Index

Abstract

This study aims to analyze the contribution of Domestic Investment (DDI) and Foreign Investment (DFI) to economic growth in Indonesia under President Jokowi. The data used are the 2014-2019 quarterly time series from the Word Bank, BPS and BPKM. This research uses descriptive quantitative method, with multiple regression analysis with SPSS. Hypothesis testing uses the t test (partial test) and F test (simultaneous test) with a significance of α = 0.05. The results of hypothesis testing show that partially FDI has a negative effect on economic growth in Indonesia, while DDI has no significant effect on economic growth. However, simultaneously DDI and FDI have no significant effect on economic growth. At the end of the study, it is suggested that the role of the government as a regulator is needed to increase DDI and FDI so as to increase economic growth. Furthermore, Indonesia needs to improve the quality of innovative human resources as an attraction for investors to invest in Indonesia, such as Malaysia, Thailand and Vietnam.

Keywords: Domestic direct investment (DDI), Foreign direct investment (FDI), Economic growth, Contribution, President Jokowi, Indonesia.

JEL Classification : E22, E23.

Received: 18 September 2020 / Revised: 21 October 2020 / Accepted:4 November 2020/ Published: 16 November 2020  

Contribution/ Originality

The paper's primary contribution is finding that contribution FDI and DDI to Indonesia economic growth hasn’t been significant; however role of the government as regulator can encourage increased investment through ease of licensing. Furthermore, it necessary to provide innovative human resources as an attraction for investors to invest in Indonesia.


1. INTRODUCTION

Economic growth is one of the indicators used to measure the success of a country's economic development. A country can be said to be experiencing economic growth if there is an increase in national income. The increase in national income can be seen from the large amount of Gross Domestic Product (GDP) produced each year. However, to achieve economic growth, a country is faced with limited capital or investment. The disruption of economic growth due to limited investment will have an impact on economic development, which in turn will have an impact on poverty and unemployment.

To accelerate economic development, sustainable economic growth must be maintained. High economic growth must be supported by investment because economic growth that is not supported by investment will not be sustainable growth.

Furthermore, high and sustainable economic growth can increase productivity so it can help increase economic development in long term. Therefore, investment can play an important and vital role in driving long-term economic growth (Syaparuddin, 2019).

Braunstein (2006) investment has become an essential commodity for a country's economy. Because the investment can drive the economic sector, thereby creating jobs and enabling technology transfer, and will promote sustainable economic growth.

According to a World Bank report, Indonesia in 72 out of 190 countries based on the Ease of Doing Business (EoDB) category. The 2018 World Investment Report also shows that there has been significant investment growth in Foreign Direct Investment (FDI) to Indonesia

Domestic direct investment and foreign direct investment are one of the important sources of financing and are able to contribute to supporting Indonesia's economic development the development of domestic direct investment and foreign direct investment can be seen in Figure 1.

Figure-1. Development of direct foreign investment (FDI) and domestic direct investment (DDI) in Indonesia in 2014-2019.

According to BPS data, gross fixed capital formation contributed 32.16% to GDP in Indonesia in 2017, followed by household consumption at 56.13%, exports 20.37%, government consumption 9.1%, LNPRT consumption 1.18 % and imports being a deduction factor of 19.17%. The contribution of investment to the formation of GDP or economic growth in Indonesia is the second largest after consumption. Therefore, investment heaven can be created by improving the investment climate, increasing the ease of doing business, accelerating investment realization, overcoming obstacles faced by investors and increasing the role of DDI and FDI.

Data from the Investment Coordinating Board (BKPM) recorded that both FDI and DDI reached Rp. 463.1 trillion with FDI of Rp. 307 trillion and DDI of Rp. 156.1 trillion. Continue on 2019, investment realization was recorded at Rp. 809.6 trillion with a composition of FDI of Rp. 423.1 trillion and DDI of Rp. 386.5 trillion. Based on it, it shows that the investment trend in the era of President Joko Widodo's administration is increasing from year to year. The realization of domestic direct investment (DDI) and foreign direct investment (FDI) reached Rp. 721.3 trillion in 2018, then increased to Rp. 809.6 trillion in 2019. This achievement is expected to trigger an increase in the target of DDI and FDI in 2020 which have been set by the government at Rp. 886.1 trillion (BKPM, 21 April 2020).

