanwhile, Tajikistan
has the lowest control level, which affects low
economic growth.
In addition to the government perspective, the
determining factor for the high economic growth of
a country is that it comes from the people. Human
quality greatly affects economic growth, therefore,
the government, as the driving force of the state,
should develop the quality of its people. Also,
human development should be continuously carried
out for the community to benefit the country.
Development has many sub-levels in achieving the
expected economic growth, which is also related to
the Human Development Index, [5]. The human
development index can be used as a benchmark in
the fields of education, health, life expectancy, and
literacy rates. The Human Development Index is a
factor that influences economic growth. Also, the
improvement and distribution will accelerate
growth, [6].
The authors in [7] explained that if the
development of human resources has increased, it
will also affect the increase economically because
the existence of quality human resources can make a
real contribution to the growth of an economy, even
though economic growth has a dual relationship.
causation with the human development index in
which each region has its results as a result of
differences in the composition of the three
components of the human development index in
influencing economic growth in a given region.
Table 2. Classification of Human Development
Index
Classification
Index
Low
<0.550
Medium
0.550-0.699
High
0.700-0.799
Very High
>0.800
Source: World Bank
The table above shows the classification of the
human development index. Good development is
classified in the index of 0.700 and above.
Meanwhile, less than 500 index indicates that the
government is required to improve. The following is
the average human development index data for 15
low-middle-income countries in Asia.
Table 3. Average Human Development Index of 15
Asian Low-middle Income Countries 2016-2020
Country
HDI
Bangladesh
0.623667
Cambodia
0.587253
India
0.643187
Indonesia
0.71284
Iran
0.787067
Kyrgyztan
0.696787
Mongolia
0.73476
Myanmar
0.57812
Nepal
0.596853
Pakistan
0.552773
Philippines
0.712947
Sri Langka
0.778907
Tajikistan
0.661493
Timor Leste
0.5984
Vietnam
0.700533
Source: World Bank
Based on Table 3, there are six countries with a
high human development index, namely Indonesia,
Iran, Mongolia, the Philippines, Sri Lanka, and
Vietnam. Meanwhile, the nine others are still in the
medium classification. Therefore, a government
policy is needed to improve human development to
affect the country's economic growth.
Macroeconomic factors are also very influential
on economic growth, such as inflation and exchange
rates. According to [8], the determinants of a
country's economic growth are the exchange and
inflation rates. Inflation is an economic condition
that often occurs even though this situation is not
wanted. Milton Friedman also stated that it exists
everywhere and will always be a monetary
phenomenon, which indicates that there is an
excessive and unstable monetary growth condition,
[9]. Inflation occurs when the condition of the price
level rises, and this increase can hurt production
activities. This is because when production costs
rise, it will cause investment activities to shift to
activities that do not spur national products, hence,
the productive investment will decrease, and
economic activity will decline. When the production
of goods decreases, it will affect the level of
economic growth.
Although inflation has a fairly bad impact on
the rate of economic growth, it does not mean that
the inflation rate should be lowered to zero percent.
The condition of the inflation rate at zero percent
will also not be able to encourage economic growth
but will cause stagnation. Furthermore, government
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policies will have a significant impact on economic
activity should they keep the inflation rate relatively
low. An inflation rate that is below 5% is ideal
because it can increase economic activity.
Table 4. Average Inflation of 15 Low-middle
Income Countries in Asia 2016-2020
Country
Inflation
Bangladesh
5.608458
Cambodia
2.654746
India
4.513632
Indonesia
3.096901
Iran
20.76119
Kyrgyztan
2.513171
Mongolia
4.572697
Myanmar
6.737302
Nepal
5.419931
Pakistan
6.649381
Philippines
2.840292
Sri Langka
4.696081
Tajikistan
6.327735
Timor Leste
0.31566
Vietnam
3.148978
Source: World Bank
Based on Table 4, the nine countries with an
ideal average inflation rate are Cambodia, India,
Indonesia, Kyrgyzstan, Mongolia, the Philippines,
Sri Lanka, Timor Leste, and Vietnam, while others,
such as Bangladesh, Iran, Myanmar, Nepal,
Pakistan, and Tajikistan have less than ideal
inflation rates. The high rate will affect the country's
economic growth. This will indirectly affect the
economic growth of a country like Iran with a very
high average inflation rate. Effective policies are
needed by a country to decrease or maintain its
inflation rate at an ideal level.
