a global value chain rationale for the allocation of belt ... marvasi.pdf · a global value chain...

Kaku Attah Damoah1,2

Giorgia Giovannetti1,3

Enrico Marvasi1,4

1 UNIVERSITÀ DI FIRENZE2 UNICEF FIRENZE

3 EUROPEAN UNIVERSITY INSTITUTE4 POLITECNICO DI MILANO

A Global Value Chain

Rationale for the Allocation of

Belt and Road Projects

The Belt and Road Initiative

• Officially announced by Xi Jinping in 2013

• Is a China-led initiative to easing bottlenecks to Eurasian trade

• Infrastructure development is the most explicit and visible aspect of the project

• Potential to enhance policy coordination, trade facilitation, financial integration as well as capital and labour mobility

2

A GVC Rationale for the Allocation of B&R Projects

Attah Damoah, Giovannetti, Marvasi

LUISS, Roma 21/10/2019

A large scale project

• More than sixty countries

• Gross Domestic Product is $23 trillion(30% of world GDP)

• Population approximately 4.4 billion people(around 60% of the world population)

• Six land corridors

3




B&R land corridors

4




Main questions regarding the BRI

Two main aspects have been considered yet by researchers:

1. impacts and the effects of the BRI on

• trade costs

• trade and GVC participation (via lower trade costs)

• GDP, growth and development

2. reasons behind the BRI and the official rhetoric in favor of the initiative

• strategic and geo-political reasons

• economic reasons (mostly macroeconomic)

5




Implications and impacts

• Trade costs→ are going to decrease much as BRI countries lack infrastructure (e.g. low logistics performance index)

• shipment times will decrease by 1.2-2.5% [de Soryres et al. (2018) ]

• expected fast growth of container traffic [Vinokurov et al. (2018)]

• Trade flows→ trade volume increases gravity and comparative advantage model [Baniya, Rocha, & Ruta (2019)], mostly due to

• improvements in hard (i.e. physical) and soft (i.e. administrative and ICT) connectivity [Garcia-Herrero & Xu (2017) and Ramasamy et al. (2017)]

• GVC and trade in intermediates (TiVA, 28 BRI countries only) [Boffa (2018)]

• GDP and growth→ poorer countries gain more, China major beneficiary [Enderwick (2018), Villafuerte et al. (2016)]

• Risk of exposure to China’s demand and competition shocks [Boffa (2018)]

• Network position matters, prioritizing weak links reinforces the network [Derudder et al. (2018)] 6




Non-economic reasons are relatively vague

• Promoters often stress the mutual benefits and the creation of win-win situations, not everyone shares such positive attitude towards the initiative

• Strategic and geo-political interests go beyond economics [Cheng (2016)]

• Some distrust among recipient countries

o e.g. for India Nataraj and Sekhani (2015) and Banerjee (2016) argue that, despite some distrust,

• B&R projects are likely to bring about gains from trade and from infrastructure building,

• while an ineffective involvement may lead to isolation risks 7




China’s economic reasons are stated very explicitly

• sustain China’s economic growth and transition towards a more balanced development pattern [Huang (2016)]

• “comparative advantages in manufacturing, such as low labor costs, have begun to disappear. For this reason, the Chinese leadership wants to capture the higher end of the global value chain. To do this, China will need to upgrade its industry.” (pp.8) [Cai (2017)]

• “we should gradually migrate our low-end manufacturing to other countries and take pressure off industries that suffer from an excess capacity problem. At the same time, we should support competitive industries such as construction engineering, high-speed rail, electricity generation, machinery building and telecommunications moving abroad.” Hu Huaibang, Chairman of the China Development Bank, 2016

8




Are BRI investments following a GVC rationale?

• Economic motivations explicitly include GVC among the reasons

1. Investments may follow specialization and GVC trade

• exploiting within-sector division of labor by moving L-intensive phases abroad (smaller investments, higher returns)

• prioritizing central hubs can bring about scale economies

2. Investments may not follow specialization and GVC trade

• reinforcing weak GVC links in less central countries may increasediversification and stabilize the network

• because they simply search connection to new (large) markets

• because they respond to other factors (geography, political considerations)

9




Our research questions

• Do BRI investments favor countries that trade intermediates or trade them more with China?