The development of investment in the era of President Joko Widodo's administration continues to increase from year to year from 2014 to 2019. In 2014. According to Jokowi (Joko Widodo), the role of foreign investors is still very much needed to encourage development and economic growth as well as job creation.

Investment has an important role in Gross Domestic Product (GDP). Its contribution reached 33.48 percent in 2018, the second largest after household consumption. To support economic development in Indonesia, the government is currently trying to attract more foreign investors to invest in Indonesia. The government uses various methods, from infrastructure development to licensing facilities and tax incentives.

Although it is noted that it continues to increase, investment in Indonesia is not without problems. First, BKPM data shows that investment realization continues to slow down and this is very evident in the investment realization data as of 2018. Investment in Indonesia only grew 4.1% in 2018 compared to 2017. Furthermore, in 2018 it was also noted that FDI growth experienced negative growth. of -8.8%. The growth in investment realization per 2018 was supported by DDI, which at that time managed to grow by 25.3%. DDI realization was also recorded to exceed the target where DDI realization was recorded at Rp. 328.6 trillion, 114.3% of the target of Rp. 287.6 trillion.Second, the sectors that are of interest to investors also appear to be shifting away from sectors prioritized by the government. The government wants investment to enter the labor-intensive manufacturing sector in order to stimulate economic growth and create new jobs. However, BKPM data actually shows that investors are increasingly interested in investing in the service sector rather than in the manufacturing sector. In 2014 to 2016, the manufacturing industry was recorded to absorb the most investment with a composition of 43% to 54.8% of the total investment realization. In 2017 to 2019, it was noted that investors began to invest more in the service sector, where in 2017 it was noted that the service sector realized investment of IDR 293.4 trillion or 42.3% of the target. Entering 2018, investment in the service sector is increasingly dominating where at that time the realization of investment reached Rp. 367 trillion or 50.9% of the total investment in 2018. The shift in investment from the manufacturing sector to the service sector is also correlated with decreased employment.

BKPM data shows that employment in 2014, 2015 and 2016 was recorded at 1.43 million, 1.43 million and 1.39 million workers, respectively. When the service sector began to dominate investment, namely in 2017 and 2018, employment was recorded at 1.17 million and 960,052 million workers, respectively. Third, the incremental capital output ratio (ICOR) was recorded at 6.3 in 2018, higher than Indonesia's global competitors such as India and Vietnam, which recorded ICORs of 4.64 and 4.31 respectively. This shows that at the macro level investment in Indonesia is still inefficient. Regarding ICOR, senior economist Indef Faisal Basri revealed that the high ICOR was caused by many unqualified investments in which the investment yield industry only used a small amount of its production capacity when operating. According to Faisal, this is what the government tends not to pay attention to. The government only tends to invite FDI to enter and invest in Indonesia without considering its leverage to the national economy. "The ICOR was not paid attention, but the important thing is that foreigners come. Foreigners will not want to come if those here are miserable," said Faisal, (Bisnis.com, 2019). Therefore, in the future, regulatory and institutional reforms are needed so that ICOR Indonesia can be increasingly suppressed and can compete with other countries at the global level. Based on the foregoing, a research problem can be formulated:

  1. Can domestic direct investment (DDI) and foreign direct investment (FDI) partially increase economic growth in Indonesia under President Joko Widodo?
  2. Can domestic direct investment (DDI) and foreign direct investment (FDI) simultaneously increase economic growth in Indonesia under President Jokowi?.

2. LITERATURE REVIEW

2.1. Economic Growth

Economic growth can be defined as the development of activities in the economy that cause increased goods and services produced in society. From one period to another the ability of a country to produce goods and services will increase. This increased capability is due to the production factors that will always experience an increase in quantity and quality (Sukirno, 2011).

