Direct and Indirect Effects of Business Environment on BRI Countries’ Global Value Chain Upgrading
Abstract
:1. Introduction
2. Theoretical Analysis and Hypothesis
2.1. Direct Effect of Business Environment on Status Elevation on the Global Value Chain
2.2. FDI’s Impact on the Host Country’s Status Elevation on the Global Value Chain
2.3. Indirect Effect of Business Environment on BRI Countries’ Status Elevation on the Global Value Chain
3. Data and Statistical Model
3.1. Data
3.2. Variables
- Dependent variable: BRI countries’ status on the global value chain (GVCs). Koopman (2012) decomposes the total exports of China and the U.S. to measure the status of manufacturing industries on the global value chain [33]. This study adopts sophistication level of exports, coined by Hausmann et al. (2007) [34], as the substitution indicator for status on the global value chain. However, according to the methods by Schott (2008), export similarity index among two countries can be measured by the following equation [35]:
- 2.
- Key independent variables: (1) business environment (dtf). Business environment is an important indication of economic soft power of a country. Premier Li Keqiong once noted that business environment is in itself productivity. Business environment in China has been improving on the whole. According to Doing Business 2019 Report by the World Bank, business environment in China was ranked 46, elevated by 32 places compared with 2018. Significant progress has also been made in multiple sub-indicators of business environment. Electricity indicator improved by 84 places, starting businesses indicator grew by 65 places, and protection for minority investors increased by 55 places. Djankovetal (2010) attests that the indicator representing business environment of a country in the ease of doing business index by the World Bank is consistent with theories about FDI [36]. Pinheiro-Alves and Zambujal-Oliveira (2012) demonstrate the efficacy of the ease of doing business index in interpreting business environment through factor analysis and Cronbach’s alpha [37]. Referring to Li (2018), this study adopts ease of doing business score to measure the overall business environment of an economy [38]. Five sub-category indicators are used to investigate the specific category of business environment, including facilitation for construction permission (construct), facilitation for paying taxes (tax), facilitation for protection over investors (protect), facilitation for contract enforcement (contract), and facilitation for insolvency. The five sub-indicators accurately reflect the specific changes in business environment at each economy over time. The impact of business environment change on economies can also be detected in an accurate manner. The higher the business environment indicator, the more convenient the conditions for operation activities in the country. (2) foreign direct investment (FDI). In recent years, thanks to continuous efforts in opening-up and consistent improvement in business environment, the use of FDI in China has been kept in a good momentum, forming a stark contrast with the downward trend of FDI globally. China ranked third, behind the U.S. and the U.K., in terms of FDI use in 2016. One year later, China secured the second place in FDI use. According to the statistics of United Nations Conference on Trade and Development (UNCTAD), global FDI experienced a four-year downturn with a decline of 31.5% in 2019 from the 2015 level. In 2019, the total FDI in China, with banks, securities, insurances, and other fields included, reached 141.2 billion USD, increased by 2.1% over the preceding year. China’s share of FDI in global FDI grew from 6.7% in 2015 to 10.1% in 2019, up by 3.4 percentage points. Tang and Zhang (2017) reveals FDI inflow boosts inflow of foreign intermediate products and introduction of advanced technologies, which improves quality of export products, increases the domestic value added in gross export, and ultimately elevates the status on the global value chain [19]. However, FDI may also impede the status elevation on the global value chain due to the competition brought by imported intermediate products and lock-in on low end of the value chain. This study adopts FDI stock of countries to measure FDI level at different countries. Data are from the database of UNCTAD.
- 3.