Furthermore, the exchange rate is a
macroeconomic factor that influences the economic
growth of a country. It is the one unit price of
foreign currency against domestic or vice versa. The
demand and supply of a particular currency can
affect its exchange rate. According to [10], the
exchange rate was identified as one of the most
influential economic factors in a country's economic
growth conditions.
Table 5. Average Exchange Rate of 15 Low- middle
Income Countries in Asia 2016-2020
Country
Exchange Rate
Bangladesh
82.33935
Cambodia
4062.875
India
69.04525
Indonesia
13931.19
Iran
37801.1
Kyrgyztan
70.9513
Mongolia
2505.877
Myanmar
1384.982
Nepal
110.3561
Pakistan
128.7846
Philippines
50.3955
Sri Langka
164.9661
Tajikistan
9.772423
Timor Leste
1
Vietnam
22633.15
Source: World Bank
Based on Table 5, most Asian lower-middle-
income countries have variable exchange rate
volatility, including Iran, which has a very high
average exchange rate of 37,801.1 rials to the dollar.
The weakening of the Iranian rial exchange rate was
caused by sanctions from the US because Iran was
developing a nuclear program, therefore, all
transactions using the currency would be subject to
fines from the US. Vietnam has a depreciating
currency value due to the intentionality of its central
bank to weaken the dong currency and boost the
country's exports to China after the depreciation of
the Yuan. This greatly affected Vietnam's economic
growth, which continued to increase, as it was
triggered by the industrial and manufacturing
production sectors as well as foreign investment.
These results are expected to reveal several
factors that influence the economic growth of low-
middle-income countries in Asia. In addition, it can
provide recommendations for the government to
make an effective and efficient policy that can
maintain and increase the level of economic growth.
Effective policies are very necessary for a country,
especially those with lower middle income. High
income will have an impact on the development of a
country.
In recent years, various literature has been
carried out by several research teams on the control
of corruption effect, the human development index,
and macroeconomics on economic growth and the
results are as follows. Control of corruption has a
positive influence on the level of economic growth
in a country. In other words, when a country's
control of corruption is good, it can increase
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economic growth. According to [11], control of
corruption is positively and significantly related to
growth. The study emphasized that it is one of the
main factors used to examine economic growth in
Kazakhstan. Similarly, the authors in [12] explained
control of corruption positively affects Asian
economic growth. Based on the study by [13]
control of corruption failed to significantly affect
the level of economic growth in sub-Saharan
Africa.
The Human Development Index significantly
influences the economic growth of a country.
According to [14], it positively affects economic
growth in East Java province between 2016-2018.
Similarly, the authors in [15] showed that the
Human Development Index significantly influences
economic growth in Southeast Asia. This is contrary
to [16] that the Human Development Index
negatively affects the economic growth of the
Bangka Belitung Islands from 2010-2017.
The macroeconomic variable inflation rate has a
significant negative effect on economic growth.
When the inflation rate decreases, the rate of
economic growth will increase. This is further
emphasized by [17] regarding the exchange rate,
inflation, and economic growth in developing
countries. The results showed inflation negatively
affects economic growth. This is similar to [18] that
the inflation rate negatively influences economic
growth in Vietnam. However, the study in [19]
indicated it positively affects economic growth in
the euro area.
The exchange rate is a variable that negatively
and significantly influences the economic growth of
a country. This is supported by [20] that the
exchange rate negatively affects the economic
growth in Turkish. Similarly, the study in [21]
emphasized it negatively influences the economic
growth in Turkey. The results are contrary to [22]
that the real exchange rate positively affects the
regional economic growth in Indonesia.
In summary, the literature review proposes
several points in common. Most of the literature
suggests that control of corruption, human
development index, inflation, and exchange rates
have a significant effect on economic growth.
However, a gap phenomenon still occurs in several
studies, therefore, further research is needed. This is
possible because of the use of methods and several
ways of obtaining data to produce different results.