To calculate the rate of economic growth the following formula can be used:

Where:
G = Economic growth rate (%).
GDP1 = GDP calculated at fixed prices in the first year (1).
GDP0 = GDP calculated at fixed prices in the previous year (year 0).

2.2. Domestic Direct Investment

According to the Capital Investment Law no. 25 of 2007, domestic direct investment or domestic investment is an investment activity to conduct business in the territory of the Republic Indonesia which is carried out by domestic investors using domestic capital.

2.3. Foreign Direct Investment

According to the Capital Investment Law no. 25 of 2007 foreign direct investment or foreign investment is an activity of investing to conduct business in the territory of the Republic Indonesia which is carried out by foreign investors, either fully using foreign capital or jointly with domestic investors.

3. FRAMEWORK AND THE FORMULATION OF HYPOTHESIS

3.1. Framework

The thinking framework is a model or also a description in the form of a concept in which it describes a relationship between one variable and another. Therefore, it is better if this frame of mind is made in the form of a diagram or schematic, with the aim of being able to temporarily explain the symptoms that are the object of the problem.

The framework in this study explains the contribution of DDI and FDI to Indonesia's economic growth in 2014-2019 under President Joko Widodo's administration, both partially and simultaneously. This research suggests that DDI and FDI affect economic growth in Indonesia. Based on this, a scheme of the relationship between economic growth with DDI and FDI can be made

Figure-2. Thinking Framework and Hypotheses.

3.2. Research Hypothesis

Based on the above framework of thought, the following hypothesis can be formulated:
H1: Domestic Direct Investment (DDI) has a positive and significant effect on economic growth in Indonesia under President Jokowi.
H2: Foreign Direct Investment (FDI) has a positive and significant effect on economic growth in Indonesia under President Jokowi.
H3: Domestic Direct Investment (DDI) and Foreign Direct Investment (FDI) have a positive and significant effect on economic growth in Indonesia under President Jokowi.

4. EMPIRICAL REVIEW

Research results by Lean and Tan (2011); Trisnu and Purbadharmaja (2014); Zekarias (2016); Jufrida, Syechalad, and Nasir (2016); Iamsiraroj (2016); Mahriza (2019); Tran and Hoang (2019) show that foreign investment (FDI) has a significant positive effect on economic growth, while the research results of Jufrida et al. (2016) show that foreign investment has no effect on economic growth.

The results of research by Moudatsou (2003) in European Union countries regarding the impact of FDI on the economic growth of these countries during the period 1980-1996, show that the determinants of growth vary across members of the European Union and only FDI flows have a significant effect on economic growth. These empirical results indicate that FDI has a positive impact on economic growth in the European Union, both directly and indirectly through strengthening trade. Reza, Fan, Reza, and Wang (2018) FDI and GDP have a causal relationship in Bangladesh. Where the country's ability to increase economic growth can encourage the entry of greater FDI flows.  Mah and Yoon (2010) who reveal the determinants of FDI flows to Indonesia and Singapore. Empirical evidence shows that for Indonesia, market size and wages do not have a significant effect, while the interest rate has a positive and statistically significant effect on FDI flows.

Furthermore, the research results of Trisnu and Purbadharmaja (2014); Jufrida et al. (2016); Ibrahim and Dahie (2016); Emmanuel and Kehinde (2018); Mahriza (2019); Tran and Hoang (2019) show that domestic investment (DDI) ) has a positive and significant effect on economic growth, while the results (Lean & Tan, 2011) show that domestic investment has a negative effect on economic growth. The research results of Herman Kambono and Elyzabet Indrawati Marpaung show that foreign investment has a significant positive effect on economic growth, while domestic investment has no effect on economic growth.

5. RESEARCH METHODS

The method used in this research is quantitative descriptive method. The quantitative method is a research method based on the philosophy of positivism, used to examine specific populations or samples, data collection using research instruments, quantitative / statistical data analysis, with the aim of describing and testing predetermined hypotheses (Sukirno, 2011).

