THE IMPACT OF SIX PROVINCES OF THE SOUTHEAST REGION TO FDI IN VIET NAM IN PERIOD 20092013

Foreign Direct Investment (FDI) is one of the most important parts of the economic development strategy in Viet Nam, also the practice of attracting FDI into the country has received more and more attention from the Government. In our country, The South East is a region which has kept its leading position in attracting FDI for many years, however, it has 6 provinces with different factors and there has been a significant disparity between provinces in the region. Therefore, this study was carried out to find the impact of Southeastern provinces to attracting FDI in Viet Nam, and also to find the shift of FDI between the provinces in recent years (period 20092013)

THE MINISTRY OF EDUCATION AND TRAING FOREIGN TRADE UNVERSITY Department: external economic -oOo - THE IMPACT OF SIX PROVINCES OF THE SOUTHEAST REGION TO FDI IN VIET NAM IN PERIOD 2009-2013 Teacher: Tran Van Hoang Class: K51C Group: Ho Chi Minh city, March, 2014 MEMBER LIST OF THE 5th GROUP NGUYỄN THỊ NGỌC BÌNH MSSV: 1201016043 PHAN THỊ DUNG MSSV: 1201016096 QUẾ THỊ THU HẰNG MSSV: 1201016144 NGUYỄN THỊ MAI KA MSSV:1201016206 PHAN THANH PHƯƠNG LAN MSSV: 1201016233 Abstract Foreign Direct Investment (FDI) is one of the most important parts of the economic development strategy in Viet Nam, also the practice of attracting FDI into the country has received more and more attention from the Government In our country, The South East is a region which has kept its leading position in attracting FDI for many years, however, it has provinces with different factors and there has been a significant disparity between provinces in the region Therefore, this study was carried out to find the impact of Southeastern provinces to attracting FDI in Viet Nam, and also to find the shift of FDI between the provinces in recent years (period 2009-2013) The study uses one-way Analysis of Variance theory (one-way ANOVA) and Honestly Significant Differences method (HSD) or Tukey method with data collected from Foreign Investment Agency, Ministry of Planning and Investment The results revealed that the amount of FDI into each province is different from the others in the period from 2009-2013 Key words: ANOVA, FDI, Tukey, Vietnam, Southeast Vietnam Introduction FDI is an area which received much attention and interest from both domestic and foreign researchers In Viet Nam, researches mainly focuses on analyzing the reality of attracting FDI and its impact on the socio-economic development Recently there have been a number of studies identifying factors having effects on attracting FDI inflows into Viet Nam include: “impact of provincial institutions” (Tran Thi Giang Quynh, 2011), “impact of corruption” (Le Thi Hai Yen, 2011), “impact of economic freedom” (Doan Ngoc Dieu Hang, 2012),…However, there have been few studies on the impact of specific localities to FDI into a specific region This experiment use one-way ANOVA method to analyze the impact of Southeastern provinces to attracting FDI into the South East region of Viet Nam, they include: Ho Chi Minh City, Vung Tau, Dong Nai, Binh Duong, Binh Phuoc and Tay Ninh This research focuses on solving main problems: (1) Find the differences between the provinces in attracting FDI into the South East Region of Viet Nam; (2) Find the tendency of FDI shift in recent years Theory and research methodology 2.1 Theory: ANOVA stands analysis of variance - variance analysis Analysis of variance is a collection of statistical models used to analyze the differences between group means and their associated procedures In ANOVA setting, variance in a particular variable is partitioned into components due to different sources of variation In its simplest form, ANOVA provides a statistical test and generalizes T-Test to more than two groups Therefore, ANOVA is often used in comparing three or more means for statistical significance A common use of the method is the analysis of experimental data or the development of models The simplest experiment suitable for ANOVA analysis is the completely randomized experiment with a single factor If experiments are happened with too many factors, it is very difficult to specific the result and the experiment will be more complex It is named ANOVA for a single factor or one-way ANOVA ANOVA for a single factor is used when there is only considered factor to define its influences on the other factors The considered factor is used in distributing observe into many groups When we conduct a