Strengthening bilateral relations and support in multilateral forums: Brazil-Africa

relations (1995-2010)1

PhD. Juliana J. Costa2

The research problem of this article is investigate the mechanisms employed by a

country to win the votes and support of other countries in multilateral forums. States

deepen their bilateral relations to win support at the multilateral level to increase their

weight and prestige in international system.

Cooperation at international organizations is an important topic, because these

institutions are important to diffuse information and as an arena of power to states.

Therefore, countries with lower relative power or limited resources use multilateral

forums as an instrument to achieve their demands in the current international system.

Despite advanced research does not deal with emerging countries, leaving open some

questions: How a country with limited economic and political power can win allies at

multilateral organizations? What are the benefits offered by an emerging country for this

purpose? The strengthening of bilateral relations generates multilateral support?

Through Brazil-Africa relations between 1995 and 2010, this article aims to verify

whether the increase of bilateral relations generates vote convergence among countries at

United Nations General Assembly (UNGA).

This study also has the following secondary hypotheses:

- Brazil, to win the multilateral support of other states, used bilateral strategies, such

as trade and technical cooperation with African countries;

- African countries increased their support to Brazil at UNGA during the period.

To achieve this goal, this research has three sections. First, studies on the "exchange"

of bilateral benefits for support in multilateral forums.

The second section presents general African foreign policy in FHC and Lula

governments. In addition, shows the variables chosen as indicative of Brazilian strategy

to win allies in Africa - bilateral trade and technical cooperation projects between Brazil

and Africa.

The last section has four parts. At first, the choice of UNGA as a parameter of

international alignment. The second presents the methodology and the model used to

verify the main hypothesis. In the third, the data, descriptive statistics and their possible

results. In the last part, the results and the proof or not of the hypothesis.

Finally, in conclusion, it will be possible to answer the research problem that is the

strengthening of bilateral relationship increased the support of beneficiary countries at

multilateral forums.

This article, thus, contributes to the study of emerging countries in the international

system, complementing existing research on the strategies used by countries to win allies

at international organizations.

1. BILATERAL STRATEGIES AND THE SUPPORT AT INTERNATIONAL

ORGANIZATIONS

1 This article is part of PhD thesis presented in March 2015 at International Relations Institute at the University of São Paulo (IRI /USP). 2 International PhD Relations at International Relations Institute at University of Sao Paulo and professor at School of

Commerce Foundation Alvares Penteado and University Anhembi Morumbi.

Some International Relations researchers examines the factors that influences

cooperation between States, such as alliances, external assistance or commitment to

international institutions.

Some states, at international organizations, such as UNGA are more susceptible to

bilateral pressures. Thus, the more a state is dependent in terms of trade, aid or protection,

is more vulnerable to pressure from the most powerful states. (KEOHANE, 1966, p. 19).

From these considerations, in the 60s an extensive literature began to study voting

patterns in UNGA (Alker, 1964; Russett, 1966; Kim; Russett, 1996; Voeten, 2000). In

the same decade, there were studies investigating the use of foreign aid by United States

to influence the votes at UN (Wilcox, 1962; Mason, 1964; Westwood, 1966; Kaplan,

1967; Plan; Riggs 1967, Black, 1968).

Andrew Westwood (1966, p. 105) concluded that efforts to make translate aid in

ideological support by the beneficiaries would probably not be necessary because the use

of foreign aid to promote cooperation has become more important than the ideological

issue1.

In the 80s, these studies identified how and when major powers "buy" votes though

foreign aid to achieve their expected results (Wittkopf, 1973; Rai, 1980; Kegley and

Hook, 1991; Wang, 1999). Besides traditional motivations for development assistance to

the least developed countries, donor governments also consider, in their foreign aid

allocations, its own national interests, such as political and security interests, investment

and trade (Maizels; Nissanke, 1984 p. 879), with political or security interests dominating

the results2.

In the 70s and 80s, researchers concluded that bilateral donors pursue their own

interests when allocate aid, and there is a strong empirical evidence demonstrating the

association between foreign aid and voting behavior at UNGA, focusing on the developed

countries, major donors in the world.

In recent years, research on cooperation with the US at UN has two sides: first, based

on the fact that divisions at UN reflects the wider international cleavages, and states

creates preferences similar to US (Kim; Russett 1996; Voeten, 2000).

The second highlights the strategic voting and policies made by the United States to

create common preferences and to influence to vote with US, known as vote buying. In

this case, cooperation is induced by state policies and foreign aid, which would influence

the recipient nations. Thus, more dependent a state is from US aid, closer will be their

votes convergence with US (Wang, 1999; Lai; Morey, 2006, p 388.).

Foreign aid would serve not only to the economic interests of donors, but also to buy

political support of receivers3 (Langhammer, 2004), since US government gives some

weight to votes at UNGA.

For Alesina and Dollar (2000), the correlation between friendship variables at UN

and aid flows can be interpreted in two ways: to help buy votes at UN in favor of the

donor; or UN votes are a reliable indicator of political alliances between countries and

these alliances defines aid flows (Alesina, Dollar, 2000).

According to the authors, the second interpretation is more plausible, as many votes

at UN are significant from the point of view of foreign policy. However, it would not be

clear why donor countries are concerned to buy these votes, as the voting patterns are

strongly correlated with alliances and similarities of political, economic and geopolitical

interests.

The best interpretation is that donors favors your friends with foreign aid, and an

observable proof of friendship would be UN votes, suggesting that an exogenous change

in voting patterns indicates a change in geopolitical alliances patterns that would bring a

change in aid (Alesina, Dollar, 2000, p. 46)

However, the two interpretations are consistent with the view that aid is used for

strategic purposes and is not easy disaggregate, econometrically, the two interpretations,

or aid causes UN votes or votes at UN causes aid? (Alesina, Dollar, 2000, p. 46)

Other studies found evidence that US foreign aid and other developed countries

would be offered to members of UNGA to shape their voting patterns (Lay; Morey, 2006).

Therefore, the hypothesis that UN voting affects foreign aid is plausible, at least in key

voting, for donors. However, political donors’ agendas are critical and could take aid

allocations away from the needs questions (Boone, 1996; Alesina, Dollar, 2000; Collier,

Dollar, 2002).

The aid distribution, therefore, is strongly related to donors’ geopolitical interests and

foreign policy preferences (Maizels; Nissanke, 1984; Boone, 1996; Cashel-Greement;

Schraeder et al, 1998; Svensson, 1999; Alesina, Dollar, 2000; Alesina; Weder, 2002;

Neumayer, 2003).

The few studies that propose to bring evidence of vote-buying show a connection

between changes in aid flows to a US receiver and vote convergence (Wang, 1999).

However, these correlations can be explained in two different ways. On the one hand, UN

vote would be associated with foreign aid, since this allocation would be used to reward

or punish countries to vote in certain ways. On the other hand, UN vote could not be

important for donors, but rather a reflection of sincere political preferences between UN

members. Thus, any relationship between UN voting and aid flows could be interpreted

as an evidence that donors prefer to contribute to regimes with the same view and with

similar foreign policy goals.

Thus, variable "regime" began to be used to explain the link between UN votes and

foreign aid allocation (Lay; Morey, 2006). Democratic governments would be more likely

to vote according to their own preferences and a reduction in foreign aid allocation would

not influence their vote, because they have the winning coalitions and the electorate

support (Bueno Mesquita Et Al., 2003). For autocratic leaders, the lack of popular

legitimacy would cause government dependence on supply private goods to elite groups

(Bueno Mesquita Et Al., 2003).