- Control variables. In reference to existing research, this study selects the following control variables which relates to BRI countries’ status on the global value chain. (1) export scale. This study uses the logarithm of the export value in the database of World Development Indicators by the World Bank; (2) resource endowment. The share of the sum of historical export of ores, metals, and fuels in GDP is adopted as its substitution variable; (3) intellectual property rights protection. It is measured by the intellectual property right payment with relevant data derived from World Development Indicators (WDI) of the World Bank; (4) interest rate. High interest rate affects return on investment and investment cost of multinationals, which is a vital impacting factor for FDI. Data are from WDI; (5) per capita wealth (wealth). It is denoted by the logarithm of per capita GDP, and data come from WDI; (6) domestic average level of production (level). It is denoted by the ratio of value added of industry to sales value of industry. Data are from WDI; (7) industrial openness (open). It is measured by the ratio of trade volume to sales value of industry with data derived from WDI. The descriptive statistics of key variables are shown in Table 1.
3.3. Econometric Model
4. Empirical Results
4.1. Benchmark Regression Results
4.2. Industry Heterogeneity Analysis
4.3. Robustness Checks
5. Further Analysis
6. Conclusions and Policy Implication
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Ambec, S.; Coria, J. Prices vs quantities with multiple pollutants. J. Environ. Econ. Manag. 2013, 66, 123–140. [Google Scholar] [CrossRef] [Green Version]
- Hu, D.; Jiao, J.; Tang, Y.; Han, X.; Sun, H. The effect of global value chain position on green technology innovation efficiency: From the perspective of environmental regulation. Ecol. Indic. 2021, 121, 107195. [Google Scholar] [CrossRef]
- Antràs, P. Conceptual aspects of global value chains. World Bank Econ. Rev. 2020, 34, 551–574. [Google Scholar] [CrossRef]
- Dallas, M.P. ‘Governed’ trade: Global value chains, firms, and the heterogeneity of trade in an era of fragmented pro-duction. Rev. Int. Political Econ. 2015, 22, 875–909. [Google Scholar] [CrossRef]
- Caselli, F.; Coleman, W.J. The world technology frontier. Am. Econ. Rev. 2006, 96, 499–522. [Google Scholar] [CrossRef] [Green Version]
- Pietrobelli, C.; Rabellotti, R. Global value chains meet innovation systems: Are there learning opportunities for developing countries? World Dev. 2011, 39, 1261–1269. [Google Scholar] [CrossRef] [Green Version]
- Ge, J.; Fu, Y.; Xie, R.; Liu, Y.; Mo, W. The effect of GVC embeddedness on productivity improvement: From the per-spective of R&D and government subsidy. Technol. Forecast. Soc. Chang. 2018, 135, 22–31. [Google Scholar]
- Humphrey, J.; Schmitz, H. Governance and Upgrading: Linking Industrial Cluster and Global Value Chain Research; Institute of Development Studies: Brighton, UK, 2015; Volume 120. [Google Scholar]
- Chen, L.; Luo, S.; Zhao, T. Financial constraints, trade mode transition, and global value chain upgrading of Chinese firms. Sustainability 2019, 11, 4527. [Google Scholar] [CrossRef] [Green Version]
