International Journal of IT-based Management for Smart Business Vol. 3, No. 1 (2016) pp.9-14 http://dx.doi.org/10.21742/ijitmsb.2016.3.02 The Determinants of Foreign Direct Investment in Mongolian Economic Growth Erdenebat Mungunzul 1 and Taikoo Chang 21 1 Dept of Economics, Graduate School, Daegu University 201 Daegudaero, Chinryangup, Kyungsansi, Kyungbuk, 38453, Korea 2 Dept of Economics, Daegu University 201 Daegudaero, Chinryangup, Kyungsansi, Kyungbuk, 38453, Korea Corresponding Author: tkchang1@hanmail.net Abstract This study tried to estimate the determinants attracting FDI inflow to Mongolia by two ways. The first is single country (Mongolia) data using the determinants attracting FDI inflow to Mongolia from the period 1995-2014. The second model is about determinants attracting FDI by top investment countries using panel data, using random and fixed effects model from the period 2005-2013. The most investment countries are Netherlands, China, Luxemburg, Virgin Islands (UK), Singapore, Canada, South Korea, USA, Russia, Australia, Hong Kong and Japan. These countries have been the predominant investor to Mongolia during the last decades. China is major investment country and almost 90% exports of Mongolia go to China including mining industrial products such as coal, copper, gold, zinc etc. Mongolia and China are neighbor countries and has distance advantage. The distance between countries have significant role to define FDI inflows in Mongolia. But the results showed that the distance between countries has positive and insignificant relationship. It was revealed that the partner country in too far or too short has no attention and investment role to FDI in Mongolia. Keywords: Foreign direct investment (FDI), Random Effect Model, Fixed Effect Model, Panel data, mining sector. 1. Introduction Foreign direct investment (FDI) is usually viewed as a channel through which technology is able to spread from developed countries to developing countries. Although the evidence on the relationship between FDI and economic growth is ambiguous, several studies argue that the host country s absorptive capacity plays an important role in explaining FDI. For instance, Blomstrom et al. (1994) state that FDI is positive and significant only for higher income countries and that has no impact in lower income countries. Borensztein et al. (1998) point out that the contribution of FDI to economic growth is enhanced by its interaction with the level of human capital in the host country. Balasubramanyam et al. (1996) argue that FDI plays different role in the growth process due to the differing trade policy regimes. Although there are different types of international capital flows, FDI is the subject of many researches. FDI is an investment made abroad either by establishing a completely new enterprise in a host Article history: Received (August 16, 2016), Review Result (October 23, 2016), Accepted (November 10, 2016) Print ISSN: 2205-8362, eissn: 2207-5348 IJITMSB Copyright c 2017 GV School Publication
The Determinants of Foreign Direct Investment in Mongolian Economic Growth country or by acquiring enough shares to gain full managerial control in an existing foreign enterprise. 2. Methodology and data analysis 2.1. Model Specification 2.1.1. Factors affecting the ability to attract FDI in Mongolia Uusing by log-linear Regression: The basis of equation: Y(FDI it )= β0+ β1(gdp it ) + β2(exr it ) + β3(exp it )+ β4(inf it )+ β5(infra it )+ β6(openess it )+ β7(politic it )+ ε it where FDI it is the Foreign direct investment in Mongolia in current US$ at time t. GDP it is the GDP in current US$ for Mongolia at time t and is the measure of market size. EXR it is the real effective exchange rate of Mongolia at time t and is the measure of currency value. Openess it is the trade openness of Mongolia at time t and is computed as ratio of imports plus export of goods and services divided by GDP. INFRA it is the measure of infrastructure development index of Mongolia. EXP it is the measure of exports of goods and services as a percentage by GDP of Mongolia. INF it is measured by the consumer price index reflecting the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. POLITIC it is the index of Mongolian political and economic risk index measured by world bank. (-2.5 weak, 2.5 strong). ε it is the error term over the time t. 2.1.2. Panel Data Analysis of FDI Inflows from the Selected Developed Countries to Mongolia by Using Fixed Effects and Random Effects