Luận án Lan tỏa năng suất các yếu tố tổng hợp từ FDI trong ngành sản xuất: Vai trò định hướng thị trường của doanh nghiệp FDI, khả năng hấp thụ của doanh nghiệp nội địa và thể chế cấp tỉnh

To further advance the understanding regarding the spillover effects of FDI on domestic manufacturing enterprises in emerging countries, future research could explore a number of potential directions as follows: Firstly, researchers could investigate the role of absorptive capacity in determining the spillover effects of FDI on domestic firms‘ TFP. This could involve examining the impact of R&D activities, technology transfer, and other knowledge- related factors on the ability of domestic firms to absorb the spillover effects of FDI enterprises. Secondly, researchers could explore the impact of FDI origin on the spillover effects of FDI on domestic firms‘ TFP. By examining how the home country‘ s technological prowess and industry composition affect the spillover effects of FDI in the host country, researchers could gain a deeper understanding of the underlying mechanisms driving FDI spillovers. Thirdly, there is a need to investigate the influence of informal institutions, listed as cultural elements, on the spillover effects of FDI on domestic firms‘ productivity gains. A comprehensive understanding of the impact of institutions on FDI spillovers could be gained by exploring the relationship between informal institutions and productivity spillovers from FDI. Future research could explore solutions for the role of local governments in attracting FDI and facilitating its positive spillovers.

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ises in Vietnam Pursuant to Decree 56/2009/ND-CP dated 30/06/2009 regarding classifying enterprises into total capital or average number of employees per year in the area of agricultural, forestry and fishery enterprises, details are as follows: Enterprise scale Super-small enterprises L ≤ 10 Small enterprises 10< L≤200 Average enterprises 200<L≤300 Large enterprises L>300 172 Appendix A8: TFP contributions towards output increase Source: APO Database 2021 Country Period % Growth value Contribution (100%) Out- put Growth Labor Growth Capital Growth TFP Growth Labor Capital TFP Vietnam 1995–2000 7.1 1.2 6.2 -0.3 17% 87% -4% Vietnam 2000–2005 7 1.5 5.5 0 21% 79% 0% Vietnam 2005–2010 6.1 2.3 5.3 -1.6 38% 87% -26% Vietnam 2010–2015 5.3 0.4 3.5 1.3 8% 66% 25% Vietnam 2015–2019 6.4 1.7 3.3 1.4 27% 52% 22% Philippines 1995–2000 4.4 1.7 2.7 0.1 39% 61% 2% Philippines 2000–2005 4.7 1.3 1.7 1.7 28% 36% 36% Philippines 2005–2010 4.9 1.4 2.1 1.3 29% 43% 27% Philippines 2010–2015 5.7 1.1 3.1 1.4 19% 54% 25% Philippines 2015–2019 6.6 1.6 4.6 0.5 24% 70% 8% Indonesia 1995–2000 0.7 2.2 3.7 -5.2 314% 529% -743% Indonesia 2000–2005 4.5 1.9 2.6 0 42% 58% 0% Indonesia 2005–2010 5.4 1.7 3.5 0.1 31% 65% 2% Indonesia 2010–2015 5.3 2.5 4.2 -1.3 47% 79% -25% Indonesia 2015–2019 4.8 2.3 3.5 -1 48% 73% -21% Thailand 1995–2000 0.7 1.7 1.8 -2.8 243% 257% -400% Thailand 2000–2005 5.3 1.9 1 2.4 36% 19% 45% Thailand 2005–2010 3.7 1.3 2.1 0.3 35% 57% 8% Thailand 2010–2015 3 0.9 1.8 0.3 30% 60% 10% Thailand 2015–2019 3.6 0.4 1.7 1.5 11% 47% 42% Malaysia 1995–2000 4.8 1.9 4.2 -1.4 40% 88% -29% Malaysia 2000–2005 5.4 1.6 2.1 1.6 30% 39% 30% Malaysia 2005–2010 4.8 1.5 2.6 0.7 31% 54% 15% Malaysia 2010–2015 5.1 1.5 3.2 0.4 29% 63% 8% Malaysia 2015–2019 4.2 1.1 2.8 0.4 26% 67% 10% Brunei 1995–2000 2.8 0.8 2.4 -0.3 29% 86% -11% 173 Brunei 2000–2005 0.9 0.7 1.6 -1.3 78% 178% -144% Brunei 2005–2010 0.1 0.6 2.9 -3.4 600% 2900% -3400% Brunei 2010–2015 0.9 0.3 5 -4.5 33% 556% -500% Brunei 2015–2019 1.9 -0.1 2.1 0 -5% 111% 0% Singapore 1995–2000 6.2 2.1 3.5 0.5 34% 56% 8% Singapore 2000–2005 4.9 1.5 2.1 1.3 31% 43% 27% Singapore 2005–2010 7.2 2.8 2.4 2 39% 33% 28% Singapore 2010–2015 4.7 1.6 2.7 0.3 34% 57% 6% Singapore 2015–2019 3.7 0.5 2 1.1 14% 54% 30% Korea 1995–2000 5.6 0.7 3 1.9 13% 54% 34% Korea 2000–2005 5 1.4 2.8 0.7 28% 56% 14% Korea 2005–2010 4.4 0.9 2.2 1.3 20% 50% 30% Korea 2010–2015 3 1.2 1.7 0.2 40% 57% 7% Korea 2015–2019 2.8 -0.2 1.6 1.4 -7% 57% 50% Japan 1995–2000 1 -0.2 0.8 0.4 -20% 80% 40% Japan 2000–2005 1.2 0.2 0.4 0.7 17% 33% 58% Japan 2005–2010 0 0 0.2 -0.3 0% 0% 0% Japan 2010–2015 1 0.2 0 0.9 20% 0% 90% Japan 2015–2019 0.8 0.1 0.3 0.4 13% 38% 50% US 1995–2000 4.2 1.4 1.7 1.1 33% 40% 26% US 2000–2005 2.5 0.6 1.2 0.8 24% 48% 32% US 2005–2010 0.9 -0.1 0.8 0.1 -11% 89% 11% US 2010–2015 2.2 1 0.6 0.5 45% 27% 23% US 2015–2019 2.3 1 0.9 0.4 43% 39% 17% ASEAN 1995–2000 2.5 1.7 3.2 -2.3 68% 128% -92% ASEAN 2000–2005 5 1.6 2.2 1.3 32% 44% 26% ASEAN 2005–2010 5.1 1.7 3 0.4 33% 59% 8% ASEAN 2010–2015 4.8 1.4 3.4 0.1 29% 71% 2% ASEAN 2015–2019 4.8 1.4 3.2 0.2 29% 67% 4% 174 Appendix A9: Contribution of FDI sector towards Vietnam’s economy Value Ratio Year Total (Billion VND) State economy Private economy FDI economy Total (%) State economy Private economy FDI economy 2005 914000.84 343,883 431,548 138,570 100 37.62 47.22 15.16 2006 1061564.52 389,533 501,432 170,600 100 36.69 47.24 16.07 2007 1246769.29 440,687 594,617 211,465 100 35.35 47.69 16.96 2008 1616047.13 566,812 767,632 281,604 100 35.07 47.5 17.43 2009 1809148.95 628,074 867,810 313,265 100 34.72 47.97 17.31 2010 2739843.17 662,604 1,362,614 413,937 100 24.18 49.73 15.11 2011 3539881.31 834,970 1,797,178 544,774 100 23.59 50.77 15.39 2012 4073762.29 959,672 2,121,219 633,507 100 23.56 52.07 15.5 2013 4473655.6 1,045,291 2,280,493 760,130 100 23.3 50.98 16.99 2014 4937031.68 1,139,544 2,500,528 857,689 100 23.08 50.65 17.37 2015 5191323.73 1,185,894 2,628,289 906,511 100 22.84 50.63 17.46 2016 5639401 1,284,522 2,832,253 1,003,123 100 22.78 50.22 17.79 2017 6293904.55 1,404,435 3,145,811 1,170,973 100 22.31 49.98 18.6 2018 7009042.13 1,495,494 3,514,624 1,369,513 100 21.34 50.2 19.54 2019 7707200.29 1,587,127 3,895,948 1,534,823 100 20.59 50.6 19.91 2020 8044385.73 1,662,352 4,067,451 1,609,112 100 20.66 50.5 20 2021 8479666.5 1,796,228 4,243,095 1,697,904 100 21.18 