Nhân tố ảnh hưởng đến quyết định thực hiện đầu tư FDI vào ASEAN của doanh nghiệp việt nam

BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC KINH TẾ TP HCM KHƯƠNG THỊ PHƯƠNG THẢO NHÂN TỐ ẢNH HƯỞNG ĐẾN QUYẾT ĐỊNH THỰC HIỆN ĐẦU TƯ FDI VÀO ASEAN CỦA CÁC DOANH NGHIỆP VIỆT NAM LUẬN VĂN THẠC SĨ KINH TẾ Tp Hồ Chí Minh - Năm 2016 BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC KINH TẾ TP HCM KHƯƠNG THỊ PHƯƠNG THẢO NHÂN TỐ ẢNH HƯỞNG ĐẾN QUYẾT ĐỊNH THỰC HIỆN ĐẦU TƯ FDI VÀO ASEAN CỦA CÁC DOANH NGHIỆP VIỆT NAM CHUYÊN NGÀNH: TÀI CHÍNH – NGÂN HÀNG MÃ SỐ: 60340201 LUẬN VĂN THẠC SĨ KINH TẾ NGƯỜI HƯỚNG DẪN KHOA HỌC: PGS.TS LÊ THỊ LANH Tp Hồ Chí Minh - Năm 2016 LỜI CAM ĐOAN Tôi xin cam đoan luận văn “ Nhân tố ảnh hưởng đến định thực đầu tư FDI vào ASEAN doanh nghiệp Việt Nam” công trình nghiên cứu tác giả, thực hướng dẫn khoa học PGS.TS Lê Thị Lanh Các số liệu kết nghiên cứu trình bày luận văn hồn tồn trung thực chưa cơng bố cơng trình nghiên cứu khác Thành phố Hồ Chí Minh, tháng 10 năm 2016 Tác giả luận văn Khương Thị Phương Thảo MỤC LỤC TRANG BÌA LỜI CAM ĐOAN MỤC LỤC DANH MỤC TỪ VIẾT TẮT DANH MỤC BẢNG TÓM TẮT CHƯƠNG 1: GIỚI THIỆU 1.1 Lý chọn đề tài nghiên cứu 1.2 Mục tiêu nghiên cứu 1.3 Đối tượng nghiên cứu 1.4 Phạm vi nghiên cứu 1.5 Phương pháp nghiên cứu 1.6 Đóng góp luận văn 1.7 Cấu trúc nội dung nghiên cứu CHƯƠNG 2: CƠ SỞ LÝ THUYẾT VÀ TỔNG QUAN CÁC NGHIÊN CỨU TRƯỚC ĐÂY 2.1 Khái niệm hình thức FDI 2.2 Vai trò FDI 2.3 Đặc điểm FDI 2.3.1 Chênh lệch suất cận biên vốn nước .8 2.3.2 Chu kỳ sản phẩm 2.3.3 Ảnh hưởng FDI làm mở rộng vốn đầu tư quốc gia .9 2.3.4 Ảnh hưởng FDI tăng suất sản xuất thông qua đầu tư vốn theo chiều sâu 10 2.4 Khung nghiên cứu lý thuyết 11 2.4.1 Lý thuyết chiết trung ( Eclectic), Dunning 12 2.4.2 Học thuyết lợi độc quyền, Stephen Hymer 13 2.4.3 Học thuyết nội hoá (Internalization), Buckley Casson 13 2.4.4 Lý thuyết bước phát triển đầu tư (Investment Development Path - IDP), Dunning 14 2.5 Các nghiên cứu trước 18 2.5.1 Nghiên cứu nước 18 2.5.2 Nghiên cứu nước 24 CHƯƠNG 3: PHƯƠNG PHÁP NGHIÊN CỨU VÀ MƠ HÌNH NGHIÊN CỨU 26 3.1 Mơ hình nghiên cứu 26 3.2 Phương pháp thu thập xử lý liệu 33 3.2.1 Phương pháp thu thập liệu 33 3.2.2 Phương pháp xử lý liệu 34 CHƯƠNG 4: KẾT QUẢ NGHIÊN CỨU 39 4.1 Thống kê tổng quát 39 4.2 Kiểm định kết hồi quy 35 4.2.1 Nhóm phương trình hồi quy xem xét yếu tố ảnh hưởng tới định đầu tư doanh nghiệp Việt Nam vào nước Asean 35 4.2.2 Nhóm phương trình hồi quy xem xét ảnh hưởng riêng lợi nhuận doanh nghiệp Việt Nam mối liên hệ với biến động tỷ giá chéo quốc gia tới định định đầu tư doanh nghiệp Việt Nam vào nước Asean 47 4.2.3 Nhóm phương trình hồi quy xem xét ảnh hưởng riêng biến động giá chứng khoán doanh nghiệp Việt Nam mối liên hệ với định định đầu tư vào nước Asean 54 CHƯƠNG 5: KẾT LUẬN 58 5.1 Kết luận 58 5.2 Hạn chế đề tài 60 5.3 Nghiên cứu đề xuất 61 DANH MỤC TỪ VIẾT TẮT ASEAN: Hiệp hội quốc gia Đông Nam Á (Association of Southeast Asian Nations) SUR: Phương trình hồi quy khơng liên quan ( Seemingly Unrelated Regressions) FDI: Đầu tư trực tiếp nước ( Foreign Direct Investment) M&A: Mua bán sáp nhập (Mergers and Acquisitions ) TTCK: Thị trường chứng khốn MNC: Cơng ty đa quốc gia( Multinational Corporation) DN: Doanh nghiệp DANH MỤC BẢNG Bảng 3.1 Danh sách 29 doanh nghiệp Bảng 3.2 Danh sách quốc gia Bảng 3.3 Tóm tắt biến Bảng 4.1 Thống kê tổng quát nhóm biến vĩ mô quốc gia ASEAN Bảng 4.2 Thống kê tổng quát nhóm biến liên quan DN Việt Nam định đầu tư FDI hay M&A Bảng 4.3 Thống kê tổng quát nhóm biến M&A, đầu tư, mục đích kinh nghiệm 41 Bảng 4.4 Tương quan biến Bảng 4.5 Kết phương trinh hồi quy Bảng 4.6 Kết phương trinh hồi quy Bảng 4.7 Kết phương trinh hồi quy Bảng 4.8 Kết phương trinh hồi quy Bảng 4.9 Kết phương trinh hồi quy Bảng 4.10 Kết phương trinh hồi quy Bảng 4.11 Kết phương tr Bảng 4.12 Kết phương tr Bảng 4.13 Kết phương tri Bảng 4.14 Kết phương tr MỞ ĐẦU Với mục tiêu nghiên cứu tác động nhân tố: Corruption, Business, IPRS, SHRS, GDP, Population, Bilateral, Tax, RDI, Firms, MTB, MAP, Forex, Profits, Regional, Purpose đến định thực đầu tư trực tiếp nước ngồi cơng ty niêm yết TTCK Việt Nam thông qua kiểm định mơ hình SUR Tác giả tiến hành đánh giá mức độ ảnh hưởng biến mô hình từ quốc gia ASEAN nhận đầu tư Tác giả lấy liệu nghiên giai đoạn 2008 – 2015 công ty Việt Nam niêm yết ASEAN Exchanges kết hợp số liệu sàn chứng khoán nước Kết nghiên cứu cho thấy nhân tố Corruption, Business, Regional Purpose giải thích tốt tác động lên định lựa chọn đầu tư trực tiếp nước doanh nghiệp Việt Nam Từ khóa: FDI, đầu tư nước ngoài, đầu tư khu vực ASEAN CHƯƠNG 1: GIỚI THIỆU 1.1 Lý chọn đề tài nghiên cứu Trong xu phát triển mạnh mẽ kinh tế toàn cầu, hoạt động đầu tư khơng cịn bị giới hạn lãnh thổ quốc gia mà mở rộng thị trường giới thông qua thương vụ đầu tư nước như: M&A, đầu tư trực tiếp FDI mới,… Theo số liệu thông kê Worldbank, tổng vốn đầu tư trực tiếp nước ngồi FDI năm 2009 1.361 nghìn tỷ la Mỹ, năm 2015 2.04 nghìn tỷ đô la Mỹ.