• Do sectoral specialization and the position in the trade network play a role in projects allocation?

✓ Yes → BRI is building up on existing GVC, reinforcing them and may increase division of labor and centralization of the network, facilitating shock transmission

No → BRI is likely to change the GVC patterns, decentralize the network increasing interconnectedness but also stability

10




Preview of results

1. More investment projects in large and relatively poor countries, while richer countries get fewer but greater investments

2. Project recipients display relatively more diversified export structures and their specialization tends to overlap more with that of China

3. Investments tend to favor central countries that are more involved in GVC as suppliers of intermediates to China

4. Also in intra-industry trade and export sophistication export are positively associated with (larger) investments

5. Geography and political proximity also matter, but do not explain all

11




Data on B&R projects

• Reconnecting Asia project of the Center for Strategic and International Studies (CSIS)

• List of countries involved in the BRI, some of which have already received and completed infrastructure projects

• Our dataset includes roads, rails, seaports, and dryportsinfrastructure projects completed between 2013 and 2018

• A total of 329 completed infrastructure projects in B&R countries. Roads account for 65% of all completed projects

12




Trade and specialization

13




Cum. positive

Lafay RCA

OBOR 19.713

of which

projects 18.525

non-projects 23.128

non-OBOR 19.588

Total 19.630

Aggregate

RCA overlap

(Balassa)

Aggregate

RCA overlap

(Lafay)

OBOR 0.400 0.467

of which

projects 0.409 0.496

non-projects 0.374 0.383

non-OBOR 0.299 0.448

Total 0.333 0.454

• B&R countries RCA overlaps with China

• Even more so for projects recipients

• Projects recipients have a more diversified export structure

Trade in intermediate goods

14




Interm. exp

/Total exp.

Interm. imp.

/Total imp

Int. exp. to CHN

/Interm. imp.

Int. imp. from CHN

/Interm. imp.

OBOR 70.1% 63.5% 4.2% 5.0%

of which

projects 71.2% 64.4% 4.6% 4.9%

non-projects 66.9% 61.0% 3.1% 5.5%

non-OBOR 71.4% 64.2% 3.6% 4.8%

Total 70.9% 63.9% 3.8% 4.9%

• Projects recipients slightly more involved in intermediate trade

• They tend to supply intermediates to China

World intermediate trade network + B&R countries

(manufacturing, 2012)

15




China’s intermediate exports


16




China’s intermediate imports


17




B&R countries (only) intermediate trade network


18




Allocation of B&R projects

𝑦𝑖 = 𝛼 + 𝛽1𝑅𝐶𝐴𝑖𝑗 + 𝛽2 𝐶𝐸𝑁𝑖+𝛽3𝐸𝑥𝑝𝑖𝑗 + 𝛽4𝐼𝑚𝑝𝑖𝑗

+𝛽5𝐸𝑥𝑝𝑖𝑗𝐶𝐻𝑁 + 𝛽6𝐼𝑚𝑝𝑖𝑗

𝐶𝐻𝑁

+𝜷7′𝒁𝑖 + 𝜀𝑖

• 𝑦𝑖 is n. proj. / value of proj. (ln) completed between 2013-2018

• 𝑅𝐶𝐴𝑖𝑗 sector-level rca overlap with China

• 𝐶𝐸𝑁𝑖 is country centrality in the B&R intermediate trade network

• 𝐸𝑥𝑝𝑖𝑗 and 𝐼𝑚𝑝𝑖𝑗 are interm. shares over total exp/imp

• 𝐸𝑥𝑝𝑖𝑗𝐶𝐻𝑁 and 𝐼𝑚𝑝𝑖𝑗

𝐶𝐻𝑁 are China’s sh. on int. exp/imp

• 𝒁𝑖 country-level controls

• All regressors are lagged at 2012 19




Income and population

• B&R countries are relatively poor, but also very heterogeneous

• The income gap between countries that received (and completed) projects and the other B&R countries is even larger

