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e-ISSN: 1647-7251

VOL15, N.º 2, TD1

Thematic Dossier – Brazil-China relations:

The rise of modern International Order

December 2024

329

BRAZILIAN TIVA UNDER US-CHINA STRATEGIC COMPETITION AND IMPACT

ON EXPORT-RELATED JOBS (2000-2015)

ALBERTO J. LEBRÓN VEIGA

alebronchina@yahoo.com

Ph.D. in International Political Economics, Peking University (China) and a MA degree in Chinese

Economic Structure (Renmin University of China). His latest publications include: “西欧去工业化的

发展与影响研究: 贸易增加值与民粹主义崛起之间关系的探索” (Development and Impact of

Deindustrialization in Western European Union: Trade in Value Added and the Rise of Political

Populism). CNKI, Peking University, 2023, 1-209

(https://www.lib.pku.edu.cn/jsym/index.htm?keyword=西欧去工业化的发展与影响研究:%20贸易增加

值与民粹主义崛起之间关系的探索), “Transición del Eje Tradicional Euroatlántico al Nuevo Modelo

Euroasiático en las Cadenas Globales de Valor (1998 - 2018)”. Casus Belli, Universidad Nacional

de la Defensa (Buenos Aires - Argentina), no. 3, 2022, 73-87

(https://fe.undef.edu.ar/publicaciones/ojs3/index.php/casusbelli/article/download/51/81) y

“Political Economy of China and US Value Chains in Latin America”. Journal of Business,

Universidad del Pacífico (Lima - Peru) 14, no. 1, 2023, 87-107.

https://doi.org/10.21678/jb.2022.2031.

CARLOS M. MARTIN

2172251@ucc.edu.ar

International Relations Ph.D. candidate at Universidad Católica de Cordoba (Argentina), a

researcher at Centro de Estudios La Franja y la Ruta from Universidad Católica de Cordoba, and

the founder of Hasiapacifico, a consulting company based in the People’s Republic of China and

the Macau Special Administrative Region since 2020. Carlos M. Martin has a bachelor’s degree in

Business and Administration, a Master’s degree in Corporate Finance and Investment Banking,

and a Master’s degree in Strategic Studies and International Security.

https://orcid.org/0000-0001-9501-2028.

Abstract

Domestic discussion in Brazil about its most suitable commercial partners to promote

economic development, through deeper and broader integration onto the Global Value Chain

(GVC), is a subject with divergent political narratives. Therefore, empirical evidence is crucial

to complement those political considerations with a comprehensive scientific approach on the

available sets of optimal choices for Brazil under great power strategic competition between

China and US. Even though increasing volumes of Trade-in-Value-Added (TiVA) can boost

both exports and GDP growth rates, long-term effects on labor market conditions in Brazil are

linked to variables such as industrial value-added, domestic production, vertical integration,

technological transfers and capital-labor ratios (K/L). Within the period 2000-2015, Brazilian

TiVA exchanges with China did grow at a much faster rate than those of US, thus becoming

the world second largest partner for Brazil. Through this chapter, therefore, we will measure

overall effects of TiVA exchanges with both China and US on Brazilian labor market. And will

also determine which countries/industries might become the most optimal choice for Brazil in

terms of TiVA.

Keywords

Trade in Value Added, GVC, Brazil, Great Power Politics, China, US.

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

330

Resumo

A discussão interna no Brasil sobre os seus parceiros comerciais mais adequados para

promover o desenvolvimento económico, através de uma integração mais profunda e ampla

na Cadeia Global de Valor (CGV), é um assunto com narrativas políticas divergentes. Por

conseguinte, a evidência empírica é crucial para complementar estas considerações políticas

com uma abordagem científica abrangente sobre os conjuntos disponíveis de escolhas óptimas

para o Brasil sob competição estratégica de grandes potências entre a China e os EUA. Embora

o volume crescente de comércio de valor acrescentado (TiVA) possa impulsionar as

exportações e as taxas de crescimento do PIB, os efeitos a longo prazo nas condições do

mercado de trabalho no Brasil estão ligados a variáveis como o valor acrescentado industrial,

a produção interna, integração vertical, transferências tecnológicas e relações capital-trabalho

(K/L). No período 2000-2015, as trocas brasileiras de TiVA com a China cresceram a um ritmo

muito mais rápido do que as dos EUA, tornando-se assim o segundo maior parceiro mundial

do Brasil. Neste capítulo, iremos, portanto, medir os efeitos globais das trocas de TiVA com a

China e os EUA no mercado de trabalho brasileiro. Para além disso, este artigo também

determinará quais os países/indústrias que se podem tornar a escolha ideal para o Brasil em

termos de TiVA.

Palavras-chave

Comércio de valor acrescentado, Cadeia Global de Valor, Brasil, Política de Grandes Potências,

China, EUA.

How to cite this article

Veiga, Alberto J. Lebrón & Martin, Carlos M. (2024). Brazilian Tiva Under Us-China Strategic

Competition and Impact on Export-Related Jobs (2000-2015). Janus.net, e-journal of international

relations. VOL 15 N.º 2, TD1 – Temathic Dossier – “Brazil - China Relations: The Rise Of Modern

International Order”. December 2024, pp. 329-353. https://doi.org/10.26619/1647-

7251.DT0324.16.

Article received on 4 January 2024 and accepted for publication on 09 September 2024.

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

331

BRAZILIAN TIVA UNDER US-CHINA STRATEGIC COMPETITION

AND IMPACT ON EXPORT-RELATED JOBS (2000-2015)

ALBERTO J. LEBRÓN VEIGA

CARLOS M. MARTIN

1. Introduction

This paper will estimate Brazilian TiVA exchanges with both US and China, within the

GVC, to measure their overall impact on Brazilian export-related jobs. We aim at

theorizing whether Brazil should further deepen its commercial ties with either China, US

or both; under conditions of great power politics (Mearsheimer, 2001). Bilateral TiVA

exchanges and their impact on export-related jobs, therefore, will be determinant to

assess potential optimal choices for commercial policies in Brazil when considering the

period 2000-2015.