Đối với tổng giá trị thương vụ M&A tồn cầu, năm 2008 đạt xấp xỉ nghìn tỷ đô la Mỹ, năm 2015 tổng giá trị tăng lên đáng kể đạt mức 4.31 nghìn tỷ la Mỹ Những số liệu nêu phần phản ánh tình hình phát triển với tốc độ nhanh hoạt động đầu tư xuyên quốc gia giới Theo Hội nghị quốc gia thương mại phát triển, đầu tư trực tiếp nước ngồi (FDI) tồn cầu vượt 1.5 nghìn tỷ la Mỹ năm 2011, với mức ý nghĩa tăng trưởng kinh tế có tăng trưởng mạnh Xu hướng FDI thể phát triển kinh tế toàn cầu dẫn dắt sách thương mại đầu tư tự Chính phủ kết hợp với phát triển kinh tế Sự đa dạng hóa hoạt động thị trường nước chiến lược cần thiết cơng ty để tối đa hóa lợi nhuận thời đại tồn cầu hóa nay, việc lựa chọn thực M&A hay đầu tư trực tiếp FDI để mở rộng kinh doanh định quan trọng nhà quản trị Việt Nam đánh giá là kinh tế có tốc độ phát triển nhanh, xu hướng đầu tư giới tác động lớn đến kinh tế Việt Nam Năm 2008, Việt Nam đầu tư trực tiếp nước 104 dự án, ứng với tổng vốn đăng ký 3,147 triệu đô la Mỹ Tổng số dự án đầu tư trực tiếp có tăng lên đạt 118 dự án năm 2015, tổng vốn đăng ký lại giảm 774 triệu đô la Mỹ Xu hướng đầu tư hội nhập với kinh tế giới đặt nhiều thách thức cho doanh nghiệp Việt Nam Thấy cần thiết việc tìm mơ hình phù hợp nhằm giúp tổ chức 108 M Nagano / Emerging Markets Review 16 (2013) 100–118 five countries, while those by Ginarte and Park (1997) use quinquennial data rather than annual data, thereby assuming that the legal environment remains constant throughout each five-year period Further, the indices proposed by Gompers et al (2003) not necessarily represent the legal environment in terms of SHR protection objectively, since they evaluate the corporate governance structure of the existing legal system Based on these limitations, this study employs IMD's annual quantitative data Further, we obtain data on the firm-specific variables, Xi, including R&D Intensity, Firm Size, ROA, and Market to Book from Thomson Reuters's Thomson Bank One We define Regional Networks as Regional Experience multiplied by Bilateral Trade We obtain information regarding Regional Experience to input the quantitative dummy variable data from the Overseas Business Operating Firm Databook of Toyo Keizai Shimpo Sha The missions of Japanese firms' local bases are also indicated in the Overseas Business Operating Firm Databook; these missions or activities are often categorized as “sales distribution,” “manufacturing,” and/or “R&D.” The variable Entry Purpose equals one when the local base's purpose is “sales distribution” and zero otherwise However, since a local base may have more than one purpose, the variable also equals one when the local base has other purposes in addition to “sales distribution” and zero otherwise (Table 4) We repeatedly estimated several empirical equations, but we only report the pertinent results herein Finally, as demonstrated by Svensson (2005) and Olken and Barron (2009), the level of host-country corruption is another important factor that may influence FDI inflows We therefore employ the Corruption Perception Index of Transparency International as a proxy for the level of host-country corruption for Eqs (1) and (2), but we not report the empirical results since the coefficients are not significant Empirical results 3.1 Similarities in the determinants between these two types of FDI Our first empirical results are presented in Table As for the country-level macroeconomic variables, the coefficients of per capita GDP, Population, and Corporate Tax are significant The signs of the coefficients of per Table Descriptive statistics Cross-border M&A (N = 205) Greenfield FDI (N = 1956) No FDI firms (N = 20,367) Cross-border M&A (N = 205) Greenfield FDI (N = 1956) No FDI firms (N = 20,367) Cross-border M&A (N = 205) Greenfield FDI (N = 1956) No FDI firms (N = 20,121) Note: The figures in this table indicate the mean and standard deviation of the variables employed in this paper The variables are categorized by FDI type (i.e., cross-border M&A firm, greenfield FDI firm, and firms without FDI) M Nagano / Emerging Markets Review 16 (2013) 100–118 Table Determinants of cross-border M&A and greenfield FDI decisions: SUR empirical results Independent variables Panel A IP_Rights Score SH_Rights Score IP Rights Score ∗ IPR Sensitive SH Rights Score ∗ SHR Sensitive IP Rights Score^2 SH Rights Score^2 Corporate Tax IPR Score ∗ IPR Sensitive ∗ Corporate Tax SHR Score ∗ SHR Sensitive ∗ Corporate Tax Per capita GDP Population Bilateral Trade R&D_Intensity Firm Size Market-to-Book Regional Networks Entry Purpose Const Year dummy Industrial dummy (2 digits) Country dummy Chi2 Pseudo R2 Observations Panel B IP_Rights Score SH_Rights Score Corporate Tax Market-to-Book Regional Networks Entry Purpose Note 1: In this estimation, the dependent variables are the cross-border M&A and greenfield FDI dummies The independent variables are the legal environment variables, host-country macroeconomic variables, and home-country firm-specific variables The estimation results for Models A and B are indicated in Panel A and those for the test of the differences for each pair of coef ficients are indicated in Panel B Panel C indicates the predicted probability of each empirical equation Note 2: ***, **, and * denote significance at 1, 5, and 10%, respectively The dependent variable is equal to one if firm i invests in country c and zero otherwise The year and industry dummies are included in all the equations 110 M Nagano / Emerging Markets Review 16 (2013) 100–118 Table Effects of firm stock return on cross-border M&A and greenfield FDI decisions: SUR empirical results Independent variables Panel A IP_Rights Score SH_Rights Score IP Rights Score ∗ IPR Sensitive SH Rights Score ∗ SHR Sensitive IP Rights Score^2 SH Rights Score^2 Per capita GDP Population Bilateral Trade Corporate Tax R&D_Intensity Firm Size Regional Networks Entry Purpose Market Adj Price Forex Adj Price IP Rights Score ∗ IPR Sensitive ∗ Market Adj Price SH Rights Score ∗ SHR Sensitive ∗ Market Adj Price IP Rights Score ∗ IPR Sensitive ∗ Forex Adj Price SH Rights Score ∗ SHR Sensitive ∗ Forex Adj Price Const Year dummy Industrial dummy (2 digits) Country dummy Chi2 Pseudo R2 Observations Panel B IP_Rights Score SH_Rights Score Corporate Tax Market Adj Price Forex Adj Price Regional Networks Entry Purpose M Nagano / Emerging Markets Review 16 (2013) 100–118 capita GDP and Corporate Tax are negative and that of Population is positive These results fully support our first hypothesis that these macroeconomic variables are common determinants of both types of FDI in the host country The positive sign of the parameter for Population suggests that both cross-border M&A and green field FDI are encouraged when the host country has a large population Javorcik (2004) also shows a positive and significant sign of the parameter for this variable in the case of 6707 Eastern European host-country cases The negative sign of per capita GDP is also debatable in the literature Generally, the parameter is expected to be positive when a firm increases FDI to a high-growth economy However, per capita income and unit labor cost are positively correlated in emerging countries Accordingly, it is plausible that a home-country firm has an incentive to invest in a low unit labor cost country and, consequently, the sign of the per capita GDP parameter would be negative A negative relation between per capita income and FDI is also reported in Javorcik (2004) and Huizinga and Voget (2009) The negative sign of the Corporate tax parameter suggests that a home-country firm is likely to invest in a low corporate tax country This result agrees with the view of Huizinga and Voget (2009), who also report a negative sign for the parameter for corporate tax rate in relation to cross-border M&A for 8042 European M&A deal observations Panel B of Table reports the statistical test results of the differences in each pair of independent variable coefficients for the CBMA (cross-border M&A) and GFFDI (greenfield FDI) equations, as specified in Models A and B The z-values of the tests for CBMA coefficient − GFFDI coefficient > are indicated beside the difference in the coefficients enclosed within parentheses Panel B also reports that the absolute value of the Corporate Tax coef ficient for GFFDI is statistically larger than that of CBMA in both models 3.2 Impact of host-country legal environment on FDI The empirical results for Model A show that the coefficients of IP Rights Score are significantly positive in the case of both dependent variables (i.e., CBMA and GFFDI) Meanwhile, the coefficient of SH Rights Score is significantly positive for CBMA but not significant for GFFDI These results suggest that an aspect of our second hypothesis, namely that IPR and SHR protection laws influence either type of FDI but not both, is not always supported, as the results show that IPR protection law reform attracts both types of FDI to the host country These positive signs of the parameter for the IPR protection law results are consistent with the papers of Lee and Mansfield (1996) and Maskus (1998), which examine U.S home-country firms and South American host countries Meanwhile, the results are consistent with the other aspect of our second hypothesis, namely that SHR protection law reform increases inward cross-border M&A but not greenfield FDI In Model B, we employ the intersection of the variables of IP Rights Score and Corporate Tax, and of SH Rights Score and Corporate Tax These intersections are also multiplied by IPR Sensitive and SHR Sensitive, respectively The empirical results show that the coefficient of the intersected variable IP Rights Score × IPR Sensitive × Corporate Tax is significantly negative in the case of GFFDI However, the coefficients of the intersected variable SH Rights Score × SHR Sensitive × Corporate Tax are not significant both for CBMA and for GFFDI These results suggest that in combination with taxation reform, IPR protection legal reform influences greenfield FDI but not cross-border M&A However, the results also indicate that although the coefficient of the IPR protection law variable positively influences both types of FDI, in combination with a macroeconomic variable, it only influences greenfield FDI Judging from the above two empirical results, we regard Hypothesis as empirically supported The IP Rights Score coefficient of the CBMA equation is not always significantly larger than that of the GFFDI equation in the case of Model A The coefficient difference test of CBMA coefficient − GFFDI coefficient > in Model B is also not significant However, the results show that the SH Rights Score coefficient of the CBMA equation is significantly larger than that of the GFFDI equation in both Models A and B These results have two Notes to Table Note 1: In this estimation, the dependent variables are the cross−border M&A and greenfield FDI dummies The independent variables are the legal environment variables, host-country macroeconomic variables, and home-country firm-specific variables The estimation results for Models A and B are indicated in Panel A and those for the test of the differences for each pair of coefficients are indicated in Panel B Panel C indicates the predicted probability of each empirical equation Note 2: ***, **, and * denote significance at 1, 5, and 10%, respectively The dependent variable is equal to one if firm i invests in country c and zero otherwise The year and industry dummies are included in all the equations 