T-Test, we usually make Type error with 5% If we run some T-Test on data, the chance to make errors will be increased These are unacceptable errors because it influences on the experiment results Therefore, ANOVA controls for these errors and remain Type error at 5% with the advantage is no limited by the number of trials Supposing that there are k groups n1, n2,…, nk They can have difference sizes µ1, µ2,…, µk are the means of groups Group Group … Group k X11 X21 … Xk1 X12 X22 … Xk2 … … … … X1n1 X2n2 … Xknk Xij is the 𝑗𝑡ℎ observation of group i Hypothesis H0:µ1=µ2=…=µk H1:µ1≠µ2≠…≠µk Step 1: Calculating mean 𝑥̅𝑖 for each group 𝑥̅𝑖 = Calculating mean 𝑥̅ for many groups ∑𝑛 𝑗=1 𝑥𝑖𝑗 𝑥̅ = 𝑛1 𝑛 ∑𝑘 𝑖=1 ∑𝑗=1 𝑥𝑖𝑗 𝑛 Step 2: Finding square difference in sum Square difference within group SSW=SS1+SS2+…+SSk With 𝑛 SS1=∑𝑗=1 (𝑥1𝑗 − 𝑥̅1 )2 𝑛 SS2=∑𝑗=1 (𝑥2𝑗 − ̅̅̅) 𝑥2 Square difference between: Square difference in sum: SSG=∑𝑘𝑖=1 𝑛𝑖 (𝑥̅𝑖 − 𝑥̅ )2 SST=SSW+SSG Step 3: Counting variances Variances within group MSW= Variances between groups MSG= Step 4: Finding F ratio Crucial rule: Reject H0 when F>Fk-1, n-k,α 𝑆𝑆𝑊 𝑛−𝑘 𝑆𝑆𝐺 𝑘−1 ANOVA Table Difference Square differences in sum Degree of Variance freedom (df) Testing value 𝑆𝑆𝐺 Between groups SSG k-1 MSG= Within group SSW n-k MSW= Total SST n-1 𝑘−1 F= 𝑀𝑆𝐺 𝑀𝑆𝑊 𝑆𝑆𝑊 𝑘−1 Tukey’s test also known as HSD Tukey – Honestly Significant Differences, is a single test multiple comparison procedure and statistical test Named after John Tukey, it compares all possible pairs of means The confidence coefficient for the set, when all sample sizes are equal, is exactly − α For unequal sample sizes, the confidence coefficient is greater than − α In other words, the Tukey method is conservative when there are unequal sample sizes Before running an experiment, we must design the experiment including the necessary test to analysis data In some cases, Tukey's HSD test comes in handy, allowing the researcher to further research the matter even after data has been collected and analysis run HSD Tukey is a post-hoc test, meaning that it is performed after an analysis of variance test The purpose is to define many differences in group Meanwhile, ANOVA only detect there are differences between groups, but don’t know ecxactly which groups and which groups among the sample in specific have significant differences Therefore, Tukey’s test compares mean of each population pair Suppose H0: µ1=µ2 H0: µ2=µ3 H0: µ3=µ1 H1: µ1≠µ2 H1: µ2≠µ3 H1: µ3≠µ1 With k population, the mean pair need comparing is: 𝐶𝑘2 = Tukey standard: 𝑘! 𝑘(𝑘 − 1) = 2! (𝑘 − 2) 𝑇 = 𝑞𝛼,𝑘,𝑛−𝑘 √ 𝑀𝑆𝑊 𝑛𝑖 With q is value in distributing table MSW is variance within group k and n-k are degrees of freedom Testing value D1= |𝑥̅1 - ̅̅̅| 𝑥2 D2= |𝑥 ̅̅̅2 - ̅̅̅| 𝑥3 Crucial rule: Reject H0 if D>T 2.2 Research methodology: To study the impact of the regional capital direct investment FDI into Vietnam, we mainly use quantitative research methods Besides, combined with the methods of analysis, synthesis methods such as ANOVA analysis of variance a variable, a method is used quite common in studies in Vietnam and worldwide Quantitative research method is the collection and analysis of information on the basis of data obtained from the market The purpose of the study is to make quantitative conclusions about market research through the use of statistical methods for data processing and data Content analysis of quantitative data is collected from the market, the data processing through the conventional statistical methods, simulation or run the data processing software and provides the main conclusions determined Research on the impact of the regional capital direct investment FDI is proposed as follows: FDI = f (Market, labor, infrastructure, government policy, the cumulative impact) In particular, each element team uses a number of indicators to represent Specifically: Market - Factor: The average population of the area and the population growth rate Population growth areas or high bronze promises to attract more FDI Also, instead of using GDP, the study used the average monthly income of workers by local government management, representing purchasing power market, with expectations high monthly income will be the potential for health high consumption, thus stimulating FDI inflows into the region - Labor factor: Which areas have abundant labor resources, the region has the potential to generate enough labor to meet the manufacturing process - Infrastructure factors: Technical infrastructure: The quality of the technical infrastructure and the level