Other variables are relevant. Carter and Stone (2011, p. 3) believe US punishes or

rewards receptors differently depending on their regime type, the government's political

orientation, level of development and alliance relationship, would explain the

effectiveness US attempts to influence votes at UNGA.

The UNGA votes are also used in studies to establish an association between UN

votes and aid by many donors and multilateral institutions (Clay; Lee, 2005; Oatley,

Thacker, 1999).

The most robust study on International Monetary Fund programs (IMF) shows that

the loan fund would be significantly shaped by geopolitical preferences of major

shareholders, particularly US.

In these studies, UN vote is a control variable (Steinwand, Stone, 2008). Thacker

(1999) and Barro and Lee (2005) conclude that the increasing vote convergence with US

could be associated with a higher probability of IMF loan.

Other recent researches emphasizes votes designated as important by United States

to study vote buying. Andersen et al. (2006) assumes alignment to US in important

UNGA polls as a concession, and use these votes to build a measure of political

concessions from the country to US, to then estimate the probability of a country to get

an IMF loan.

Other studies also attempt to establish a relationship between being a temporary

member of Security Council (SC) and the granting of loans by IMF (Kuziemko; Werker,

2006; Dreher et al, 2009.).

To Dreher et al. (2009), IMF loans would be a mechanism of major shareholders to

gain favors from UNSC members. Some developing countries would give more value to

loans than their votes at UNSC, and developed countries would value UNSC votes more

than loans. Therefore, some developing countries would be willing to sell their votes in

UNSC for IMF loans.

The studies on relationship between foreign aid and UNGA voting, although

emphasize developed countries, it is important because demonstrates that States are

willing to use different tools to influence voting behavior of other countries in multilateral

forums. However, this literature does not address support among developing countries at

international organizations and tools used by them to form alliances.

Therefore, this article, assuming the argument that countries "buys" support in

multilateral organizations polls, seeks to prove if it occurs between developing countries

which, in recent years, increased their power in international system and its presence at

international organizations.

As developing countries have a limited capacity of foreign aid, one way to win such

support would be bilateral cooperation projects, since money invested would be smaller

and would also promote the development of recipient countries.

Another one would be trade, because it guarantees, such as cooperation or foreign

aid, development and economic growth of the largest commercial attention receptor. The

similarity of positions at multilateral level would increase between countries with

increasing trade flows.

This study therefore aims to investigate vote buying, basically dedicated to developed

countries, it may be applied to the analysis of multilateral support among developing

countries.

2. BRAZIL-AFRICA RELATIONS IN RECENT YEARS (1995-2010):

2.1. Regions of interest in FHC and Lula foreign policies in numbers:

In Lula government, there was a direction to South-South relations, especially Latin

America and Africa, by extending or reactivating contacts with non-traditional partners

in these regions.

Lula's foreign policy creators believed intensifying contacts with the South, Brazil

could win allies and their support for their demands at international level - development

and a permanent seat on the UN Security Council.

This change can be seen in bilateral presidential trips. While FHC made 48 trips to

North (41.7% of total) and 67 to South (58.2%), Lula traveled 47 times to North (26.1%

of total) and 123 to South (68 3% of total), especially African countries (Source: MRE,

2010, p.9).

This diversification also occurs in trade, with an increase in Brazilian exports, which

increases from US$ 61.68 billion in FHC government, to US$ 133.92 billion in the next

government, increasing 117%.

In the period, exports to South surpassed those for North, and the exports volume to

South along Lula government, exceeding exports to North, increasing 276% for the

former and 76% for the second.

Chart 1 – Brazilian Exports Destination Evolution

Self elaboration. Source: MDIC

However, change is still slow because the South share in Brazilian exports in Lula

government is similar to North participation, and has not grown so much from the

previous government, from 39.10% to 49 49%. The change, is marginal, and European

and North American markets remain relevant.

Chart 2 - Brazilian Exports Destinies by Government

Self elaboration. Source: MDIC

In imports, the movement is similar, but slower. Brazilian imports grew 62%, from

US$ 63.26 billion during Cardoso government, to US$ 102.45 in Lula government.

A change occurred in the origins of Brazilian imports, with an increase in South

imports and a decrease of those coming from North. South imports grew from US$ 173.9

billion to US$ 386.95 billion, an increase of 123% between the two governments. Imports

from North pass from US$ 333.39 billion to US$ 437.45 billion in the Lula government,

an increase of 31%.

40,50

71,20

25,19

100,34

-

20,00

40,00

60,00

80,00

100,00

120,00

2002 2010

BRAZILIAN EXPORTS DESTINATION

EVOLUTION (US$ BILLION -YEAR BASE

2005)

North

South

0,00

50,00

100,00

150,00

200,00

250,00

300,00

FHC LULAUS

$ b

illi

on

FO

B (

yea

r b

ase

20

05

)

BRAZILIAN EXPORTS DESTINIES BY

GOVERNMENT

Africa

Latin America

European Union

Middle East

Asia (-China)

China

USA

Asia

Graph 3 - Brazilian imports origins evolution

Source: AliceWeb. Self elaboration.

Noticed an increase in almost all markets, except United States and Middle East. The

imports that increases faster are from Asia, largely due to China.

Graph 4 – Imports origins by market and government

Source: AliceWeb. Self elaboration.

Between two governments occurred a fall in almost all markets, except Asia and

Africa, which would explain the increase in imports from South.

The data collected, until now, confirms the relative change in Brazilian foreign policy

hypothesis, with the intensification of contacts with South, which could be a strategy to

increase the Brazilian bargaining power in the international system.

2.2. The lines of African politics in comparative perspective

The two governments had different strategies of relationship with Africa. In FHC,

the approach was selective, especially the relations with South Africa, Angola, countries

of South Atlantic Peace and Cooperation Zone (ZOPACAS, in portuguese) and the

Community of Portuguese Language Countries (CPLP, in portuguese) and greater

participation in UN peace missions4, most of it in Africa and the conclusion of Mercosur

South Africa Framework Agreement.

333,4

437,4

173,9

386,9

0

100

200

300

400

500

FHC LULA

BRAZILIAN IMPORTS ORIGINS

EVOLUTION (US$ BILLION - YEAR-BASE

2005)

North

South

0,0

50,0

100,0

150,0

200,0

250,0

300,0

FHC LULAUS

$ b

illi

on

FO

B (

yea

r b

ase

20

05

)

IMPORTS ORIGINS BY MARKET AND

GOVERNMENT

Africa

Latin America

European Union

Middle East

Asia (-china)

China

USA

Asia

In Lula government, the approach was more diversified due to the emphasis in

foreign policy to the relations with South, based on strategic and economic interests,

which one is Brazilian global projection.

Presidential trips to Africa shows these characteristics. While FHC visited in his 4

trips to continent, only two countries (Angola and South Africa), Lula, in his 34 trips,

visited 29 countries. Lula was also present in regional African summits.

FHC closed Brazilian embassies at Cameroon, Democratic Republic of Congo and

Tanzania. In Lula government, the number of Brazilian embassies in Africa doubled, to

34, highlighting the reopening of three closed embassies in the previous government.

Figure 1 - Re-opened embassies in Africa

Source: MRE, 2010, p. 2.

Despite embassies opening in relevant countries for bilateral trade, such as Benin and

Ivory Coast, in important countries in region, such Cameroon, and for commercial

interests, such Mauritania and Tanzania, with the establishment of Brazilian companies

after embassies opening. Also the opening in countries with which Brazil had few

contacts and little relevance in the international and African scene, as Botswana and

Burkina Faso, featuring a little pragmatic strategy, more focused on speech.