• Investments seem to go where the infrastructure is more lacking and perhaps the return on each dollar spent is likely to be higher

• Projects tend to go towards large countries

20




GDPpc (2012)

(US $)

Pop. (2012)

(mln)

OBOR 10627 50.2

of which

projects 7700 62.5

non-projects 19603 12.4

non-OBOR 16927 35.3

Total 14693 40.6

Number and value of completed projects

vs. GDP per capita

21




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6 7 8 9 10 11 12Log GDP per capita 2012

95% CI predicted nprojects

Total Number of Completed Projects between 2012 and 2018

poorer countries get more projects richer countries get larger investment

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16

18

20

22

24

6 7 8 9 10 11 12Log GDP per capita 2012

95% CI predicted ln_mvproject

Log average value of projects

Number of projects (poisson model)

22




(1) (2) (3) (4) (5) (6)

VARIABLES Dependent Variable: Number of Completed Projects

RCA overlap 0.489*** 0.301*** 0.564*** 0.407*** 0.119* 0.441***

(0.0659) (0.0677) (0.0671) (0.0662) (0.0684) (0.0679)

Betweenness 0.315*** 0.240*** 0.293*** 0.263*** 0.204*** 0.233***

(0.0109) (0.0106) (0.0107) (0.0112) (0.0111) (0.0111)

Intermediate Export -0.311*** -0.156* -0.154* -0.581*** -0.530*** -0.544***

(0.0806) (0.0850) (0.0811) (0.0822) (0.0872) (0.0829)

Intermediate Import 0.476*** 0.220*** 0.335*** 0.193*** -0.0988* 0.0314

(0.0612) (0.0602) (0.0618) (0.0599) (0.0589) (0.0600)

Intermediate Export CHN 0.411*** 0.795*** 0.528*** 0.169 0.247** 0.192

(0.111) (0.109) (0.109) (0.118) (0.120) (0.118)

Intermediate Import CHN 0.412** 0.747*** 1.160*** 1.449*** 1.157*** 1.756***

(0.177) (0.181) (0.169) (0.180) (0.188) (0.175)

GDP per capita (ln) -0.408*** -0.335***

(0.0101) (0.0122)

Logistics index -0.121*** -0.0757**

(0.0293) (0.0299)

Export soph. (ln) -1.254*** -0.903***

(0.0624) (0.0635)

Constant 4.574*** 1.642*** 12.94*** 4.563*** 2.526*** 10.43***

(0.125) (0.129) (0.588) (0.135) (0.136) (0.597)

Observations 1,586 1,508 1,612 1,586 1,508 1,612

Sector FE Yes Yes Yes Yes Yes Yes

Region FE No No No Yes Yes Yes

Pseudo R2 0.172 0.0461 0.0745 0.285 0.236 0.255

Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1

Value of projects (OLS)

23




(1) (2) (3) (4) (5) (6)

VARIABLES Dependent Variable: Projects value (ln)

RCA overlap 1.279*** 0.728*** 0.989*** 0.979*** 0.621** 0.811***

(0.246) (0.254) (0.252) (0.236) (0.241) (0.243)

Betweenness 0.675*** 0.663*** 0.634*** 0.686*** 0.690*** 0.660***

(0.0308) (0.0205) (0.0275) (0.0335) (0.0238) (0.0309)

Intermediate Export -1.045*** -0.231 -0.909** -0.964*** -0.313 -0.884**

(0.381) (0.385) (0.379) (0.370) (0.374) (0.370)

Intermediate Import 1.037*** 0.791*** 0.817*** 0.809*** 0.705*** 0.713***

(0.241) (0.233) (0.234) (0.235) (0.230) (0.231)

Intermediate Export CHN -0.269 0.0985 -0.146 -1.067* -0.654 -0.968*

(0.522) (0.473) (0.512) (0.553) (0.510) (0.541)