Section 2 in this chapter will introduce a theoretical framework about optimal choices for

Brazilian commercial policies under conditions of aforementioned great power politics or

strategic competition between China and US. Several US scholars and politicians have

noted that Chinese economic engagement with the Western Hemisphere has significant

national security implications for their country (Ellis, 2005). It can be inferred, therefore,

that US has strong incentives to undermine Chinese commercial ties in Latin America

(including Brazil). However, an effective vertical integration with China has strengthened

the fundamentals for industrial development and long-term economic growth in countries

like Brazil, despite such “Chinese threat” to geostrategic interests of US. This creates a

dilemma in peripheral countries that must choose between maximizing their own

economic interests or those of US (Farrell & Newman, 2019; Vogelmann, 2020).

Section 3 will just introduce the data and related empirical evidence. Relevant variables,

from export-related jobs to TiVA magnitudes (such as Foreign Value Added -FVA- and

Indirect Value Added or DVX), will be estimated using standard input-output

computation. Interpretation of those numbers, i.e. how export-related jobs are correlated

to TiVA exchanges, will be shared in section 4. And a brief conclusion has also been

drafted in section 5.

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

332

2. Theoretical framework of constraints for optimal choice in trade and

commercial policies under great power politics between China and US

The political economy of optimal choices in foreign trade policies can be analyzed from

two complementary perspectives. Academic discussion on how states interact within a

given international order, from either realist or liberal theoretical approaches, can provide

some basic understanding of policy making and strategic choices. This paper will assume

that specific economic considerations based on rational choices might pose conflicts with

hegemonic interests under conditions of great power politics between China and US.

Both realists and liberals do attach importance to the influence of great powers over a

given international order (Keohane & Nye, 1977). Even though realists have refused to

rule out international cooperation as a feasible option, it would never take place if actual

distribution of power is challenged (Grieco, 1990; Jervis, 1999; Mearsheimer, 2001;

Snidal, 1991; Taliaferro, 2011). This is a reasonable assumption irrespective of recurrent

discussions about underlying reasons and different dimensions related to strategic

decision-making within countries (Buzan, 1995; Singer, 1961). Autonomy of a given

country within the international system will depend on geographical position, relative

power, resources endowment, foreign investments and technology transfers

dependence, among other variables (Lee & Thompson, 2022; Krasner, 1978). Therefore,

it can be deducted that not every country is free to pursue the materialization of its own

optimal choices, given external pressure and influence exerted from a superpower such

as US. In a nutshell, great powers can exert influence over other countries’ choices,

subordinating core interests of the latter to theirs (Beckley, 2018; Karen & William, 1994;

Taliaferro, 2004).

From an economic perspective, however, agents are expected to make optimal choices

based on rational considerations such as profit maximization. States are not an exception

and, among other spheres of action, will seek to remain competitive within the GVC. The

boom in international trade resulting from globalization has generated a gradual

geographic fragmentation of production processes. The GVC is based on “trade in tasks”

(Inomata, 2017; Xing & Detert, 2011; Xing, 2021). Since fragmentation of production

favors a drastic reduction in overall costs, increasing competitiveness has contributed to

greater trade volumes and economic growth rates (Baldwin & Lopez-Gonzalez, 2015,

Feenstra, 1998; Kwok, 2018). Several authors have also established a direct relationship

between domestic participation in the GVC and industrial development (Baldwin & Lopez-

Gonzalez, 2015; Gereffi & Fernandez-Stark, 2011; Vrh, 2017). Main logic behind this

assertion is that further integration onto the GVC, either through forward (DVX) or

backward linkages (FVA), contributes to increase overall productivity (Dauth et al., 2014;

Donoso et al, 2015; Iodice & Tomasi, 2016; Lurweg & Westermeier.A., 2010; Kreutzer &

Berger, 2018). Choi et al. (2019), for instance, have provided empirical evidence that

innovation enables certain countries to improve their position within the GVC. So

industrial upgrading, which stems from sustained increases in productivity, can boost

both domestic value added and export-related jobs (Montalbano et al., 2018; Shimbov

et al., 2019).

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

333

Main assumption of this paper, consistent with aforementioned literature and empirical

evidence, is that greater vertical integration onto the GVC can contribute to economic

development and create additional jobs in non-industrialized countries such as Brazil. A

virtuous circle of industrial development would require from backward linkages (FVA) to

promote a forward integration (DVX) onto the GVC. Then both variables would also result

in a positive impact on Brazilian domestic value added (DVA), overall gross exports

(EXGR) and export-related jobs (EMP).

Graph 1: Vertical integration, through backward and forward linkages, has a positive

impact on export-related jobs.

Source: Authors

Then should countries such as Brazil abandon their optimal choices in commercial

policies, interrupt its value chain integration with China and subordinate to the core

interests of hegemonic powers like US? Realists would answer in the affirmative. For

them, US-China strategic competition can be described as a battlefield which is not on

the sphere of direct confrontation but in other actors’ soil (Gill-Tiney, 2023; Treistman,

2017). Realist theorists, like John Mearsheimer (1994), warned almost three decades

ago that a wealthier China could increase its military capabilities and challenge the US-

led international order. According to realist theories like “Power Transition” or

“Hegemonic Stability”, a declining hegemon becomes more assertive as ascending

powers reduces their power gap (Feng, 2013; Gilpin, 1988). This will happen whenever

emerging powers, like China, were perceived as a threat against an international order

primarily conceived to benefit the hegemonic power (Mearsheimer, 2019; Nye, 2011).