Another important action was the debt forgiveness to African countries, according to

the Millennium Development Goals, indicating the attempt of Lula government to deepen

and diversify its relationship with African.

2.3. Brazil-Africa Trade flow between 1995 and 2010:

The trade also presents market diversification the increase of Brazilian exports to

Africa, however, African participation in Brazilian exports varies very little, despite the

growth in total exports volume of Brazil.

Africa's share in exports was 3.1% in FHC, while Lula was 4.9%, an increase of 1.8%

(Source: MDIC), confirming the markets diversification. However, Africa's share of total

Brazilian exports is still modest, taking, on both governments, the fifth place.

Graph 5 - Africa's participation in Brazilian exports by government

Self elaboration. Source: MDIC.

Between 1995 and 2002, exports to Africa grew US$ 500 million, a 26% increase

compared to 159% between 2003 and 2010, from US$ 3.03 billion in 2003 to US$ 7.66

billion in 2010 (SOURCE: MDIC). In the exports volume, the difference between two

governments is much higher, indicating that the exports growth to Africa region was part

of a general increase of movement of Brazilian exports and not a phenomenon of

emphasis in Brazilian trade relations with African countries.

Chart 6 - Exports to Africa by government

Self elaboration. Source: MDIC.

In Exports by African region, there is an equilibrium, except for Central and Eastern

Africa, whose exports do not exceed 5% of total exports to the continent. In FHC

government which, according to literature favored Portuguese-speaking countries, these

countries have a minimum share of Brazilian total exports to Africa, about 6.6% (Source:

AliceWeb).

Therefore, the selectivity in FHC government is not proven by Brazilian exports

share by African region. Moreover, in Lula government, exports increased, especially to

Portuguese-speaking countries, with an increase of 111% (Source: AliceWeb), while the

share of other regions does not show a significant change.

0,0%

2,0%

4,0%

6,0%

TOTAL 1º MANDATO 2º MANDATO

AFRICA'S SHARE IN BRAZILIAN

EXPORTS BY GOVERNMENTS

FHC LULA

0

10

20

30

40

50

60

TOTAL 1º TERM 2º TERM

US

$ B

ILL

ION

(Y

EA

R B

AS

E 2

005)

EXPORTS TO AFRICA BY GOVERNMENT

FHC LULA

Chart 7 - African regions shares in Brazilian exports to Africa

Self elaboration. Source: AliceWeb.

There was no diversification in African markets buyers because their participation

has not changed from one government to another. There has been a change of position,

especially Angola and Algeria, whose exports increased, respectively, 124% and 78%.

Chart 8 - Major buyers in Africa

Self elaboration. Source: AliceWeb

There were no major changes in the products exported to Africa, with no change in

position of the top ten export products, reflecting low diversification, different from

intentions and efforts of Lula government.

0,0%5,0%

10,0%15,0%20,0%25,0%30,0%35,0%40,0%45,0%

FHC LULA

AFRICAN REGIONS SHARES

IN EXPORTS TO AFRICA

Central Africa North Africa South Africa

Western Africa Eastern Africa CPLP

0%

5%

10%

15%

20%

25%

Co

un

try

Shar

e in

Bra

zilia

n

Exp

ort

s

MAJOR AFRICAN BUYERS

FHC

LULA

Chart 9 - Products exported to Africa

Self elaboration. Source: AliceWeb.

There was an increased African participation in Brazilian imports, which passed from

4.16% in FHC government to 8.09% in Lula government, a growth of 95% (Source:

MDIC). However, this increment was due to an expansion in total imports, not changing

the position of African countries in imports, continuing to be the sixth market of Brazilian

purchases abroad.

Graph 10 - African share in Brazilian Imports by government

Source: AliceWeb. Self elaboration.

Between 1995 and 2002, imports from Africa increased 127%, while in the next

government grew 243% (Source: MDIC). This volume grew from US$ 17.8 billion during

Cardoso government to US$ 71.1 billion in Lula government, an increase of 299%, much

higher than the growth in total imports volume was 105%. This increase was due to the

purchase of oil, because Brazil reduced its Middle East imports and started to import it

from Africa, through the Brazilian Petrobrás activities.

0% 10% 20% 30% 40%

SUGAR

REACTORS

ORE

CHEMICAL PRODUCTS

FATS AND OILS

Share in exports to Africa

Prod

cts

MAJOR PRODUCTS EXPORTED TO AFRICA BY GOVERNMENT

LULA

FHC

0,0%

2,0%

4,0%

6,0%

8,0%

10,0%

TOTAL 1º MANDATO 2º MANDATO

AFRICAN SHARE IN BRAZILIAN

IMPORTS BY GOVERNMENT

FHC LULA

Graph 11 – Imports Volume from Africa by government

Self elaboration. Source: AliceWeb.

There were no major changes in African regions of Brazilian imports, with little

attention to Central Africa and East Africa, with less than 1.5% together. This is because

there are, in these regions, major oil exporters, main product imported by Brazil.

The regions with the highest growth were West Africa and CPLP, whose increases

were, respectively, 36% and 124%, again due to oil imports originated from Nigeria, in

the first region, and Angola, in the second group. There were declines in imports from

North Africa and Southern Africa, especially in this last area, the decrease of a traditional

Brazilian partner, South Africa.

These data demonstrate that was not diversification in imports. On the contrary, there

was a concentration in Portuguese-speaking countries and Nigeria.

Graph 12 – Imports share by African Region

Self elaboration. Source: AliceWeb.

The analysis of supplier markets confirm the concentration in oil producers since,

except Nigeria and Angola - major oil producers - and Morocco - with a discrete high,

other markets decreased their share in Brazilian imports.

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

TOTAL 1º MANDATO 2º MANDATO

US

$ B

ILL

ION

(Y

EA

R-B

AS

E 2

005)

IMPORTS VOLUME FROM AFRICA BY

GOVERNMENT

FHC LULA

0%10%20%30%40%50%60%

FHC LULA

IMPORTS SHARE BY AFRICAN

REGION

Central Africa

North Africa

South Africa

Western Africa

Eastern Africa

Graph 13 - Markets Suppliers by government

Self elaboration. Source: AliceWeb.

There is a concentration of imported products from Africa, and oil and oil products

are the main products, a permanent fact in two governments, changing only the

participation of these products in imports. Total imports of oil increased from US$ 16.9

billion during Cardoso government to US $ 61.9 billion, growth of 60.9% (Source:

AliceWeb). Further, Brazilian imports from Africa remained concentrated on oil, from

78.2% to 87.05%.

Brazil-Africa trade balance, between two governments, is in deficit due to high

imports of African oil. As well as in imports, the deficit is much higher in Lula

government, largely by the increase in oil imports.

Between the two governments, flow trade with Africa grew 44%, while trade flow

between Brazil and the world in the period increased 84.33% (Source: MDIC). The

Brazilian trade with the world has increased almost twice, indicating that exchange with

region did not follow the exchange with the world.

Chart 14 - Trade Flow with Africa by government

Self elaboration. Source: AliceWeb.

The Brazil-Africa trade relations has shown little change, with a low participation of

Africa in Brazilian trade flow and growth below increase in Brazilian total trade.