2 Methodology and Variables
2.1 Methodology
This study utilized a type of data sekunder obtained
from the World Bank in the form of panel data, time
series, and cross-section. The time series data were
obtained over 5 years, from 2016 to 2020, while
cross-section data were obtained from 15 countries
in Southeast Asia, including Bangladesh, Cambodia,
India, Indonesia, Iran, Kyrgyzstan, Mongolia,
Myanmar, Nepal, Pakistan, the Philippines, Sri
Lanka, Tajikistan, Timor Leste, and Vietnam.
Furthermore, this study utilized four independent
and one dependent variable. The dependent variable
is the rate of economic growth, while the
independent variable is the rate of human
development, the rate of inflation, and the level of
unemployment. Subsequently, the data obtained
from the World Bank were analyzed using the
EViews 10 analysis tool. The analysis technique
used is data panel regression with the following
regression models:
LN_GDPit = 𝛽0 + 𝛽1CCit + 𝛽2HDIit - 𝛽3INFit -
𝛽4NTit + eit (1)
Where LN_GDP is LN Gross Domestic Product
(Million USD), CC is Control of Corruption(index),
HDI is Human Development Index (index), INF is
Inflation Rate (%), NT is Exchange Rate, 𝛽0 is
Constant, 𝛽1, 𝛽2,...., 𝛽6 is Regression Coefficient, and
e is Error Term.
2.2 Variables
2.2.1 Control of Corruption
Control of corruption is an effort to encourage
future generations and develop a steadfast rejection
of all forms of social vices. This study used the
Control of corruption Index data sourced from the
World Bank. Control of corruption is suspected to
positively affect economic growth. In other words,
the higher the control, the greater the level of
economic growth, and vice versa.
2.2.2 Human Development Index
The stages of human development are the process of
accessing the necessary resources for a healthy and
good level of individual life. In a country, these
stages are measured by employing the Human
Development Index. The index estimates the three
dimensions of human well-being including health,
education, and income. This study utilized Human
Development Index data sourced from the World
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Bank. The index positively affects economic
growth, indicating that the increase in the human
development index tends to raise the level of
economic growth, and vice versa.
2.2.3 Inflation
Inflation is regarded as the rise in the price of goods
and services. This increase occurs due to the rise in
the number of requests compared to the supply of
goods or services in the market. This study utilized
data percentages sourced from the World Bank. The
inflation rate is thought to negatively affect
economic growth, indicating that, the lower the
inflation rate, the higher the economic growth rate,
and vice versa.
2.2.4 Exchange Rate
The exchange rate is the price of one unit of foreign
currency against the domestic currency or vice
versa. The demand and supply of a particular
currency can affect its exchange rate. The data for
this study were sourced from the World Bank. The
exchange rate is believed to hurt the rate of
economic growth, hence, the exchange rate
decreases with an increase in the rate of economic
growth.
3 Result and Discussion
3.1 Result
3.1.1 Selection of a Regression Model
There are three choices of panel data regression
models, namely the common effect model (CEM),
fixed effect model (FEM), and random effect model
(REM).
Table 6. Panel Data Regression Model Selection
Test
Prob
Decision
Uji Chow
0.0000
FEM
Uji Hausman
0.2492
REM
Uji Lagrange Multiplier
0.0000
REM
Source: Results of Data Processing with Eviews 10
(2022)
Based on the table above, it can be concluded
that the best model for estimating the research data
is the Random Effect Model (REM).
3.1.2 Classic Assumption Test
Compliance with modern econometric requirements
in conducting assessments has a significant impact
on the quality of calculations, [23]. One that must be
met is the classical assumption test.
3.1.2.1 Normality test
A normality test is used in determining whether the
independent and the dependent variables are
normally distributed or not in the regression model.
The Jarque-Bera test is used to detect normality. In
the Figure 2 you will find the normality test. Based
on the test above, the Jarque-Bera probability value
is 0.098178, which is greater than 5 percent or 0.05,
therefore, it can be concluded that the data in this
research model were normally distributed.
3.1.2.2 Deteksi Multikolinieritas
A multicollinearity test is used to determine whether
there is a linear relationship between independent
variables or not. Therefore, when the correlation
value between independent variables is below 0.8, it
indicates that there is no multicollinearity problem,
[24].