The descriptive method takes problems or focuses attention on problems as they are when the research is carried out, the results of the research are then processed and analyzed to draw conclusions (Sukirno, 2011). The author uses descriptive methods to determine the phenomenon currently underway, while quantitative methods are used to test classical assumptions and statistical tests with multiple linear regression analysis. Furthermore, through multiple regression analysis, the effect of DDI and FDI on economic growth in Indonesia will be examined.

5.1. Method of Collecting Data

In this study, the data used is secondary data, namely cross section data per quarter 2014-2019 period. According to the source, the data consists of domestic direct investment data, foreign direct investment data and economic growth data obtained from the Central Statistics Agency (BPS), the Investment Coordinating Board (BPKM) and Word Bank.

5.2. Data Analysis Method

Mathematically, the relationship between DDI and FDI on economic growth can be stated in the following equation:

EG = a + b1DDI+ b2FDI+ E

Where:
EG          = Economic Growth.
DDI        = Domestic direct investment.
FDI         = foreign direct investment.
a              = Constant.
b1, b2     = Regression coefficients of DDI and FDI.

6. RESEARCH RESULTS AND DISCUSSION

6.1. Classical Assumption Test Results

6.1.1. Normality Test Results

The normality test is used to determine whether the data population is normally distributed or not. If the data is not normally distributed, or the number of samples is small and the type of data is nominal or ordinal, the method used is non-parametric statistics. In this discussion we will use the One Sample Kolmogorov-Smirnov test using a significance level of 0.05. The data is declared to be normally distributed if the significance is greater than 5% or 0.05. The normality test can be seen in Table 1.

Table-1. Normality test.

Model
Kolmogorov-Smirnova
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
Growth
.107
24
.200*
.970
24
.669
DDI
.141
24
.200*
.949
24
.262
FDI
.173
24
.061
.953
24
.321

Note: *. This is a lower bound of the true significance.
a. Lilliefors Significance Correction.

From the results above we look at the Kolmogorov-Smirnov column and it can be seen that the significance value for economic growth is 0.200; for DDI of 0.200; and for FDI of 0.061. Because the significance for all variables is greater than 0.05, it can be concluded that the data on the economic growth variables, DDI, and FDI are normally distributed. Statistic figures show that the smaller the value, the more normal the data distribution. The results of the autocorrelation test can be seen in Table 2.

6.2. Autocorrelation Test Results

s The autoceralation test aims to test the linear regression model whether there is a correlation of confounding errors in period t with errors in period t-1 (previous) or not. If there is a correlation, it is said that there is an autocorrelation problem. How to detect autocorrelation problems is to use the Durbin Watson (DW) test and then compare the test results with the Durbin Watson (DW) table. If d <dL, there is negative autocorrelation. If dL≤d≤dU or (4-dU) ≤d≤ (4-dL) then the test result is without a decision. Then if U≤d≤ (4-dU), then there is no autocorrelation. Furthermore, if d≥ (4-dL) then the conclusion is that there is positive autocorrelation (Ghozali, 2018). The results of the autocorrelation test can be seen in Table 2.

Table-2. Autocorrelation Test.

Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Durbin-Watson
1
.471a
.222
.148
.00123245
1.469

Note:
a. Predictors: (Constant), FDI, DDI.
b. Dependent Variable: Growth.

From the output above, it is obtained that the DW value generated from the regression model is 1.387. Meanwhile, from the DW table with a significance of 0.05 and the amount of data (n) = 24, seta k = 2 (k is the number of independent variables), the dL value is 1.1878 and the dU is 1.5464 (see attachment). Because the DW value (1.469) is in the area between dL and dU, the null hypothesis is accepted which means there is no autocorrelation.

6.3. Multicollinearity Test Results

The multicollinearity test is used to determine whether or not there are deviations from the classic multicollinearity assumption, namely the linear relationship between independent variables in the regression model. The prerequisite that must be met in the regression model is the absence of multicollinearity. Testing the presence or absence of multicollinearity symptoms is done by looking at the VIF (Variance Inflation Factor) and Tolerance values. If the VIF value is below 10.00 and the Tolerance value is more than 0.100, it can be concluded that the regression model does not have a multicollinearity problem. The results of the multicollinearity test can be seen in Table 3.

