Mechanisms of how FDI contributes to GDP in Asian Countries. A study

Table of contents

Abstract

1 Introduction

2 Literature Review

3 Methodology

4 Result and Discussion
4. 1 Descriptive statistics
4.2 Causal mediation Analysis
4.3 Managerial Implication

5 Conclusion

Appendix

Abstract

The study aims to analyze mechanisms by which foreign direct investment inflows (FDI) contributes to gross domestic product (GDP) in Asian countries. FDI is used as an independent variable. GDP is used as dependent variable. While export (EXP), house hold consumption (HHC), and gross capital formation (GCF) are used as mediator variables. Many studies analyzed direct relationship between FDI and GDP without explaining how FDI contributed to GDP. Therefore, little is known about the way FDI contributes to GDP in receiving country. The study focuses on the question “what is the indirect relationship between FDI and GDP in Asian Countries?”. The novelty of this paper is to provide a deep understanding on how FDI is related to GDP in Asian countries which did not get much attention in prior literature. The study used causal mediation analysis with bootstrap procedure. Annual data 2018 related to FDI, GDP, EXP, HHC, and GCF were collected from the World Bank website. The empirical results indicate that there were statistically significant mediation effects of the mediator variables (EXP, HHC, and GCF) in the relationship between FDI and GDP, while direct relationship was not statistically significant. FDI increased GDP by increasing EXP, GCF, and HHC. Asian governments should continue stimulating FDI to support their economic growth.

Keywords: Investment, Household, Export, Gross domestic product.

1 Introduction

The impact of foreign direct investment on economy growth got much attention in all continents. The findings of the prior researches show mixed results. Some of them concluded that FDI has positive impact on GDP. While other concluded that FDI has negative effect on GDP. For instance, Raghuveer and Muthusamy (2019) investigated the relationship between FDI and economic growth in some Asian countries including Bangladesh, China, India, Lao PDR, Mongolia, Korea Republic and Sri Lanka. They used Ordinary Least Squares, Augmented Dicky-Fuller and Granger Causality test, and found that the effect of FDI inflow on economic growth was not the same in the analyzed countries. Diouf and Hai (2017) examined the effect of the interaction between FDI, trade openness and economic growth with by focusing on Asian FDI, trade and 13 West African countries covering the period 1980-2015. They used Fully Modified Ordinary Least Squares (FMOLS, and their findings revealed that FDI and trade significantly contributed to economic growth. Raj and Pahwa (2018) investigated the impact of FDI inflows on the economic growth of India using regression technique and with regression model. They concluded that FDI had a significant impact on the growth of Indian economy. Isaac and John (2017) analyzed the quantifiable effect and path of Chinese FDI on economic growth in Africa by analyzing a sample of 20 African countries for the period 2003 to 2012.They concluded that increasing a 1 percent in China’s FDI stock in Africa significantly raised Africa’s gross domestic product (GDP) growth by 0.607 percent, provide that all things remain equal.

On contrast of the results indicating a positive effect of FDI on economic growth, there are other findings that reveal a negative effect of FDI on economic growth. For instance, Abdelbagi (2015) indicated that the impact of FDI on economic growth was negative and statistically significant in low-income and middle-income countries. Igor (2015) revealed that FDI had negative influence on local investment in the republic of Croatia. Umeora (2013) concluded that FDI did not rise GDP, instead increased inflation, and had negative effect on exchange rate in Nigeria.

The results of the previous researches did not show how FDI contributed to economic growth in a host country. Additionally, economic activities are interconnected in such a way one activity can have spillovers on other activities. Ignoring such interactions lead to wrong conclusions. This is the case for all studies that analyzed the relationship between FDI and economic growth. They focused on analyzing direct relationship without analyzing indirect relationship between FDI, and economic growth. For instance, when a multinational company is created, it will hire employees and pay salaries. It will also bring modern technology. It can increase export, etc. Increasing salaries will increase income in a host country, which can increase demand of goods and services. The increase in the demand of goods and services will increase production of goods and services. As it can be seen not considering indirect effect of FDI is misestimation of the impact of FDI in receiving country. This idea is supported by Mamingi and Martin (2018) who indicated that the direct effect of FDI on GDP is small when FDI is considered in isolation, but indirect effect is more significant than direct effect. Hanousek, Kocenda and Maurel (2010), indicated there exist direct and indirect effects of FDI in emerging European markets, however panel studies are seemingly to find relatively lower spillover effects.

Given the inconsistent findings of the studies above, it is clear that both academics and practitioners are unclear as to the contribution of FDI on GDP. Based on the limitations of the prior studies, the research question is “what was the indirect relationship between foreign direct investment inflows and gross domestic product in Asian countries?”. The general purpose of this study is to analyze the indirect relationship between foreign direct investment inflows (FDI) and gross domestic product (GDP). Specifically, the study will analyze:

- The mediation effect of EXP in the relationship between FDI-GDP.
- The mediation effect of HHC in the relationship between FDI-GDP.
- The mediation effect of GCF in the relationship between FDI-GDP.

The research questions are:

- What was the mediation effect of EXP in the relationship between FDI-GDP?
- What was the mediation effect of HHC in the relationship between FDI-GDP?
- What was the mediation effect of GCF in the relationship between FDI-GDP?