Fig. 2: Normality Test Results
Source: Results of Data Processing with Eviews 10 (2022)
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Table 7. Multicollinearity Test Results
CC
HDI
INF
NT
CC
1.000000
0.246767
-0.256182
-0.022730
HDI
0.246767
1.000000
0.269714
0.508057
INF
-0.256182
0.269714
1.000000
0.589059
NT
-0.022730
0.508057
0.589059
1.000000
Source: Results of Data Processing with Eviews 10 (2022)
Table 8. Heteroscedasticity Test Results
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
1.905011
0.828001
2.300735
0.0244
CC
-0.103242
0.154680
-0.667451
0.5067
HDI
-0.271301
1.159019
-0.234078
0.8156
INF
-0.001871
0.004004
-0.467187
0.6418
NT
-1.27E-06
1.12E-05
-0.113319
0.9101
Source: Results of Data Processing with Eviews 10 (2022)
Based on the multicollinearity test, the value between the dependent variables was below 0.8, therefore,
there was no multicollinearity problem in the regression model of this study.
3.1.2.3 Heteroscedasticity Test
Heteroscedasticity tests help in determining whether
the residuals of a regression model are constant or
not and this was conducted using the Glesjer
method. The heteroscedasticity problem occurs
when the p-value of each independent variable is
greater than 5 percent or 0.05.
Based on the test above, the p-value of each
independent variable is smaller than 5 percent or
0.05. Therefore, it can be concluded that there was
no heteroscedasticity problem.
3.1.2.4 Autocorrelation Test
An autocorrelation test is used to define whether
there is a correlation between independent variables
in a model or not. This test was conducted using the
Durbin-Watson method.
According to [25], the Durbin-Watson statistic
between -2 and +2, indicates that there is no
autocorrelation symptom and the level of
significance used in the study is 5 percent. The
Durbin-Watson value was 1.581103, which
indicated that there was no autocorrelation problem
in the regression model. This is because the value
(1.581103) is still between -2 and +2.
3.1.3 Regression Estimation Results
Based on the selection results, the random effect
model (REM) was concluded to be the best. The
following are the regression results using the
Random Effect Model:
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Table 9. Estimated Result of Random Effect Regression Model
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
20.17205
0.951651
21.19689
0.0000
CC
0.331688
0.157633
2.104185
0.0390
HDI
8.089599
1.195880
6.764558
0.0000
INF
-0.007849
0.004118
-1.905810
0.0608
NT
-2.50E-05
1.18E-05
-2.121794
0.0374
Effects Specification
S.D.
Rho
Cross-section random
2.013156
0.9985
Idiosyncratic random
0.078525
0.0015
Weighted Statistics
R-squared
0.572402
Mean dependent var
0.438414
Adjusted R-squared
0.547968
S.D. dependent var
0.117952
S.E. of regression
0.079303
Sum squared resid
0.440227
F-statistic
23.42627
Durbin-Watson stat
1.432869
Prob(F-statistic)
0.000000
Unweighted Statistics
R-squared
-0.031729
Mean dependent var
25.13663
Sum squared resid
310.1349
Durbin-Watson stat
0.002034
Source: Results of Data Processing with Eviews 10 (2022)
Table 10. Individual Parameter Significance Test (t-Test)
Variable
t-Statistic
t-Table
Description
CC
2.104185
1.66691
Significant
HDI
6.764558
1.66691
Significant
INF
-1.905810
1.66691
Significant
NT
-2.121794
1.66691
Significant
Source: Results of Data Processing with Eviews 10 (2022)
Based on Table 9, the following regression equation
was obtained:
LN_GDPit = 20,17205 + 0,331688CCit +
8,089599HDIit – 0,007849INFit -
2,502133 NTit (2)
3.1.4 Statistical Test
3.1.4.1 Individual Parameter Significance Test (t-
Test)
Individual parameter significance test or t-test, to
determine the effect of each independent variable on
the dependent variable. If the t statistic value is
greater than the t table, the variable has a significant
effect.
Based on Table 10, the results showed that the
control of the corruption variable had a positive and
significant effect on the level of economic growth.
