Global Journal of Business and Social Science Review journal homepage: Macroeconomic Determinants of FDI Inflow: Malaysia Evidence *

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1 Global Journal of Business and Social Science Review journal homepage: ISSN Macroeconomic Determinants of FDI Inflow: Malaysia Evidence * Sridevi R.K. Narayanan 1*, Hassanudin Mohd Thas Thaker 2 1, 2 Department of Business Studies, Faculty of Business, Economics and Accounting, HELP University, Malaysia ABSTRACT Objective The main objective of this paper is to investigate whether labor productivity is an important contributing factor to FDI inflows and in turn if FDI enhances labor productivity. Hence, this is ensured by an investigation of whether a bi-directional causality e between FDI and labor productivity exists. Methodology/Technique To increase the robustness of our estimation model, a few control variables such as Trade Openness, inflation and income per capita in addition to labor productivity are included as explanatory variables in determining FDI inflows. In this paper, we used annual calendar data spanned between 1990 and 2012 and employed the multiple regressions to generate the results. Findings The finding suggests that labor productivity (LBRPROD) and inflation (INF) have positive relationship with the FDI while income per capita (ICP) and openness (OPN) seems to be negatively related with FDI. The findings from this study are consistent with the past and existing literature where there is strong association between FDI and labor productivity. However, this study also revealed that openness seems to be insignificant towards FDI inflows contradicting past literature which argued that openness plays an important in FDI. But the negative relationship between FDI and trade openness could be addressed via implementation of provision for trade protection. Novelty Enhance the knowledge in the relationship of LBRPROD and INF with FDI. Type of Paper: Empirical Keywords: Foreign Direct Investment, Labor Productivity, Multiple Regression, Trade Openness, Malaysia. 1. Introduction. The economic growth and development of Malaysia has been astounding over the past few decades and has been taking huge steps in the way forward to becoming a fully developed country. The success of Malaysia is partly and mostly due to the FDI received over the past decades, making it a preferred destination of FDI in the South East Asia and ASEAN alike for foreign direct investors. * Paper Info: Revised: September, 2015 Accepted: December, 2015 * Corresponding author: sridevi.n@help.edu.my Affiliation: Faculty of Business, Economics and Accounting, HELP University, Malaysia ISSN GATR Enterprise. All rights reserved.

2 FDI is simply defined as investment from one country into another (normally by companies rather than governments) that involves establishing operations or acquiring tangible assets, including stakes in other businesses. 1 Given the importance of FDI to Malaysia s growth and economic transformation, we devote this paper into examining the determinants of FDI and focusing on labor productivity as the main determinant and other economic variables as the control variables to increase the robustness of this study. 1.1 Objective of Study. This paper aims to investigate the impact of the selected determinants of FDI inflow in Malaysia so that it can identify the main determinants that influence FDI inflows as a guide for policy makers in formulating their policies with regards to attracting and sustaining high levels of FDI inflows, which is inarguably very much needed for continuous growth and development of the country as it still is dependent on foreign funds for such purpose. Given the strong currents of competition for FDI, it is imperative that we re-examine the determinants of FDI for Malaysia with the inclusion of recent data to remain relevant with changing business and economic environment albeit the abundance of previous studies on the same issues. In the face of increasing competition for FDI inflows especially among its ASEAN neighbors, Malaysia needs to be more focused how to over-ride its neighbors in attracting FDI and it is hoped that this simple study can shed some light for policy makers to design appropriate policy measures to optimize FDI inflows into the country 1.2 Research Question H1: Do countries with large GDP per capita more likely to be successful in attracting FDI? H2: does GDP Per capita exhibit a bi-directional causality with FDI? H3: Will a country with greater degree of international openness be more attractive in FDI attraction? H4: Does labor productivity have a bi-directional impact on FDI? H5: What would be the likely impact of inflation on FDI? 1.3 Structure of the Paper The rest of the paper is organized as follows: Section 1.4 will discuss the FDI flow trend of Malaysia over the period of study ranging from 1990 to 2012.measured as a percentage of GDP. Section 2 will review the past literature on FDI determinants and benefits of FDI. Section 3 will discuss the methodology, the data sources and description of the variables used. Section 4 will carry the results of the analysis and followed by discussion of the results in the findings section and subsequently the concluding remarks will address the policy implications and recommendations as well as limitations of the study and recommendation for future research. 1 UNCTAD World Investment Report P a g e