Model: This section examines the factors determining FDI inflows from the selected developed countries to Mongolia using annual dataset from the period 2005 to 2013 and consisting of 12 countries data. The study used cross countries panel data and the selected variables are: market size of home and host countries, trade openness of host country, distance of home and host countries. The basis of following equation: Y(FDI ijt )= β0+ β1(gdp it ) + β2(gdp jt ) + β3(dist ijt )+ β4(openness jt ) +timedummies+ε ijt where FDI ijt is foreign direct investment in current US$ of country i at time t GDP it is GDP in current US$ for country i at time t and is the measure of market size GDP jt is GDP in current US$ for Mongolia at time t and is the measure of market size DIST ijt is distance between Mongolia and country i. Openness jt is the trade openness of Mongolia at time t and is computed as ratio of imports plus export of goods and services divided by GDP. Timedummies is the dummy variables by year. ε ijt is the error term over the time t. 10 Erdenebat Mungunzul and Taikoo Chang
International Journal of IT-based Management for Smart Business Vol. 3, No. 1 (2016) pp.9-14 2.2. Empirical results 2.2.1. Factors Affecting the Ability to Attract FDI in Mongolia Using by Log-linear Regression: The data obtained from years to 1995-2014 were calculated by using SPSS software and the results are as follows: Table 1. Regression results of factors affecting FDI inflows in Mongolia Variables Value Standard error t Pr> t Lower bound (95%) Upper bound (95%) LogEXP 0.205 0.111 1.848 0.087-0.035 0.444 LogINF 0.054 0.104 0.515 0.615-0.171 0.279 LogGDP 0.747 0.197 8.792** 0.002 0.322 1.173 LogINFRA 0.148 0.192 0.767 0.457-0.268 0.563 LogPOLITIC -0.043 0.112-0.382 0.709-0.285 0.200 LogTRADE 0.069 0.106 0.649 0.528-0.160 0.297 R square : 0.882 Adjusted R square : 0.828 DW stat. : 1.56 The R-square emerges to be of high magnitude demonstrating effectiveness of the regression and variables used. The adjusted R-square of the magnitude 0.828 reflects the strength of the estimation. Table 1 shows that the estimated coefficient of GDP to the FDI is statistically significant in log-linear regression. Its sign is positive and consistent with the expectation. 2.2.2. Panel Data of FDI Inflows from the Selected Developed Countries to Mongolia by Using Fixed Effects and Random Effects Model: The data analysis result for regression is shown in table 2. The result shows the independent variable FDI is highly related with home country s GDP. The existence of high correlation among the independent variables will lead to the problem of multi-collinearity in the estimation. It is because of the panel data estimation which takes the collinearity problems. The results of coefficients sign and their significance levels of fixed and random effects are almost similar. Both random effects and fixed effects model confirm the significance of home country s market size (GDP) at 5 percent level of significance. When p-value=0.0495(fixed model) and p-value=0.0503(random effects model) are run though significance tests, it shows a positive and significant relationship. The result shows the home country s GDP is positive related and significant with FDI. The trade openness of the home country is positively related but insignificant with FDI. The distance is also positively and insignificant with FDI. The time dummies variables(dummy_t6-dummy_t8) are highly related at 5% significant level with dependent variable in fixed or random effects model. The adjusted R-square of the magnitudes are 0.80 and 0.89 reflects the strength of the estimation in fixed effects and random effects model. The aim of this study is also to choose the appropriate panel data model either fixed effects model or random effects model. To decide between fixed or Copyright c 2016 GV School Publication 11