0%5%

10%15%20%25%30%35%40%45%50%55%

FHC LULA

Sh

are i

n B

razil

ian

Im

ports

from

Afr

ica

MAJOR AFRICAN SUPPLIERS

BY GOVERNMENT

Algeria

Nigeria

South Africa

Morocco

Angola

Benin

-16,00

-14,00

-12,00

-10,00

-8,00

-6,00

-4,00

-2,00

-

TOTAL 1º TERM 2º TERM

US

$ B

illi

on

(ye

ar-b

ase

20

05

)

TRADE FLOW WITH AFRICA BY

GOVERNMENT

FHC

LULA

2.4. Technical cooperation between Brazil and Africa:

Another important element in Brazil-Africa relations strengthening between FHC

and Lula was technical cooperation in areas such as agriculture, health, education,

environment and professional training.

The basic guideline of Brazilian Technical Cooperation for Development (TCDC) is

the transfer of knowledge and technologies to developing countries, human resources and

training. The TCDC projects during the period were concentrated in areas considered

priorities for foreign policy. - Africa and South America What has changed is the position

of these regions. In FHC government, South America ranked first, with 30% and Africa

second place with 26%, the next government, the positions are reversed, Africa ranks first

36% of while South America goes to the second place with a 27% (PUENTE, 2008, p.

173).

There was a significant growth of technical cooperation with Africa, with

diversification in recipient countries and areas of these projects. The FHC government,

were 13 African countries benefited in 16 areas and Lula were 38 beneficiaries in 30

different areas (Source: DAI-MRE).

Chart 12 - Comparative Table of Beneficiaries and TCDC areas by government

Self elaboration. Source: DAI-MRE.

Occurred a greater diversification in African regions, with growth in four of the

regions, except for South Africa, with a drop of 27.7 percentage points. In FHC

government, the projects were for South Africa, specifically South Africa, CPLP and

Western Africa, composed of three Portuguese-speaking countries. In the next

government, there was a significant change in regions benefited from cooperation

projects, except for the increasing participation of North Africa.

0

10

20

30

40

BENEFICIARIES AREAS

COMPARATIVE TABLE OF

BENEFICIARIES OF TCDC AND

AREAS BY GOVERNMENT

FHC

LULA

Graph 13 - African regions shares in TCDC for Africa

Self elaboration. Source: DAI-MRE.

Despite diversification of countries benefited by Lula government, there is a

centralization in the Portuguese-speaking countries in both governments. In government

FHC, these countries account for 52.9% while the next government that number drops to

49.6% (Source: DAI-MRE).

Graph 14 - Country share in TCDC for Africa- FHC

Self elaboration. Source: DAI-MRE.

0%

10%

20%

30%

40%

50%

60%

70%

FHC LULA

AFRICAN REGIONS SHARES

IN TCDC FOR AFRICA

North Africa

Central Africa

Western Africa

Eastern Africa

South Africa

CPLP

0%

5%

10%

15%

20%

25%

COUNTRY SHARE - FHC

Graph 15 - Country share in TCDC for Africa – Lula

Self elaboration. Source: DAI-MRE.

The predominant areas are similar, health, education, culture and agriculture. Lula

government was responsible for signing of a number of general cooperation agreements

- 16 agreements - as its predecessor just signed two agreements5 (Source: DAI-MRE).

Graph 16 - Cooperation projects with Africa by Area and Government

Source: DAI-MRE. Self elaboration.

There was cooperation a greater diversification in regions and countries and in areas

which these instruments are signed.

The FHC government commercial, diplomatic and technical relationship with Africa

was restricted to traditional partners, especially those of Portuguese and South Africa,

and the oil-producing countries in the variable trade, keeping the selectivity.

With the emphasis on South-South relations, on Lula government there was a revival

of African politics through the expansion of African partners not only in trade but in

several areas, such as TCDC.

0%2%4%6%8%

10%12%14%16%18%

COUNTRY SHARE - LULA

0

10

20

30

40

50

60

LULA FHC

Nu

mb

er o

f p

roje

cts

Area

PROJECTS BY AREA AND

GOVERNMENT

Health

Education

Agriculture

Culture

Sports

General Agreement

Science & Technology

Thecnical Cooperation

Joint Comission

In contrast to the strengthening relations with Africa, Brazil has gained, in Lula

government, the support of the CPLP countries in several Brazilian candidacies for

positions in international organizations such as UN Security Geral and the Directorate-

General of Food and Agriculture Organization (FAO). These achievements show the

"exchange" favors between Brazil and Africa, as pointed out by the literature of

developed countries.

3. CONVERGENCE BETWEEN BRAZIL AND AFRICA IN GENERAL

ASSEMBLY OF THE UNITED NATIONS (UNGA)

3.1. UNGA vote as a measure for foreign policies guidelines:

There are few tools available to measure quantitatively the guidelines and alignments

in international system. One is UNGA votes, where almost every state is present and main

issues on international agenda are discussed.

However, opinions about this methodology are not consensual. For Dixon (1981)

UNGA would be only a passive arena related to States interaction while for Kennedy

(2006) that vote would be just symbolic, not a demonstration of countries alignments.

Furthermore, there is no way to know precisely whether the UNGA votes are a simple

expression of States preferences - which would make the vote a reliable measure of

convergence between states and of general foreign policies guidelines - or a reflection of

economic incentives between states, something discussed previously.

Individual members affect UNGA political processes, in other words, the internal

policy could determine what is voted and focus only on voting patterns would be ignore

the larger picture of international politics and the UN itself (KEOHANE, 1967).

Despite these empirical inconsistencies, many researchers use these data to determine

States behavior and to understand the broader elements of international politics, because

in the international system, there is no other organization or forum in which all States

vote on a regular basis about different international issues.

Therefore, the study of these polls in a long period of time and over different areas

can reveal possible changes in states behavior (Voeten, 2000, p. 151-2) and national

foreign policies.

UNGA voting is used to evaluate countries position only regional alignments in

international issues (Lijphart, 1963; Marin-Bosch, 1998; Selcher, 1978) and as indicators

of states foreign policies orientations (Thacker, 1999; Tomlin, 1985; Voeten, 2000).

These works support the use of UNGA as a parameter to analyze alignments between

the countries in international system and the general direction of national foreign policies.

3.2. Methodology:

To prove the research hypothesis - bilateral relations strengthening strategies

generate more multilateral support of recipient countries to donors - will be used panel

data analysis.

The advantage of this model related to cross-sectional models, according Hsio

(1986), is the ability to control heterogeneity among individuals and increase estimates

accuracy (Cameron; Travedi, 2005).

To check the effect of the interest variables were made three separate estimates. First,

through the pooled regression model (POLS). After using the random effects model (RA).

Finally, using the fixed effects model (FE), which allows consistent estimators in the

presence of heterogeneity observed correlated with other covariates.

Subsequently, tests were conducted to choose the most appropriate model to

maximize the efficiency, given that coefficients are consistent.

In POLS model, the estimator considers all information as transversal units, ignoring

the element time, that is, we have in the database N x T units. Although frequently used,

there is a problem to hypothesis validity that there is no information about idiosyncratic

error correlated with explanatory variables. Therefore, disregarding database temporality,

the model does not allow the control of specific heterogeneity (ci), causing inconsistency

and bias in the estimates if the heterogeneity is correlated with some of the regressors, ie

if there is some endogenous regressor. Furthermore, POLS requires exogenous weak, ie

that regressor and composes error vit are not correlated in the same period6.

It also requires full rank to avoid perfect multicolinearity, as well as the other two

models presented below.