Table-3. Multicollinearity Test.

Model
Collinearity Statistics
Tolerance
VIF
1. (Constant)
DDI
.716
1.396
FDI
.716
1.396

From the above results it can be seen that the value of the variance inflation factor (VIF) of the two variables, namely PMDN and PMA is 1.396 less than 10 and Tolerance is more than 0.100, so it can be concluded that between the independent variables there is no multicollinearity problem.

6.4. Heteroscedasticity Test Results

The heteroscedasticity test is used to determine whether or not there are deviations from the classic assumption of heteroscedasticity, namely the inequality of variants of the residuals for all observations in the regression model. The prerequisite that must be met in the regression model is the absence of heteroscedasticity symptoms. There are several test methods that can be used including the Park test, Glesjer test, Viewing regression chart patterns, and the Spearman correlation coefficient test. If the significance value between the independent variables and the absolute residual is more than 0.05, there is no heteroscedasticity problem. The results of the Heteroscedasticity test can be seen in Table 4.

Table-4. Heteroscedasticity Test.

Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
.051
.000
129.835
.000
DDI
-.010
.005
-.427
-1.876
.075
FDI
-.012
.005
-.529
-2.327
.030

Note: Dependent Variable: Growth.

From the output above, it can be seen that the significance value of the three independent variables is more than 0.05. Thus it can be concluded that there is no heteroscedasticity problem in the regression model.

6.5. Results of Multiple Linear Regression Analysis

The data analysis method used in this study is the Multiple Linear Regression method. Multiple linear regression analysis is an analysis used to determine whether or not DDI and FDI have contributed to economic growth in Indonesia under Jokowi. The results of multiple regression analysis can be seen in Table 5.

Table-5. Multiple regression analysis.

Model
Unstandardized Coefficients
Standardized Coefficients
B
Std. Error
Beta
1
(Constant)
.051
.000
DDI
-.010
.005
-.427
FDI
-.012
.005
-.529

From Table 5, the following equation is obtained:
EG = 0,051 – 0,010DDI – 0,012FDI
Meaning:
a. The effect of DDI on economic growth is -0.010. This means that the contribution of DDI to economic growth is -0.010% with the assumption of constant FDI (FDI = 0).
b. The effect of FDI on economic growth is -0.012. If FDI is increased by 1%, economic growth will decrease by -0.012%. Assuming constant DDI (DDI = 0).

6.6. Statistical Test Results

The statistical test is used to determine whether the independent variable partially and simultaneously has a significant influence on the dependent variable. Statistical tests include t test, F test and coefficient of determination (R2)

6.7. T Test Results (Effect of DDI on Economic Growth)

The first hypothesis test is the t test, which is used to partially see the effect of each independent variable (independent) on the dependent variable.
The basis for decision making is:

1. If the value of t count> t alpha or sig <alpha then Ho is rejected and Ha is accepted. This means that the free variable affects the dependent variable.
2. If the value of t count <t alpha or sig> alpha then Ha is rejected and Ho is accepted. This means that the free variable has no effect on the dependent variable.
The t test results can be seen in Table 6.

Table-6. Effect of DDI on economic growth.

Model
t
Sig.
1
(Constant)
129.835
.000
DDI
-1.876
.075
FDI
-2.327
.030

From the estimation results, the t value is -1.876 and t alpha -2.0796 with a confidence level of 95%. Because t count = -1.876> t table = -2.0796 or the value of Sig = 0.075> α = 0.05, it means that domestic investment (DDI) has no effect on economic growth in Indonesia. The results of this study indicate that the increase in DDI has a negative and insignificant to economic growth in Indonesia under Jokowi. The results of this study are also not in line with research conducted by Trisnu and Purbadharmaja (2014); Jufrida et al. (2016); Ibrahim and Dahie (2016); Emmanuel and Kehinde (2018); Tran and Hoang (2019) and Kambono and Marpaung (2020) who show that domestic investment (DDI) and foreign investment (FDI) have a positive and significant effect on economic growth.