Hence, US-China strategic competition can be depicted as a sole hegemonic power (US)

that has become more assertive against its main emerging rival (China), to prevent other

peripheral countries (Brazil) from being neutral or even deepening ties with the latter.

Such political restrictions, however, would come at the expense of efficient optimal

choices for commercial and trade policies in peripheral countries like Brazil.

FVA

DVX

DVAEXGR

EMP

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

334

The present paper, nonetheless, aims at offering some empirical evidence on potential

costs of subordinating national interests to foreign ones when pursuing non-optimal

choices in trade and commercial policies. A clear correlation between TiVA flows with

export-related jobs can help to determine some optimal choices for commercial policies

in Brazil which should not be dependent of hegemonic interests imposed from US.

3. Data and methodology

Correlations between Brazilian export-related jobs and TiVA flows have been derived from

standard Input-Output Tables (IOT). IOT are configured using Transactions (T), Value-

Added (VA) and Final Demand (FD) sets of matrixes from Eora26 MRIOT (Lenzen et al.,

2013)

. Here gross output (X) will be equal to the sum of intermediate consumption (T)

plus final demand (FD). Using matrix algebra notation this can be expressed as:

X = T + FD

(1)

Rearranging:

X = AX + FD

X = (I-A)-1 FD

X = L FD

(2)

Whereas X is the gross output matrix. FD is the matrix of goods that are used for final

demand (also noted as Y). A is the matrix of input-output coefficients obtained after

dividing T between X (T = AX). Thus (I-A)-1 will result in an inverse Leontief matrix

expressing the total output required both directly and indirectly to produce a unit of goods

for final demand (L).

The Eora26 MRIO database is available under license at www.worldmrio.com.

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

335

Table 1: Basic scheme of a standard Multi-Regional Input Output Table (MRIOT)

Source: Authors

For a correct classification of industries, Brazilian IOT and EORA-26 have been

harmonized as shown in Table 2.

Table 2: Classification of industries in Brazilian IOT and EORA26.

BRA IOT (Source: IBGE)

EORA26 (Source: EORA)

Agriculture and Forestry

Agriculture

Grazing and Fishing

Fishing

Crude Oil and Natural Gas

Mining and Quarrying

Iron Ore

Other Minerals and Ores

Food and Beverages

Food & Beverages

Tobacco Products

Textiles

Textiles and Wearing Apparel

Clothing

Leather and Footwear

Wood Products Except Furniture

Wood and Paper

Cellulose and Paper Products

Newspapers, Magazines and Electronic Publishing

Petroleum Refining and Coke Products

Petroleum, Chemical and Non-

Metallic Mineral Products

Alcohol

Chemical Products

Resins and Elastomers

Pharmaceutical Products

Pesticides

RoW BRAZIL CHINA USA RoW BRAZIL CHINA USA OUTPUT EXPORTS

INDUSTRIES INDUSTRIES INDUSTRIES INDUSTRIES FD AGG FD AGG FD AGG FD AGG X EXP

RoW INDUSTRIES AX(20x20)

Intermediate use

by Brazil of

exports from

RoW

AX(20x20) AX(20x20) RoW INDUSTRIES FD (20x6)

Final use by Brazil

of exports from

RoW

FD (20x6) FD (20x6)

BRAZIL INDUSTRIES

Intermediate use

by RoW of

exports from

Brazil

Intermediate use

of domestic

output X

Intermediate use

by China of

exports from

Brazil

Intermediate use

by USA of exports

from Brazil

BRAZIL INDUSTRIES

Final use by RoW

of exports from

Brazil

Final use of

domestic output

Final use by China

of exports from

Brazil

Final use by USA

of exports from

Brazil

CHINA INDUSTRIES AX(20x20)

Intermediate use

by Brazil of

exports from

China

AX(20x20) AX(20x20) CHINA INDUSTRIES FD (20x6)

Final use by Brazil

of exports from

China

FD (20x6) FD (20x6)

USA INDUSTRIES AX(20x20)

Intermediate use

by Brazil of

exports from USA

AX(20x20) AX(20x20) USA INDUSTRIES FD (20x6)

Final use by Brazil

of exports from

USA

FD (20x6) FD (20x6)

RoW BRAZIL CHINA USA

VA RoW VA BRA VA CHN VA USA

X = AX + Y

Exports are

calculated by

substracting

intermediate and

final use of

domestic output

to X

T MATRIX

VA MATRIX

PRIMARY INPUTS

OUTPUT

X = AX + VA

FD MATRIX

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

336

Soaps and Detergents

Inks, Varnishes, Enamels, Lacquers

Other Chemical Products

Rubber and Plastic Products

Cement and Other Non-Metallic Mineral Products

Manufacturing of Steel and Steel Alloys

Metal Products

Non-Ferrous Metals

Fabricated Metal Products Except Machines and Equipment

Machines and Equipment (including maintenance)

Electrical and Machinery

Household Appliances

Office Equipment

Electric Machines and Materials

Electronic and Communication Equipment

Medical and Optical Equipment

Passenger and Light Utility Vehicles, Trucks and Busses

Transport Equipment

Vehicle Parts

Other Transport Equipment

Furniture and Other Manufacturing

Other Manufacturing and Recycling

Electricity, Gas, Water, Sewerage and Drainage Services

Electricity, Gas and Water

Construction

Wholesale and Retail Trade

Transport and Postal Services

Transport, Post and

Telecommunications

Information Services

Finance and Insurance

Financial Intermediation and

Business Activities

Property Services and Hiring

Business Services

Maintenance and Repair

Hotels and Restaurants

Private Education

Education, Health and Other

Services

Private Health Services

Other Services

Public Education

Public Administration

Public Health Services

Public Administration and Social Security

EORA26 items have also been reduced from 26 to 20 following the standard classification

of IBGE for overall jobs in Brazil

As “Other Manufacturing”, “Recycling”, “Wholesale Trade”, “Retail Trade”, “Post and Telecommunications”,