The paper is organized as follows. The next section two presents the literature review. The section three indicates the methodology. The section four presents the empirical findings including descriptive statistics, and the results of the causal analysis. Section five concludes the research.

2 Literature Review

This section presents the findings of the prior researches on the impact of FDI on GDP, HHC, and GCF. It also makes a critical analysis of these findings. The findings will allow to support the results of this research. FDI can contribute in a host country through different ways. According to Prince and Vijay (2019) FDI are able to bring much-needed capital to emerging countries, make progress the manufacturing and trade sectors, bring in more efficient technologies, boost local production and exports, create jobs and develop local skills, improve infrastructure and contribute to sustainable economic growth overall. However, not all FDI has positive impact of economic growth. Susilo (2018) indicated that not all FDI appear to be beneficial to host economies. He analyzed the impact of F.D.I on Economic Growth in the United States using multiple linear regression model. According to him some sectors provide positive relationship to economic growth and some provides negative effect. The effect of FDI on economic growth depends on the sector where they are oriented.

Mona (2015) analyzed the association between economic growth and the FDI inflow in 41 Sub-Sahara Africa countries. Analysis was performed using regression, and found FDI has a positive effect on economic growth in countries analyzed. Bhavish, Nitisha and Sheereen (2016) found consistent result after analyzing data from 32 Sub-Saharan African countries covering 2008-2014. They concluded that FDI did have a positive and significant impact on economic growth in those countries.

Bibhuti and Farid (2020) analyzed the causal nexus between FDI and GDP in Bangladesh. They used augmented Dickey-Fuller, augmented Dickey-Fuller generalized least square, Kwiatkowski-Phillips-Schmidt-Shin, and Lee-Strazicich unit root tests to check stationarity, augmented autoregressive distributed lag (augmented ARDL) bounds to test cointegration, and Granger causality to analyze the direction of causality. A long-run relationship between FDI and GDP was revealed. An unidirectional causality running from GDP to FDI was also detected. Opposite results was found by Sonja and Tanja (2016) after investigating the effect that FDI had on economic growth in European Union. Their result indicated a negative interdependence between FDI and GDP and no positive impact of FDI on the value of GDP was in the EU during 2005 to 2015.

The impact of FDI on EXP is not well known. There are contradictory results on the impact of FDI on EXP. According to Selimi, Reçi and Sadiku (2016) some studies concluded that FDI have positive effect on the EXP performance. However, other studies did not find any impact on the EXP performance. Mukhtarov, Alalawneh, Ibadov and Huseynli (2019) found that there was a positive and statistically significant impact of FDI on export in the long-run in Jordan. The estimation results showed that a 1% increase in FDI increases exports by 0.13%. The result of estimated Error Correction Model indicated that FDI negatively affected exports with a two-year gap in Ethiopia (Tessema, 2019).

The studies conducted to analyze the impact of FDI on GDP did not address the question related to how FDI contribute to GDP. However, the Expenditure method of calculating GDP indicates that GDP equals the sum of spending on produced goods and services measured at current market prices (Susilo,2019). The full equation of GDP is GDP = C + I + G + (X-M), where C is household spending; I refers to capital investment spending, G is government spending; X is exports of goods and services, and M is imports of goods and services. A part of FDI can be included in GDP via capital investment spending. However, not all FDI inflows is invested in fixed asset. A share of FDI can be used in salaries paying, working capital payment, raw material acquisition, etc. All those payments can contribute to increasing GDP as indirect effect of FDI. As far as what is paid by an economic agent is produced by another economic agent. It is clear that indirect relationship between FDI and GDP did not get much attention, and little is known in the mechanism by which FDI contribute to GDP.

3 Methodology

To analyze mechanisms by which FDI contributes to GDP in Asian countries annual data 2018 related to GDP, FDI, EXP, GCF, and HHC were collected on the World Bank web site. Data related to 37 Asian countries were collected. A resampling method based on the bootstrap resampling procedure was used. This method is recognized to performs better than the Baron and Kenny method in case of small sample size studies Omokri, Agbedey and Nwajei (2018). Bootstrapping method is generally used to test mediation with samples between 20-80 observations Koopman, Howe, Sin and Hollenbeck (2015). R software was used to complete the analysis.

The bootstrapping method provides four results. The first result is the average causal mediation effect (ACME). The second result is the average direct effect (ADE). The third result is the total effect. The last result is the proportion mediated. The ACME is the indirect effect. The ACME can be obtained by multiplying the coefficient of FDI when FDI is regressed on mediator variable (a), and the coefficient of mediator variable when FDI and mediator variable (b) are regressed on GDP. ACME is equal to a*b. ADE is the effect of the mediator variable when the mediator variable is controlled. The total effect is the sum of ACME and ADE. Proportion mediated is the result of indirect effect divided by total effect. The proportion mediated can be understood as the variance accounted for (VAF). If VAF is less than 20%, the indirect effect is not significant; therefore, there is no mediation. If VAF is between 20% and 80%, there is partial mediation. A VAF value of greater than 80% implies full mediation Hadi, Abdullah and Sentosa (2016).

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