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Table of Contents Chapter 1: INTRODUCTION Chapter 2: THEORETICAL BASIS Chapter 3: DATA COLLECTION Chapter 4: EMPIRICAL MODEL AND HYPOTHESIS TESTS Chapter 5: CONCLUSION 14 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 1: INTRODUCTION Since the introduction of doi moi (renovation) economic reforms in 1986, Vietnam’s economy has been among the fastest growing economies in the region Its economic structure reflected an increasing share of industry and services while the share of agriculture declined Vietnam has been successful in poverty reduction strategies and has been able to ensure rapid growth with relative equity Among the factors that led to this success, foreign direct investment (FDI) has played a crucial role, providing Vietnam’s economy with its relatively scarce factor, capital, and representing an extremely important instrument for integration in the world economy, especially at the regional level However, FDI infusion in different localities is not identical Therefore, this paper attempts to identify the main factors that help with the attraction of foreign direct investment capital in a locality of Vietnam The survey results that there are some factors that have been evaluated as much more important; while, others are considered to be relatively less important in the current context of Vietnam With purpose to determine the decisive factors that influence the selection of investment locations in Vietnam, our group chooses the topic: “THE FACTORS AFFECTING THE INFUSION OF FOREIGN DIRECT INVESTMENT CAPITAL INTO A LOCALITY IN VIETNAM” LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 2: THEORETICAL BASIS According to the eclectic theory developed by professor Dunning and Mr Nguyen Manh Toan’s report from Da Nang Economics University, location advantages of different countries are the key factors to determining who will become host countries for the activities of transnational corporations The specific advantages of each country in general and each locality of it in particular can be divided into three categories: The infrastructure benefits consist of export processing zones ( EPZs ) as well as industrial zones Political advantages: common and specific government policies that affect FDI flows Resources advantages includes geography, number of labors After considering the factors as above, we come to decision on researching these ones: Industrial zone (the number of industrial and export processing zones): this belongs to technical infrastructure and seems to be one of the most important factors to attract FDI to any area in Viet Nam Therefore, the expectation of Industrial zone is positive (+) School (the number of all types of schools in one area): This kind of social infrastructure is one criterion that encourages foreign companies investing in a locality More schools will reflect higher level of labor force The expectation School is positive (+) Policy (measured based on level): open and flexible policies of the local authority will motivate foreign firms to establish their new business or invest money in this locality There are increasing levels of good policy : LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 0: normal 1: good 2: very good The coefficient is expected to have positive (+) sign Density (people/km2): Foreign companies when decide to invest in one area also want to exploit a great number of young labor forces with low salary Therefore, the expectation density is positive (+) Finally, Region: Different kinds of topography may create advantages or disadvantages for economy development in each locality and this affect the amount of FDI as well This Dummy variable includes: 0: mountain area and midland 1: coast 2: Delta Its expectation sign is positive (+) Therefore, the model proposed is: FDI = INDUSTRIAL ZONE + + DENSITY + SCHOOL + POLICY REGION LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 3: DATA COLLECTION 3.1 Source of survey: The data is collected from some websites of General Statistic Office as well as Industrial Zones in Vietnam 3.2 Scope of survey: My group collected the data from 45 provinces in Vietnam randomly, after that we classified them into categories: population density, the number of industrial zones, school, policy, and region 3.3 Data table: Number 10 11 12 13 14 15 16 17 18 Province An Giang Bà Rịa - Vũng Tàu Bắc Giang Bắc Kạn Bạc Liêu Bắc Ninh Bến Tre Bình Định Bình Dương Bình Phước Bình Thuận Cà Mau Cần Thơ Đà Nẵng Đắk Lắk Đồng Nai Hà Nam Hà Nội FDI (million $) 82.5 26289.3 Region Populaiton density 608 1569 468.4 17.9 46.1 2361.2 148.3 591.4 14130.4 466.7 1371.2 780.4 709.5 2970.5 101.7 16794.1 207.6 20534.6 0 1 2 1 2 