“Transport”, “Education, Health and Other Services”, “Private Households” and “Others” have been

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

337

3.1 Brazilian export-related jobs by industry/country

First, as in Duran & Banacloche (2022), we have estimated overall employment

associated with Brazilian exports by industry/country of destination. Vector N* of

Brazilian workers by industry has been sourced from standard Supply-Use tables (SUT)

which are available at Instituto Brasileiro de Geografia e Estatistica (IBGE)

The employment coefficient vector matrix is calculated as follows:

EC = N*x-1 = 󰇣















󰇤

(3)

Where N* is the labor factor of sector N. And Xn is the gross value of production of

sector N. Equation 4 plots the multiplier of EC:

MEC = 

 (I – A)-1 =







   

   

   

    

   







(4)

Whereas lij comes from the Leontief inverse matrix or (I – A)-1. The matrix of technical

coefficients, which results from dividing transactions of intermediate inputs (Tij) between

the diagonalized and inverted gross value of production (xn), is labelled as the NxN matrix

of domestic technical coefficients A:

A = 

A =







    

    

    

    

    















   

   

   

    

    







A =







 

 

 

    

 













    

    

    

    

    







(5)

simplified to “Other Manufacturing and Recycling”, “Wholesale and Retail Trade” and “Education, Health

and Other Services”; while “Re-exports” are not considered for labor market comparisons, original

EORA26 IOT items were reduced to 20.

Available at https://www.ibge.gov.br/

JANUS.NET, e-journal of International Relations

e-ISSN: 1647-7251

VOL 15 N.º 2, TD 1

Thematic Dossier

Brazil-China relations: The rise of modern International Order

December 2024, pp. 329-353

Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

338

The inverse Leontief matrix, therefore, has been derived from (5):

L = (I – A)-1

L =







    

    

    

    

    







(6)

Where I is the NxN identity matrix. Export-related jobs, then, will result from multiplying

corresponding Brazilian diagonalized exports by the MEC:

EMPexp = MEC ê

EMPexp =













    









(7)

A row sum results in the number of workers required from industry i to satisfy final

demand for exports by country (region).

Table 3: Export-related jobs by industries/countries (regions)

Source: Authors’s calculation from EORA-26 MRIOT

CHN HKG MAC USA RoW CHN HKG MAC USA RoW

Agriculture 14.905 8.301 0.174 110.263 428.772 38.544 15.058 0.327 115.071 656.553

Fishing 0.836 20.544 0.058 425.326 170.078 3.094 15.436 0.053 259.168 147.476

Mining and Quarrying 7.137 0.394 0.001 8.684 23.698 42.012 0.744 0.004 14.237 60.124

Food & Beverages 1.054 2.869 0.065 20.273 81.911 8.881 7.472 0.168 29.541 190.647

Textiles and Wearing Apparel 2.506 2.524 0.023 227.049 188.034 13.302 4.663 0.045 200.327 290.803

Wood and Paper 2.396 1.302 0.007 77.287 108.096 11.514 1.902 0.012 79.222 153.370

Petroleum, Chemical and Non-Metallic Mineral Products 2.978 0.737 0.008 58.406 97.763 22.714 1.743 0.022 67.970 229.411

Metal Products 2.582 0.617 0.004 42.131 111.326 19.183 1.122 0.009 57.286 235.411

Electrical and Machinery 2.354 0.783 0.007 42.337 89.573 20.101 1.405 0.013 60.494 233.340

Transport Equipment 1.344 0.076 0.001 28.190 73.598 8.117 0.144 0.002 34.261 156.103

Other Manufacturing and recycling 0.424 0.056 0.001 36.682 41.683 2.195 0.082 0.002 32.588 64.181

Electricity, Gas and Water 0.919 0.183 0.002 8.624 19.757 6.997 0.387 0.005 11.702 44.410

Construction 2.131 1.010 0.002 8.202 31.989 15.519 1.982 0.005 8.139 63.674

Maintenance and Repair 0.994 0.952 0.008 28.076 51.530 6.303 1.950 0.018 29.492 101.804

Wholesale and Retail Trade 32.562 31.186 0.262 919.453 1687.537 178.112 55.092 0.508 833.398 2876.794

Hotels and Restraurants 1.690 0.320 0.012 7.499 111.052 15.134 0.763 0.041 12.222 266.710

Transport, Post and Telecommunications 12.332 2.119 0.031 97.881 271.836 101.779 4.911 0.087 144.664 719.580

Finacial Intermediation and Business Activities 7.915 1.394 0.018 60.736 183.837 76.312 3.644 0.058 99.966 521.602

Public Administration 0.016 0.114 0.001 0.020 4.662 0.132 0.169 0.001 0.019 8.535

Education, Health, Private Households and Other Services 5.212 1.025 0.016 31.283 130.882 32.910 1.868 0.039 34.106 277.334

Total 102.290 76.509 0.700 2238.402 3907.614 622.856 120.537 1.420 2123.875 7297.860

2000

2015

Unit: ˈ 000

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Table 3 shows that Brazilian total export-related jobs by industry/country (region) have

almost doubled between 2000 and 2015.

3.2 Vertical integration “in” and “from” Brazil

Vertical integration has emerged as standard indicator for trade in value added (Duran &

Banacloche, 2022; Koopman et al., 2014; Wang et al., 2013). Vertical integration can be

estimated from TiVA data that has been derived in aforementioned EORA26 MRIO tables

(Aslam & Rodrigues-Bastos, 2017; Casella et al., 2019). Vertical integration “in” Brazil

will be defined as the Foreign Value Added (FVA) content of its exports generated by

other countries. Conversely, vertical integration “from” Brazil refers to Brazilian indirect

value added embodied in exports of other countries or DVX. Both variables shall be

considered to further measure Brazilian integration onto the Global Value Chain (using

an index labelled as GVC).