of industrialization influence It’s very important to the inflow of foreign investment in a country or a locality A system of technical infrastructure complete (including the system of roads, rail, aviation, power supply network, water, telecommunications and other utility services), is wishes to all foreign investors In the 80s and 90s, to attract investment, many countries have established export processing zones (EPZ) Shenzhen Export Processing Zone of China is a successful example of this model However, not all countries achieved similar results Infrastructure modern techniques within EPZs are important factors but the human resources to serve the export processing zones, geographical location and other policy mechanisms also significantly affected the success of the export processing zones Speaking of technical infrastructure not only comes to roads , bridges, warehouses, yards but also not to mention other support services such as banking, auditing firms, investment problems, Lack of support needed by these activities, the investment environment will be seriously affected In addition, the performance of the local industrial base, the presence of industry support, the existence of a reliable partner for foreign companies and joint venture may also be important requirements need to be considered Social Infrastructure: In addition to the technical infrastructure, attract investment environment is influenced by fairly large social infrastructure Social infrastructure including health systems and health care for the people, the education system and training, recreation and other services In addition, the social value, customs, religion, and culture which constitute the general picture of the social infrastructure of a country or a locality Research by UNDP / World Bank showed tendency to invest in Southeast Asia has many positive changes thanks to the “discipline of the labor force”, “as well as” political stability and economic “in many countries in the region” - A key element of government policy: Foreign investment flows into developing countries is not only determined by economic factors, but also be governed by political factors The stability of the macro economy, combined with political stability is considered very important Some recent research suggests very tight relationship between the stability diagram Factors affecting the choice of investment location political attracting foreign investment Policy of openness and consistency of government also play a very important role Using a dummy variable number of key economic areas industrial zones 2, saying that the macroeconomic policies are aimed towards facilitating investors PCI components are also used Because of differences in measurement methods in 2007 and 2009 PCI team should not use the composite index, instead we use the PCI training employees, an index has been Malesky (2008 ) documents Union has a strong impact on the rate of realized capital registered capital and new capital in 2006 Since the object of this report is for the people, we not use synthetic PAPI, instead, we I only use the index to provide public services, saying it would ensure better measure the impact of the public sector This index includes private security, public health, education and basic infrastructure Our hypothesis is that the only place this number as high investment environment proved more favorable, thereby enhancing FDI Regarding to competitiveness index provincial, we get index Training employees to represent the support of local government, including index components as the number of vocational training centers under local management reason, the job placement center, the quality of education provided by the provinces Also the land is considered a key factor to show the political will to non-state enterprises, we use variables for the evaluation of business risks recovered land (1 is highest, lowest 5), this variable proved higher business confidence in the political system and expect long working time, stable Variables taken from the PCI components, access to land - Factor accumulation: the team now number over 1000 people, the average size of the labor, capital, asset values and financial investment and average turnover of businesses in the area Two hypotheses that we ask is, some businesses previously large scale, high value assets, revenue or good will attract more FDI, or will be less attracted by psychological fears competition We favor the hypothesis that early because Vietnam emerging markets, so will a lot of potential