POLS model

Yit= α + Xit β + εit

E(εit / x) = 0; εit ~ IID (0, σ2) (1)

The POLS estimation allows the control of annual effects through the use of year

dummies (ds), as well as dummies for specific groups of individuals (dj). Thus, the POLS

model becomes:

POLS model with year and specific groups dummies

Yit= α + Xit β + γ ds + λ dj +εit (2)

E(εit / x) = 0; εit ~ IID (0, σ2)

The random-effects model (RA) deal with the specific unobserved heterogeneity (ci)

as a random variable, distributed independently of covariates and with homocedastic

variance. In this model, the specific effect becomes part of the error and therefore can not

be correlated with any regressor in all periods, otherwise all the estimators will be

inconsistent violating one of the Gauss-Markov assumptions of estimation by OLS. Since

the exogenous strict hypothesis uit error should not be correlated with the regressors nor

specific effect in any time.

The random effects model is estimated by generalized least squares (GLS) when the

matrix of variance-covariance matrix is known. The estimation of feasible generalized

least squares (FGLS) is used when this matrix is unknown.

Random effects model:

Yit= α + Xit β + vit = α + Xit β + (ci + εit) (3)

where vit is the composite error give by ci + εit

E(vit / Xis) = 0; to i s

vit ~ IID (0, σ2)

The fixed effects analysis (FE) examines different intercepts for individuals,

assuming that the slopes are constant, as well as variance. The specific effect ci is not

treated more like a random variable as in random effects model, but as a parameter to be

estimated. Unlike RA, the FE model allows that the specific effect ci be correlated with

Xit covariates. The FE estimation requires strict exogeneity, in other words, that all

regressors are uncorrelated with ui error for all periods.

By making FE estimation, is necessary to use one of the processing techniques to

eliminate heterogeneity. The most common are the first differences and the within

transformation.

Fixed Effects Model:

Yit= α + ci + Xit β + εit (4)

Transformation to eliminate ci: Yit - Ym = (Xit - Xm) β + (εit – εm)

E(εit / Xis, ci) = 0; for i s

εit ~ IID (0, σ2)

After these estimations, tests will be done needed to confirm what are the most

consistent estimators and, among these, the most efficient. If there is unobserved

heterogeneity not correlated with any regressor, the estimators of fixed and random

effects are consistent, the latter being more efficient. If heterogeneity is correlated with a

regressor, the first is the only consistent. At the end, I will perform the Breusch- Pagan

tests for the presence of specific heterogeneity and Hausman to verify the correlation

between this and the covariates7.

An important limitation of fixed effect method is the inability to estimate the effect

of constant variables in time. Therefore, if the Hausman test (1978) indicates no

difference between the estimators FE and RA, besides the last is the most efficient, it also

allows the inclusion of constant variables in time.

Votes Convergence Model

The sample covers 1158 UNGA resolutions between 1995 and 2010. The database

has information beyond these four types of variables: political, commercial, economic

and geographical, some of them used as a control in the estimates. The model can be

explained by the following table:

Figure 3 – Votes Convergence Model

INDEPENDENT VARIABLE INTERVENING VARIABLE DEPENDENT VARIABLE

The basic equation to be estimated can be summarized as follows:

𝑽𝒐𝒕𝒊𝒏𝒈 = 𝜶 + 𝜷𝟏(𝒄𝒐𝒐𝒑)𝒊𝒕 + 𝜷𝟐(𝒆𝒙𝒑 𝒐𝒖 𝒊𝒎𝒑)𝒊𝒕 + 𝜷𝟑(𝑷𝒊𝒃𝒑𝒆)𝒊𝒕 + 𝜷𝟒(𝑼𝑺𝑨𝟐)𝒊𝒕 + 𝜷𝟓(𝑪𝑷𝑳𝑷)𝒊𝒕 + 𝜷𝟔(𝑳𝒖𝒍𝒂)𝒊𝒕 + 𝜷𝟕(𝒄𝒐𝒍)𝒊𝒕 + 𝜺𝒊𝒕 (5)

where i is the African country, t the year and α e εit are respectively constant and

idiosyncratic error, coop and exp or imp are independent variables and voting is the

dependent variable.

The variable voting indicates the percentage of convergence vote between Brazil and

each of African countries between 1995 and 2010, excluding abstentions8.

Brazilian share in

each african country

exports.

Brazilian share in

each african country

imports.

Number brazilian cooperation projects

with each african

country.

PIB per capita of

each african country

Vote convergence

between USA and

african country.

CPLP

Colonizing Country

Vote Convergence

between Brazil and

each african country..

The bilateral relations strengthening will be measured by three independent

variables:

- Number of cooperation projects between Brazil and Africa between 1995 and 2010,

called COOP;

- Brazil's share in total exports of each African country between 1995 and 2010,

called EXP;

- Brazilian share in total imports of each African country between 1995 and 2010,

called IMP.

These variables were chosen because they are the way of an emerging country with

limited resources to provide cash assistance to "buy" votes in the UNGA.

3.3. Data:

To calculate the dependent variable, were used data collected by Anton Strezhnev

and Erik Voeten (2009), with the voting records at UNGA between 1946-2012. After

collecting similar votes at UNGA between Brazil and each of the African countries

between 1995 and 2010, was calculated the convergence percentage between two

countries from the total voting they participated9.

The variables related to bilateral trade (EXP and IMP) were calculated from the

exports and imports percentage of each African country on Brazilian total exports and

imports of these states in each of the years of the staudy.

The variable cooperation was calculated from the amount of bilateral cooperation

projects signed between Brazil and each African country between 1995 and 2010.

The per capita GDP of each African country - PIBpercapita (base year 2005) - was

chosen to control the influence of development level on voting decisions, taken from data

provided by the United Nations Conference on Trade and Development (UNCTAD).

It was also used the vote convergence among African countries and US in the period,

excluding abstentions, due to the same reason explained to Brazil - calculated in the same

way that vote - to remove the possible effect of convergence between African and USA -

major international power – from the results.

The variable CPLP was designed because, according to trade and cooperation data,

this community has an important role in policy towards Africa. This variable is a dummy

call CPLP, and the non-members will be number 0 and members number 1.

The following intervening variable is related to colonization. As most of the African

countries were colonized, we chose a dummy that takes into account the colonizing

country. Countries that were not colonized is zero, the former British colonies the number

1, the former French colonies number 2, the Belgian former colonies the number 3, the

former Spanish colonies number 4, the ex- Italian colony number 5, the former German

colonies the number 6 and the former colonies Portuguese number 7.

The last intervening variable, called Lula, was a dummy to see the behavior of the

data from the Lula entry. The data for the years 1995 to 2002 was number 0, while data

for 2003 to 2010 was received number 1.

Below variables description (Table 1) and their descriptive statistics (Table 2).

Table 1 - Description of variables

Voting Vote percentage between Brazil and

African countries

coop Número of cooperation projects

Brasil-African countries

exp ou imp Percentage of brazilian share in

African country trade

logpibpercapita log percapita pib of each African

country by year

eua Porcentagem similar votes beyween

USA and African country

cplp Dummy related to CPLP

col Dummy related to colonization

year Year of the data

ccode Dummy related to each country

Continuous

Variables

Mean Median Standard

Deviation

Mínimum Maximum

Vot2 84.665 85.938 7.689 21.428 100

Coop 0.469 0.000 1.501 0 14

Exp 0.817 0.035 2.975 0 54.558

Imp 1.550 0.659 2.571 0 28.446

Logpibpercapita 6.644 6.265 1.122 4.443 9.907

USA2 78.550 78.947 7.948 21.428 100

Dummies

Variables

Frequency 0 1 2 3 4 5 6 7

cplp 752 96

col 32 288 320 48 16 32 32 80

The relationship between chosen variables indicates that vote convergence between

a country and a country/region at UNGA can be explained from the share of this country

in region/country trade and the number of cooperation projects between one country and

this region/country. However, this relationship may be affected by factors such as per

capita GDP, convergence with the United States, CPLP membership and fidelity to the

colonizing country.