This can be seen from the t-statistical value
(2.104185), which is greater than the t-table
(1.66691). The human development index variable
had a positive and significant effect on the level of
economic growth, according to the t-statistic value
(6.764558), which is greater than the t-table
(1.66691). Meanwhile, the inflation rate variable
had a negative and significant effect on the rate of
economic growth, based on the t-statistic value
(1.90581), which is greater than the t-table
(1.66691). The exchange rate variable had a
negative and significant effect on the level of
economic growth, based on the t-statistic value
(2.121794), which is greater than the t-table
(1.66691).
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3.1.4.2 Simultaneous Significance Test (F Test)
The simultaneous regression coefficient test was
carried out to find out whether all the independent
variables jointly have an effect on and are
significant to the dependent variable. The test
criterion is that if the value of F-Statistic > F- table
means that together, at least one of the independent
variables has a significant effect on the dependent
variable.
Table 11. Simultaneous Significance Test (F Test)
df
F-Statistic
F-Table
Description
4,70
23,42627
2,50
Significant
Source: Results of Data Processing with Eviews 10
(2022)
Based on Table 11, the f-statistic value was
23,42627, where the value was greater than the f-
table (2.50), indicating that the variables of control
of corruption, human development index, inflation
rate, and exchange rate together affected the rate of
economic growth.
3.1.4.3 Coefficient of Determination (R2)
Based on the regression estimation using the
Random Effect Model (REM), the coefficient of
determination (R2) was 0.572402. This indicates that
the independent variable used in this study affected
the dependent variable by 57.2402% and 42.7598%
is explained by variables not found in the research
model.
3.2 Discussion
3.2.1 The Effect of Control of Corruption on the
Economic Growth
According to the results, the control of corruption
had a positive and significant impact on the level of
economic growth, indicating that when the
conditions of controlling corruption are good, it will
increase the rate of economic growth and vice versa.
Corruption practices stemming from the abuse of
power will hinder economic growth. The value of a
low control of corruption can reduce high economic
costs to enable the government budget to be used
and distributed fairly without leaking national
income. Theoretically, this study proves the "Sand
the Wheels" hypothesis that corruption can hinder
the rate of economic growth.
Control of Corruption is one factor that
effectively contributes to economic growth.
Therefore, when a country is corrupt, it will shake
economic growth, [26]. The occurrence of
corruption in a country can result in damage to the
economic competition which can reduce domestic
productivity, create market distortions so that goods
sold reach high enough prices, reduce the amount of
domestic investment, and can cause economic
inefficiency which is marked by increasing costs in
a country. business as well as creating an income
gap characterized by inequality and injustice to be
able to increase poverty, then all of this will have an
impact on decreasing economic growth.
According to [11], control of corruption has a
positive impact on economic growth. Similarly, [12]
stated that control of corruption has a positive and
significant impact on increasing economic growth.
However, this is inversely proportional to [27],
which found that effective control of corruption
does not have a positive impact on development in
Africa.
3.2.2 The Effect of the Human Development
Index on the Rate of Economic Growth
According to the results, the human development
index had a positive and significant impact on the
level of economic growth, indicating that when
human development conditions are good, it would
increase the rate of economic growth and vice versa.
Human capital is an important factor in the
economy. However, economic performance
becomes better when the quality of human resources
is good. The authors in [28] emphasized that human
capital is the most important factor in determining
the character and pace of social and economic
development in the country concerned.
A high level of human development largely
determines the ability of the population to absorb
and manage sources of economic growth, both
related to technology and to institutions as an
important means of achieving economic growth,
[29]. The Human Development Index plays an
important role in modern economic development
because good human development will maximize
production factors. A good-quality population will
be able to innovate and develop existing production
factors. Apart from that, high human development
will also result in a high population so it will
increase the level of consumption.
This study is in line with [30] which suggested
that an increase in the level of the human
development index will lead to increased
opportunities for economic growth. It is also similar
to [31] which stated that the human development
index has a positive effect on economic growth.
Contrastingly, the authors in [32] revealed that the
human development index has a negative influence
on economic growth.
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3.2.3 The Effect of Inflation on the Rate of
Economic Growth
The results showed that inflation had a negative and
significant impact on the rate of economic growth,
indicating that a decrease in the inflation rate will
increase the rate of economic growth and vice versa.