To estimate both FVA and DVX figures, alongside Brazilian DVA embodied in its own

exports, we calculate a matrix of value-added flows (F):

F =







    

    

    

    

    







F = 

 L ê

F =













   

   

   

    

    













    

    

    

    

    













   

   

   

    

    













(8)

Whereas 

is the value-added coefficients matrix. 

 can be obtained by summing each

column of the full technical coefficient’s matrix A, putting these elements on the diagonal

of a square matrix and subtracting it from an identity matrix of the same size. L is the

full inverse Leontief matrix. And ê is the diagonalized export vector. Their product results

in the value-added flows matrix F. This, henceforth, describes how value added contained

in the exports of each industry/country (region) is generated and distributed across

countries (see Table 4).

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ROW CHN HKG MAC USA ROW CHN HKG MAC USA

Agriculture 58257.0 1680.7 166.6 1.2 18774.3 320319.3 25024.6 744.1 12.3 71482.4

Fishing 2127.3 52.9 6.1 0.0 542.1 7531.1 493.7 16.1 0.3 1359.2

Mining and Quarrying 192396.6 6814.0 1405.4 5.3 59860.4 1512714.5 144918.9 9231.3 69.9 318835.7

Food & Beverages 234797.9 5300.8 690.2 4.3 51590.6 1236092.9 72397.8 2642.3 41.3 192144.9

Textiles and Wearing Apparel 227047.5 12811.7 2958.9 15.1 66862.0 822652.8 123793.9 6391.1 116.5 167415.5

Wood and Paper 231722.9 7318.8 1010.7 6.4 88166.8 960513.6 75806.2 3122.9 49.7 238236.3

Petroleum, Chemical and Non-Metallic Mineral Products 834631.2 29856.8 2646.5 17.3 320513.3 3038020.4 293488.7 8411.7 119.0 740527.4

Metal Products 329093.4 16986.6 1431.9 7.0 124013.1 1352669.4 166903.5 4751.0 56.9 366579.6

Electrical and Machinery 823228.7 59216.1 17305.8 29.5 342274.5 3762461.6 779757.3 69518.2 276.9 845691.6

Transport Equipment 1091335.6 39645.6 5738.1 26.0 363477.9 4902829.9 471094.5 19000.4 224.8 1073490.5

Other Manufacturing and recycling 66750.7 3622.3 712.5 4.7 24860.5 280965.8 40252.0 2294.7 34.8 70627.1

Electricity, Gas and Water 3620.0 145.8 28.3 0.1 1519.4 1937.6 210.4 11.1 0.1 600.2

Construction 6718.7 291.0 46.8 0.2 2370.4 45886.9 5229.6 250.2 2.2 10302.3

Maintenance and Repair 439.5 15.3 2.6 0.0 155.4 2446.9 209.5 10.0 0.1 667.2

Wholesale and Retail Trade 18264.4 634.7 108.9 0.5 6456.7 101682.6 8706.5 414.5 5.4 27727.0

Hotels and Restraurants 17911.5 469.7 66.9 0.4 4327.3 111096.1 7274.8 296.9 4.7 18953.0

Transport, Post and Telecommunications 153868.1 5254.3 1041.4 4.4 48963.3 942650.2 81057.8 4564.9 51.1 202728.9

Finacial Intermediation and Business Activities 71911.2 3022.6 639.9 2.7 28117.6 369253.5 38861.1 2353.7 26.9 94008.8

Public Administration 1153.4 42.2 7.8 0.0 409.2 5618.5 514.2 27.6 0.3 1426.4

Education, Health, Private Households and Other Services 18714.8 713.5 111.4 0.6 6339.7 103937.0 10145.9 443.6 6.0 23233.0

FVATOT 4383990.6 193895.3 36126.9 125.9 1559594.5 19881280.6 2346141.1 134496.2 1099.2 4466037.1

ROW CHN HKG MAC USA ROW CHN HKG MAC USA

Agriculture 103189.4 17997.0 4568.4 144.0 32768.7 446219.9 85167.2 30441.1 888.2 121717.4

Fishing 392.2 22.3 89.1 0.9 1239.2 1198.4 186.4 341.5 3.1 3668.6

Mining and Quarrying 306091.4 228153.1 19077.1 117.2 119039.6 1344465.7 1867944.6 125916.8 826.0 377887.7

Food & Beverages 39465.5 2862.5 3095.3 134.9 12346.1 170347.8 30266.9 21972.7 755.2 43697.3

Textiles and Wearing Apparel 71641.0 5418.0 2474.0 25.5 24519.2 256626.4 51755.8 11179.4 136.9 71865.3

Wood and Paper 148348.7 12768.0 6830.9 45.6 115323.9 632067.8 136746.6 40408.0 287.3 407628.8

Petroleum, Chemical and Non-Metallic Mineral Products 342378.6 35653.0 10521.2 94.4 164539.9 1445063.8 388654.3 60914.5 565.2 508945.5

Metal Products 334981.4 24762.2 9641.6 53.8 165352.4 1442675.1 280230.6 50387.1 316.6 485576.6

Electrical and Machinery 202593.4 21656.1 8361.8 49.3 113507.4 858786.2 234146.2 42471.9 285.5 337498.2

Transport Equipment 171513.9 5982.8 1403.7 11.5 44909.2 590014.7 58135.4 8111.1 73.9 161664.7

Other Manufacturing and recycling 11463.8 898.4 235.2 2.3 5997.5 45983.3 10717.3 1396.3 14.5 22861.2

Electricity, Gas and Water 88352.3 14417.3 3094.3 26.5 39223.3 379274.6 164452.5 19461.0 164.4 126393.2