for FDI to take advantage and accumulate The data were taken from the GSO, Department of Foreign Investment Promotion, Department of Industry and Trade of Vietnam, Research and Development Center and community support Because changes in administrative decentralization ( of Can Tho, Lai Chau, Dak Lak and Ha Noi ), we only included data from 57 full provincial boundaries throughout the country have not changed since the 2001-2010 figures obtained year later The researchers use OLS estimation method to test the model To take a closer look changes after 2007, we conducted split into two data sets and run independently period 2001 to 2007 and from 2008 to 2010 to see a change in investor psychology between adjacent stages but despite seeing too many drastic changes Next, go deep study analyzed the impact of two factors that are basic education and political conditions for FDI after the period Results and discussion REGISTERED CAPITAL OF FDI INTO THE SOUTH EAST REGION OF VIET NAM IN PERIOD 2009-2013 (unit: Million Dollars) Year Ho Chi Minh Vung Tau Dong Nai Binh Duong Binh Phuoc Tay Ninh 2009 984.4 2857.5 2299.9 2152.8 100.5 94.4 2010 1895.3 2400.6 378.7 362.3 161.7 5.5 2011 2755.71 880.82 215.82 464.55 32.32 480.4 2012 468.71 453.33 618.85 1631.4 70.19 124.58 2013 948.98 116.32 745.09 713.98 74.49 169.3 Table 1: SUMMARY Groups Count Sum Average Variance TP Hồ Chí Minh 7053.1 1410.62 831537.8091 Vũng Tàu 6708.57 1341.714 1480521.6562 Đồng Nai 4258.36 851.672 697735.1063 Bình Dương 5325.03 1065.006 620415.0832 Bình Phước 439.2 87.84 2296.9477 Tây Ninh 874.18 174.836 32767.5755 ANOVA PSource of Variation SS df MS F Between Groups 8171603.1104 1634320.6221 2.6754 Within Groups 14661096.7116 24 Total 22832699.8221 29 value F crit 0.0465 2.6207 610879.0297 Level of significance 0.05 Table shows the impact of six provinces in the Southeast region of Viet Nam to attract FDI in Vietnam in period 2009 – 2013 by using ANOVA data F ratio is the calculated ratio between MSG and MSW is used MSG is the total differences of edge of FDI in period 2009 - 2013 between the provinces in the region MSW is the total differences of edge of FDI within the provinces through the years With F=2.6754 and 𝐹𝑘−1,𝑛−𝑘, = 2.6207, so F >𝐹𝑘−1,𝑛−𝑘, It means that the impact of each province to attract FDI in Vietnam over the years from 2009 to 2013 is different And the p-value = 0.0465 < 0.05 It is found that the H0 assumption is rejected In other words, the statistical significance level suggests that the diffirent impact of province in South East area to attract FDI in Vietnam over the years 2009 - 2013 is reliable However, we are not clear that there is a difference between the province and another one through the year To see more clearly how the different levels are, we used Tukey analysis Table 2: Tukey table Absolute Std Error Critical Comparison Difference of Difference Range Results Group to Group 68.906 349.5365588 1527.5 Means are not different Group to Group 558.948 349.5365588 1527.5 Means are not different Group to Group 345.614 349.5365588 1527.5 Means are not different Group to Group 1322.78 349.5365588 1527.5 Means are not different Group to Group 1235.784 349.5365588 1527.5 Means are not different Group to Group 490.042 349.5365588 1527.5 Means are not different Group to Group 276.708 349.5365588 1527.5 Means are not different Group to Group 1253.874 349.5365588 1527.5 Means are not different Group to Group 1166.878 349.5365588 1527.5 Means are not different Group to Group 213.334 349.5365588 1527.5 Means are not different Group to Group 763.832 349.5365588 1527.5 Means are not different Group to Group 676.836 349.5365588 1527.5 Means are not different Group to Group 977.166 349.5365588 1527.5 Means are not different Group to Group 890.17 349.5365588 1527.5 Means are not different Group to Group 86.996 349.5365588 1527.5 Means are not different Table shows that we use Tukey analysis tool to find out the difference among groups or between the provinces in the South East region to attract FDI period 20092013 We compare 15 pairs with the average number of pairs is calculated according to the formula Basing on the table, we can see that: 𝐷𝑖 < 𝑇 𝐷𝑖 is the absolute deviations of the average sample pairs T is the Tukey standard With Q statistic = 4.37 and a significance level 95%, results in T= 1527.5 > Di Thus we can conclude that the registered capital of FDI into provinces in the Southeast in Viet Nam period 2009 - 2013 is different, in other words, impact of each province to attract FDI in Vietnam over