An increase in the inflation rate will have an impact
on high prices and will result in reduced purchasing
power for the people, which in turn can have an
impact on decreasing economic growth.
Meanwhile, low inflation can make a country's
economic condition stable and healthy. This is
because the inflation rate is an increase in the price
of goods or services, and when the price is stable,
subsequently, the capital purchased for the
production of goods or services can be achieved.
The creation of good market conditions will
increase economic growth. Inflation can cause the
rate of profit to decrease, and consequently have an
impact on reducing capital accumulation. This
ultimately results in a falling economic growth rate,
[33].
In line with the results, the study in [34]
discovered that inflation hurts economic growth.
Similarly, the authors in [18] showed that high
inflation rates can damage economic activity.
However, this is inversely proportional to [19],
which concluded that the inflation rate has a positive
impact on the rate of economic growth in the euro
area.
3.2.4 The Effect of the Exchange Rate on the
Rate of Economic Growth
Based on the results, the exchange rate had a
negative and significant impact on the level of
economic growth, therefore, a decrease in the
exchange rate would increase the rate of economic
growth and vice versa. A weakening exchange rate
can be a burden on economic growth. The
government will feel burdened by the payment of
government spending, in this case, the exchange rate
weakens. Also, the weakening of the exchange rate
will have an impact on countries that use a lot of
imported raw materials. This is because when the
exchange rate weakens, the price of imported goods
will increase such that the industry struggles to
fulfill raw materials, this will subsequently have an
impact on slowing economic growth. The exchange
rate is one of the benchmarks in terms of advancing
the economic growth of a country, therefore
maintaining its stability is an obligation for the
government to improve the rate of economic growth
faster.
This study is in line with [35] that the exchange
rate coefficient negatively affects economic growth.
Similarly, [20] explained the exchange rate
negatively influences economic growth. However,
this study is inversely proportional to [22] that the
exchange rate positively affects regional economic
growth.
4 Conclusion
Based on the results, the control of corruption and
the human development index had a positive and
significant impact on the level of economic growth
in lower-middle-income countries in Asia between
2016-2020. Meanwhile, inflation and exchange rates
had a negative and significant impact on economic
growth rates.
This study implies that all independent variables
(control of corruption, human development index,
inflation rate, and exchange rates) can be used as a
reference in policymaking. This is because the
variables had a significant influence on the rate of
economic growth. Effective and efficient policies
can be expected to assist the country in increasing
the rate of economic growth. Furthermore, monetary
and fiscal policies can be used to strengthen the
local currency and maintain inflation rates to avoid
the adverse effects of exchange rate volatility and
inflation on economic growth.
The limitation of this study is that it only used
two macroeconomic variables, therefore, further
research is expected to use other macroeconomic
variables. This is to enable the government to see
the overall impact of macroeconomics on economic
growth and allow policy-making to be more
effective.
References:
[1] M. . P. Todaro and S. C. Smith,
Pembangunan Ekonomi, 11th ed. Jakarta:
Erlangga, 2014.
[2] M. L. Jhingan, Ekonomi Pembangunan dan
Perencanaan, Edisi 15. Jakarta: PT Raja
Grafindo Persada, 2013.
[3] N. G. Mankiw, Makroekonomi, Keenam.
Jakarta: Erlangga, 2008.
[4] Z. Zhuo, A. S. M. O, B. Muhammad, and S.
Khan, “Underlying the Relationship Between
Governance and Economic Growth in
Developed Countries,” J. Knowl. Econ., vol.
12, no. 3, pp. 1314–1330, 2020, doi:
10.1007/s13132-020-00658-w.
[5] T. Zulham, T. C. Dawood, T. Farlian, J.
Saputra, R. Juliansyah, and F. Hadi, “The
nexus of human development index,
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
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economic and population growth on
environmental degradation in Aceh Province,
Indonesia,” WSEAS Trans. Environ. Dev.,
vol. 17, pp. 314–320, 2021, doi:
10.37394/232015.2021.17.31.
[6] A. Melliana and I. Zain, “Indeks
Pembangunan Manusia di Kabupaten / Kota
Provinsi Jawa Timur dengan Menggunakan
Regresi Panel,” J. Sains Dan Seni Pomits,
vol. 2, no. 2, pp. 237–242, 2013.