112 M Nagano / Emerging Markets Review 16 (2013) 100–118 implications First, IPR protection law reform influences both types of FDI, but it is statistically impossible to determine which type of FDI is more significantly influenced Second, the impact of SHR law reform on cross-border M&A is clearly statistically larger than that on greenfield FDI 3.3 Impact of home-country firm FDI experience on FDI choice The empirical results that explain the relationship between individual firm managerial environment concerning past foreign market entry and the FDI decision are described next The coefficient of Regional Networks is not significant for CBMA but is significantly positive for GFFDI The coefficient of Entry Purpose is significantly positive for CBMA but is not significant for GFFDI These results support Hypothesis and indicate that firm-level factors concerning past FDI experience and investment decision making influence the firm's FDI choice A positive relation between regional production network and FDI is also reported by Kimura and Kiyota (2006) and the other results are also consistent with their 22,182-participant study However, a variable that represents the purpose of establishing the firm production network is not employed in any literature to our best knowledge Therefore, our positive sign of the parameter for CBMA is a unique result obtained in this study The coefficient difference of Regional Networks is significantly negative in both Models A and B In other words, the coefficient of the GFFDI model is significantly larger than that of the CBMA model in both models The coefficient difference of Entry Purpose is significantly positive for both models As shown in Panel B of Tables and 6, in the CBMA model, the value of the coefficient of Entry Purpose is statistically larger than that in the GFFDI model, while in the GFFDI model, the value of the coef ficient of Regional Networks is larger than that in the CBMA model These results suggest that the foreign market entry purpose in fluences the choice of cross-border M&A and that having a regional network influences the choice of greenfield FDI 3.4 Impact of home-country stock price on FDI choice The empirical results that examine the relationship between the home-country firm's stock price and choice of FDI are shown in Tables and In the analysis of Model A, the coefficient of the employed stock price variable (i.e., Market Adj Price) is not significant for CBMA but is significantly positive for GFFDI In the analysis of Model B, the coefficient of the employed foreign exchange adjusted stock price variable (i.e., Forex Adj Price) is not significant for CBMA but is significant for GFFDI These results suggest that a home-country firm's prior stock price does not influence its choosing of cross-border M&A but influences its choosing of greenfield FDI Both Chari et al (2010) and Erel et al (2012) show a positive relationship between the firm's cross-border M&A investment decision and the cumulative abnormal stock price return of the mother country firm Our results are thus consistent with these studies, but we also show a positive relationship between the firm's greenfield FDI decision and its growth opportunity, which is a novel finding As shown in Panel B, the statistical differences in the Market Adj Price coefficients between equations (A) and (B) and Forex Adj Price coefficients between equations (A) and (B) are highly significant In the GFFDI model, the values of the coefficients of Market Adj Price and Forex Adj Price are larger than those in the CBMA model These results imply that the home-country firm's stock price prior to the investment and having a regional network influence its choosing of greenfield FDI Table presents the empirical results of the relationship between the home-country firm's stock price and FDI choice when we employ cumulative abnormal returns as proxies of firm stock price In Model C, the coefficient of the one-month cumulative abnormal stock price return (CAR1m) is significantly positive for CBMA but not significant for GFFDI The empirical result is also similar when we employ the three-month cumulative abnormal stock price return (CAR2m) The coefficient is significantly positive for CBMA but not significant for GFFDI Panel B shows the statistical test results of the difference between the coefficients of CAR1m and CAR2m These results show that the coefficients of CAR1m and CAR2m in the CBMA model are larger than those in the GFFDI model, suggesting that a home-country firm's stock price increases immediately after it chooses cross-border M&A but not immediately after it chooses greenfield FDI This relationship between the firm's cumulative abnormal returns and choice of cross-border M&A contrasts with that between the firm's stock price prior to investment and choice of greenfield FDI M Nagano / Emerging Markets Review 16 (2013) 100–118 Table Effects of firm cumulative abnormal returns on cross-border M&A and greenfield FDI decisions: SUR empirical results Independent variables Panel A IP_Rights Score SH_Rights Score IP Rights Score ∗ IPR Sensitive SH Rights Score ∗ SHR Sensitive IP Rights Score^2 SH Rights Score^2 Per capita GDP Population Bilateral Trade Corporate Tax R&D_Intensity Firm Size Regional Networks Entry Purpose CAR1m CAR3m IP Rights Score ∗ IPR Sensitive ∗ CAR1m SH Rights Score ∗ SHR Sensitive ∗ CAR1m Const Year dummy Industrial dummy (2 digits) Country dummy Chi2 Pseudo R2 Observations Panel B