- Witkowska, J. Foreign direct investment in the changing business environment of the European Union’s new member states. Glob. Econ. J. 2007, 7, 4. [Google Scholar] [CrossRef]
- Bah, E.-H.; Fang, L. Impact of the business environment on output and productivity in Africa. J. Dev. Econ. 2015, 114, 159–171. [Google Scholar] [CrossRef] [Green Version]
- Acemoglu, D.; Johnson, S.; Robinson, J.A. The colonial origins of comparative development: An empirical investigation. Am. Econ. Rev. 2001, 91, 1369–1401. [Google Scholar] [CrossRef]
- Pipkin, S.; Fuentes, A. Spurred to upgrade: A review of triggers and consequences of industrial upgrading in the global value chain literature. World Dev. 2017, 98, 536–554. [Google Scholar] [CrossRef]
- Wu, Z.; Hou, G.; Xin, B. Has the belt and road initiative brought new opportunities to countries along the routes to participate in global value chains? SAGE Open 2020, 10, 2158244020902088. [Google Scholar] [CrossRef] [Green Version]
- Dai, X. Business Environment and GVC Upgrading. Econ. Theory Bus. Manag. 2020, 39, 47. (In Chinese) [Google Scholar]
- Gereffi, G.; Humphrey, J.; Sturgeon, T. The governance of global value chains. Rev. Int. Political Econ. 2005, 12, 78–104. [Google Scholar] [CrossRef]
- Li, X.; Zhou, W.; Hou, J. Research on the impact of OFDI on the home country’s global value chain upgrading. Int. Rev. Financ. Anal. 2021, 77, 101862. [Google Scholar] [CrossRef]
- Kee, H.L.; Tang, H. Domestic value added in exports: Theory and firm evidence from China. Am. Econ. Rev. 2016, 106, 1402–1436. [Google Scholar] [CrossRef] [Green Version]
- Tang, Y.H.; Zhang, P.Y. FDI, Global value chain embeddedness and domestic value added in exports. Stat. Res. 2017, 34, 36–49. (In Chinese) [Google Scholar]
- Dai, X.; Qin, S.J. How does optimization of business environment increase the domestic value-added of enterprise’s export. J. Int. Trade 2020, 11, 15–29. (In Chinese) [Google Scholar]
- Chen, J.; Liu, Y.; Liu, W. Investment facilitation and China’s outward foreign direct investment along the belt and road. China Econ. Rev. 2020, 61, 101458. [Google Scholar] [CrossRef]
- Wang, J.B. The China–Indochina Peninsula economic corridor. In Routledge Handbook of the Belt and Road; Routledge: London, UK, 2019; pp. 213–217, 573. [Google Scholar]
- Morrison, A.; Pietrobelli, C.; Rabellotti, R. Global value chains and technological capabilities: A framework to study learning and innovation in developing countries. Oxf. Dev. Stud. 2008, 36, 39–58. [Google Scholar] [CrossRef]
- Bi, K.; Huang, P.; Wang, X. Innovation performance and influencing factors of low-carbon technological innovation under the global value chain: A case of Chinese manufacturing industry. Technol. Forecast. Soc. Chang. 2016, 111, 275–284. [Google Scholar] [CrossRef]
- Van Waarden, F. Institutions and innovation: The legal environment of innovating firms. Organ. Stud. 2001, 22, 765–795. [Google Scholar] [CrossRef]
- Yu, W.; Ramanathan, R. Business environment, employee competencies and operations strategy: Anempirical study of retail firms in China. IMA J. Manag. Math. 2013, 24, 231–252. [Google Scholar] [CrossRef]