[7] V. Costantini and S. Monni, “Sustainability
and human development,” Econ. Polit., vol.
25, no. 1, pp. 11–31, 2008.
[8] E. Wiriani and Mukarramah, “Pengaruh
Inflasi dan Kurs terhadap Pertumbuhan
Ekonomi Indonesia,” J. SAMUDRA Ekon.,
2020.
[9] R. Dornbusch, R. Startz, and S. Fischer,
Makroekonomi. Jakarta: Media Global
Edukasi, 2004.
[10] A. H. M. Y. Chowdhury, M. K. Hamid, and
R. A. Akhi, “Impact of Macroeconomic
Variables on Economic Growth: Bangladesh
Perspective,” Inf. Manag. Comput. Sci., vol.
2, no. 2, pp. 19–22, 2019, doi:
10.26480/imcs.02.2019.19.22.
[11] A. Absadykov, “Does Good Governance
Matter? Kazakhstan’s Economic Growth and
Worldwide Governance Indicators,” Otoritas
J. Ilmu Pemerintah., vol. 10, no. 1, pp. 1–13,
2020, doi: 10.26618/ojip.v10i1.2776.
[12] K. Abdillah, R. D. Handoyo, and W.
Wasiaturrahma, “The Effect of Control
Corruption, Political Stability,
Macroeconomic Variables on Asian
Economic Growth,” J. Ilm. Bid. Ilmu Ekon.,
vol. 15, no. 2, p. 161, 2020, doi:
10.24269/ekuilibrium.v15i2.2678.
[13] K. Omoteso and H. I. Mobolaji, “Corruption,
governance and economic growth in Sub-
Saharan Africa: A need for the prioritisation
of reform policies,” Soc. Responsib. J., vol.
10, no. 2, pp. 316–330, 2014, doi:
10.1108/SRJ-06-2012-0067.
[14] S. R. Arifin and Fadllan, “Pengaruh Indeks
Pembangunan Manusia (IPM) dan Tingkat
Pengangguran Terhadap Pertumbuhan
Ekonomi di Provinsi Jawa Timur Tahun
2016-2018,” IQTISHADIA J. Ekon. Perbank.
Syariah, vol. 8, no. 1, pp. 38–59, 2021, doi:
10.19105/iqtishadia.v8i1.4555.
[15] M. Fajar and Z. Azhar, “Indeks Persepsi
Korupsi Dan Pembangunan Manusia
Terhadap Pertumbuhan Ekonomi Di Negara-
Negara Asia Tenggara,” J. Ecogen, vol. 1,
no. 3, p. 681, 2019, doi:
10.24036/jmpe.v1i3.5114.
[16] Y. Sari, A. Nasrun, and A. K. Putri,
“Analisis Pengaruh Indeks Pembangunan
Manusia Dan Kemiskinan Terhadap
Pertumbuhan Ekonomi Kabupaten/Kota Di
Provinsi Kepulauan Bangka Belitung Tahun
2010-2017,” Equity J. Ekon., vol. 8, no. 1,
pp. 1–13, 2020, doi: 10.33019/equity.v8i1.9.
[17] E. Olamide, K. Ogujiuba, and A. Maredza,
“Exchange Rate Volatility, Inflation and
Economic Growth in Developing Countries:
Panel Data Approach for SADC,”
Economies, vol. 10, no. 3, 2022, doi:
10.3390/economies10030067.
[18] B. H. Ngoc, “The asymmetric effect of
inflation on economic growth in vietnam:
Evidence by nonlinear ARDL approach,” J.
Asian Financ. Econ. Bus., vol. 7, no. 2, pp.
143–149, 2020, doi:
10.13106/JAFEB.2020.VOL7.NO2.143.
[19] N. Kryeziu and E. A. Durguti, “The Impact
of Inflation on Economic Growth,” Int. J.
Financ. Bank. Stud., vol. 8, no. 1, pp. 01–09,
2019, doi: 10.20525/ijfbs.v8i1.297.
[20] Ö. Karahan, “Influence of Exchange Rate on
the Economic Growth in the Turkish
Economy,” Financ. Assets Invest., vol. 11,
no. 1, pp. 21–34, 2020, doi:
10.5817/fai2020-1-2.