IP_Rights Score SH_Rights Score Corporate Tax CAR1m CAR3m Regional Networks Entry Purpose Note 1: In this estimation, the dependent variables are the cross-border M&A and greenfield FDI dummies The independent variables are the legal environment variables, host-country macroeconomic variables, and home-country firm-specific variables The estimation results for Models A and B are indicated in Panel A and those for the test of the differences for each pair of coefficients are indicated in Panel B Note 2: ***, **, and * denote significance at 1, 5, and 10%, respectively The dependent variable is equal to one if firm i invests in country c and zero otherwise The year and industry dummies are included in all the equations 114 M Nagano / Emerging Markets Review 16 (2013) 100–118 3.5 Re-examination with a probit model with sample selection Table presents the empirical results of the re-examination of the similarities and differences in the FDI determinants of cross-border M&A and greenfield FDI The results indicate that the coefficient of CAR1m in Model A is positively related to cross-border M&A decisions, consistent with the empirical results shown in Table Further, the coefficient of Market Adj Price in Model B is positively related to greenfield FDI decisions, consistent with the results in Table Table also presents the empirical results for the other variable coefficients The results show that Regional Networks and greenfield FDI decisions are positively related in Model B and that the coefficient of Regional Networks is not significant for CBMA in Model A The results also show that Entry Purpose and cross-border M&A decisions are positively related in Model A and that the coefficient of Entry Purpose is not significant for GFFDI in Model B These results are also consistent with the empirical results shown in Tables to On the other hand, the coefficient of the proxy of the home-country firm's internal funding ability, ROA, is not significant in Models A and B This finding suggests that ROA influences neither greenfield FDI nor cross-border M&A decisions Table Effects of firm-specific factors on FDI choice: probit model with sample selection results Independent variables/dependent variable IP_Rights Score SH_Rights Score R&D_Intensity Firm Size Regional Networks Entry Purpose ROA Market Adj Price CAR1m Per capita GDP Growth Population Bilateral Trade Const Year dummy Industrial dummy (2 digits) Country dummy LR Test of rho = 0: Chi^2 Observations Note 1: In this estimation, the determinants of cross-border M&A and greenfield FDI are examined using a probit model with sample selection to check the robustness of the empirical results in Tables to The dependent variable of Model A is cross-border M&A and that of Model B is greenfield FDI Models A and B are estimated using the second empirical model where the dependent variables are the firm FDI dummies, respectively Note 2: ***, **, and * denote significance at 1, 5, and 10%, respectively The dependent variable is equal to one if firm i invests in country c and zero otherwise The year and industry dummies are included in all the equations M Nagano / Emerging Markets Review 16 (2013) 100–118 Discussion and conclusions Based on the empirical evidence presented herein, we can draw the following conclusions Some host-country variables promote both types of FDI, but the home-country firm's preference of the type of FDI is determined by the host-country's legal environment and individual firm-level variables The existing literature shows evidence of the determinants that encourage cross-border M&A and greenfield FDI, but this study is the first to present the similarities and differences of such determinants using a common sample As for similarities in cross-border M&A and greenfield FDI determinants, our results regarding the relationship between the country-level variables and FDI (Hypothesis 1) are entirely consistent with the findings of the existing literature Our study's results suggest that per capita GDP is significantly and negatively related to both cross-border M&A and greenfield FDI decisions Although we originally hypothesized that the sign of the per capita GDP coefficient is positive, unit labor cost and household income are in general correlated in emerging host countries, which negatively influence FDI decisions Our empirical results for the country-level variable coefficients also yield valuable insights We find that in addition to per capita GDP, Population, and Corporate Tax all influence both cross-border M&A and greenfield FDI Our first main conclusion, therefore, is that while these country-level variables commonly increase or decrease both types of FDI, they not determine the firm's choice of either investment type In other words, while the country-level variables employed in this study are required conditions to encourage FDI in the host country, they not determine the type of FDI chosen by the home-country firm Regarding differences in these two types of FDI determinants (Hypothesis 2), we find that whether changes in the legal environment influence a home-country firm's FDI decision depends on the aspect of the legal environment as well as on type of FDI For instance, while cross-border M&A is not influenced by an enhancement of the host country's IPR protection laws, greenfield FDI is promoted by such an enhancement; these results are consistent with the conclusions drawn by Lai (1998), Branstetter et al (2006), and Javorcik (2004) In