3 2. Review of the benefits from FDI to host countries Findlay (1978) reveals that multinational firms own and transfer technology which may not be available in the host country that allows them to be more productive and profitable than firms that are not multinational in nature. Because such a transfer is assumed to contribute to the technical progress of the host economies, it is also assumed to contribute ultimately to their growth. Rivera-Batiz and Rivera-Batiz (1991) found that increasing returns due to specialization as a result of FDI. Borenszten, De Gregorio, and Lee, (1998) tested the effects of FDI on growth in a crosscountry regression analysis involving FDI in industrialized countries for two decades and concluded that FDI is an important vehicle for technology transfer and higher growth than domestic investment. However, it was asserted that FDI only contributed to high productivity given that the host country has a minimum threshold of human capital stock. Numerous other studies have attempted to provide theoretical and empirical answers to the question of the overall impact of FDI on the host economy and which have provided interesting and testable propositions valid under certain conditions and pointing towards a positive overall FDI effect.. Wang and Blomström (1989), in a working paper entitled FDI and technology transfer: A simple model concluded that technology transfer was a result of strategic interaction between subsidiaries of MNCs and host country firms. The paper also touched on the cost of technology transfer and the cost of learning or absorbing the technology by host firms. It can, therefore, be concluded further that technology transfer will depend on how fast the learning/absorption takes place. In a nutshell, FDI is an important source of private external funding for developing countries and its role in significantly promoting economic growth and development is undeniable looking at how FDI has shaped many newly industrialized countries (NIC) like Singapore, Taiwan, South Korea and Hong Kong. According to Razin and Sadka (2001), FDI benefits the host countries in many ways, for example, In the transfer of technology, specifically in the form of new variety of capital inputs. In promoting competition in the domestic factor market In promoting Human capital development of host country through employee training from the operation of new business. In contributing to the host countries tax revenues through corporate taxation. Most empirical studies conclude that FDI contributes to both factor productivity and income growth in host countries.beyond what domestic investment normally would trigger. It is more difficult, however, to assess the magnitude of this impact, not least because large FDI inflows to Developing countries often concur with unusually high growth rates triggered by unrelated factors. Whether, as sometimes asserted, the positive effects of FDI are mitigated by a partial crowding out of domestic investment is far from clear. Some researchers have found evidence of crowding out while others conclude that FDI may actually serve to increase domestic investment. Regardless, even where crowding out does take place, the net effect generally remains beneficial not least as the replacement tends to result in the release of scarce domestic funds for other Investment purposes in lower developed countries. 127 P a g e

4 2.1 Review of Literature of FDI determinants. Erdhal Demirham, et.al,(2008) used cross-sectional econometric analysis over a period between for a sample of 38 developing countries, concluded that degree of openness, telephone lines and growth rate per capita have a significant and positive effect on FDI inflows while tax rate and inflation rate tend to affect FDI inflows negatively. Similarly, Khodicar, et al in a research paper done on FDI determinants in developing countries using comparative analysis on 68 developing countries from Asia, Africa and Latin America employing panel data approach over a short period from , stressed that countries with larger GDP growth rate, higher proportion of International Trade coupled with businessfriendly environment are more successful in attracting FDI. A more comprehensive study on FDI determinants revealed in an IMF working paper,2010 by James Walsh and Jiang Yan Yu entitled Determinants of FDI: A Sectorial Approach where data observed was from 1985 to 2008, for 27nadvanced and emerging market countries. Data on net FDI flows were examined from primary, secondary and tertiary sectors. As FDI flows were the dependent variable, the independent variables include openness, real exchange rate, inflation, FDI stock, GDP growth, GDP per capita and real GDP growth per capita were used as proxy for host countries market size and growth potential. GMM estimator based on Arellano-Bond methodology was used to estimate the relationship between FDI flows and the macroeconomic variables. The results showed that the relationship between primary sector FDI and economic variables is minimal, as primary sector which involves extraction of raw materials and oil are not dependent on macroeconomic factors. The secondary sector FDI tends to be more responsive to the macroeconomic variables. A depreciated real exchange rate is seen to be good for the manufacturing sector investment and high GDP have less influence on manufacturing investment. However, openness did not appear to impact upon secondary FDI since some of these manufactured goods are consumed domestically. The tertiary sector FDI tends to have links with macroeconomic variables but differently from the secondary sector FDI. For example, openness and real exchange rate have a positive effect on FDI meaning that the more open the economy with fewer barriers, the more the FDI inflows into the tertiary sector and the stronger the domestic currency, the higher the FDI inflows to this sector. Oladipo, (2013), in a study on macroeconomic determinants of FDI in Nigeria, used time series data for a period between 1985 to2010, testing determinants such as Money Supply,Poverty Level, Exchange rate,interest rate GDP, Inflation, Openness, government capital expenditure, Government recurrent expenditure for which, data was obtained from Central Bank of Nigeria.GMM technique was employed to analyze the results. It was found that Exchange rate, interest rates, openness, and money supply tend to be significantly and positively affecting FDI. 3. Methodology and theoretical Framework This section will focus on the determinants that influence the FDI inflows and the source of data. It also depicts the theoretical framework and the model specification used to show the relationship between the Dependent variable (FDI) and independent variable (Openness, Inflation Labor productivity, and Income per capita. A bi-directional model between Income per capita and FDI with Income per capita as the dependent variable and Income per capita as the independent variable as well as Labor productivity as dependent and FDI as independent was included to remove the spontaneity bias. 128 P a g e