3.4. Data Presentation:

After reviewing Brazil-Africa exports, was discovered that Brazilian share in African

trade is very low, only 1.76% of African imports. Despite growing from year 2000, it

falled from 2006.

Graph 17 - Brazilian share in African imports

Source: Unctad. Self elaboration.

0,0%

0,5%

1,0%

1,5%

2,0%

2,5%

3,0%

19

95

19

96

19

97

19

98

19

99

20

00

20

01

2002

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10Bra

zili

an s

har

e in

Afr

ican

Import

s

Anos

EVOLUTION OF BRAZILIAN SHARE

IN AFRICAN IMPORTS

Between governments, the Brazilian share in African imports increased, a growth of

110.18%, from 1.01% to 2.12%.

Graph 18 - Brazilian share in African imports by government

Source: Unctad. Self elaboration.

Brazilian share in African exports is 2.024% during the period. Unlike the

predominantly upward trend in imports, Brazilian share in African exports was not

constantly growing, with down in certain years and growth from 2000.

Graph 19 – Brazilian share in African exports

Source: Unctad. Self elaboration.

The Brazilian share in African exports between the two governments increased,

growing 35.73%, from 1.75% to 2.38%.

0,0%

0,5%

1,0%

1,5%

2,0%

2,5%

TOTAL 1º TERM 2º TERM

Bra

zili

an s

har

e in

Afr

ican

im

port

s

BRAZILIAN SHARE EVOLUTION IN

AFRICAN IMPORTS BY GOVERNMENT

FHC LULA

0,0%

0,5%

1,0%

1,5%

2,0%

2,5%

3,0%

3,5%

Bra

zili

an S

har

e in

Afr

ican

Ex

port

s

YEARS

BRAZILIAN SHARE EVOLUTION IN

AFRICAN EXPORTS

Graph 20 - Brazilian share in African exports by government

Source: Unctad. Self elaboration.

These data show that, despite the increase of Brazilian share in African imports and

exports, Brazil is not a relevant partner for Africa, which would not justify an increasing

vote convergence at UNGA, as other countries are more relevant and therefore, deserve

more support in the Assembly.

In bilateral cooperation, the evolution between 1995 and 2010 was significant, from

only 2 projects to 78 projects, despite having suffered some setbacks.

Graph 20 - Brazil-Africa bilateral cooperation evolution

Source: DAI-MRE. Self elaboration.

The significant increase in bilateral cooperation projects is important as it would

contribute to grow convergence between Brazil and Africa at UNGA.

The voting at UNGA, there was a high degree of convergence between Brazil and

Africa, especially when abstentions where considered (VOT1), coming in one of the years

to 100% convergence.

0,0%

0,5%

1,0%

1,5%

2,0%

2,5%

3,0%

1º TERM 2ª TERM TOTAL

Brazil

ian

Sh

are in

Afr

ican

Exp

orts

BRAZILIAN SHARE EVOLUTION IN

AFRICAN EXPORTS BY

GOVERNMENT

FHC LULA

020406080

100

Nu

mb

er o

f C

oop

era

tion

Proje

cts

Year

BRAZIL-AFRICA

COOPERATION PROJECTS

EVOLUTION

Graph 21 - Brazil-Africa convergence of developments in UNGA per year

Source: UN Strezhnev; Voeten, 2012. Self Elaboration

The high degree of convergence between Africa and Brazil at UNGA apparently

could harm hypothesis proof, since its increase would not point significant changes in the

general direction of African countries at UNGA, because there is previous strong

convergence, and is not necessary for Brazil "buy" African votes. So, it will only be used

convergence excluding abstentions.

However, as pointed out in the literature, one reason to "buy" votes would also reward

or punish allies.

There was no significant change in voting pattern between Africa and Brazil at

UNGA between two governments, with a slight setback in vote convergence, including

abstentions (VOT1), from 99.4% in FHC to 98.6% in Lula. Without abstentions (VOT2),

there is a reverse movement, from 83.7% to 85.6% in.

Graph 22 - Brazil-Africa Convergence at UNGA by government

Source: UN Strezhnev; Voeten, 2012. Self Elaboration.

In both governments, main allies were not countries with Brazil has strong or old

bilateral relations. The country with the highest convergence is Seychelles islands, while

Angola – traditional Brazilian partner - appears among the countries with less

convergence. This information is interesting, but not as significant, since convergence is

high with all African countries.

0,0%20,0%40,0%60,0%80,0%

100,0%120,0%

Con

ver

gen

ce p

erce

nta

ge

at U

NG

A

YEARS

BRAZIL AFRICA CONVERGENCE AT

UNGA

VOT1 VOT2

70,0%

75,0%

80,0%

85,0%

90,0%

95,0%

100,0%

105,0%

FHC LULA FHC LULA FHC LULA

1º TERM 2º TERM TOTAL

Bra

zil-

Afr

ica

con

ver

gen

ce

per

cen

tag

e at

UN

GA

BRAZIL-AFRICA CONVERGENCE AT

UNGA BY GOVERNMENT

VOT1 VOT2

This evolution shows apparently that efforts to strengthen bilateral relations by Lula

government did not change significantly Brazil-Africa convergence at UNGA. It is

because this convergence was already high at the beginning of Lula administration, not

justifying the government strategies to reinforce relations with Africa to gain their support

in multilateral forums, and should therefore have another logic, to be explored by future

researches.

The descriptive analysis showed that the independent variables did not cause

significant changes in Africa's voting patterns related to Brazil, contradicting the

hypothesis that these strategies could modify voting patterns in multilateral forums.

3.5. Results:

After tests to find the most consistent estimation model, the results of the coefficients

were similar for all variables in all models tested.

From the results was noticed, in all models, a positive relationship between the

variables cooperation and import and vote convergence, the growth on cooperation and

Brazilian share in African imports increased Brazil-Africa similar votes. In export and

Lula variables, we found a negative relationship with vote convergence, the increase in

Brazil's share of African exports and from the Lula government reduced vote convergence

at UNGA between the two partners.

As all models showed similar relationships between variables, the best method to

choose the model would be significance degree and, from the numbers, the most

significant model was the random effects (RE), because it was which were found the

greatest significance for the chosen variables.

After choose the model, variables calculations were made, finding the following

correlation coefficients with vote convergence at UNGA.

Table 3 - Correlation Coefficients Import

vot200 Coeficiente coop .3774865

imp100 .2609045

lula -2.155566

logpibperc~a 1.215576

eua200 .5778057

cplp -1.730221

col

1 -1.48046

2 -.7673221

3 -3.462226

4 -4.006992

5 -1.465307

6 -1.821095

7 (omitted)

When considered imports, it can be said that there is a positive relationship between

cooperation and vote convergence at UNGA, so a cooperation agreement generates an

increase of 0.37 percentage point in vote similarity between the two partners. This

relationship is also found in the import, which an increase of 1% in imports generates an

increase 0.26 percentage point in vote convergence.