- Humphrey, J.; Schmitz, H. Governance in global value chains. IDS Bull. 2001, 32, 19–29. [Google Scholar] [CrossRef] [Green Version]
- Adarov, A.; Stehrer, R. Implications of foreign direct investment, capital formation and its structure for global value chains. World Econ. 2019, 44, 3246–3299. [Google Scholar] [CrossRef]
- Li, R.; Liu, Y.; Bustinza, O.F. FDI, service intensity, and international marketing agility: The case of export quality of Chinese enterprises. Int. Mark. Rev. 2019, 36, 213–238. [Google Scholar] [CrossRef]
- Contractor, F.J.; Dangol, R.; Nuruzzaman, N.; Raghunath, S. How do country regulations and business environment impact foreign direct investment (FDI) inflows? Int. Bus. Rev. 2020, 29, 101640. [Google Scholar] [CrossRef]
- Hall, B.H.; Moncada-Paternò-Castello, P.; Montresor, S.; Vezzani, A. Financing constraints, R&D investments and innovative performances: New empirical evidence at the firm level for Europe. Econ. Innov. New Technol. 2016, 25, 183–196. [Google Scholar] [CrossRef]
- Wu, N.; Liu, Z. Higher education development, technological innovation and industrial structure upgrade. Technol. Forecast. Soc. Chang. 2021, 162, 120400. [Google Scholar] [CrossRef]
- Koopman, R.; Wang, Z.; Wei, S.-J. Estimating domestic content in exports when processing trade is pervasive. J. Dev. Econ. 2012, 99, 178–189. [Google Scholar] [CrossRef]
- Hausmann, R.; Hwang, J.; Rodrik, D. What you export matters. J. Econ. Growth 2007, 12, 1–25. [Google Scholar] [CrossRef]
- Schott, P. The relative dophistication of Chinese exports. Econ. Policy 2006, 23, 6–49. [Google Scholar] [CrossRef]
- Djankov, S.; Ganser, T.; McLiesh, C.; Ramalho, R.; Shleifer, A. The effect of corporate taxes on investment and entrepreneurship. Am. Econ. J. Macroecon. 2010, 2, 31–64. [Google Scholar] [CrossRef] [Green Version]
- Pinheiro-Alves, R.; Zambujal-Oliveira, J. The Ease of Doing Business Index as a tool for investment location decisions. Econ. Lett. 2012, 117, 66–70. [Google Scholar] [CrossRef]
- Li, T.T. Business Environment of the Host Country and the Location Selection of Outward FDI Enterprises: Evidence from Chinese Micro Data; Jinan University: Jinan, China, 2018. [Google Scholar]
- Baron, R.M.; Kenny, D.A. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Personal. Soc. Psychol. 1986, 51, 1173. [Google Scholar] [CrossRef]
- Wang, J.B. Analysis on trade potentiality of “b&r” economic corridors: Based on trade competitiveness, complementarities and industrial international competitiveness. Asia-Pac. Econ. Rev. 2017, 4, 93–100. (In Chinese) [Google Scholar]
Variable | Code | Mean | SD | Minimum | Maximum | |
---|---|---|---|---|---|---|
Dependent variable | Status on global value chain | chain | 8.207649 | 4.898577 | 0 | 23.34099 |
Independent variable | Business environment | dtf | 5.893868 | 0.2909366 | 4.906891 | 6.483816 |
Foreign direct investment | FDI | 4.162892 | 0.9984578 | −5 | 6.894549 | |
Control variable | Per capita wealth | wealth | 17.51375 | 14.57597 | 0 | 70.59955 |
Intellectual property rights protection | iprp1 | 6.463159 | 3.167798 | 0 | 10.72787 | |