6.8. T-test Results (Effect of FDI on Economic Growth)

From the estimation results, the t value is -2.327 and t alpha -2.0796 with a confidence level of 95%. Because t count = - 2.327 <t table = -2.0796 or the value of Sig = 0.030 <α = 0.05, the regression analysis model is significant. Because the regression analysis model is significant, it means that partially FDI has a negative and significant effect on economic growth in Indonesia. The results of this study indicate that the purpose of implementing foreign investment (FDI) in Indonesia to increase economic growth has not been achieved in the Jokowi era because an increase in FDI investment will reduce economic growth.

In theory, an increase in investment (DDI and FDI) should increase economic growth, but in this study investment, both DDI and FDI, have a negative effect on economic growth. Therefore, increasing investment in the context of advancing economic growth requires equitable distribution of infrastructure development to absorb human resources so that it can reduce unemployment and poverty levels, and further increase economic growth in Jokowi's era in Indonesia.

6.9. F Test Results

The F test is used to determine whether the independent variables (DDI and FDI) jointly affect the dependent variable (economic growth).
Basic decision making:

1. If F count> F alpha or sig <alpha then Ho is rejected and Ha is accepted. This means that the free variable affects the dependent variable.
2. If F count <F alpha or sig> alpha then Ho is rejected and Ha is accepted. This means that the free variable has an effect on the dependent variable.
Result of F-test in Table 7.

Table-7. F-test.
Model
F
Sig.
1
Regression
2.990
.072b
Residual
Total

6.10. Coefficient of Determination

Based on the simultaneous test, the calculated F value is 2.990 and Fα with a 95% confidence level is 3.26. Because F count = 4.1> F table = 3.47 or the value of Sig = 0.072> α = 0.05, the regression analysis model is not significant. Because the regression analysis model is not significant, it means that simultaneously DD and FDI do not have a significant effect on Economic Growth in Indonesia under President Joko Widodo (Jokowi).

The coefficient of determination (R2) is used to predict how much the contribution of the influence of the independent variable to the dependent variable. The coefficient of determination is between zero and one. A value close to one means that the independent variables provide almost all the information needed to predict the variation in the dependent variable. On the other hand, a small coefficient of determination indicates that the ability of the independent variable to explain the variation of the dependent variable is very limited (Ghozali, 2018). R2 test results can be seen in Table 8.

Table-8. R2.-Test

Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.471a
.222
.148
.00123245

Note:
a. Predictors: (Constant), PMA, PMDN.
b. Dependent Variable: Growth.

The results of the R square show that 22.2% of economic growth is explained by DDI and FDI and the remaining 78% is explained by other factors that contribute to economic growth but are not included in the equation, for example household consumption, government spending and net exports. R2 test results are synchronous with the F test (simultaneous test).

7. CONCLUSIONS AND RECOMMENDATIONS

7.1. Conclusion

This study aims to see the effect of DDI and FDI on economic growth in 2014-1019 in Indonesia in the era of Joko Widodo, president of the Republic of Indonesia. The conclusion of this study is

  1. Partially DDI has no significant effect on economic growth. Meanwhile, FDI has a negative and significant effect on economic growth.
  2. Simultaneously, DDI and FDI have no significant effect on economic growth.

7.2. Suggestion

This research has been attempted in accordance with scientific procedures, but it still has limitations because it only uses the DDI and FDI variables as variables that affect economic growth. In theory and implementation there are many other variables that affect the variable of economic growth. Furthermore, the data obtained only comes from several websites, for example BPS, Word bank and BKPM.
In this study, there are several suggestions that can be taken into consideration: Jokowi said that foreign investment (FDI) is the key for Indonesia to survive amid the threat of a recession and global economic uncertainty caused by the intensifying trade war between the United States and China. However, in reality, the relocation of foreign investors from Indonesia to other Southeast Asian countries, especially Vietnam, Malaysia and Thailand, is one of a number of economic challenges that will be faced by President Joko Widodo's administration. Therefore, Indonesia needs to increase its competitiveness by cutting birography that hinders investment procedures and preparing innovative human resources so that investors who have entered Indonesia do not leave Indonesia again, which has resulted in increased unemployment and an impact on slowing economic growth.