50.04 20.02 175 Appendix A10: Over-15-year-old labor structure in terms of economic sectors Unit: thousand people Year Total State economy Non-state economy FDI sector % Contribution FDI 2000 37075.3 4358.2 32358.6 358.5 1 2001 38180.1 4474.4 33356.6 349.1 0.9 2002 39275.9 4633.5 34216.5 425.9 1.1 2003 40403.9 4919.1 34731.5 753.3 1.9 2004 41578.8 5031 35633 914.8 2.2 2005 42774.9 4967.4 36694.7 1112.8 2.6 2006 43980.3 4916 37742.3 1322 3 2007 45208 4988.4 38657.4 1562.2 3.5 2008 46460.8 5059.3 39707.1 1694.4 3.6 2009 47743.6 5040.6 41178.4 1524.6 3.2 2010 49124.4 5025.2 42370 1729.2 3.5 2011 50547.2 5024.8 43423.8 2098.6 4.2 2012 51690.5 5017.4 44423.3 2249.8 4.4 2013 52507.8 4994.9 44994.6 2518.3 4.8 2014 53030.6 4893.2 45269.3 2868.1 5.4 2015 53110.5 4779.9 45132.8 3197.8 6 2016 53345.5 4702.3 45052.2 3591 6.7 2017 53708.6 4595.4 44905.4 4207.8 7.8 2018 54282.5 4525.9 45215.4 4541.2 8.4 2019 54659.2 4226.2 45664.6 4768.4 8.7 2020 53609.6 4098.4 44777.4 4733.8 8.83 2021 49072 3951.7 40534 4586.3 9.35 176 Appendix A11: Vietnamese productivity Year Productivity (Milion VND/ People) Growth (%) 2005 21.4 0 2007 25.3 18% 2008 32 26% 2009 37.9 18% 2010 43.9 16% 2011 55 25% 2012 62.8 14% 2013 68.3 9% 2014 74.3 9% 2015 78.9 6% 2016 84.4 7% 2017 93.2 10% 2018 102.1 10% 2019 110.5 8% 2020 117.4 6% 177 Appendix A12: Export share in terms of industries in Vietnam 2005 2010 2015 2020 2021 Exports 56.3 65.3 84.7 104.2 104.2 Heavy industrial goods and minerals 20.3 20.3 38.5 55.1 55.1 Light industrial goods and handicrafts 23.1 30.1 33.9 38.4 38.4 Agricultural produce 7.7 9.6 7.7 6.3 6.3 Forest products 0.4 0.7 1.2 1.3 1.3 Seafood products 4.7 4.5 3.4 3.1 3.1 Non-monetary gold 0 0 0 0 0 178 Appendix A13: Number of businesses operating until December 31 of each year in terms of locality by Province/City and Year No Provinces 2017 2018 2019 2020 2021 1 Hồ Chí Minh 204,918 228,267 239,623 254,699 268,465 2 Hà Nội 133,981 143,119 155,940 165,875 178,493 3 Bình Dương 22,976 27,566 31,599 34,836 37,668 4 Đồng Nai 18,865 21,183 22,398 24,270 25,055 5 Đà Nẵng 18,417 20,375 22,566 23,666 24,703 6 Hải Phòng 21,598 21,613 19,918 20,195 19,806 7 Thanh Hóa 9,557 11,127 11,763 13,152 14,088 8 Bắc Ninh 5,674 6,398 7,069 12,769 13,944 9 Nghệ An 11,456 11,706 10,855 11,636 12,414 10 Bà Rịa - Vũng Tàu 8,956 9,611 10,097 10,946 11,393 179 Appendix A14: Employees’ average monthly income in operating enterprises with production and business results classified in terms of enterprise types divided by Enterprise types and Year Employees’ income 2010 2015 2016 2017 2018 2019 2020 Total number of 4,124 6,966 7,514 8,269 8,836 9,325 9,547 State enterprises 6,553 9,509 11,411 11,887 12,556 14,210 15,330 Private enterprises 2,950 4,588 4,515 5,599 5,369 5,821 5,221 Enterprises with foreign investment 4,252 7,502 8,504 9,035 9,764 10,066 10,516 180 Appendix A15: The number of enterprises in operation until December 31 of each year in terms of economic sectors The number of enterprises in terms of industry classification 2017 2018 2019 2020 2021 Total number of 654,633 714,755 758,610 811,538 857,551 Agriculture, Forestry and Fisheries 9,951 10,766 10,085 11,398 12,011 Industry and Construction 212,170 228,147 239,755 258,431 270,549 Service 432,512 475,842 508,770 541,709 574,991 Structure % Agriculture, Forestry and Fisheries 2% 2% 1% 1% 1% Industry and Construction 32% 32% 32% 32% 32% Service 66% 67% 67% 67% 67% 181 Appendix A16: Total factor productivity spillovers from FDI in manufacturing: the role of FDI’s market orientation 1. Fixed Effects Estimation Method 2. Random Effects Estimation Method F test that all u_i=0: F(87409, 89118) = 3.07 Prob > F = 0.0000 rho .68127524 (fraction of variance due to u_i) sigma_e .66359289 sigma_u .97018626 _cons 2.719611 .0199911 136.04 0.000 2.680428 2.758793 hhi -2.530509 .0880722 -28.73 0.000 -2.70313 -2.357888 technologygap -.154755 .0089031 -17.38 0.000 -.1722051 -.1373049 labourquality .0448815 .0033749 13.30 0.000 .0382667 .0514963 forAB1 -.0040275 .0022729 -1.77 0.076 -.0084825 .0004274 forward .0041677 .0124175 0.34 0.737 -.0201705 .0285059 backexportAB1 -.1165186 .0136725 -8.52 0.000 -.1433166 -.0897206 backexport2 -.4569167 .0575519 -7.94 0.000 -.5697179 -.3441155 backdomesAB1 .2259611 .0106533 21.21 0.000 .2050807 .2468414 backdomes1 .6385526 .0878987 7.26 0.000 .4662719 .8108333 horexportAB1 .1637251 .0149207 10.97 0.000 .1344807 .1929694 horexport2 .5057921 .0618648 8.18 0.000 .3845377 .6270464 hordomesAB1 -.7975797 .0133911 -59.56 0.000 -.8238262 -.7713331 hor_domestic1 -.2873066 .0108911 -26.38 0.000 -.308653 -.2659602 Ln_Ab .5105409 .0027394 186.37 0.000 .5051716 .5159101 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] corr(u_i, Xb) = 0.3109 Prob > F = 0.0000 F(14,89118) = 4345.50 overall = 0.5471 max = 4 between = 0.6195 avg = 2.0 within = 0.4057 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 87,410 Fixed-effects (within) regression Number of obs = 176,542 > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi, fe . xtreg Ln_TFP Ln_Ab hor_domestic1 hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 182 3. Hausman test rho .48866746 (fraction of variance due to u_i) sigma_e .66359289 sigma_u .64871915 _cons 3.643831 .0148878 244.75 0.000 3.614652 3.673011 hhi -2.540293 .0522023 -48.66 0.000 -2.642607 -2.437978 technologygap -.19632 .0075819 -25.89 0.000 -.2111804 -.1814597 labourquality -.0020074 .0022653 -0.89 0.376 -.0064474 .0024326 forAB1 -.0039723 .0021099 -1.88 0.060 -.0081078 .0001631 forward -.0642216 .0116055 -5.53 0.000 -.0869679 -.0414753 backexportAB1 -.2398176 .0119183 -20.12 0.000 -.263177 -.2164582 backexport2 -.7376189 .0503172 -14.66 0.000 -.8362389 -.6389989 backdomesAB1 .2972109 .0085209 34.88 0.000 .2805102 .3139115 backdomes1 1.051723 .0502994 20.91 0.000 .9531381 1.150308 horexportAB1 .3047544 .0129964 23.45 0.000 .2792819 .3302269 horexport2 .7518374 .0541405 13.89 0.000 .6457239 .8579508 hordomesAB1 -.9374829 .0104351 -89.84 0.000 -.9579354 -.9170304 hor_domestic1 -.386625 .0065098 -59.39 0.000 -.3993839 -.3738661 Ln_Ab .6393428 .0020045 318.96 0.000 .6354141 .6432715 Ln_TFP Coef. Std. Err. z P>|z| [95% Conf. Interval] corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(14) = 194488.62 overall = 0.5675 max = 4 between = 0.6523 avg = 2.0 within = 0.3997 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 87,410 Random-effects GLS regression Number of obs = 176,542 > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi, re . xtreg Ln_TFP Ln_Ab hor_domestic1 hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp Prob>chi2 = 0.0000 = 20325.78 chi2(14) = (b-B)'[(V_b-V_B)^(-1)](b-B) Test: Ho: difference in coefficients not systematic B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg hhi -2.530509 -2.540293 .0097835 .0709341 technology~p -.154755 -.19632 .041565 .0046669 labourqual~y .0448815 -.0020074 .0468889 .0025017 forAB1 -.0040275 -.0039723 -.0000552 .0008452 forward .0041677 -.0642216 .0683893 .0044167 backexpor~B1 -.1165186 -.2398176 .123299 .0067002 backexport2 -.4569167 -.7376189 .2807022 .0279356 backdomesAB1 .2259611 .2972109 -.0712498 .0063943 backdomes1 .6385526 1.051723 -.4131705 .0720844 horexportAB1 .1637251 .3047544 -.1410293 .0073293 horexport2 .5057921 .7518374 -.2460453 .0299342 hordomesAB1 -.7975797 -.9374829 .1399032 .0083923 hor_domest~1 -.2873066 -.386625 .0993184 .0087315 Ln_Ab .5105409 .6393428 -.1288019 .0018672 FE RE Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients . hausman FE RE 183 4. Test for Serial Correlation 5. Test for Heteroskedasticity 6. Regression results with domestic manufacturing enterprises Prob > F = 0.0000 F( 1, 20843) = 952.575 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data > backexportAB1 forward forAB1 labourquality technologygap hhi . xtserial Ln_Ab hor_domestic1 hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexport2 Prob>chi2 = 0.0000 chi2 (87410) = 5.1e+36 H0: sigma(i)^2 = sigma^2 for all i in fixed effect regression model Modified Wald test for groupwise heteroskedasticity . xttest3 rho .68930345 (fraction of variance due to u_i) sigma_e .63243095 sigma_u .94199831 _cons 3.225714 .0280688 114.92 0.000 3.1707 3.280729 2014 -.5871885 .0071476 -82.15 0.000 -.6011978 -.5731792 2013 -.0027022 .0061857 -0.44 0.662 -.0148262 .0094217 2012 .2423602 .0062135 39.01 0.000 .2301817 .2545387 nam hhi -2.099327 .1239816 -16.93 0.000 -2.34233 -1.856324 technologygap -.1148521 .0290654 -3.95 0.000 -.1718201 -.057884 labourquality .0387906 .0039516 9.82 0.000 .0310455 .0465357 forAB1 .012027 .0027477 4.38 0.000 .0066414 .0174126 forward .1552857 .0142965 10.86 0.000 .1272648 .1833067 backexportAB1 .0624045 .016214 3.85 0.000 .0306251 .0941839 backexport2 .2693714 .0624809 4.31 0.000 .1469093 .3918335 backdomesAB1 .1951248 .0178905 10.91 0.000 .1600594 .2301901 backdomes1 -.2731826 .1323126 -2.06 0.039 -.5325144 -.0138508 horexportAB1 -.0677401 .0175209 -3.87 0.000 -.102081 -.0333993 horexport2 -.2450879 .0666132 -3.68 0.000 -.3756494 -.1145265 hordomesAB1 -.8697116 .0214379 -40.57 0.000 -.9117297 -.8276935 hor_domestic1 -.206604 .0158822 -13.01 0.000 -.237733 -.1754751 Ln_Ab .6403022 .0046833 136.72 0.000 .6311229 .6494814 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 82,465 clusters in madn) corr(u_i, Xb) = 0.0965 Prob > F = 0.0000 F(17,82464) = 2047.22 overall = 0.5461 max = 4 between = 0.5900 avg = 2.0 within = 0.4989 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 82,465 Fixed-effects (within) regression Number of obs = 162,924 > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 ,fe r . xtreg Ln_TFP Ln_Ab hor_domestic1 hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 184 7. Regression results for domestic manufacturing enterprises engaged in exports. rho .96027006 (fraction of variance due to u_i) sigma_e .44507848 sigma_u 2.1881361 _cons 1.025189 .1695909 6.05 0.000 .6927797 1.357598 2014 -.1100312 .0196652 -5.60 0.000 -.1485762 -.0714862 2013 .0374622 .0203121 1.84 0.065 -.002351 .0772753 2012 -.1191692 .0961744 -1.24 0.215 -.3076774 .069339 nam hhi -.916977 .3765014 -2.44 0.015 -1.654944 -.1790096 technologygap -3.892457 1.270251 -3.06 0.002 -6.382232 -1.402683 labourquality .038325 .0170475 2.25 0.025 .0049107 .0717392 forAB1 .0440452 .0101407 4.34 0.000 .0241688 .0639217 forward .2131491 .0459987 4.63 0.000 .1229885 .3033096 backexportAB1 .2230895 .0689102 3.24 0.001 .088021 .358158 backexport2 .7464733 .2140343 3.49 0.000 .3269521 1.165995 backdomesAB1 -.2373426 .0419272 -5.66 0.000 -.3195225 -.1551626 backdomes1 -1.662685 .3144979 -5.29 0.000 -2.279122 -1.046249 horexportAB1 -.2310989 .0752543 -3.07 0.002 -.3786022 -.0835955 horexport2 -.7550556 .2180836 -3.46 0.001 -1.182514 -.3275975 hordomesAB1 .3140541 .0888648 3.53 0.000 .1398732 .488235 hor_domestic1 .1762927 .0456199 3.86 0.000 .0868747 .2657107 Ln_Ab .1564429 .0306687 5.10 0.000 .0963302 .2165556 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 23,366 clusters in madn) corr(u_i, Xb) = -0.6165 Prob > F = 0.0000 F(17,23365) = 23.91 overall = 0.1336 max = 4 between = 0.1216 avg = 1.2 within = 0.2441 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 23,366 Fixed-effects (within) regression Number of obs = 27,323 > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 & export1==1 ,fe r . xtreg Ln_TFP Ln_Ab hor_domestic1 hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 185 8. Regression results for domestic manufacturing enterprises engaged in exports in industrial zone rho .95366849 (fraction of variance due to u_i) sigma_e .47260809 sigma_u 2.1441819 _cons 1.013982 .2098006 4.83 0.000 .6027574 1.425206 2014 -.1895005 .0249161 -7.61 0.000 -.2383377 -.1406632 2013 -.0258445 .0265009 -0.98 0.329 -.0777882 .0260992 2012 -.0674349 .0995489 -0.68 0.498 -.2625579 .1276882 nam hhi -1.326316 .4317657 -3.07 0.002 -2.172608 -.4800239 technologygap -3.659181 1.122269 -3.26 0.001 -5.858909 -1.459452 labourquality .039351 .0202703 1.94 0.052 -.0003803 .0790824 forAB1 .0604694 .0134542 4.49 0.000 .0340982 .0868406 forward .2907938 .0623837 4.66 0.000 .1685173 .4130704 backexportAB1 .3810321 .0851403 4.48 0.000 .214151 .5479131 backexport2 1.245868 .2933112 4.25 0.000 .670957 1.820779 backdomesAB1 -.3691735 .0502498 -7.35 0.000 -.4676667 -.2706803 backdomes1 -2.142975 .3759778 -5.70 0.000 -2.879918 -1.406031 horexportAB1 -.4095144 .0912995 -4.49 0.000 -.588468 -.2305607 horexport2 -1.301886 .3003484 -4.33 0.000 -1.89059 -.713181 hordomesAB1 .5093971 .1079234 4.72 0.000 .2978594 .7209348 hor_domestic1 .2638699 .0569255 4.64 0.000 .1522919 .3754479 Ln_Ab .1728073 .0380382 4.54 0.000 .0982497 .2473649 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 21,966 clusters in madn) corr(u_i, Xb) = -0.6040 Prob > F = 0.0000 F(17,21965) = 22.27 overall = 0.1444 max = 4 between = 0.1332 avg = 1.1 within = 0.2947 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 21,966 Fixed-effects (within) regression Number of obs = 24,727 > gnghiep==1 ,fe r > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 & export1==1 & con . xtreg Ln_TFP Ln_Ab hor_domestic1 hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 186 9. Regression results for domestic manufacturing enterprises engaged in exports, located outside of industrial zones. rho .97147448 (fraction of variance due to u_i) sigma_e .30565325 sigma_u 1.7837252 _cons 1.466247 .1607909 9.12 0.000 1.150874 1.78162 2014 .0451746 .0261587 1.73 0.084 -.0061327 .0964819 2013 .1195744 .0275564 4.34 0.000 .0655256 .1736231 2012 .3287882 .2390003 1.38 0.169 -.1399834 .7975597 nam hhi 1.436742 .7417942 1.94 0.053 -.0182021 2.891686 technologygap -158.367 27.8594 -5.68 0.000 -213.01 -103.724 labourquality -.0200858 .0319157 -0.63 0.529 -.0826849 .0425133 forAB1 -.014162 .0143904 -0.98 0.325 -.0423872 .0140632 forward -.0484669 .059852 -0.81 0.418 -.1658597 .068926 backexportAB1 -.0387505 .1046172 -0.37 0.711 -.243945 .1664441 backexport2 -.394439 .3478854 -1.13 0.257 -1.076776 .2878981 backdomesAB1 -.0366411 .0682492 -0.54 0.591 -.170504 .0972218 backdomes1 -1.50636 .3551374 -4.24 0.000 -2.202921 -.8097991 horexportAB1 .072271 .1160284 0.62 0.533 -.1553054 .2998474 horexport2 .5667843 .3668198 1.55 0.123 -.1526904 1.286259 hordomesAB1 .0631289 .1167545 0.54 0.589 -.1658715 .2921293 hor_domestic1 .1222149 .0475979 2.57 0.010 .0288572 .2155727 Ln_Ab .0541038 .0302599 1.79 0.074 -.0052476 .1134552 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 1,672 clusters in madn) corr(u_i, Xb) = -0.8437 Prob > F = 0.0000 F(17,1671) = 9.25 overall = 0.0761 max = 4 between = 0.0853 avg = 1.6 within = 0.2885 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 1,672 Fixed-effects (within) regression Number of obs = 2,596 > gnghiep==0 ,fe r > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 & export1==1 & con . xtreg Ln_TFP Ln_Ab hor_domestic1 hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 187 10. Regression results for domestic manufacturing enterprises with fewer than 100 employees. rho .67093563 (fraction of variance due to u_i) sigma_e .65486146 sigma_u .93508142 _cons 3.333746 .0303158 109.97 0.000 3.274327 3.393165 2014 -.6322769 .0078894 -80.14 0.000 -.6477402 -.6168136 2013 .0144708 .0072306 2.00 0.045 .0002989 .0286426 2012 .265651 .0068685 38.68 0.000 .2521889 .2791131 nam hhi -2.222556 .1422867 -15.62 0.000 -2.501437 -1.943675 technologygap -.1014633 .02798 -3.63 0.000 -.1563039 -.0466227 labourquality .0321059 .0042891 7.49 0.000 .0236994 .0405125 forAB1 .0054787 .0029158 1.88 0.060 -.0002363 .0111936 forward .1273767 .0156448 8.14 0.000 .0967129 .1580405 backexportAB1 .0625663 .017785 3.52 0.000 .0277078 .0974249 backexport2 .1526644 .0722698 2.11 0.035 .0110158 .2943129 backdomesAB1 .1751167 .020488 8.55 0.000 .1349604 .215273 backdomes1 -.3292828 .1495318 -2.20 0.028 -.6223644 -.0362013 horexportAB1 -.0688096 .0193783 -3.55 0.000 -.1067909 -.0308283 horexport2 -.1127223 .0784372 -1.44 0.151 -.2664588 .0410143 hordomesAB1 -.842437 .0245443 -34.32 0.000 -.8905437 -.7943303 hor_domestic -2.023594 .1807477 -11.20 0.000 -2.377859 -1.66933 Ln_Ab .6627657 .0048863 135.64 0.000 .6531886 .6723428 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 76,991 clusters in madn) corr(u_i, Xb) = 0.0636 Prob > F = 0.0000 F(17,76990) = 2070.76 overall = 0.5529 max = 4 between = 0.5934 avg = 1.9 within = 0.5226 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 76,991 Fixed-effects (within) regression Number of obs = 144,505 > <=100 ,fe r > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 & laodong_cuoi . xtreg Ln_TFP Ln_Ab hor_domestic hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 188 11. Regression results for domestic manufacturing enterprises with higher than 100 employees. rho .81190589 (fraction of variance due to u_i) sigma_e .37274327 sigma_u .77441732 _cons 1.661832 .0787897 21.09 0.000 1.507386 1.816279 2014 -.1299962 .0145536 -8.93 0.000 -.1585248 -.1014677 2013 -.0014436 .0115822 -0.12 0.901 -.0241473 .0212602 2012 .114586 .0139707 8.20 0.000 .0872002 .1419718 nam hhi -.4693312 .1794759 -2.62 0.009 -.8211467 -.1175156 technologygap -.5362111 .075378 -7.11 0.000 -.6839699 -.3884523 labourquality .1031133 .0120054 8.59 0.000 .0795799 .1266467 forAB1 .0174767 .0056728 3.08 0.002 .0063567 .0285966 forward .1047649 .025999 4.03 0.000 .0538008 .1557291 backexportAB1 -.064938 .0332613 -1.95 0.051 -.130138 .0002621 backexport2 .0784408 .1060415 0.74 0.459 -.1294259 .2863075 backdomesAB1 .0416601 .024999 1.67 0.096 -.007344 .0906641 backdomes1 -.4648895 .2775293 -1.68 0.094 -1.008913 .0791341 horexportAB1 .0870541 .0353226 2.46 0.014 .0178135 .1562948 horexport2 -.0354865 .1028235 -0.35 0.730 -.2370451 .166072 hordomesAB1 -.360661 .0380982 -9.47 0.000 -.4353426 -.2859794 hor_domestic -.4500864 .3257489 -1.38 0.167 -1.088632 .1884591 Ln_Ab .2623193 .0151102 17.36 0.000 .2326997 .2919389 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 8,648 clusters in madn) corr(u_i, Xb) = 0.1624 Prob > F = 0.0000 F(17,8647) = 51.01 overall = 0.2838 max = 4 between = 0.3002 avg = 2.1 within = 0.2177 