408 61 347 457 532 247 801 130 151 227 854 722 134 835 914 1962 School Policy 252 652 Industrial zone 18 347 222 241 319 357 438 319 292 431 402 264 174 682 527 285 1471 15 1 16 0 1 0 2 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 Hà Tĩnh Hải Dương Hải Phòng Hậu Giang Hồ Bình Hưng n Khánh Hồ Kiên Giang Lai Châu Lâm Đồng Lạng Sơn Long An Nam Định Nghệ An Ninh Bình Ninh Thuận Phú Yên Quảng Nam Quảng Ngãi Quảng Ninh Tây Ninh Thái Bình Thái Nguyên Thanh Hố Thừa Thiên Huế Tiền Giang TP.Hồ Chí Minh 8371.4 2671.1 5143.2 639.5 127.1 1148.8 808.2 2790.8 4.0 523.8 206.0 3499.6 182.5 1494.6 602.2 10145.1 8133.9 4903.4 3789.9 3784.2 919.2 231.7 113.3 7054.6 1883.9 462.3 30011.2 2 2 1 2 2 2 1 2 604 538 1221 474 173 1226 224 268 42 123 88 322 1107 177 648 1170 572 437 336 490 266 1140 221 306 215 675 3530 540 604 478 244 486 375 325 517 267 471 497 419 591 1056 322 424 298 531 441 416 421 603 439 1482 393 385 981 1 1 2 3 2 1 20 1 0 1 0 1 2 1 0 2 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 4: EMPIRICAL MODEL AND HYPOTHESIS TESTS 1) Model FDI = INDUSTRIAL ZONE + SCHOOL + POLICY + DENSITY + REGION We have the result from Gretl software: Model 1: OLS, using observations 1-45 Dependent variable: FDI const INDUSTRIAL ZONE SCHOOL POLICY DENSITY REGION Coefficient Std Error -3023.01 862.137 757.328 127.255 4.47475 1.46112 2778.14 914.435 2.64933 0.810737 -879.838 734.027 Mean dependent var Sum squared resid R-squared F(5, 39) Log-likelihood Schwarz criterion 4171.496 1.88e+08 0.911832 80.66754 -406.9070 836.6539 t-ratio -3.5064 5.9513 3.0626 3.0381 3.2678 -1.1986 p-value 0.00116 (tcrit 2.02) (at 5% significance level) Therefore, we reject H0, which means variable INDUSTRIAL ZONE has significant explanation to the model We the same with variables: SCHOOL, POLICY, DENSITY and we come to conclude that all of these independent variables are significantly explaining the amount of FDI to Vietnamese locality at 5% level Similarity, with variable REGION: ( = 1.1986) < ( tcrit 2.04) (at 5% significance level) Therefore, we not have enough evidence to reject H 0: = 0, we can remove variable REGION This can be explained as following facts: When the foreign organizations intend to invest their capital in one locality, they initially carried out surveys on some important aspects of this area and they may be deeply impressed by local infrastructure, the labor force and natural resources If they find out one locality providing them with all of these things, they will almost invest money in this area without caring much about what kind of topography this is They believe that whether the land is coast, midland or delta, they can cope with it and take advantages of it Thus, in this model, independent variable REGION is statistically insignificant in explaining the variation of FDI LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Further modifications must be done to the original model in order fix the problem LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 2) Model FDI = INDUSTRIAL ZONE + SCHOOL + POLICY + DENSITY We have the result from Gretl software: Model 2: OLS, using observations 1-45 Dependent variable: FDI Coefficient Std Error -3669.4 676.321 785.685 125.718 const INDUSTRIAL ZONE SCHOOL POLICY DENSITY 4.49338 2043.06 2.53454 Mean dependent var Sum squared resid R-squared F(4, 40) Log-likelihood Schwarz criterion 1.46899 681.999 0.809444 4171.496 1.95e+08 0.908584 99.39003 -407.7210 834.4752 t-ratio -5.4255 6.2496 p-value 10 multicollinearity may happen However, t-ratio is quite high and there is no correlation among independent Variables, because: Correlation coefficients, using the observations - 45 5% critical value (two-tailed) = 0.2940 for n = 45 INDUSTRIAL ZONE 1.0000 SCHOOL POLICY 0.2306 0.6828 1.0000 0.4689 1.0000 DENSIT Y 0.6979 INDUSTRIAL ZONE 0.3808 SCHOOL 0.4638 POLICY 1.0000 DENSITY Or Minimum possible value = 1.0 Values > 10.0 may indicate a collinearity problem INDUSTRIAL ZONE 3.221 SCHOOL 1.505 POLICY 2.406 11 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com DENSITY 2.246 The correlation matrix indicates that there is no collinearity between variables because pair correlation coefficient between independent variables is quite low ( smaller than 10.0) (The specific result is shown in the Appendix, page 16 ) 2.2- Normality of residual testing After taking test statistic for normality, we have the result : Test for null hypothesis of normal distribution: Chi-square(2) = 1.285 with p-value 0.52593 P-value is equal to 0.5259 which is greater than 0.05 Alternatively, we can test as following: - Null hypothesis : H0 : U has normal distribution - Alternative hypothesis : Based on the result above, JB= < H1 : H0 is wrong = 1.128, whereas = 9.49 ( = 5%) we not have enough evidence to reject H0 This indicates that the disturbance term has normal distribution and the model is right with the assumptions of the Ordinary Least Squares estimator (The specific result and graph is shown in the Appendix, page 17 ) 12 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 2.3- Heteroscedasticity testing We detect heteroscedasticity by using White test, and the result is: Unadjusted R-squared = 0.489011 Test statistic: TR^2 = 22.005491, with p-value = P(Chi-square(14) > 22.005491) = 0.078502 P-value is equal to 0.078502 and greater than 0.05 On the other hand, we can test as following: - Null hypothesis : H0 : Var(Ui) = - Alternative hypothesis : Based on the result above, nR2 = for all i H1 : H0 is wrong = 22.00549, whereas, = (17)= 27.59 ( < = 5%) we not have enough evidence to reject H0 This indicates that disturbance term is homoscedastic and the model is right with the assumptions of the Ordinary Least Squares estimator (The specific result is shown in the Appendix, page 18 ) 13 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 2.4- Autocorrelation testing Although the structure of our economic data is cross-sectional data, we try testing our model with autocorrelation as Time-series data Then we get the result from DurbinWatson test: Durbin-Watson statistic = 1.73645 p-value = 0.171644 The P-value here is more than 0.05, this means our model does not have Autocorrelation Besides, we also have another table to prove that our model does not have Autocorrelation (The specific result is shown in the Appendix, page 19 ) 14 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 5: CONCLUSION 5.1 The optimal model: After conducting some tests, our group could find the most optimal model It is FDI = -3669.4 + 785.685 INDUSTRIAL ZONE + 4.49338 SCHOOL + 2043.06 POLICY + 2.53454 DENSITY 5.2 Practical significance: One of the striking developments in Vietnam in recent years has been the large external capital inflow mostly in the form of foreign direct investment (FDI) The effect of FDI has been largely positive on Vietnam’s domestic economy, providing an engine of economic growth by increasing productive capacity and enhancing productivity Foreign – invested operations now contribute to nearly 10% of Vietnam’s GDP, more than 30% of gross capital formation Therefore perception of factors which influence FDI infusion in Vietnam, nowadays, is getting more and more important 5.2 Model application: Using the OLS on this model has been very useful to determine that FDI in Vietnam is greatly affected by the number of industrial zones, schools, government policies and population density The overall outcome of the regression shows the robust results For the most of regressions run for this model the results show that the independent variables are important factors that influence the FDI attraction in Vietnam This regression indicates Therefore our group suggests some ideas to increase FDI inflows into Vietnam: 15 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com - Firstly, Vietnam must complete infrastructures by building more factories, industrial zones, improving transportation in order to make distribution faster and more convenient - Secondly, Vietnam government also needs to encourage foreign investor factors, issuing the open – policies, tries to create an equal business environment - Last but not least, we should concern more about quantity as well as quality of work force To make sure the good work source, whole society must focus and spend money on building schools, universities, replacing old facilities by modern ones, advance teacher’s capacity… 16 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com APPENDIX Multicollinearity 17 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Normality of residual testing 18 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Heteroscedasticity 19 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Autocorrelation testing 20 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ... identify the main factors that help with the attraction of foreign direct investment capital in a locality of Vietnam The survey results that there are some factors that have been evaluated as much... locations in Vietnam, our group chooses the topic: ? ?THE FACTORS AFFECTING THE INFUSION OF FOREIGN DIRECT INVESTMENT CAPITAL INTO A LOCALITY IN VIETNAM? ?? LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com... teacher’s capacity… 16 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com APPENDIX Multicollinearity 17 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Normality of residual testing
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