[21] E. Ozata, “The effect of exchange rate
volatility on economic growth in Turkey,”
Pressacademia, vol. 9, no. 1, pp. 42–51,
2020, doi:
10.17261/pressacademia.2020.1191.
[22] I. Yuliadi, “Determinants of Regional
Economic Growth in Indonesia,” J. Ekon.
Stud. Pembang., vol. 21, no. 1, 2020, doi:
10.18196/jesp.21.1.5035.
[23] Y. Alikhanli, “Granger causality analysis of
foreign trade impact on economic growth:
Case of Azerbaijan,” WSEAS Trans. Environ.
Dev., vol. 16, no. 2007, pp. 384–389, 2020,
doi: 10.37394/232015.2020.16.38.
[24] D. N. Gujarati, Dasar-dasar Ekonometrika :
Edisi Ketiga. Jakarta: Erlangga, 2006.
[25] S. Santoso, Mahir Statistik Parametrik:
Konsep Dasar dan Aplikasi dengan SPSS.
Jakarta: PT Elex Media Komputindo, 2019.
[26] T. Samarasinghe, “Impact of Governance on
Economic Growth,” MPRA (Munich Pers.
RePEc Arch., no. 89834, pp. 1–50, 2018.
[27] H. Adefeso, “Corruption , Political
Instability and Development Nexus in
Africa : A Call for Sequential Policies
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.94
Heru Wahyudi, Suripto,
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Volume 20, 2023
Reforms,” 2018.
[28] D. S. Mirza, “Pengaruh Kemiskinan,
Pertumbuhan Ekonomi, Dan Belanja Modal
Terhadap Ipm Jawa Tengah,” Jejak, vol. 4,
no. 2, pp. 102–113, 2011.
[29] A. G. Brata, “Jurnal EKONOMI
PEMBANGUNAN,” J. Ekon. Pembang.,
vol. 7, no. 2, pp. 113–122, 2002.
[30] E. Elistia and B. A. Syahzuni, “the
Correlation of the Human Development
Index (Hdi) Towards Economic Growth
(Gdp Per Capita) in 10 Asean Member
Countries,” J. Humanit. Soc. Stud., vol. 2,
no. 2, pp. 40–46, 2018, doi:
10.33751/jhss.v2i2.949.
[31] A. N. Pradana and H. Sumarsono, “Human
Development Index, Capital Expenditure,
Fiscal Desentralization to Economic Growth
and Income Inequality in East Java
Indonesia,” Quant. Econ. Res., vol. 1, no. 2,
pp. 108–118, 2018.
[32] M. Muqorrobin and A. Soejoto, “Pengaruh
Indeks Pembangunan Manusia (IPM)
Terhadap Pertumbuhan Ekonomi Provinsi
Jawa Timur,” Pendidik. Ekon., p. 6, 2017.
[33] M. A. Samsuddin and S. Amar,
“Determinants of Economic Growth in
Developing Countries of G20 Members,”
Adv. Econ. Bus. Manag. Res., vol. 152, pp.
177–183, 2020, doi:
10.2991/aebmr.k.201126.021.
[34] A. L. Kusumatrisna, I. Sugema, and S. H.
Pasaribu, “Efek Threshold Inflasi Terhadap
Pertumbuhan Ekonomi Regional Di
Indonesia,” J. Ekon. Pembang., vol. 27, no.
1, pp. 43–52, 2019, doi:
10.14203/jep.27.1.2019.43-52.
[35] O. A. Adaramola and O. Dada, “Impact of
inflation on economic growth: Evidence
from Nigeria,” Invest. Manag. Financ.
Innov., vol. 17, no. 2, pp. 1–13, 2020, doi:
10.21511/imfi.17(2).2020.01.
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
Heru Wahyudi made a research framework and
collected literature reviews. Suripto proposes policy
recommendations. Fakhri Rizal Husain wrote the
research. Widia Anggi Palupi collects and processes
research data.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
The research in this manuscript is supported by
Lembaga Penelitian dan Pengabdian kepada
Masyarakat (LPPM) Universitas Lampung.
Conflict of Interest
The authors have no conflict of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
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