the years from 2009 to 2013 is different But we can’t conclude that the difference between the provinces is smaller or greater This is recognized that we can’t compare the different levels between provinces in spite of the different amount FDI into the provinces of Southeast in period 2009-2013 Because the annual growth rate is not uniform between the provinces, specifically in Vung Tau and Dong Nai; Vung Tau Province is inherently attracted to a large of FDI In period 2009-2011 its FDI increased dramatically, but declining later And FDI into Dong Nai province fluctuated wildly However, we can see the disparities of FDI registered capital between groups or between provinces in the region And FDI into Ho Chi Minh province is the best in the Southeast of Viet Nam in period 2009-2013 By results of research, we can conclude that the impact of the provinces in the South East region to attract FDI in Vietnam in the period 2009-2013 is different And due to the economic development in the provinces is not uniform, we can’t compare the different degree of influence between provinces to attract FDI in Vietnam for the period 2009-2013 Because the research is still limited, we hope we can made a complete research in the future Maybe it will be clearer and fuller Conclusion This study analyzed the impact of six provinces to attracting FDI into the South East Region of Viet Nam in period 2009-2013 using data of Foreign Investment Agency, Ministry of Planning and Investment The results show that different provinces attract different amount of FDI, and from 2009 to 2013 FDI inflows tend to shift from developed city like Ho Chi Minh City and Vung Tau to growing provinces like Binh Duong and Dong Nai Therefore there are several policies suggested as follow: (1) Discover potential and step up attracting FDI to provinces which still have limited development level comparing with the others such as Binh Phuoc, Tay Ninh, and also further develop provinces with strong growth, target to balance the development level of provinces in the region (2) Localities in all the region need to coordinate preparing strategy to attract and use FDI effectively, associated with International economic integration of Viet Nam; (3) Government's Investment promotion Agencies need to incorporate with local organizations of the region to unite the practice of attracting FDI in the region The study’s results can be of interest to domestic and foreign investors, managers to have a more comprehensive view of the region’s attracting FDI situation, then they can have reasonable decisions to maximize the potential of the region Reference Damon Verial (2001), “What Is the Tukey HSD Test?”, http://classroom.synonym.com/tukey-hsd-test-2611.html, 27/02/2014 DSc Nguyen Dinh Hien (2013), “Links area - the optimal solution to attract FDI”, http://kinhtevadubao.com.vn/xuc-tien-dau-tu/lien-ket-vung-giai-phap-toi-uu-de-thu-hutfdi-777.html, 29/03/2013 General statistics office (2013), “investment and construction”, statistical yearbook of Viet Nam 2012, 159 – 192 General statistics office, “investment”, statistical yearbook of Viet Nam 2010, 147 – 176 General statistics office, “investment”, statistical yearbook of Viet Nam 2009, 101 – 127 General statistics office, “investment”, statistical yearbook of Viet Nam 208, 89 – 116 Ha Van Son (2004), “business statistics”, statistical publishing house, TP.HCM Hoang Trong, Chu Nguyen Mong Ngoc (2008), “One-Factor Analysis of Variance”, Applied Statistics in economic and society, Labor – Social publishers, HCMC Minh Khue (2008), “The impact of foreign investment to economic development - Society in Vietnam”, journal of economic forecast, statistical publishing house, Ha Noi 10 Ministry of planning and investment Foreign Investment Agency (2013), the situation of foreign direct investment in twelve months in 2013, http://fia.mpi.gov.vn/News.aspx?ctl=newsdetail&p=2.39&aID=1550, 26/02/2014 11 Ministry of planning and investment Foreign Investment Agency (2013), the situation of foreign direct investment in twelve months in 2011, http://fia.mpi.gov.vn/News.aspx?ctl=newsdetail&p=2.39&aID=1550, 24/02/2014 12 Nguyen Manh Toan (2010) "Factors effecting to attraction of foreign direct investment into a local in Vietnam", Journal of science and technology of Da Nang University, 5/40 13 Nguyen Thi Tuong Anh, Nguyen Huu Tam (2013), “Quantitative study of factors affecting the attraction of foreign direct investment in Vietnam's provinces in the current period”, External economics magazine No 2013/04 14 Le Minh Toan (2002) “Learning about foreign investment in Vietnam”, the National Political Publishing, Hanoi 15 Nguyen Van Tuan (2005), Foreign Direct Investment to Economic Development in Vietnam, The Justice Publisher, Hanoi.9 16 Wikipedia.org (2013), “Tukey's range test”, http://en.wikipedia.org/wiki/Tukey's_range_test, 24/02/2013 17 Wikipedia.org (2014), “analysis http://en.wikipedia.org/wiki/Analysis_of_variance, 29/02/2013 of variance”, [...]