the context of the recent dramatic increases in cross-border M&A, our empirical results suggest that enhancements of SHR protection laws are required Our finding of a positive relationship between the legal environment concerning SHR protection and cross-border M&A supports the conclusions of Giovanni (2005) Indeed, Indonesia and the Philippines scored between four and five points on the IMD SHR scale and thus they belong to the lowest cohort of the 45 sample countries On the other hand, Malaysia, Singapore, and India scored between six and seven points, paralleling the recent cross-border M&A increases in these countries In terms of firm-level factors, we find that the existence of a regional network in the host country and home-country firm stock price are two major determinants in the decision whether to choose either FDI, but not both Our results in Table also show that Bilateral Trade influences both types of FDI, whereas Regional Networks, the variable intersecting Bilateral Trade and Regional Experience, only influence greenfield FDI (Hypothesis 3) This finding occurs because Bilateral Trade is a country-specific variable, whereas Regional Experience, which pertains to the existence of operations in the host country, is a firm-specific variable In other words, our empirical results suggest that firm-specific variables determine the choice of FDI once country-level variables have been converted into firm-specific variables For instance, in 2010–2011, several Japanese brewery firms announced cross-border M&A deals with companies in Australia and Brazil Although Japan, as a country, has significant bilateral export and import relationships with these two countries, the Japanese brewery firms in question not have local distribution channels there Accordingly, their acquisitions were based on their own decisions as individual firms These cases are also consistent with our empirical results that show a positive relationship between Entry Purpose and cross-border M&A The empirical results on the relationship between the home-country firm's stock price and FDI decision (Hypothesis 4) also provide important implications We find that cross-border M&A is not influenced by firm stock price prior to the investment decision Although these two variables are positively related, our results show that the investment decision rather induces the stock price change, not the other way around A possible reason for this outcome is that many crossborder M&A deals by Japanese firms are aimed at Although China also scored 3.0–4.0 SHR points during the sample period, it has substantially more cross-border M&A in flows than outflows In our study, we estimated several empirical models in addition to models (1) and (2) In one of these additional models, we employed the intersection of SH Rights Score and per capita GDP and obtained a significantly positive coefficient In the case of China, this suggests that the country's economic growth substitutes for its legal environment 116 M Nagano / Emerging Markets Review 16 (2013) 100–118 acquiring new additional customers and responding to demand in host countries Following such deals, the stock market expects an improvement in the financial performance of the acquiring firm, thereby confirming the positive relationship between stock price and cross-border M&A How should we then understand how the above legal environment and firm-level factors work together to influence home-country firm FDI choice? The interpretation of our conclusions runs as follows In contrast to green field FDI, cross-border M&A can dramatically increase a firm's sales network capabilities even in the short run, which can potentially lead to an improvement in its operating profit If this were so, then all firms would have preferred crossborder M&A to greenfield FDI in the past However, in reality, greenfield FDI still significantly outnumbers crossborder M&A, because the probability of completing cross-border M&A deal after an announcement is low For instance, of the 243 cross-border M&A deals we originally obtained for our sample, 97 were terminated prior to completion Ultimately, our dataset only included the 146 completed cross-border M&A deals In short, based on our sample, cross-border M&A has an approximately 40% probability of incompletion It is often thought that cross-border M&A is a ready-made international business strategy, while greenfield FDI is a tailor-made international business strategy for entering new foreign markets In the ready-made strategy, although thorough due diligence is necessary to close a successful deal, such due diligence is not a sufficient condition, since unexpected environmental changes may affect the deal immediately after the transaction In this regard, the tailor-made strategy of entry enables the home-country firm to cope with the host-country market more flexibly and thus have a higher probability of completion The characteristics of cross-border M&A may also influence the firm's choice Specifically, the legal environment concerning SHR protection is one of the factors that may influence this probability The better the enforcement of SHR protection laws, the greater is the probability of firms choosing cross-border M&A because strong SHR protection by law enables the home-country firm to control the target host-country firm in order to achieve its ultimate purpose of market entry, even in the case of the ready-made strategy of entry In the case of greenfield