The logpibpercapita and USA2 control variables also have positive relationship with

vote convergence, with higher values than independent variables, showing that exogenous

factors to bilateral strengthening strategies influences vote convergence. Since the cplp

and col variables has a negative relationship, which there is a decrease in convergence

when considered these elements.

The fact that took our attention was Lula variable, with a negative coefficient, ie be

Lula government decreases by 2.15 percentage points convergence vote. It was expected

an increase in vote convergence if it were found a positive relationship between

cooperation and voting, due to the significant increase in cooperation projects in Lula

government. However, this expectation was frustrated.

One possible explanation is that in previous government the number of projects was

very small, ie, the sample was very limited, which meant that the standard error was too

high, increasing the range for prediction, becoming impossible, therefore, to find a

reliable statistical relationship between variables cooperation and Lula.

Figure 2 - Prediction margins with Lula variable

In export variable, the results are similar, except for the variable export, with

negative value.

Table 4 - Correlation Coefficients export

vot200 Coefficient

coop .3905596

exp100 -.0234868

lula -1.875475

logpibperc~a 1.171761

eua200 .5788757

cplp -1.406769

col

1 -1.287292

2 -.7272931

3 -3.775539

4 -4.441501

5 -1.405062

70

75

80

85

90

95

Lin

ea

r P

redic

tion

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14COOP

lula=0 lula=1

Predictive Margins of lula with 95% CIs

6 -2.051337

7 (omitted)

When considered exports, the correlation between voting and cooperation is positive,

increasing to 0.39, which means that 1 cooperation agreement generates increased 0.39

percentage point in vote convergence between the two partners. The export variable has

a negative relationship, which means an increase of 1% in Brazilian share in African

exports generates a decrease of 0.023 percentage point.

This fact is interesting, as usually we believed that countries give more importance

to their sales and thus converge at UNGA voting with countries that import their products.

The logpibpercapita and USA2 control variables have a positive relationship with the

dependent variable, with values higher than independent variables, confirming the

importance of exogenous factors to bilateral relationship strengthening in vote

convergence at UNGA. The control variables related to CPLP and colonization have a

negative relationship with the vote variable, having a negative effect on them.

Lula variable continued with a negative effect, helping to confirm the argument that

was not found a statistical relationship between Lula and cooperation and vote

convergence between Brazil and African countries.

Until now, were found a relationship between the chosen independent variables -

cooperation and export/import - and vote convergence, although relatively low, which

means that there is possible evidence "purchase" of African votes by Brazil. However,

not possible to determine the influence of government on this strategy.

FINAL CONSIDERATIONS

Several authors sought to understand alliances at international organizations, leading

to an extensive literature on the vote “buying” of its allies to achieve a favorable position

of these organizations on their interests.

These studies deal with votes “buying” by great powers, especially the US, seeking

to prove that these countries use international aid to gain the support of recipient countries

in multilateral organs, and there is there is no studies that seek to verify the presence of

this dynamic in the case of emerging countries.

This article aimed to evaluate this phenomenon among emerging countries. For this,

was selected Brazil that, in recent years, went through a process of international ascension

and sought to increase their ability to influence, particularly at international organizations.

For this, Brazil-Africa relationship was chosen as Lula administration, have

undertaken strategies to strengthen relations with this region. One of the reasons was to

gain the South support to Brazilian multilateral demands. Thus, the general assumption

is that countries strengthen their bilateral relationship to gain the recipient countries

support at multilateral level.

However, the independent variable of literature could not be used in our case because

the capacity and amount of international aid provided by developing countries is low. To

solve this problem, we used the study of African politics that show, between FHC and

Lula government, a significant increase in bilateral trade and cooperation projects with

Africa. Thus, the independent variables were bilateral trade and cooperation with African

countries.

In data analysis, it was clear that between the two governments, there were no major

changes in Brazil-Africa relations, focused on traditional partners such as Portuguese-

speaking countries, South Africa and oil exporters such as Nigeria and Algeria. However,

there was a significant increase in bilateral cooperation projects, despite the concentration

of recipient countries.

Trade was analyzed from the Brazilian Share African imports and exports, to check

how bilateral trade could conquer a country in multilateral forums. However, the

Brazilian weight in African trade is still relatively low, occurring little change between

two governments, which apparently does not justify a possible increase on vote

convergence.

After, in the dependent variable – Brazil-African countries vote convergence at

UNGA, there is a high convergence degree between partners, particularly when

considered abstentions.

Through the random effects model, we tested the hypothesis, proving that

cooperation and trade influence vote convergence between Africa and Brazil at UNGA,

with some limits.

In trade, there was a different influence between imports and exports. The first have

positive influence on votes, ie its increase causes an increase in convergence, while the

latter have a negative effect on convergence, that is, its increase leads to decrease in

similar votes. This result is interesting because at first look we are led to imagine that

countries give more importance to partners who buy their products, since this increases

the government's ability to invest in the country and accumulate international reserves, in

addition to maintain its power.

In government variable, despite the increase in bilateral cooperation projects in Lula

government, vote convergence between Brazil and African countries decreased. This does

not mean that Lula government had no influence on cooperation, because this is not

measured by the proposed model.

Despite the relationships found between dependent and independent variables were

also found stronger links between control variables and Brazil-Africa vote convergence,

ie exogenous factors to strengthen bilateral relationship influence countries votes. This

prove some literature discussions that is very difficult isolate, empirically, all bilateral

variables from systemic variables to find evidence of vote “buying”.

Therefore, this study confirmed the hypothesis that bilateral relations strengthening

increases recipient countries support at multilateral level in the case of an emerging

country. However, for this statement have greater empirical validity more studies are

necessary with a larger number of emerging countries and allies and more variables,

opening to researchers an interesting research field.

NOTES

1 With least developed countries entry in the UN, the majority required for resolutions approval depended more and more of their votes and must meet their demands that are not so concerned with the ideological cleavage, as were concerned with development, rising some alliances between them, such as Non-Aligned Movement and the G-77. 2The study conducted in Cold War, in which great powers interests were strongly influenced by issues related to international security and maintenance of spheres of influence. 3 There are indications that US and the G7 countries keep records of UN Member States votes and that their behavior influence bilateral relations, including aid (BARNEBECK ET AL., 2006). 4 The more active participation in UN peacekeeping missions is related to Brazilian campaign to UNSC permanent member, an important goal of FHC multilateral foreign policy. 5 General agreements are relevant because is the first diplomatic step towards conciliation objectives related to cooperation. 6 The fixed effects models and random effects consider the presence of specific heterogeneity, which are considered part of the intercept and first part of the error in the second, and require, unlike the POLS model, strict exogeneity. This

implies that error term should be uncorrelated with any of the covariates in any period of time, assuming that error has conditional mean zero values in the past, present and future of covariates (CAMERON; TRAVEDI, 2005). 7 The Hausman test (1978) is used to compare the RE and FE models under the null hypothesis that observed heterogeneity is not correlated with the regressors model. If Ho is true, RE estimators are consistent, efficient and FE are consistent. If the correct hypothesis is the alternative, then RE model generates inconsistent estimators and

consistent FE. So if the null hypothesis is true, it is better to use the RA model as estimates fewer parameters relative to FE. If the alternative hypothesis is true, it is preferred the EF model, which is the only one to produce consistent estimates. 8 The abstentions were excluded because when considered the abstentions, it was noticed a high convergence rate in most cases, with 100% convergence for some countries in some years. Thus, there would not be a high degree of variation so to perceive the relationship between chosen variables. 9 This was necessary because African countries do not always vote in all resolutions due to debt issues of its annual contribution to UN - which means that the debtor country is prohibited from voting - and a lack of personnel to be present in all voting or internal conflicts in their countries.