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 8,648 Fixed-effects (within) regression Number of obs = 18,419 > > 100 ,fe r > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 & laodong_cuoi . xtreg Ln_TFP Ln_Ab hor_domestic hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 189 12. Regression results for domestic manufacturing enterprises in the high-tech industry. rho .64911018 (fraction of variance due to u_i) sigma_e .44550813 sigma_u .60593977 _cons 3.118525 .1181933 26.38 0.000 2.88683 3.35022 2014 .2598344 .0209378 12.41 0.000 .2187899 .3008788 2013 -.8831212 .0363613 -24.29 0.000 -.9544003 -.811842 2012 .2586283 .0240804 10.74 0.000 .2114233 .3058333 nam hhi -1.093244 .1384118 -7.90 0.000 -1.364573 -.8219149 technologygap -.3473149 .1637945 -2.12 0.034 -.668402 -.0262278 labourquality .0302578 .0096804 3.13 0.002 .0112812 .0492344 forAB1 .0429065 .0114506 3.75 0.000 .0204599 .0653531 forward -.9110923 .0709238 -12.85 0.000 -1.050124 -.7720601 backexportAB1 .2191326 .0739097 2.96 0.003 .0742472 .364018 backexport2 -.3077886 .239298 -1.29 0.198 -.7768855 .1613083 backdomesAB1 .1154853 .0551541 2.09 0.036 .0073665 .2236041 backdomes1 2.119358 .2117423 10.01 0.000 1.704279 2.534437 horexportAB1 -.2972723 .0794144 -3.74 0.000 -.4529487 -.1415959 horexport2 .2254556 .2529871 0.89 0.373 -.2704761 .7213874 hordomesAB1 -.5960233 .1249462 -4.77 0.000 -.8409558 -.3510907 hor_domestic -3.011847 .3526747 -8.54 0.000 -3.703197 -2.320497 Ln_Ab .8746659 .0391728 22.33 0.000 .7978754 .9514565 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 6,976 clusters in madn) corr(u_i, Xb) = 0.3156 Prob > F = 0.0000 F(17,6975) = 336.68 overall = 0.7743 max = 4 between = 0.8166 avg = 2.1 within = 0.6423 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 6,976 Fixed-effects (within) regression Number of obs = 14,581 > anh ==21|nganh25,fe r > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 & nganh==20| ng . xtreg Ln_TFP Ln_Ab hor_domestic hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 190 13. Regression results for domestic manufacturing enterprises in the low-tech industry rho .70380012 (fraction of variance due to u_i) sigma_e .61180201 sigma_u .94306827 _cons 3.250212 .0278898 116.54 0.000 3.195549 3.304876 2014 -.5507479 .0077768 -70.82 0.000 -.5659904 -.5355054 2013 -.0098216 .0068305 -1.44 0.150 -.0232094 .0035663 2012 .2470868 .0068638 36.00 0.000 .2336339 .2605398 nam hhi -2.551018 .1551461 -16.44 0.000 -2.855104 -2.246932 technologygap -.0670705 .0185122 -3.62 0.000 -.1033544 -.0307866 labourquality .0278419 .0037794 7.37 0.000 .0204343 .0352495 forAB1 .0010494 .0026817 0.39 0.696 -.0042067 .0063055 forward .0996975 .0140463 7.10 0.000 .0721669 .1272282 backexportAB1 .0021142 .016847 0.13 0.900 -.0309059 .0351344 backexport2 -.0285038 .0660992 -0.43 0.666 -.1580581 .1010506 backdomesAB1 .1467029 .027513 5.33 0.000 .0927775 .2006282 backdomes1 -1.25279 .2040134 -6.14 0.000 -1.652655 -.8529239 horexportAB1 -.0143878 .0183492 -0.78 0.433 -.0503521 .0215766 horexport2 .0107172 .0716031 0.15 0.881 -.1296248 .1510591 hordomesAB1 -.8078949 .0266168 -30.35 0.000 -.8600639 -.755726 hor_domestic -.4658805 .2218174 -2.10 0.036 -.9006421 -.0311189 Ln_Ab .6605507 .0046233 142.87 0.000 .651489 .6696124 Ln_TFP Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 70,602 clusters in madn) corr(u_i, Xb) = 0.0151 Prob > F = 0.0000 F(17,70601) = 1897.26 overall = 0.5606 max = 4 between = 0.5968 avg = 2.0 within = 0.5353 min = 1 R-sq: Obs per group: Group variable: madn Number of groups = 70,602 Fixed-effects (within) regression Number of obs = 138,690 > ganh > 21 & nganh 30 ,fe r > ort2 backexportAB1 forward forAB1 labourquality technologygap hhi i.nam if sohuu==0 & nganh < 20 |n . xtreg Ln_TFP Ln_Ab hor_domestic hordomesAB1 horexport2 horexportAB1 backdomes1 backdomesAB1 backexp 191 Appendix A17: Total factor productivity spillovers from FDI in manufacturing: the role of domestic firms’ absorption 1. Fixed Effects Estimation Method rho .69801476 (fraction of variance due to u_i) sigma_e 1.2724599 sigma_u 1.9345659 _cons 1.718591 .0620489 27.70 0.000 1.596977 1.840205 hhi .1667539 .025267 6.60 0.000 .1172313 .2162765 technologygap -.5402557 .0650122 -8.31 0.000 -.6676776 -.4128339 scale 5.520026 1.631526 3.38 0.001 2.322285 8.717766 fs1export1 -.1534613 .0694835 -2.21 0.027 -.2896469 -.0172758 bs1export1 .2740409 .1287256 2.13 0.033 .0217427 .5263391 hs1export1 .4450559 .1447406 3.07 0.002 .1613689 .7287429 fs1 -.0359186 .0267291 -1.34 0.179 -.0883069 .0164697 bs1 -.2840863 .0605951 -4.69 0.000 -.4028507 -.1653218 hs1 -.2703354 .0687417 -3.93 0.000 -.4050669 -.1356038 export1 .3792597 .0099569 38.09 0.000 .3597446 .3987749 labourquality .0420799 .0022163 18.99 0.000 .037736 .0464237 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Robust (Std. Err. adjusted for 489,347 clusters in ID) corr(u_i, Xb) = 0.1179 Prob > F = 0.0000 F(11,489346) = 371.33 overall = 0.0489 max = 6 between = 0.0509 avg = 2.3 within = 0.0219 min = 1 R-sq: Obs per group: Group variable: ID Number of groups = 489,347 Fixed-effects (within) regression Number of obs = 1,104,994 > nologygap hhi if sohuu_16==0 & nam_1 <2016, fe r . xtreg lnTFP2 labourquality export1 hs1 bs1 fs1 hs1export1 bs1export1 fs1export1 scale tech 192 2. Random Effects Estimation Method 3. Hausman test rho .61688215 (fraction of variance due to u_i) sigma_e 1.2724599 sigma_u 1.6146522 _cons 1.77953 .0059609 298.54 0.000 1.767847 1.791213 hhi -.3839234 .0227381 -16.88 0.000 -.4284892 -.3393576 technologygap -.6231247 .0046973 -132.65 0.000 -.6323313 -.613918 scale 10.21084 .357681 28.55 0.000 9.509797 10.91188 fs1export1 -.1464495 .0723117 -2.03 0.043 -.2881779 -.0047212 bs1export1 .3244973 .1272696 2.55 0.011 .0750536 .573941 hs1export1 .9882278 .1450164 6.81 0.000 .7040009 1.272455 fs1 .0005281 .0179316 0.03 0.977 -.0346172 .0356734 bs1 -.584503 .040107 -14.57 0.000 -.6631113 -.5058946 hs1 .1290143 .0453879 2.84 0.004 .0400557 .2179729 export1 .8377975 .009447 88.68 0.000 .8192818 .8563132 labourquality .1413505 .0018092 78.13 0.000 .1378044 .1448965 lnTFP2 Coef. Std. Err. z P>|z| [95% Conf. Interval] corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(11) = 42814.37 overall = 0.0689 max = 6 between = 0.0848 avg = 2.3 within = 0.0185 min = 1 R-sq: Obs per group: Group variable: ID Number of groups = 489,347 Random-effects GLS regression Number of obs = 1,104,994 > nologygap hhi if sohuu_16==0 & nam_1 <2016, re . xtreg lnTFP2 labourquality export1 hs1 bs1 fs1 hs1export1 bs1export1 fs1export1 scale tech Prob>chi2 = 0.0000 = 29157.30 chi2(11) = (b-B)'[(V_b-V_B)^(-1)](b-B) Test: Ho: difference in coefficients not systematic B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg hhi .1667539 -.3839234 .5506773 .0106864 technology~p -.5402557 -.6231247 .082869 .003146 scale 5.520026 10.21084 -4.690813 .2733536 fs1export1 -.1534613 -.1464495 -.0070118 .0380725 bs1export1 .2740409 .3244973 -.0504564 .0717424 hs1export1 .4450559 .9882278 -.5431719 .0827647 fs1 -.0359186 .0005281 -.0364466 .0144054 bs1 -.2840863 -.584503 .3004167 .0320617 hs1 -.2703354 .1290143 -.3993497 .03665 export1 .3792597 .8377975 -.4585378 .0046812 labourqual~y .0420799 .1413505 -.0992706 .0009147 FE1 RE1 Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients . hausman FE1 RE1 193 4. Test for Serial Correlation 5. Test for Heteroskedasticity 6. Regression results with Driscoll-Kraay standard errors Prob > F = 0.0000 F( 1, 257483) = 2783.459 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data > echnologygap hhi . xtserial lnTFP2 labourquality export1 hs1 bs1 fs1 hs1export1 bs1export1 fs1export1 scale t Prob>chi2 = 0.0000 chi2 (489347) = 4.2e+40 H0: sigma(i)^2 = sigma^2 for all i in fixed effect regression model Modified Wald test for groupwise heteroskedasticity . xttest3 _cons 1.718583 .0296687 57.93 0.000 1.660433 1.776732 hhi .1668243 .1774629 0.94 0.347 -.1809974 .514646 technologygap -.5402563 .0518135 -10.43 0.000 -.641809 -.4387035 scale 5.520015 1.985714 2.78 0.005 1.628078 9.411952 fs1export1 -.1534678 .0518095 -2.96 0.003 -.2550128 -.0519228 bs1export1 .2739808 .0848128 3.23 0.001 .1077503 .4402112 hs1export1 .4451127 .1823119 2.44 0.015 .0877871 .8024382 fs1 -.0359118 .112358 -0.32 0.749 -.2561299 .1843064 bs1 -.2839676 .1657472 -1.71 0.087 -.608827 .0408918 hs1 -.2704481 .2786909 -0.97 0.332 -.8166736 .2757775 export1 .3792618 .0915902 4.14 0.000 .1997478 .5587757 labourquality .0420772 .0208055 2.02 0.043 .0012991 .0828554 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Drisc/Kraay within R-squared = 0.0219 maximum lag: 2 Prob > F = 0.0000 Group variable (i): ID F( 11,489347) = 236.00 Method: Fixed-effects regression Number of groups = 489348 Regression with Driscoll-Kraay standard errors Number of obs = 1104998 > nologygap hhi if sohuu_16==0 & nam_1 <2016, fe . xtscc lnTFP2 labourquality export1 hs1 bs1 fs1 hs1export1 bs1export1 fs1export1 scale tech 194 7. Regression results using GMM (Generalized Method of Moments) estimation. 195 Estimated results of export ability and spillover effects 196 8. Fixed Effects Estimation Method 9. Random Effects Estimation Method F test that all u_i=0: F(534138, 624586) = 1.53 Prob > F = 0.0000 rho .48939545 (fraction of variance due to u_i) sigma_e 2.564435 sigma_u 2.5106104 _cons 2.968003 .0074337 399.26 0.000 2.953433 2.982573 fs1xk3 -.0387482 .0217932 -1.78 0.075 -.0814622 .0039658 bs1xk3 -.0023791 .0414502 -0.06 0.954 -.0836202 .078862 hs1xk3 .0597598 .0529081 1.13 0.259 -.0439385 .163458 scale 30.51423 1.332698 22.90 0.000 27.90219 33.12628 technologygap -.0237127 .0001793 -132.26 0.000 -.0240642 -.0233613 hhi -4.675948 .0721364 -64.82 0.000 -4.817333 -4.534563 fs1 .6622176 .0409403 16.18 0.000 .581976 .7424592 bs1 .0648765 .0878701 0.74 0.460 -.1073461 .2370992 hs1 -.2778513 .1007285 -2.76 0.006 -.4752759 -.0804268 xk3 -.0053819 .0035506 -1.52 0.130 -.0123409 .0015771 labourquality .5696095 .0048928 116.42 0.000 .5600198 .5791993 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] corr(u_i, Xb) = 0.0468 Prob > F = 0.0000 F(11,624586) = 3622.50 overall = 0.0785 max = 7 between = 0.0826 avg = 2.2 within = 0.0600 min = 1 R-sq: Obs per group: Group variable: ID Number of groups = 534,139 Fixed-effects (within) regression Number of obs = 1,158,736 . xtreg lnTFP2 labourquality xk3 hs1 bs1 fs1 hhi technologygap scale hs1xk3 bs1xk3 fs1xk3,fe rho .27022909 (fraction of variance due to u_i) sigma_e 2.564435 sigma_u 1.5605025 _cons 3.061875 .0058921 519.66 0.000 3.050327 3.073423 fs1xk3 -.0780969 .0171101 -4.56 0.000 -.111632 -.0445617 bs1xk3 .0352282 .0313374 1.12 0.261 -.0261921 .0966484 hs1xk3 .084146 .0379113 2.22 0.026 .0098412 .1584508 scale 39.82811 .7323943 54.38 0.000 38.39265 41.26358 technologygap -.0215637 .0001291 -167.05 0.000 -.0218167 -.0213107 hhi -5.635538 .0559125 -100.79 0.000 -5.745125 -5.525952 fs1 .5583557 .0249075 22.42 0.000 .509538 .6071735 bs1 -.157252 .0532868 -2.95 0.003 -.2616921 -.0528118 hs1 .7233739 .0607741 11.90 0.000 .6042587 .842489 xk3 .0016942 .0027906 0.61 0.544 -.0037752 .0071636 labourquality .705633 .0035444 199.08 0.000 .698686 .7125799 lnTFP2 Coef. Std. Err. z P>|z| [95% Conf. Interval] corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(11) = 92896.93 overall = 0.0826 max = 7 between = 0.0908 avg = 2.2 within = 0.0582 min = 1 R-sq: Obs per group: Group variable: ID Number of groups = 534,139 Random-effects GLS regression Number of obs = 1,158,736 . xtreg lnTFP2 labourquality xk3 hs1 bs1 fs1 hhi technologygap scale hs1xk3 bs1xk3 fs1xk3,re 197 10. Hausman test 11. Test for Serial Correlation 12. Test for Heteroskedasticity Prob>chi2 = 0.0000 = 3594.60 chi2(11) = (b-B)'[(V_b-V_B)^(-1)](b-B) Test: Ho: difference in coefficients not systematic B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg fs1xk3 -.0387482 -.0780969 .0393487 .0134978 bs1xk3 -.0023791 .0352282 -.0376073 .0271309 hs1xk3 .0597598 .084146 -.0243862 .0369054 scale 30.51423 39.82811 -9.31388 1.113411 technology~p -.0237127 -.0215637 -.0021491 .0001244 