FDI, prior increases in the home-country firm's stock price positively influence a firm's investment decision In other words, as firm value increases in the domestic market, the firm is more likely to enter a neighboring country through greenfield FDI This probability rises if the firm already had local operations in the host country prior to the investment because a firm that is highly competitive in the domestic product or services market generally experiences stock price increases in its home country These prior stock price increases encourage the firm to establish a new production base and sales network overseas An acquiring firm's high market value in its home country affords it time and resources to successfully operate in the host country Through greenfield FDI, the firm avoids the risk of withdrawal or termination that is otherwise present in cross-border M&A Therefore, it does not choose crossborder M&A when it already has local networks in a host country Indeed, market value may even decrease when cross-border M&A market entry is not accepted by capital market participants due to its low probability of completion or view of future poor performance in the post-merger period On the other hand, market value can increase with the announcement of cross-border M&A when the future expected return of the deal makes up for the risk of incompletion In this regard, a lower stock price before the FDI decision may be better than the risk of incompletion In summary, the study contributes to the body of knowledge on this topic in four specific ways First, our study shows evidence that the host country's population size, per capital income, and corporate tax rate are common determinants for inviting inward FDI Further, we also show that the host country's legal environment and homecountry individual factors determine either type of FDI, but not both Second, we show that the host country's IPR protection law influences the incoming greenfield FDI but not the cross-border M&A decision of the home-country firm By contrast, the host country's SHR protection law influences the incoming cross-border M&A but not the greenfield FDI decision of the home-country firm Third, whether the home-country firm has past FDI experience in the host country influences the greenfield FDI decision but not the cross-border M&A decision However, when the firm has no past FDI experience in the country, whether the purpose of the new entry is to establish a sales distribution channel is a major determinant of cross-border M&A Fourth, the home-country stock price appears to influence both FDI decisions, but it increases immediately before and after the investment announcement for cross-border M&A, while a high stock price in the pre-investment period encourages the greenfield FDI decision However, the following limitations must also be recognized in our study We employ only two quanti-tative data to represent the legal environment of the host country due to data limitations In emerging M Nagano / Emerging Markets Review 16 (2013) 100–118 countries, especially, obtaining quantitative data on the prevailing legal environment is complex, but other legal environment factors may also influence incoming FDI Whether host-country legal environment factors other than IPR and SHR protection laws influence FDI choice should thus be investigated by future research In addition, we employ data on home-country Japanese firms and host countries in the Asia-Pacific region Individual FDI deal-level data are also difficult to obtain Thus, our result should be re-examined using other regional data as necessary Acknowledgments The author thanks various seminar participants for their helpful comments and suggestions This research is financially supported by KAKENHI, Grant-in-Aid for Scientific Research (C) 24530357 Appendix A Annual distribution of cross-border M&A and greenfield FDI deals of Japanese firms by industry (1999–2009) Food products Tobacco products Textile mill products Apparel & related products Lumber & wood products Furniture & fixtures Paper & allied products Printing & publishing Chemicals & allied products Petroleum refining & related ind Rubber & plastic products Leather & leather products Stone clay & glass products Primary metal industries Fabricated metal products Machinery Electrical equipment Transportation equipment Instruments related products Other manufacturing industries Source: The figures were calculated by the authors using data from Thomson Bank One, Bloomberg, and Toyo Keizai Shimpo Sha References Ahern, Kenneth R., Daminelli, Daniele, Fracassi, Cesare, 2012 Lost in translation? The effect of cultural values on mergers around the world Journal of Financial Economics http://dx.doi.org/10.1016/j.jfineco.2012.08.006 Braga, Primo, Carlos, A.P., Fink, Carsten, 1998 Reforming intellectual property rights regimes: challenges for developing countries Journal of International Economic Law (4), 537 –554 Branstetter, Lee, Fisman, Raymond, Fritz Foley, C., 2006 Do stronger intellectual property rights increase international technology transfer? Empirical evidence from U.S firm-level data Quarterly Journal of Economics 121 (1), 321 –349 Branstetter, Lee, Raymond Fisman, C., Foley, Fritz, Saggi, Kamal, 2011 Does intellectual property rights reform spur industrial development? Journal of International Economics 83 (1), 27–36 Chari, A., Ouimet, P., Tesar, L., 2010 The value of control in emerging markets The Review of Financial Studies 