5 Inflatio Income per Capital FDI Inflows Labor Productivity Openness Figure 1: The theoretical framework showing the determinants of FDI. 3.1 Data collection and estimation method The table below, a summary of the variables used in this study, its description as well as the data source. Table 1. Variables Definition Variables Definition Source FDI Foreign direct investment World Bank report ln ICP Natural log of Income per Capita World Bank report LBRPROD Labor productivity measures the amount of goods and services produced by one hour of labor. World Bank Report and Total Economy Database OPN Openness calculated as export plus import/gross domestic product International Financial Statistics (IFS), Bank Negara report and Statistic Department of Malaysia Inf Inflation proxy by Consumer price index Bank Negara report and Statistic Department of Malaysia This study employs multiple regressions to verify the association between FDI (dependent variable) and selected independent macroeconomic variables. This relationship is shown by the model specification given below: Y = f(lnicp + LBRPROD + OPN + INF + ε). 129 P a g e

6 The generic version of the model is given as follows: Y = βo + β1 (lnicp) + β2 (LBRPROD) + β3 (OPN) + β4 (INF) + ε Where: Y Ln ICP LBRPROD OPN INF βo β1 - β4 ε = FDI = natural log of income per capita = labour productivity = openness = inflation = intercept (slope of dependent variable) = coefficient of independent variables = disturbance/error term 4. Empirical Results 4.1 Descriptive Statistics Table 2. Model Summary Model R R Square Adjusted R-Square Std. Error of the Estimate Durbin-Watson a a. Predictors: (Constant), Ln ICP, LBPROD, OPN, INF b. Dependent Variable: FDI The R-square is the measure of goodness of fit, which in this case, indicates that 61.3 percentage of Variation in FDI is explained by the variation in the chosen independent variables in this model. 4.2 ANOVA Analysis ANOVA analysis or Global Hypothesis Testing is a statistical measurement to test the linear relationship between FDI and independent variables. The pre-condition to carry out this analysis requires that at least one independent variable in the model must be of significance. In order to test this analysis, the following hypotheses have been developed: Ho: β1 = β2 = β3 = β4 = 0 (All variable are irrelevant) H1: β1 β2 β3 β4 0 (All variable are relevant) Table 3. ANOVA Analysis Model Sum of Squares df Mean Square F Sig. 1 a. Dependent Variable: FDI Regression b Residual Total b. Predictors: (Constant), lnicp, TFP, OPN, INF The results of the ANOVA analysis in Table 3 shows that the p-value is less than 0.05, which is less than 5 percent of significance level. Hence, the null hypothesis is not supported and it can be concluded that at least of the independent variable is relevant and significantly influencing the FDI. 130 P a g e