hhi -4.675948 -5.635538 .9595902 .0455791 fs1 .6622176 .5583557 .1038619 .0324919 bs1 .0648765 -.157252 .2221285 .069869 hs1 -.2778513 .7233739 -1.001225 .0803289 xk3 -.0053819 .0016942 -.007076 .0021953 labourqual~y .5696095 .705633 -.1360234 .0033729 FE2 RE2 Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients . hausman FE2 RE2 Prob > F = 0.0000 F( 1, 112105) = 717.475 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data . xtserial lnTFP2 labourquality xk3 hs1 bs1 fs1 hhi technologygap scale hs1xk3 bs1xk3 fs1xk3 chi2 (534139) = 1.6e+42 H0: sigma(i)^2 = sigma^2 for all i in fixed effect regression model Modified Wald test for groupwise heteroskedasticity . xttest3 198 13. Regression results with Driscoll-Kraay standard errors _cons 3.4454 .0553666 62.23 0.000 3.33688 3.553921 scale 4.691518 1.671864 2.81 0.005 1.414593 7.968442 technologygap -.0746736 .0028428 -26.27 0.000 -.0802457 -.0691015 hhi -.7589196 .280013 -2.71 0.007 -1.307757 -.2100824 fs1xk3 -.0070641 .0147524 -0.48 0.632 -.0359795 .0218512 bs1xk3 -.1657138 .0952589 -1.74 0.082 -.3524253 .0209978 hs1xk3 .2920286 .1401943 2.08 0.037 .017242 .5668153 fs1 -.0044794 .0947464 -0.05 0.962 -.1901864 .1812275 bs1 .5592702 .2138084 2.62 0.009 .1401969 .9783436 hs1 -.545393 .2417155 -2.26 0.024 -1.019165 -.0716205 xk3 .0010251 .0050437 0.20 0.839 -.0088607 .0109108 labourquality .1982615 .0506641 3.91 0.000 .0989576 .2975653 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Drisc/Kraay within R-squared = 0.1529 maximum lag: 2 Prob > F = 0.0000 Group variable (i): ID F( 11, 30412) = 118.40 Method: Fixed-effects regression Number of groups = 30413 Regression with Driscoll-Kraay standard errors Number of obs = 36930 > f export1==1 & w>1 & sohuu_16==0,fe . xtscc lnTFP2 labourquality xk3 hs1 bs1 fs1 hs1xk3 bs1xk3 fs1xk3 hhi technologygap scale i 199 14. Regression results using GMM (Generalized Method of Moments) estimation. 200 201 Appendix A18: Total factor productivity spillovers from FDI in manufacturing: the role of provincial institution. 1. Fixed Effects Estimation Method 2. Random Effects Estimation Method F test that all u_i=0: F(61570, 74) = 11.48 Prob > F = 0.0000 rho .93279899 (fraction of variance due to u_i) sigma_e .02143869 sigma_u .0798738 _cons .0371701 .072669 0.51 0.611 -.1076262 .1819663 HHI .0084495 .0033013 2.56 0.013 .0018716 .0150274 scale2 .0448647 .0088625 5.06 0.000 .0272057 .0625237 technologygap1 -.5771624 .1854025 -3.11 0.003 -.946585 -.2077398 papi .0021119 .0017816 1.19 0.240 -.0014379 .0056618 f1papi .0011083 .0147566 0.08 0.940 -.0282947 .0305114 hpapi -.0004215 .0003775 -1.12 0.268 -.0011737 .0003308 vertical -.0019485 .5784988 -0.00 0.997 -1.154632 1.150735 horizontal1 -.0026256 .0190073 -0.14 0.891 -.0404984 .0352472 labourquality .0236303 .0036422 6.49 0.000 .0163729 .0308876 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] corr(u_i, Xb) = -0.3903 Prob > F = 0.0000 F(9,74) = 14.21 overall = 0.0194 max = 2 between = 0.0193 avg = 1.0 within = 0.6334 min = 1 R-sq: Obs per group: Group variable: ID Number of groups = 61,571 Fixed-effects (within) regression Number of obs = 61,654 > u_16==0 , fe . xtreg lnTFP2 labourquality horizontal1 vertical hpapi f1papi papi technologygap1 scale2 HHI if sohu rho .91284784 (fraction of variance due to u_i) sigma_e .02143869 sigma_u .06938384 _cons .1107025 .0098089 11.29 0.000 .0914773 .1299276 HHI .0043263 .000296 14.61 0.000 .003746 .0049065 scale2 .0053481 .0004034 13.26 0.000 .0045575 .0061386 technologygap1 .9967443 .0803081 12.41 0.000 .8393434 1.154145 papi .0002289 .0002657 0.86 0.389 -.0002919 .0007497 f1papi .0000812 .0010652 0.08 0.939 -.0020066 .002169 hpapi -.0002831 .0000663 -4.27 0.000 -.0004129 -.0001532 vertical -.0099259 .0393546 -0.25 0.801 -.0870596 .0672078 horizontal1 .00613 .0022461 2.73 0.006 .0017278 .0105322 labourquality .0168617 .0003946 42.73 0.000 .0160882 .0176352 lnTFP2 Coef. Std. Err. z P>|z| [95% Conf. Interval] corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(9) = 2798.62 overall = 0.0434 max = 2 between = 0.0435 avg = 1.0 within = 0.1033 min = 1 R-sq: Obs per group: Group variable: ID Number of groups = 61,571 Random-effects GLS regression Number of obs = 61,654 > u_16==0 , re . xtreg lnTFP2 labourquality horizontal1 vertical hpapi f1papi papi technologygap1 scale2 HHI if sohu 202 3. Hausman test 4. Test for Heteroskedasticity 5. Regression results with Driscoll-Kraay standard errors Prob>chi2 = 0.0000 = 137.98 chi2(9) = (b-B)'[(V_b-V_B)^(-1)](b-B) Test: Ho: difference in coefficients not systematic B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg HHI .0084495 .0043263 .0041232 .003288 scale2 .0448647 .0053481 .0395167 .0088534 technology~1 -.5771624 .9967443 -1.573907 .1671069 papi .0021119 .0002289 .001883 .0017616 f1papi .0011083 .0000812 .0010271 .0147181 hpapi -.0004215 -.0002831 -.0001384 .0003717 vertical -.0019485 -.0099259 .0079774 .5771586 horizontal1 -.0026256 .00613 -.0087557 .0188741 labourqual~y .0236303 .0168617 .0067686 .0036208 FE RE Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients . hausman FE RE Prob>chi2 = 0.0000 chi2 (61571) = 1.2e+31 H0: sigma(i)^2 = sigma^2 for all i in fixed effect regression model Modified Wald test for groupwise heteroskedasticity . xttest3 . _cons -.397578 .0033182 -119.82 0.000 -.4040818 -.3910742 HHI .0093174 .0010275 9.07 0.000 .0073035 .0113313 scale2 .0296108 .0031735 9.33 0.000 .0233907 .0358309 technologygap1 -.5135189 .0345144 -14.88 0.000 -.5811673 -.4458705 papi .0123293 .0003846 32.06 0.000 .0115755 .013083 f1papi -.0214378 .0038719 -5.54 0.000 -.0290266 -.0138489 hpapi -.0017618 .0002783 -6.33 0.000 -.0023072 -.0012163 vertical .8482849 .1473103 5.76 0.000 .5595563 1.137013 horizontal1 -.0170831 .0058175 -2.94 0.003 -.0284855 -.0056808 labourquality .0465572 .0061803 7.53 0.000 .0344437 .0586706 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Drisc/Kraay within R-squared = 0.1589 maximum lag: 1 Prob > F = 0.0000 Group variable (i): ID F( 9, 61571) = 7.01e+10 Method: Fixed-effects regression Number of groups = 61572 Regression with Driscoll-Kraay standard errors Number of obs = 61656 > u_16==0 , fe . xtscc lnTFP2 labourquality horizontal1 vertical hpapi f1papi papi technologygap1 scale2 HHI if sohu 203 6. Regression results using Driscoll-Kraay standard errors for enterprises with fewer than 200 employees 7. Regression results using Driscoll-Kraay standard errors for enterprises with TFP greater than 75% of the sample _cons -.531728 .0428778 -12.40 0.000 -.6157688 -.4476873 HHI .0104649 .003207 3.26 0.001 .0041792 .0167507 scale2 .0985776 .0174634 5.64 0.000 .0643492 .132806 technologygap1 -.4763747 .0573766 -8.30 0.000 -.5888332 -.3639163 papi .015287 .0014951 10.22 0.000 .0123565 .0182175 f1papi -.0194797 .0154515 -1.26 0.207 -.0497647 .0108053 hpapi -.0039054 .0006753 -5.78 0.000 -.005229 -.0025819 vertical .7972944 .5977238 1.33 0.182 -.3742473 1.968836 horizontal1 -.0279036 .0063012 -4.43 0.000 -.040254 -.0155533 labourquality .0598313 .011113 5.38 0.000 .0380498 .0816128 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Drisc/Kraay within R-squared = 0.1544 maximum lag: 1 Prob > F = 0.0666 Group variable (i): ID F( 9, 57505) = 1.78 Method: Fixed-effects regression Number of groups = 57506 Regression with Driscoll-Kraay standard errors Number of obs = 57567 > u_16==0 & laodong_8<200 , fe . xtscc lnTFP2 labourquality horizontal1 vertical hpapi f1papi papi technologygap1 scale2 HHI if sohu _cons .1544161 .0071708 21.53 0.000 .1403607 .1684716 HHI .0053359 .0009589 5.56 0.000 .0034564 .0072154 scale2 .0589109 .0002614 225.36 0.000 .0583985 .0594233 technologygap1 -1.231672 .3812199 -3.23 0.001 -1.978897 -.4844468 papi .0013304 .0003194 4.17 0.000 .0007044 .0019565 f1papi -.0083615 .0033969 -2.46 0.014 -.0150197 -.0017033 hpapi -.0006309 .0002315 -2.73 0.006 -.0010847 -.0001771 vertical .3264073 .1352183 2.41 0.016 .0613672 .5914474 horizontal1 .0128118 .0004029 31.80 0.000 .012022 .0136016 labourquality .0043558 .0002122 20.53 0.000 .0039398 .0047718 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Drisc/Kraay within R-squared = 0.7428 maximum lag: 1 Prob > F = 0.0000 Group variable (i): ID F( 9, 18838) = 10.44 Method: Fixed-effects regression Number of groups = 18839 Regression with Driscoll-Kraay standard errors Number of obs = 18858 > _16==0 & quart >3 , fe . xtscc lnTFP2 labourquality horizontal1 vertical hpapi f1papi papi technologygap1 scale2 HHI if sohuu 204 8. Regression results using Driscoll-Kraay standard errors for enterprises with TFP greater than 50% of the sample. 9. Regression results using Driscoll-Kraay standard errors for enterprises with TFP less than or equal to 50% of the sample. _cons .1523567 .000332 458.91 0.000 .151706 .1530074 HHI .0095743 .0003375 28.37 0.000 .0089128 .0102357 scale2 .0387018 .0007075 54.70 0.000 .0373152 .0400885 technologygap1 -.3696987 .0702697 -5.26 0.000 -.507429 -.2319683 papi .0007877 .0001572 5.01 0.000 .0004797 .0010957 f1papi -.0071996 .0005242 -13.73 0.000 -.0082271 -.0061722 hpapi -.0004135 .0000685 -6.03 0.000 -.0005478 -.0002792 vertical .2865938 .0224444 12.77 0.000 .2426023 .3305854 horizontal1 .0032613 .0005407 6.03 0.000 .0022016 .0043211 labourquality .0104575 .0021302 4.91 0.000 .0062822 .0146327 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Drisc/Kraay within R-squared = 0.6085 maximum lag: 1 Prob > F = 0.0000 Group variable (i): ID F( 9, 38349) = 2.25e+10 Method: Fixed-effects regression Number of groups = 38350 Regression with Driscoll-Kraay standard errors Number of obs = 38399 > _16==0 & quart >2 , fe . xtscc lnTFP2 labourquality horizontal1 vertical hpapi f1papi papi technologygap1 scale2 HHI if sohuu _cons .32944 .0217693 15.13 0.000 .2867707 .3721093 HHI .0030487 .0022376 1.36 0.173 -.0013371 .0074346 scale2 -.0849005 .1681048 -0.51 0.614 -.414397 .2445961 technologygap1 2.007043 .0765909 26.20 0.000 1.85692 2.157166 papi -.0059104 .0004797 -12.32 0.000 -.0068507 -.0049701 f1papi .0823854 .0056426 14.60 0.000 .0713255 .0934453 hpapi .0022179 .0001604 13.82 0.000 .0019034 .0025324 vertical -3.318772 .2393857 -13.86 0.000 -3.787984 -2.84956 horizontal1 .0759647 .0139121 5.46 0.000 .048696 .1032335 labourquality .010837 .0007288 14.87 0.000 .0094084 .0122656 lnTFP2 Coef. Std. Err. t P>|t| [95% Conf. Interval] Drisc/Kraay within R-squared = 0.8931 maximum lag: 1 Prob > F = 0.0000 Group variable (i): ID F( 9, 23244) = 2.44e+09 Method: Fixed-effects regression Number of groups = 23245 Regression with Driscoll-Kraay standard errors Number of obs = 23257 > _16==0 & quart <3 , fe . xtscc lnTFP2 labourquality horizontal1 vertical hpapi f1papi papi technologygap1 scale2 HHI if sohuu 205 LIST OF THE ARTICLES RELATED TO THE THESIS 1. Ngoc, P. T. B., Vu, H. Q., & Long, P. D. (2022). Domestic total factor productivity with trade and heterogenous foreign direct investment in developing countries: a case of Vietnamese manufacturing. International Journal of Emerging Markets. (SSCI/ISI, Q2) 2. Ngoc, P. T. B., Long, P. D., & Vu, H. Q., (2022). The impact of absorbing productivity spillover on export ability: evidence from an emerging market. Cogent Economics & Finance, 10(1), 2152938. (ESCI, Q2) 3. Vu, H. Q., Ngoc, P. T. B., & Quyen, N. L. H. T. T. (2022). The Effect of Institutions on Productivity Spillovers from FDI to Domestic Firms: Evidence from Vietnam. Global Business & Finance Review, 27(3), 28. (Scopus, Q4). 4. Ngọc, P. T. B., P., Long, P. D., & Vũ, H. Q., (2021). Sự lan tỏa năng suất từ doanh nghiệp FDI dang doanh nghiệp Việt Nam: bằng chứng qua hoạt động xuất khẩu và khả năng hấp thụ.Tạp chí Nghiên cứu kinh tế, 513(2), 12-22. ( Danh sách tạp chí HD9CDGSNN, mức 1 điểm). 5. Ngoc, P. T. B., Long, P. D., & Vu, H. Q., (2020). Absorbing productivity spillover and export ability: Evidence from Vietnamese manufacturing. In International Conference on Business and Finance 2020 (ICBF 2020) (pp. 152- 168). University of Economics Ho Chi Minh City, Vietnam.

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