The Determinants of Foreign Direct Investment in Mongolian Economic Growth random effects, Hausman test was used, where the null hypothesis is that the preferred model is random effects compared to the alternative the fixed effects. The Hausman test p-value showed 0.0492628, showing the fixed effects model is little bit more efficient than random effects model. Table 2. Panel data estimated by fixed and random effects model Variables Fixed effect Model Random Effect Model Coefficient t-value p-value Coefficient t-value p-value Const 39.0355 1.959* 0.0495* 29.5575 1.985(*) 0.0503(*) LogGDP jt 2.89103 2.060* 0.0425* 2.60739 1.949(*) 0.0545(*) LogGDP it 0.26296 0.1906 0.893 0.840454 0.7985 0.4267 LogDIST ijt 0.084 0.173 0.863 0.075266 0.1596 0.8735 LogTOPEN jt 1.596 0.3003 0.7647 0.191797 0.2293 0.8569 Dumm_t1 2.47750 1.174 0.2439 0.2439 0.1808 0.884 Dumm_t2 2.28562 1.332 0.1863 0.1863 0.1851 0.873 Dumm_t3 1.74151 1.332 0.2291 0.446 0.3273 0.4267 Dumm_t4 0.909515 1.211 0.4243 0.910584 1.136 0.2592 Dumm_t5 1.09960 0.8028 0.4336 0.879927 1.294 0.1991 Dumm_t6 0.436277 0.4610 0.6460 2.13260 2.247 0.0270* Dumm_t7 2.44306 3.159** 0.0022** 3.88586 3.095** 0.0026** Dumm_t8 2.09024 2.695** 0.0085** 3.45333 2.518* 0.0136* Dumm_t9 1.832 1.135 0.254 1.42815 1.125 0.2638 Adj. R square 0.80 0.89 No.of obs. 108 108 Hausman test-null hypothesis: Chi-square(9) = 0.92297 with p-value = 0.0492628 Note : (1) The coefficient of the variable is shown first, followed by the t-statistic in parentheses. (2) *, ** indicate significance level of 5 and1 percent, respectively. (*) when t-value=1.949 is almost equal to 2 and p-value-0.0545 to 0.05(table 2: column 6 and 7). 3. Summary and conclusion During last 20 years, Mongolian economy transitioned from central planned to free market economy. Through Mongolia opened to FDI, foreign investors have represented a major force in the process of economic transformation. When FDI inflows to Mongolia highly increased during 2011-2013, Mongolian endogenous economic growth showed that Mongolia was one of the fastest developing countries in the world. The rapid development of mining sector and the strong increase in output, created more jobs, offered higher-average wages, generated high level of exports, transferred knowledge and skill into Mongolia, accounted for a significant portion of tax revenue. The both study results showed the FDI is highly related to the Mongolia s economic 12 Erdenebat Mungunzul and Taikoo Chang
International Journal of IT-based Management for Smart Business Vol. 3, No. 1 (2016) pp.9-14 growth (GDP). The first model results showed FDI inflow is highly related with country s GDP in significant level 1%, if other variables are constant. The export is insignificant and positive with FDI. Politically stability is negatively insignificant. Trade openness, infrastructure and inflation are positively and insignificant with dependent variable. The second study results showed that FDI is highly related with home country s(mongolia) economic growth at 5% significant level. The result showed FDI inflow is positively significant with home country s market size. The 9 time dummies, 2005 to 2013, were used in the model. The result showed that 2010, 2011 and 2012 year s dummy variables are positively significant at 5% level with dependent variable in random and fiexed effects model. Mongolian government needs to improve the country s infrastructure. The effects of FDI in mining projects required highly developed infrastrustcure. The infrastructure level of Mongolia is below the rank 112 (of 148 countries). This is a disadvantage of Mongolia attracting FDI. The main task of Mongolian government now is to consider the investment law. The government needs to improve the investment environment and standard of services, the legal framework and keep the economic and political stability. References [1] Amrita Batchuluun, An analysis of Mining Sector Economics in Mongolia, Vol. 4, (2010). [2] A.M. Senkuku and B. Gharleghi, Factors Influencing Foreign Direct Investment Inflow in Tanzania, (2015). [3] J.H. Dunning, The Eclectic Paradigm of International Production: A restatement and some possible extensions, Journal of International Business Studies issue, Vol. 19, (1988). [4] R. Grayson, and W. Murray, Overview of Artisanal Mining in Mongolia, A Report prepared for the World Bank, (2003). [5] C.P. Kindleberger, American Business Abroad, The International Executive, Vol. 11, pp. 11-12, (1969). [6] Mongolia Mining Corporation, Interim Report, (2015). [7] Mongolian National Chamber of Commerce and Industry, Business and Investment Guide,(2014). [8] OECD, Benchmark Definition of Foreign Direct Investment, (2008). [9] OECD, The Economics of International Investment Incentives, (2002). [10] UNCTAD, World Investment Report, New York: UN, (2015). [11] US Department of State, Mongolia Investment Climate Statement, (2015). [12] World Bank, Mongolia Mining Sector Managing the Future, (2003). Copyright c 2016 GV School Publication 13
The Determinants of Foreign Direct Investment in Mongolian Economic Growth 14 Erdenebat Mungunzul and Taikoo Chang