Construction 12630.4 3153.9 944.1 4.7 4206.4 40732.7 25641.6 6074.4 24.7 9925.6

Maintenance and Repair 4636.5 385.6 235.1 1.9 2010.9 16841.0 3454.6 1290.1 10.1 5271.7

Wholesale and Retail Trade 192671.4 16023.6 9771.4 80.1 83563.1 699836.7 143556.4 53611.0 419.3 219070.3

Hotels and Restraurants 16505.8 2281.4 507.2 4.7 3128.2 79042.4 30012.2 3711.0 33.4 12228.2

Transport, Post and Telecommunications 261498.9 50844.5 9290.2 96.6 91513.1 1267042.5 611030.5 66757.9 680.8 326362.2

Finacial Intermediation and Business Activities 445205.3 73989.6 14658.0 153.8 148260.5 2160012.9 948673.1 107649.2 1123.5 546887.2

Public Administration 430.7 13.2 8.1 0.6 33.4 1781.0 131.4 37.0 3.0 102.3

Education, Health, Private Households and Other Services 58785.6 9589.4 1933.1 25.7 16708.7 288990.9 117497.2 13944.4 196.8 59577.2

DVXTOT 2812776.2 526871.7 106739.7 1074.0 1188190.7 12167003.6 5188401.0 666076.4 6808.6 3848829.1

BRAZILIAN FVA IN EXPTOT TO THE WORLD PER ORIGIN

(UNIT = '000)

2000

2015

BRAZILIAN DVX TO THE WORLD PER DESTINATION

(UNIT = '000)

2000

2015

Table 4 : Brazilian GVC matrix (F)

Source: Authors

The results for Brazil are shown in Table 5.

Table 5: FVA and DVX values for Brazil by industry / country (region) in 2000-2015

Source: Authors’ calculation from EORA-26 MRIOT

SEC 1 SEC 2 …SEC 20 SEC 1 SEC 2 …SEC 20 SEC 1 SEC 2 …SEC 20 SEC 1 SEC 2 …SEC 20

SEC 1

SEC 2

…

SEC 20

SEC 1

SEC 2

…

SEC 20

SEC 1

SEC 2

…

SEC 20

SEC 1

SEC 2

…

SEC 20

DVX OF BRAZIL EMBODIED IN CHINA

EXPORTS

DVX OF BRAZIL EMBODIED IN USA

EXPORTS

F MATRIX

BRAZIL

CHINA

USA

DVA EMBODIED IN BRAZILIAN EXPORTS

FVA FROM RoW EMBODIED IN

BRAZILIAN EXPORTS

FVA FROM CHINA EMBODIED IN

BRAZILIAN EXPORTS

FVA FROM RoW EMBODIED IN

BRAZILIAN EXPORTS

DVX OF BRAZIL EMBODIED IN RoW

EXPORTS

RoW

BRAZIL

CHINA

USA

RoW

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Finally, in order to measure Brazilian backward linkages within the GVC by

partner/industry, the 



 ratio is calculated (whereas forward linkages will be noted

as 



). Adding both 



 and 



 we will also estimate the Global Value

Chain index for Brazil (GVCBRA-S).

4. Correlation between export-related jobs and TiVA in Brazil

Brazil reveals a relatively low integration onto the GVC. Its overall GVC index ranks 32th

in the world marking a value of just 0.462%

. China, however, is the world second largest

nation when considering both FVA and DVX flows within GVC, also ahead of US. China

and US then should be considered as “core” countries which could help other “peripheral”

commercial partners like Brazil to further integrate onto the GVC.

Table 6: Brazil position in the GVC (2015)

RANK

COUNTRY

GVC INDEX

Germany

6.211%

China

4.402%

USA

4.030%

Netherlands

2.943%

France

2.812%

2.484%

Japan

2.417%

Belgium

2.404%

Italy

2.297%

South Korea

1.794%

Canada

1.474%

Singapore

1.389%

Spain

1.321%

Russia

1.079%

Switzerland

1.076%

…

Brazil

0.462%

Source: Author’s calculations from UNCTAD-EORA GVC Database

GVCBRA-WLD = (DVXBRA-WLD + FVAWLD-BRA) / EXGRWLD.

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When calculating Brazilian GVC indexes by country, as GVCBRA-S = 





 ,

empirical evidence shows a decoupling between Brazil and US alongside overall job

losses within the period 2000-2015. Yet, on the other hand, a sustained growth of

Brazil-China TiVA flows, or GVCBRA-CHN, has nonetheless contributed to substantial

increases in Brazilian exports-related jobs (508.9%)

Graph 2: There is a positive correlation between variation rates of export-related jobs

and the GVC

Source: Authors’ calculation from EORA-26 MRIOT

Empirical evidence also suggests a direct and stronger impact of DVX over employment

growth rates when compared to FVA. Then it could be theorized that backward linkages

incentivize variables such as DVX, thus boosting both exports and overall jobs, which

facilitate a continuous integration of Brazil onto the GVC.

Excluding both Macau SAR and Hong Kong SAR.

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Graph 3: DVX is more strongly correlated to export-related jobs than FVA

Source: Author’s calculations from UNCTAD-EORA GVC Database

Then, corresponding increases/decreases in GVC indexes are consistent with the main

assumption outlined throughout this chapter which is that TiVA exchanges have a direct

correlation to growth rates of export-related jobs. For instance, while GVCBRA-USA in

“Wholesale and Retail Trade” did register a sharp decrease, Brazilian export-related jobs

to US were also cut by -9.4%. Yet high growing rates in GVCBRA-CHN have contributed to

increase Brazilian export-related jobs in “Wholesale and Retail Trade” more than five

times (447%). This is significant since “Wholesale and Retail Trade” was also the largest

single source for Brazilian export-related jobs in 2015 (38,7%).