Resource endowment | resource | 16.07034 | 26.81276 | 0 | 99.98649 | |
Industrial openness | open | 85.21757 | 46.78791 | 0 | 437.3267 | |
Export scale | exscade1 | 9.50821 | 2.439018 | 0 | 12.35098 | |
Interest rate | rate | 5.543384 | 37.4895 | −31.9229 | 1158.026 | |
Domestic average level of production | Level | 27.7054 | 12.73778 | 0 | 74.8123 |
VARIABLES | (1) GVCs | (2) GVCs | (3) GVCs |
---|---|---|---|
dtf | 8.2060 *** | 6.8436 *** | 6.2188 *** |
(16.195) | (13.885) | (13.276) | |
FDI | 1.4064 *** | 1.8610 *** | |
(10.804) | (14.230) | ||
Dtf * FDI | 3.1334 *** | ||
(9.988) | |||
wealth | 0.0436 *** | 0.0391 *** | 0.0476 *** |
(4.498) | (4.315) | (5.548) | |
resource | 0.0177 *** | 0.0196 *** | 0.0212 *** |
(3.090) | (3.645) | (4.178) | |
iprp1 | 0.4248 *** | 0.3026 *** | 0.2319 *** |
(8.207) | (6.081) | (4.894) | |
open | −0.0052 * | −0.0045 * | −0.0063 *** |
(−1.944) | (−1.825) | (−2.665) | |
exscade1 | 0.3426 *** | 0.2657 *** | 0.2133 *** |
(4.565) | (3.805) | (3.233) | |
rate | −0.0318 * | 0.0134 | 0.0106 |
(−1.920) | (0.850) | (0.713) | |
level | −0.0354 *** | −0.0576 *** | −0.0646 *** |
(−2.805) | (−4.863) | (−5.775) | |
Constant term | −44.9620 *** | −40.7077 *** | 38.5919 *** |
(−16.053) | (−15.455) | (4.639) | |
Year fixed effect | YES | YES | YES |
Observation | 805 | 793 | 793 |
R-squared | 0.556 | 0.620 | 0.663 |
Number of countries | 112 | 112 | 112 |
Dependent Variables | GVCs | FDI | GVCs |
---|---|---|---|
dtf | 4.7046 *** | 2.7787 *** | 4.0875 *** |
(0.3227) | (0.2949) | (0.3273) | |
FDI | 1.0654 *** | ||
(0.1171) |
VARIABLES | (1) ld | (2) zy | (3) zb | (4) js |
---|---|---|---|---|
dtf | 0.1828 *** | 0.2039 *** | 0.1132 *** | 0.2253 *** |
(12.835) | (13.442) | (8.294) | (12.091) | |
FDI1 | 0.0412 *** | 0.0416 *** | 0.0353 *** | 0.0407 *** |
(10.950) | (10.397) | (9.792) | (8.270) | |
wealth | 0.0019 *** | 0.0000 | 0.0000 | 0.0010 *** |
(7.217) | (0.090) | (0.136) | (3.036) | |
resource | −0.0000 | −0.0006 *** | −0.0003 ** | −0.0005 *** |
(−0.098) | (−3.844) | (−2.176) | (−2.660) | |
iprp1 | 0.0069 *** | 0.0092 *** | 0.0051 *** | 0.0089 *** |
(4.827) | (6.029) | (3.714) | (4.731) | |
open | 0.0001 | 0.0001 | −0.0003 *** | −0.0001 |
(0.887) | (1.304) | (−4.957) | (−1.062) | |
exscade1 | 0.0063 *** | 0.0066 *** | 0.0074 *** | 0.0104 *** |
(3.100) | (3.079) | (3.838) | (3.922) | |
rate | −0.0008 * | −0.0012 ** | −0.0003 | −0.0006 |
(−1.751) | (−2.506) | (−0.680) | (−1.059) | |
level | −0.0009 *** | −0.0000 | −0.0002 | −0.0015 *** |
(−2.729) | (−0.059) | (−0.677) | (−3.443) | |
Constant term | −1.1744 *** | −1.3156 *** | −0.7652 *** | −1.3863 *** |
(−15.430) | (−16.232) | (−10.491) | (−13.922) | |
Year fixed effect | YES | YES | YES | YES |
Observation | 793 | 793 | 793 | 793 |
R-squared | 0.632 | 0.599 | 0.434 | 0.548 |
Number of countries | 112 | 112 | 112 | 112 |
VARIABLES | (1) GVCs | (2) ld | (3) zy | (4) zb | (5) js |
---|---|---|---|---|---|
FDI1 | 1.2641 *** | 0.0403 *** | 0.0421 *** | 0.0290 *** | 0.0359 *** |
(11.602) | (12.869) | (12.474) | (9.793) | (8.661) | |
construct | 0.0085 | 0.0007 *** | 0.0012 *** | 0.0005 *** | 0.0007 *** |