BIBLIOGRAPHY

BIBLIOGRAPHY

ALICEWEB. Disponível em: http://aliceweb.mdic.gov.br/. Acessed in: April 25th 2013.

ALESINA, Alberto; DOLLAR, David. “Who Gives Foreign Aid to Whom and Why?”.

Journal of Economic Growth, 5, 2000.

________; WEDER, Beatrice. “Do Corrupt Governments Receive Less Foreign Aid?”.

National Bureau of Economic Research Working Paper, n. 7108, 1999.

BARNEBECK, Andersen et al. “On US politics and IMF lending”. European Economic

Review, 50,2006.

BARRO, Robert J.; LEE, Jong-Wha. “IMF Programs: Who is chosen and what are the

effects?” Journal of Monetary Economics, 52, 7, 2005.

BOONE, Peter. “Politics and effectiveness of foreign aid”. European Economic Review,

40, 2, 1996.

BUENO DE MESQUITA, Bruce ET AL. The Logic of Political Survival. Cambridge:

MIT Press, 2003.

CAMERON, A. COLIN.; TRAVEDI, PRAVIN. K. Microeconometrics: methods and

applications. Cambridge Univ. Press, Nova Iorque, 2005.

CASHEL-CORDO, Peter; CRAIG, Steven G. “Donor Preferences and Recipient Fiscal

Behavior: a Simultaneous Analysis of Foreign Aid”. Economic Inquiry, v. 35, 3, 1997.

COLLIER, Paul; DOLLAR, David. “Aid Allocation and poverty reduction”. European

Economic Review, v. 46, 8, 2002.

DIXON, William. “The Emerging Image of U.N. Politics. World Politics, 34, 1, 1981.

________; STURM, Jan-Egbert; VREELAND, James Raymond. “Global horse trading:

IMF loans for votes in the United Nations Security Council”. European Economic

Review, 53, 2009.

DIVISÃO DE ATOS INTERNACIONAIS DO MINISTÉRIO DAS RELAÇÕES

EXTERIORES DO BRASIL (DAI-MRE). Disponível em: http://dai-mre.serpro.gov.br/.

Acessed in: September 28th 2013.

HAUSMAN, J. Specification tests in econometrics. Econometrica. Vol. 46. nº 6. 1978.

HSIAO, Cheng. Analysis of Panel Data. Cambridge. Ed. Cambridge Univ. Press. 1986.

KAPLAN, Jacob J. The Challenge of Foreign Aid. New York: Praeger, 1967.

KEGLEY, Charles W; HOOK, Steven W. “U.S. foreign aid and U.N. voting: did

Reagan’s linkage strategy buy defense or defiance?”. International Studies Quarterly, 35,

3, 1991.

KEOHANE, Robert. “Political Influence in the General Assembly”. International

Conciliation, n. 557, 1966.

_________, Robert. “The Study of Political Influence in the General Assembly”.

International Organization, 21, n.2, 1967

KENNEDY, Paul. The Parliament of Men: The Past, Present, and Future of the United

Nations. New York: Random House, 2006.

KIM, Soo Yeon; RUSSETT, Bruce. “The New Politics of Voting Alignments in the

United Nations General Assembly”. International Organization, 50, 4, 1996.

KUZIEMKO, Ilyana; WERKER, Eric. “How much is a seat on the Security Council

worth? Foreign Aid and bribery at the United Nations”. Journal of Political Economy,

114, 5, 2006.

LAI, Brian; MOREY, Daniel. “Impact of Regime Typeon the Influence of U.S. Foreign

Aid”. Foreign Policy Analysis, 2, 2006.

LANGHAMMER, R. J. “Halving poverty by doubling aid: is there reason for optimism?”

The World Economy, 27, 1, 2004.

LIJPHART, Arend. “The Analysis of Bloc Voting in the General Assembly: A Critique

and a Proposal. American Political Science Review, 57, 4, 1963.

MAIZELS, Alfred; NISSANKE, Machiko. “Motivations for Aid to Developing

Countries.” World Development, 12, 9, 1984.

MINISTÉRIO DAS RELAÇÕES EXTERIORES DO BRASIL (MRE). Balanço de

Política Externa 2003-2010: África. 2010. Disponível

em: http://www.itamaraty.gov.br/temas/balancodepoliticaexterna20032010/2.2.3africa-

comercioeinvestimentos/view. Acess in: June 25th 2011.

MINISTÉRIO DO DESENVOLVIMENTO, INDÚSTRIA E COMÉRCIO (MDIC).

Estatísticas de Comércio Exterior. Disponível em:

http://www.mdic.gov.br//sitio/interna/interna.php?area=5&menu=576. Acess in: July

17th 2011.

NEUMAYER, Eric. “The Determinants of Aid Allocation by Regional Multilateral

Development Bank and United Nations Agencies”. International Studies Quarterly, 47,

1, 2003.

OATLEY, Thomas; YACKEE, Jason. “American Interests and IMF Lending”.

International Politics, 41, 2004.

PLANO, Jack; RIGGS, Robert. Forging World Order, New York: Macmillan, 1967.

RAI, Kul B. “Foreign Aid and Voting in the UN General Assembly, 1967-1976”. Journal

of Peace Research, 17, 3, 1980.

RELATÓRIO BANCO MUNDIAL. Ponte Sobre O Atlântico. Brasil e África

Subsaariana: Parceria Sul-Sul para o Crescimento. Brasilia: Banco Mundial/Ipea, 2012.

RUSSET, Bruce. “Discovering Voting Groups in the General Assembly” American

Political Science Review 60, 2, 1966.

SARAIVA, José Flávio Sombra. “Política Exterior do Governo Lula: o desafio africano”.

RBPI, 45, 2, 2002.

SCHRAEDER, P. ET AL. “Clarifying the foreign aid puzzle: a comparison of American,

Japanese, French, and Swedish aid flows”. World Politics, 50, 1998.

STEINWAND, Martin C; STONE, Randall W. “The International Monetary Fund: A

review of the recent evidence”. The Review of International Organizations, 3, 2, 2008.

SVENSSON, J. “Aid, Growth and Democracy”. Economics & Politics, 11, 3, 1999.

THACKER, Strom C. “The High Politics of IMF Lending”. World Politics, 52, 1, 1999.

TOMLIN, Brian W. “Measurement Validation: Lessons from the Use and Misuse of UN

General Assembly Roll-Call Votes”. International Organization, 39, 1, 1985.

VOETEN, Erik. “Clashes in the Assembly”. International Organization, 54, 2, 2000.

________; STREZHNEV, Anton; BAILEY, Michael. "United Nations General

Assembly Voting Data", 2009. Disponível em: http://hdl.handle.net/1902.1/12379. Acess

in: January 25th 2015.

WANG, T. Y. “U.S. Foreign Aid and UN Voting: An Analysis of Important Votes”.

International Studies Quarterly, 43, 1999.

WESTWOOD, Andrew F. Foreign Aid in a Foreign Policy Framework. Washington,

D.C.: The Brookings Institution, 1966.

WILCOX, Francis O. “The Nonaligned States and the United Nations” in Neutralism and

Nonalignment. Ed. Laurence Martin. New York: Praeger, 1962.

WITTKOPF, William. “Foreign Aid and United Nations Votes: A Comparative Study”.

The American Political Science Review, 67, 3, 1973.