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Table 7: Variation rates of GVC indexes and export-related jobs in Brazilian “Wholesale

and Retail Trade”

WHOLESALE AND RETAIL TRADE (2000-2015)

VAR 00-15 (LOG SCALE)

CHN

HKG

MAC

USA

GVC

0.74

0.23

0.19

-0.47

EMPLOYMENT

1.70

0.57

0.66

-0.10

Source: Authors’ calculation from EORA-26 MRIOT

Both “Electrical and Machinery” and “Transport Equipment” have been the largest

receptors of FVA in Brazil. This implies that foreign multinational corporations did invest

in Brazil, for export purposes, while importing intermediate inputs from other countries

within the GVC. Total share of Chinese FVA embodied in Brazilian “Electrical and

Machinery” exports grew from 4.76% to 14.29%, while it decreased when considering

US (from 27.5% to 15.5%). And a similar pattern can also be seen in other industries,

such as “Transport Equipment”, where FVACHN-BRA over the total grew from 2,6% to 7,2%.

Meanwhile, US value added share embodied in Brazilian “Transport Equipment” exports

was reduced, from 24,2% to 16,6%. Therefore, even although these two industries

account for a small share of export-related jobs, growing FVACHN-BRA flows have also

contributed to increase Brazilian labor through Chinese vertical integration “in” Brazil.

Graph 4: Vertical integration in Brazil and impact on export-related jobs

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Source: Authors’ calculation from EORA-26 MRIOT

Nonetheless, as aforementioned, correlation between vertical integration and export-

related jobs is stronger when considering forward linkages or DVX. Brazilian largest DVX

shares over the total are concentrated in industries such as “Financial Intermediation and

Business Activities” (17.2%), “Mining and Quarrying” (17%), “Petroleum, Chemical and

Non-Metallic Mineral Products” (11%), “Transport, Post and Telecommunications”

(10.4%) and “Metal Products” (10.3%). Data shows that variation rates of export-related

jobs in those industries had a direct correlation to 



 increases / decreases for the

period 2000-2015 (see Graph 5).

Graph 5: Correlation between forward linkages and export-related jobs

Source: Authors’ calculation from EORA-26 MRIOT

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In addition to this, while “Financial Intermediation and Business Activities”, “Mining and

Quarrying”, “Petroleum, Chemical and Non-Metallic Mineral Products”, “Transport, Post

and Telecommunications” and “Metal Products” accounted for 65.9% of overall DVX in

Brazil, export-related jobs derived from those industries just totaled 23.8%. US

industries such as “Financial Intermediation and Business Activities”, “Petroleum,

Chemical and Non-Metallic Mineral Products”, “Metal Products”, “Wood and Paper” and

“Mining and Quarrying” accounted for 10.64% of overall Brazilian DVX exports to the

world but just 3.13% in total export-related jobs. In China, while “Mining and Quarrying”,

“Financial Intermediation and Business Activities”, “Transport, Post and

Telecommunications”, “Petroleum, Chemical and Non-Metallic Mineral Products” and

“Metal Products” accounted for 18.73% of overall Brazilian DVX exports to the world,

total export related jobs in those industries were 2.57%. This just indicates that Brazilian

vertical integration “onto” China does demand less export-related jobs compared to US.

Table 8: DVX and export-related jobs over the total for selected countries / industries

(2015)

USA

DVX

EMP

CHN

DVX

EMP

Financial Intermediation

and Business Activities

2.5%

0.98%

Mining and Quarrying

8.54%

0.41%

Petroleum, Chemical and

Non-Metallic Mineral

Products

2.33%

0.67%

Financial Intermediation and

Business Activities

4.34%

0.75%

Metal Products

2.22%

0.56%

Transport, Post and

Telecommunications

2.79%

Wood and Paper

1.86%

0.78%

Petroleum, Chemical and

Non-Metallic Mineral

Products

1.78%

0.22%

Mining and Quarrying

1.73%

0.14%

Metal Products

1.28%

0.19%

Total

10.6%

3.13%

Total

18.73%

2.57%

Source: Authors’ calculation from EORA-26 MRIOT

Biggest shares of Brazilian export-related jobs to China, over the world total by industry,

were concentrated in “Mining and Quarrying” (35.87%), “Construction” (17.38%),

“Electricity, Gas and Water” (11.02%), “Financial Intermediation and Business Activities”

(10.88%) and “Transport, Post and Telecommunications” (10.48%). Yet all those

industries put together just represented a 2.4% share over total Brazilian export-related

jobs. US five largest industries, on the other hand, had an overall share of 13.5%

(“Fishing”, “Textiles and Wearing Apparel”, “Other Manufacturing and Recycling”, “Wood

and Paper” and “Wholesale and Retail Trade”). Therefore, in absolute terms, US remains

dominant when considering Brazilian export-related jobs (accounting for 20.9% of the

total).

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Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

347

ROW CHN HKG MAC USA

Agriculture 79.53% 4.67% 1.82% 0.04% 13.94%

Fishing 34.68% 0.73% 3.63% 0.01% 60.95%

Mining and Quarrying 51.34% 35.87% 0.63% 0.00% 12.16%

Food & Beverages 80.54% 3.75% 3.16% 0.07% 12.48%

Textiles and Wearing Apparel 57.12% 2.61% 0.92% 0.01% 39.35%

Wood and Paper 62.34% 4.68% 0.77% 0.00% 32.20%

Petroleum, Chemical and Non-Metallic Mineral Products 71.28% 7.06% 0.54% 0.01% 21.12%