Funding: This study received no specific financial support.  

Competing Interests: The authors declare that they have no competing interests.

Acknowledgement: All authors contributed equally to the conception and design of the study.

REFERENCES

Braunstein, E. (2006). Foreign direct investment, development and gender equity: A review of research and policy (No. 12). UNRISD Occasional Paper,51.

Emmanuel, O. G., & Kehinde, A. J. O. S. E. (2018). Domestic investment and economy growth in Nigeria: An empirical investigation. International Journal of Business and Social Science, 9(2), 130-138.

Ghozali, I. (2018). Multivariete analysis application with IBM SPSS 25 program (9th ed.). Semarang: Diponegoro University Publishing Agency.

Iamsiraroj, S. (2016). The foreign direct investment–economic growth nexus. International Review of Economics & Finance, 42, 116-133.Available at: https://doi.org/10.1016/j.iref.2015.10.044.

Ibrahim, A. A., & Dahie, A. M. (2016). The effect of foreign direct investment, foreign aid and domestic investment on economic growth: Evidence from Somalia. Imperial Journal of Interdisciplinary Research, 2(12), 633-640.

Jufrida, F., Syechalad, M. N., & Nasir, M. (2016). Analysis of the effects of direct foreign investment (FDI) and domestic investment on Indonesia's economic growth. Journal of the Economic Perspectives of Darussalam, 2(1), 54-68.

Kambono, H., & Marpaung, E. I. (2020). The effect of domestic investment and domestic investment on the Indonesian economy. Maranatha Accounting Journal, 12(1), 137-145.

Lean, H. H., & Tan, B. W. (2011). Linkages between foreign direct investment, domestic investment and economic growth in Malaysia. Journal of Economic Cooperation and Development, 32(4), 75-96.

Mah, J. S., & Yoon, S.-C. (2010). Determinants of FDI Flows into Indonesia and Singapore. International Area Studies Review, 13(1), 63-73.Available at: https://doi.org/10.1177/223386591001300104.

Mahriza, T. (2019). The influence of domestic investment, single investment, labor and infrastructure on the economy in West Sumatra Province. Journal of Economic and Development Studies, 1(3), 691-704.

Moudatsou, A. (2003). Foreign direct investment and economic growth in the European Union. Journal of Economic Integration, 18(4), 689-707.Available at: https://doi.org/10.11130/jei.2003.18.4.689.

Reza, S. M., Fan, H., Reza, T., & Wang, B. (2018). The impact of foreign direct investment inflows on economic growth: Evidence from Bangladesh. Journal of Business and Retail Management Research, 12(2), 212-223.

Sukirno, S. (2011). Introductory macroeconomics theory. Jakarta: Rajawali Pers.

Syaparuddin. (2019). A study of investment pattern through economic sectors- based in Indonesia. International Journal of Innovation, Creativity and Change, 9(2), 227-239.

Tran, H. T. T., & Hoang, H. T. (2019). An investigation into the impacts of FDI, domestic investment capital, human resources, and trained workers on economic growth in Vietnam. Paper presented at the International Econometric Conference of Vietnam. Springer, Cham.

Trisnu, C. I. S. R., & Purbadharmaja, I. B. P. (2014). The influence of PMDN and PMA on PDRB in Bali Province. Journal of Development Economics, University of Udayana, 3, 88-95.

Zekarias, S. M. (2016). The impact of foreign direct investment (FDI) on economic growth in Eastern Africa: Evidence from panel data analysis. Applied Economics and Finance, 3(1), 145-160.Available at: https://doi.org/10.11114/aef.v3i1.1317.

Views and opinions expressed in this article are the views and opinions of the author(s), International Journal of Business, Economics and Management shall not be responsible or answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content.