... declining later And FDI into Dong Nai province fluctuated wildly However, we can see the disparities of FDI registered capital between groups or between provinces in the region And FDI into Ho Chi Minh province is the best in the Southeast of Viet Nam in period 2009-2013 By results of research, we can conclude that the impact of the provinces in the South East region to attract FDI in Vietnam in the period. .. Level of significance 0.05 Table 1 shows the impact of six provinces in the Southeast region of Viet Nam to attract FDI in Vietnam in period 2009 – 2013 by using ANOVA data F ratio is the calculated ratio between MSG and MSW is used MSG is the total differences of edge of FDI in period 2009 - 2013 between the provinces in the region MSW is the total differences of edge of FDI within the provinces through... integration of Viet Nam; (3) Government's Investment promotion Agencies need to incorporate with local organizations of the region to unite the practice of attracting FDI in the region The study’s results can be of interest to domestic and foreign investors, managers to have a more comprehensive view of the region s attracting FDI situation, then they can have reasonable decisions to maximize the potential of. .. due to the economic development in the provinces is not uniform, we can’t compare the different degree of influence between provinces to attract FDI in Vietnam for the period 2009-2013 Because the research is still limited, we hope we can made a complete research in the future Maybe it will be clearer and fuller 4 Conclusion This study analyzed the impact of six provinces to attracting FDI into the. .. provinces is smaller or greater This is recognized that we can’t compare the different levels between provinces in spite of the different amount FDI into the provinces of Southeast in period 2009-2013 Because the annual growth rate is not uniform between the provinces, specifically in Vung Tau and Dong Nai; Vung Tau Province is inherently attracted to a large of FDI In period 2009-2011 its FDI increased... is the Tukey standard With Q statistic = 4.37 and a significance level 95%, results in T= 1527.5 > Di Thus we can conclude that the registered capital of FDI into provinces in the Southeast in Viet Nam period 2009 - 2013 is different, in other words, impact of each province to attract FDI in Vietnam over the years from 2009 to 2013 is different But we can’t conclude that the difference between the provinces. .. attracting FDI to provinces which still have limited development level comparing with the others such as Binh Phuoc, Tay Ninh, and also further develop provinces with strong growth, target to balance the development level of 6 provinces in the region (2) Localities in all the region need to coordinate preparing strategy to attract and use FDI effectively, associated with International economic integration... FDI into the South East Region of Viet Nam in period 2009-2013 using data of Foreign Investment Agency, Ministry of Planning and Investment The results show that different provinces attract different amount of FDI, and from 2009 to 2013 FDI inflows tend to shift from developed city like Ho Chi Minh City and Vung Tau to growing provinces like Binh Duong and Dong Nai Therefore there are several policies... local in Vietnam", Journal of science and technology of Da Nang University, 5/40 13 Nguyen Thi Tuong Anh, Nguyen Huu Tam (2013), “Quantitative study of factors affecting the attraction of foreign direct investment in Vietnam's provinces in the current period , External economics magazine No 2013/04 14 Le Minh Toan (2002) “Learning about foreign investment in Vietnam”, the National Political Publishing,... through the years With F=2.6754 and 𝐹𝑘−1,𝑛−𝑘, = 2.6207, so F >𝐹𝑘−1,𝑛−𝑘, It means that the impact of each province to attract FDI in Vietnam over the years from 2009 to 2013 is different And the p-value = 0.0465 < 0.05 It is found that the H0 assumption is rejected In other words, the statistical significance level suggests that the diffirent impact of province in South East area to attract FDI in Vietnam