Metal Products 75.21% 6.13% 0.36% 0.00% 18.30%

Electrical and Machinery 73.99% 6.37% 0.45% 0.00% 19.18%

Transport Equipment 78.59% 4.09% 0.07% 0.00% 17.25%

Other Manufacturing and recycling 64.80% 2.22% 0.08% 0.00% 32.90%

Electricity, Gas and Water 69.94% 11.02% 0.61% 0.01% 18.43%

Construction 71.29% 17.38% 2.22% 0.01% 9.11%

Maintenance and Repair 72.94% 4.52% 1.40% 0.01% 21.13%

Wholesale and Retail Trade 72.94% 4.52% 1.40% 0.01% 21.13%

Hotels and Restraurants 90.45% 5.13% 0.26% 0.01% 4.14%

Transport, Post and Telecommunications 74.11% 10.48% 0.51% 0.01% 14.90%

Finacial Intermediation and Business Activities 74.35% 10.88% 0.52% 0.01% 14.25%

Public Administration 96.36% 1.49% 1.91% 0.01% 0.22%

Education, Health, Private Households and Other Services 80.09% 9.50% 0.54% 0.01% 9.85%

TOTAL EMPexp 71.8% 6.1% 1.2% 0.0140% 20.9%

BRAZILIAN EXPORT-RELATED EMPLOYMENT (% TOTAL)

2015

Table 9: Brazilian export-related jobs shares over world total (2015)

Source: Authors’ calculation from EORA-26 MRIOT

Graph 6: Variation rates of Brazilian export-related jobs with China and US (2000-

2015)

Source: Authors’ calculation from EORA-26 MRIOT

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Alberto J. Lebrón Veiga, Carlos M. Martin

348

Nevertheless, despite US still represents a much larger share of Brazilian export-related

jobs in absolute terms, growing TiVA exchanges with China has allowed Brazil to create

new export-related job opportunities between 2000 and 2015. Brazilian export-related

jobs grew from 2.84% to 7.33% out of the total when considering China, Hong Kong and

Macau; but were reduced from 35.4% to 20.9% in the case of US. At the same time,

Brazilian DVX to China reached a share of 23.72% in 2015, overtaking US (17.59%).

Table 10: Largest increases / decreases in Brazilian forward linkages and logarithmic

variation rates of export-related jobs (2000-2015)

USA

DVX

EMP

CHN

DVX

EMP

Construction

-0.62

-0.01

Hotels and Restaurants

1.10

2.19

Wholesale and Retail

Trade

-0.51

-0.10

Financial Intermediation and Business

Activities

1.08

2.27

Maintenance and

Repair

-0.51

0.05

Education, Health, Private Households and

Other Services

1.03

1.84

Textiles and Wearing

Apparel

-0.40

-0.13

Transport, Post and Telecommunications

1.01

2.11

Metal Products

-0.40

0.31

Other Manufacturing and recycling

1.01

1.64

Fishing

-0.39

-0.50

Electricity, Gas and Water

0.96

2.03

Source: Authors’ calculation from EORA-26 MRIOT

As shown in Table 10, all Brazilian industries without exception have boosted their export-

related jobs when increasing 



 with China. Yet, on the other hand, larger declines

of 



 correspond to either net losses or much smaller increases in export-related

jobs when considering US.

5. Conclusion

Increasing TiVA exchanges between China and Brazil constitutes a source of job creation

for the latter. But, on the other hand, a sustained decoupling with US has eliminated

114.520 export-related jobs in Brazil between 2000 and 2015. Yet export-related jobs

linked to US were one-fifth of the total in 2015. And, in the case of China, such share

was just a 6.1%.

Either considering total growth rates or overall shares of export-related jobs, China and

US are relevant TiVA partners for Brazil. Therefore, from an economic perspective,

optimal choice for Brazilian commercial policies would be maximizing TiVA exchanges

with both China and US. Brazilian continuous integration with Chinese GVC would help

the former to create more export-related jobs. And, on the other hand, a large number

of export-related jobs can be preserved in labor-intensive industries such as “Wholesale

and Retail Trade” or “Fishing” through continuous commercial exchanges with US. It

might seem obvious, therefore, that great power politics is not in the best economic

interest for Brazil.

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Brazilian Tiva Under Us-China Strategic Competition and Impact on Export-Related Jobs

(2000-2015)

Alberto J. Lebrón Veiga, Carlos M. Martin

349

Brazil should further promote forward-linkages with China in more labor-intensive

industries such as “Wholesale and Retail Trade”, “Fishing”, “Textiles and Wearing

Apparel” or “Transport, Post and Telecommunications”. Export-related jobs of

aforementioned industries, for US, totaled 1,43 million, which is almost five-times when

compared to China. Hence, given that a unit of DVXBRA-CHN requires much less export-

related jobs compared to US, Brazil could deepen its TiVA ties in more labor-intensive

activities with China.

As aforementioned, some Brazilian largest shares of DVX are still concentrated in

extractive basic industries like “Mining and Quarrying”, “Petroleum, Chemical and Non-

Metallic Mineral Products” or “Metal Products”. Yet more labor-intensive industries, such

as “Transport Equipment” or “Electrical and Machinery”, have been increasing their





 inflows from China, thus becoming the largest destinations of overall Chinese

FVA embodied in Brazilian exports. Chinese vertical integration, in Brazil, is also

coincidental with an increase of Brazilian DVX to China. And, in the case of US, both

industries have registered a sharper decline of both 



 and 



 . Therefore,

export-related jobs have been increasing faster in those industries which shown a

deepening vertical integration with China, as opposed to US.

US might consider Brazil as a relevant supplier of raw materials which contributes to

strengthen China either through its final demand or processing trade within the GVC. And

it could also see China as a competitor in Brazilian labor-intensive industries like

“Transport Equipment” or “Electrical and Machinery”. However, despite great power

politics between declining and emerging powers in Brazil, a strategic balance of TiVA

exchanges with both US and China has contributed to increase Brazilian overall export-

related jobs about 60.7% during the period 2000-2015.

6. Data resources

The Eora Global Supply Chain Database. Retrieved in June 2024, from:

www.worldmrio.com

Instituto Brasileiro de Geografia e Estatistica (IBGE). Retrieved in June 2024, from:

https://www.ibge.gov.br/

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