7 4.3 Regression results Table 4. Regression Results Model Unstandardized Coefficients Standardized Coefficients T Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF (Constant) LNICP LBRPROD OPENESS INF a. Dependent Variable: FDI Unstandardized coefficient equation FDI = (Ln ICP) (LBRPROD) (OPN) (INF) + ε Standardized coefficient equation FDI = (Ln ICP) (LBRPROD) (OPN) (INF) + ε Referring to both of above equation, the sign of coefficient indicates the association of macroeconomic determinants towards FDI. In this paper, we will refer to the standardized coefficient equation as a mode of discussion because all variables have been converted into common metric, known as standard deviation (z- Score) units, hence, the β coefficients will be more meaningful in compared with magnitude. Basically, from the equation, it can be seen that income per capita (ICP) and openness (OPN) seem to be negatively related with FDI where 1 unit increase in ICP and OPN will lead to decrease in FDI by and respectively. On the other hand labor productivity (LBRPROD) and inflation (INF) has a positive relationship with the FDI where, 1 unit increase in LBRPROD and INF will subsequently increase the FDI by and respectively. In order to identify multicollinearity issues, we have employed two statistical measures, normally used as diagnostics to assess the multicolinearity problem, namely (i) Tolerance, (ii) Variance Inflation Factor and the Pearson correlation. The benchmark for tolerance should be greater than 0.1. As for variance inflation factor (VIF) calculated as 1/Tolerance must be less than 5, otherwise, it is an indication that the data suffers from serious multi-co- linearity issue. In addition, the Pearson analysis (See Table 5) also shows there is no presence of strong correlation among the variables (rule of thumb, < 0.7), being so data used in this study is fit for research purpose. Table 5. Pearson Correlation FDI lnicp LBRPROD OPN INF FDI ** ** lnicp LBRPROD OPN ONF 1 **. Correlation is significant at the 0.01 level (2-tailed). 131 P a g e

8 Table 6. Bi-directional Relationship between Labor Productivity and FDI Unstandardized Coefficients Standardized Model Coefficients T Sig. B Std. Error Beta (Constant) LBRPROD Unstandardized coefficient equation LBRPROD = FDI + ε Standardized coefficient equation LBRPROD = FDI + ε Table 7. Bi-directional Relationship between Income Per Capita/ GDP Per Capita and FDI Standardized Unstandardized Coefficients Model Coefficients T Sig. B Std. Error Beta (Constant) LNICP Unstandardized coefficient equation LNICP = FDI + ε Standardized coefficient equation LNICP = FDI + ε 5. Discussions of Results 5.1 Total labor productivity and FDI i. The results from the analysis above yield a significant and positive relationship between FDI and labor productivity. Hence, foreign direct investors will more likely invest in a country where the labor productivity is high. This finding is consistent with past literature, which confirms that high labor productivity is desired and it can contribute towards lower cost and high profits, ceteris paribus. ii. Testing for the reverse relationship, with labor productivity as the dependent and FDI as the independent, the results also suggests a positive and significant relationship between these two variables, suggesting that, the higher the FDI, the higher the labor productivity. This implies that FDI actually enhances labor productivity and this is evidenced in past literature where the benefits of FDI in enhancing knowledge and technology transfer takes place. However, the absorption level of knowledge and technology transfer will depend on the quality of the labor force which can be upgraded through the government s efforts to enhance education and skill levels for its citizens. 5.2 Income per capita and FDI The relationship between these variable is negative, with FDI as the dependent and income per capita as the independent variable, implying that FDI does not depend on the level of per capita, which is often used as a proxy for market size. This finding is not consistent with most previous researches which supports the hypothesis that FDI is dependent on income per capita, where a large market size is a motivation for FDI inflows. 132 P a g e