(1.550) | (4.393) | (7.066) | (3.211) | (3.188) | |
protect | 0.0145 ** | −0.0001 | −0.0001 | −0.0003 * | 0.0005 ** |
(2.370) | (−0.403) | (−0.701) | (−1.696) | (2.053) | |
tax | 0.0117 ** | 0.0003 * | 0.0003 | 0.0000 | 0.0009 *** |
(2.150) | (1.842) | (1.486) | (0.216) | (4.528) | |
insolvency | 0.0824 *** | 0.0026 *** | 0.0025 *** | 0.0023 *** | 0.0029 *** |
(13.656) | (14.990) | (13.504) | (13.795) | (12.693) | |
contract | 0.0564 *** | 0.0012 *** | 0.0013 *** | 0.0012 *** | 0.0017 *** |
(7.066) | (5.146) | (5.207) | (5.759) | (5.760) | |
Constant term | −8.7577 *** | −0.3272 *** | −0.3769 *** | −0.2390 *** | −0.3327 *** |
(−13.274) | (−17.270) | (−18.429) | (−13.330) | (−13.256) | |
Year fixed effect | YES | YES | YES | YES | YES |
Observation | 1103 | 1103 | 1103 | 1103 | 1103 |
R-squared | 0.661 | 0.675 | 0.638 | 0.525 | 0.591 |
Number of countries | 112 | 112 | 112 | 112 | Number of countries |
Threshold Variable | Test | F Value | p Value |
---|---|---|---|
FDI | Single threshold | 6.565 ** | 0.021 |
Double threshold | 197.688 *** | 0.000 | |
Triple threshold | −0.921 ** | 0.020 | |
Business environment | Single threshold | 5.997 | 0.443 |
Double threshold | 102.379 *** | 0.000 | |
Triple threshold | −48.971 | 1.000 |
Variable | Business Environment (dtf) | Foreign Direct Investment (FDI) |
---|---|---|
wealth | 0.0149 * | 0.0308 *** |
(1.94) | (2.93) | |
iprp1 | 0.402 *** | 0.194 *** |
(10.92) | (3.52) | |
resource | 0.0269 *** | 0.0326 *** |
(6.38) | (5.78) | |
open | 0.00284 | −0.00320 |
(1.00) | (−1.28) | |
exscade1 | 0.331 *** | 0.365 *** |
(6.31) | (4.92) | |
rate | 0.00908 ** | −0.0148 |
(2.27) | (−1.13) | |
level | −0.0499 *** | −0.0215 |
(−5.27) | (−1.61) | |
Dtf (L ≤ r1) | 0.0595 *** | |
(3.75) | ||
dtf (r1 < L ≤ r2) | 0.125 *** | |
(8.87) | ||
Dtf (L > r2) | 0.155 *** | |
(11.05) | ||
FDI (L ≤ r1) | 0.776 *** | |
(6.34) | ||
FDI (r1 < L ≤ r2) | 1.165 *** | |
(9.20) | ||
FDI (L > r2) | 1.338 *** | |
(10.80) | ||
Threshold | Double threshold | Double threshold |
Constant | −1.765 *** | −4.153 *** |
(−3.00) | (−4.58) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
He, S.; Yao, H.; Ji, Z. Direct and Indirect Effects of Business Environment on BRI Countries’ Global Value Chain Upgrading. Int. J. Environ. Res. Public Health 2021, 18, 12492. https://doi.org/10.3390/ijerph182312492
He S, Yao H, Ji Z. Direct and Indirect Effects of Business Environment on BRI Countries’ Global Value Chain Upgrading. International Journal of Environmental Research and Public Health. 2021; 18(23):12492. https://doi.org/10.3390/ijerph182312492
Chicago/Turabian StyleHe, Shengbing, Huilin Yao, and Zhou Ji. 2021. "Direct and Indirect Effects of Business Environment on BRI Countries’ Global Value Chain Upgrading" International Journal of Environmental Research and Public Health 18, no. 23: 12492. https://doi.org/10.3390/ijerph182312492
APA StyleHe, S., Yao, H., & Ji, Z. (2021). Direct and Indirect Effects of Business Environment on BRI Countries’ Global Value Chain Upgrading. International Journal of Environmental Research and Public Health, 18(23), 12492. https://doi.org/10.3390/ijerph182312492