Intermediate Import CHN 1.221 1.220 1.525** 1.650** 1.326* 1.691**

(0.780) (0.745) (0.776) (0.824) (0.795) (0.807)

GDP per capita (ln) -0.00200 0.0368

(0.0389) (0.0373)

Logistics index 1.088*** 0.878***

(0.0846) (0.0937)

Export soph. (ln) 0.950*** 0.735***

(0.175) (0.210)

Constant 20.03*** 16.83*** 11.22*** 20.53*** 18.09*** 13.96***

(0.506) (0.459) (1.678) (0.506) (0.494) (2.015)

Observations 1,196 1,144 1,196 1,196 1,144 1,196


Region FE No No No Yes Yes Yes

R2 0.161 0.236 0.173 0.226 0.280 0.231

Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1

Geography and political proximity (PPML)

24




(1) (2) (3) (4) (5) (6)

VARIABLES Dep. Var.: Projects number Dep. Var.: Projects value (ln)

RCA overlap 0.435*** 0.122 0.430*** 0.0651*** 0.0432*** 0.0457***

(0.127) (0.124) (0.131) (0.0105) (0.0104) (0.0102)

Betweenness 0.217*** 0.0948*** 0.140*** 0.0239*** 0.0198*** 0.0157***

(0.0270) (0.0195) (0.0256) (0.00220) (0.00153) (0.00185)

Intermediate Export -0.479*** -0.244* -0.394*** -0.0342*** 0.00166 -0.0216*

(0.143) (0.147) (0.149) (0.0127) (0.0130) (0.0121)

Intermediate Import 0.189* -0.177* -0.00608 0.0302*** 0.0214** 0.0136

(0.102) (0.0951) (0.103) (0.00921) (0.00873) (0.00863)

Intermediate Export CHN 0.0333 -0.172 -0.103 -0.0366** -0.0330** -0.0392**

(0.255) (0.306) (0.303) (0.0175) (0.0157) (0.0164)

Intermediate Import CHN 1.433*** 1.144*** 1.643*** 0.182*** 0.155*** 0.199***

(0.345) (0.382) (0.392) (0.0304) (0.0286) (0.0293)

GDP per capita (ln) -0.252*** 0.00507**

(0.0380) (0.00208)

Logistics index 0.440*** 0.0661***

(0.0859) (0.00568)

Export soph. (ln) -0.176 0.124***

(0.191) (0.0118)

Common border 0.0301 0.393*** 0.226*** 0.000159 0.0220*** 0.0193***

(0.0714) (0.0747) (0.0763) (0.00510) (0.00518) (0.00525)

Distance -0.0564 -0.138 -0.134 0.0977*** 0.0899*** 0.104***

(0.0953) (0.105) (0.102) (0.00801) (0.00910) (0.00760)

Voting agreement CHN 0.0149*** 0.0275*** 0.0193*** 0.00399*** 0.00437*** 0.00467***

(0.00218) (0.00201) (0.00225) (0.000187) (0.000189) (0.000184)

Constant 3.064*** -0.351 2.961 1.860*** 1.728*** 0.626***

(0.830) (0.969) (2.170) (0.0730) (0.0761) (0.134)

Observations 1,482 1,404 1,508 1,144 1,092 1,144


Region FE Yes Yes Yes Yes Yes Yes

R2 0.421 0.448 0.388 0.460 0.524 0.505

Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1

Conclusion

• B&R investment allocation is compatible with a GVC rationale

• Opportunity for China to engage other developing countries in GVC trade and benefit from importing intermediate inputs and moving up in the value chain

• Developing countries are likely to be strongly affected by Chinese investments as the returns even to relatively small projects are likely to be large. In a network perspective strengthening the weak links is likely to make the entire network more stable

• B&R countries display a specialization that is relatively similar to that of China. Can this reinforce China’s comparative advantages and help upgrade its productions by building on the specialization of other countries in the same sectors but on different phases?

25




a global value chain rationale for the allocation of belt ... marvasi.pdf · a global value chain...

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