9 In our case, a high income per capita having a negative, albeit a weak relationship with FDI could imply that the average income level of the country, being high would mean a relatively higher labor cost and this could be the deterrent for FDI inflow. The reverse causality between Income per capita and FDI, where income per capita is now the dependent and FDI the independent also indicates a weak and negative relationship, which suggests that the impact of FDI on income per capita is weak and negative, implying that FDI does not significantly improve per capita income, which again is inconsistent with past researches can be explained by assuming that the leakages in the system are likely to be high, with high taxation on FDI corporations and corruptive practices. Also to reiterate from past findings, FDI can only contribute to the host country s income per capita if the human capital is strong and relevant for the optimal absorption of technology transfer to take effect, Wang and Blomstrom,(1980) 5.3 Inflation and FDI Inflation as a determinant of FDI is signified by a strong and positive relationship, which implies that, ceteris paribus, a high inflation will encourage more FDI inflows. This finding contradicts many previous findings, which suggests otherwise. In this case, hitching on the assumption of the Law of Supply to support this finding, it would mean a general increase in price levels, ceteris paribus, would stimulate more supply, thus encourage more participation into the economy. As it is stated in economic theory, that economic upswings accompanied by high business activity would trigger inflationary pressures but being in an optimistic market condition would boost investment both domestic and foreign. Caroline Kariuki (2015), also finds this exception phenomenon of a positive FDI inflation relationship and explains it with higher stock prices which are a motivation for FDIs. 5.4 Openness and FDI. Most previous literature supports the view that openness will encourage more FDI inflows. Openness would imply fewer restrictions on trade, hence, the volumes of imports and exports would be high and this would attract foreign business. However, in our findings openness tends to be negatively related with FDI. This could be likely due to the fact that the FDI production is largely consumed domestically and not exported, thereby does reflect in the Openness which is computed as the sum of exports and imports per GDP. To reiterate this relationship which means that high degree of openness would shun FDI can be that a high degree of openness could enhance FDI inflows from many countries, thus creating a competitive environment and creating a less profitable outcome for prospective foreign investors. Jordaan, (2004), claims that the degree of openness and FDI would have different impact depending on the type of FDI. He claims that for market-seeking FDI, the lesser the openness, the stronger the FDI inflow, suggesting a negative relationship between the two variables. 6. Policy considerations and recommendations for further studies From the findings and discussions above, it is, therefore, imperative for the policy makers to pay much attention on human capital development by focusing on education and industrial training for its workforce to be more compatible to changing industry demands. 133 P a g e

10 Since our finding suggests that high per capita income is deterrent for FDI, then the government should not be all out to pursue the high-income status as this will drive away investors in the face of higher labor cost.as Malaysia is still dependent on FDI-led growth such grandiose goals should be shelved for the time being. There must be a certain degree of closeness as a too open policy may deter the more reliable and ethical investors and attract socially undesirable investment such as those which pose environmental hazards. A high degree of openness also creates a competitive environment for FDI, which may end up with room for corruptive practices. Inflation targeting measures must not be too drastic as it is seen here that inflation promotes a positive boost to business confidence but care must be given to ensure inflation is too overwhelming for the citizens well-being and a negative impact on business costs. This study is not perfect in itself and further studies should be carried out with inclusion of more macroeconomic variables and other non-economic variables as well as in recent times, institutional issues tend to a major challenge in many developing and developed country alike and it would be important to focus on such issues to ensure a stable and certain environment to attract FDI to Malaysia References Blomstrom, M., & Wang, J. (1992). Foreign Investment and Technology Transfer: A Simple Model. European Economic Review, 36, Blomstrom, M., & Kokko, A. (1996). Multinational Corporations and Spillovers. Journal of Economic Surveys J Economic Surveys, Borensztein, E., Gregorio, J., & Lee, J. (1998). How Does Foreign Direct Investment Affect Economic Growth? Journal of International Economics, 45. Demirhan, E., & Masca, M. (2008). Determinants of foreign direct investment flows to developing countries: A cross-sectional analysis. PRAGUE ECONOMIC PAPERS, Findlay, R. (1992). Relative Backwardness, Direct Foreign Investment, and the Transfer of Technology: A Simple Dynamic Model. The Quarterly Journal of Economics, 1-1. Kariuki, C. (2015). The Determinants of Foreign Direct Investment in the African Union. JOEBM Journal of Economics, Business and Management, 3(3), Loungani, P., & Razin, A. (2007). How beneficial is foreign direct investment for developing countries? (2nd ed., Vol. 38, pp. 6-10). Princeton University Press. Mottaleb, K., & Kalirajan, K. (2010). Determinants of Foreign Direct Investment in Developing Countries: A Comparative Analysis. Margin: The Journal of Applied Economic Research, Oladipo, S. (2013). Macroeconomic Determinant of Foreign Direct Investment in Nigeria ( ): A GMM Approach. Journal of Emerging Issues in Economics, Finance and Banking (JEIEFB), 2(4). Rivera-Batiz, L., & Romer, P. (1991). International Trade with Endogenous Technological Change. NBER Working Papers Yu, J., & Walsh, J. (2010). Determinants of Foreign Direct Investment: A Sectoral and Institutional Approach. IMF Working Papers, P a g e