23 (4), 1741 –1770 Erel, Isil, Liao, Rose C., Weisbach, Michael S., 2012 Determinants of cross-border mergers and acquisitions Journal of Finance 67 (3), 1045–1082 Ferreira, Miguel A., Massa, Massimo, Matos, Pedro P., 2009 Shareholders at the gate? Institutional investors and cross-border mergers and acquisitions Review of Financial Studies 23, 601–644 118 M Nagano / Emerging Markets Review 16 (2013) 100–118 Ginarte, Juan C., Park, Walter G., 1997 Determinants of patent rights: a cross-national study Research Policy 26 (3), 283 –301 Giovanni, Julian, 2005 What drives capital flows? The case of cross-border M&A activity and financial deepening Journal of International Economics 65 (1), 127–149 Glass, Amy Jocelyn, Saggi, Kamal, 2002 Intellectual property rights and foreign direct investment Journal of International Economics 56 (2), 387–410 Gompers, Paul A., Ishii, Joy L., Metrick, Andrew, 2003 Corporate governance and equity prices Quarterly Journal of Economics 118 (1), 107–155 Head, Keith, Ries, John, 2008 FDI as an outcome of the market for corporate control: theory and evidence Journal of International Economics 74 (1), 2–20 Helpman, Elhanan, 1993 Innovation, imitation, and intellectual property rights Econometrica 61 (6), 1247 –1280 Huizinga, Harry P., Voget, Johannes, 2009 International taxation and the direction and volume of cross-border M&As Journal of Finance 64 (3), 1217–1249 Ivus, Olena, 2010 Do stronger patent rights raise high-tech exports to the developing world? Journal of International Economics 81 (1), 38–47 Javorcik, Beata Smarzynska, 2004 The composition of foreign direct investment and protection of intellectual property rights: evidence from transition economies European Economic Review 48 (1), 39 –62 Kim, Young-Han, 2009 Cross-border M&A vs greenfield FDI: economic integration and its welfare impact Journal of Policy Modeling 31 (1), 87–101 Kimura, Fukunari, Kiyota, Kozo, 2006 Exports, FDI, and productivity: dynamic evidence from Japanese firms Review of World Economics (Weltwirtschaftliches Archiv) 142 (4), 695–719 Kimura, Fukunari, Hayakawa, Kazunobu, Ji, Zheng, 2008 Does international fragmentation occur in sectors other than machinery? Asian Economic Journal, vol 22, No East Asian Economic Association, pp 343 –358 Lai, Edwin L.C., 1998 International intellectual property rights protection and the rate of product innovation Journal of Development Economics 55 (1), 133–153 LaPorta, Rafael, Lopez-De-Silanes, Florencio, Shleifer, Andrei, 2006 What works in securities laws? Journal of Finance 61 (1), –32 Lee, JeongYeon, Mansfield, Edwin, 1996 Intellectual property protection and U.S foreign direct investment The Review of Economics and Statistics 78 (2), 181–186 Mansfield, Edwin, 1995 Intellectual property protection, foreign direct investment and technology transfer International Finance Corporation Discussion Paper No 27 Maskus, Keith E., 1998 Strengthening intellectual property rights in Asia: implications for Australia Australian Economic Papers 37 (3), 346–361 Maskus, Keith E., Penubarti, Mohan, 1995 How trade-related are intellectual property rights? Journal of International Economics 39 (3–4), 227– 248 Nair-Reichert, Usha, Duncan, Roderick, 2008 Patent regimes, host country policies, and the nature of MNE activities Review of International Economics 16 (4), 783–797 Neary, Peter, 2004 Rationalizing the Penn World Table: true multilateral indices for international comparisons of real income American Economic Review 94 (5), 1411–1428 Neary, Peter, 2009 Trade costs and foreign direct investment International Review of Economics and Finance 18 (2), 207 –218 Nocke, Volker, Yeaple, Stephen, 2007 Cross-border mergers and acquisitions vs greenfield foreign direct investment: the role of firm heterogeneity Journal of International Economics 72 (2), 336 –365 Olken, Benjamin A., Barron, Patrick, 2009 The simple economics of extortion: evidence from trucking in Aceh Journal of Political Economy 117 (3), 417–452 Park, Walter G., Lippoldt, Douglas, 2005 International licensing and the strengthening of intellectual property rights in developing countries during the 1990s OECD Economic Studies, No 4, 2005/1 Rafiquzzaman, Mohammed, 2002 The impact of patent rights on international trade: evidence from Canada Canadian Journal of Economics 35 (2), 307–330 Rapp, Richard, Rozek, Richard P., 1990 Benefits and costs of intellectual property protection in developing countries Journal of World Trade 24 (5), 75–102 Smith, Pamela J., 2001 How foreign patent rights affect U.S exports, af filiate sales, and licenses? Journal of International Economics 55 (2), 411–439 Svensson, Jakob, 2005 Eight questions about corruption Journal of Economic Perspectives 19 (3), 19 –42 Uysal, Vahap, Kedia, Simi, Panchapagesan, Venkatesh, 2008 Geography and acquirer returns Journal of Financial Intermediation 17 (2), 256–275 ... lược đầu trực tiếp FDI đạt tối đa hóa lợi ích kinh doanh Từ ý nêu trên, tác giả định nghiên cứu đề tài ? ?Nhân tố ảnh hưởng đến định thực đầu tư FDI vào ASEAN doanh nghiệp Việt Nam? ?? 1.2 Mục tiêu... nước ASEAN đưa để kiểm định, nhân tố có ảnh hưởng lớn đến việc thực đầu tư trực tiếp FDI mới? - Đối với doanh nghiệp Việt Nam, yếu tố đặc trưng đóng vai trị quan trọng định đầu tư trực tiếp FDI? ... TRƯỜNG ĐẠI HỌC KINH TẾ TP HCM KHƯƠNG THỊ PHƯƠNG THẢO NHÂN TỐ ẢNH HƯỞNG ĐẾN QUYẾT ĐỊNH THỰC HIỆN ĐẦU TƯ FDI VÀO ASEAN CỦA CÁC DOANH NGHIỆP VIỆT NAM CHUYÊN NGÀNH: TÀI CHÍNH – NGÂN HÀNG MÃ SỐ: 60340201