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Faculty of Economics, Thammasat University

THAMMASAT REVIEW OF ECONOMIC AND SOCIAL POLICY

Democracy and Growth: Global Causal Evidence for Heterogeneous Political Regimes and Economic and Social Policy Tran Van Hoa

On Income Inequality and Population Size Thitithep Sitthiyot and Kanyarat Holasut

South-South Trade Growth Prospects and Policy Implications Panit Buranawijarn

Volume 2, Number 2, July - December 2016 ISSN 2465-390X (Print) ISSN 2465-4167 (Online)

THAMMASAT REVIEW OF

ECONOMIC AND SOCIAL POLICY Volume 2, Number 2, July – December 2016

ISSN 2465-390X (Print)

ISSN 2465-4167 (Online)

Thammasat Review of Economic and Social Policy

Thammasat Review of Economic and Social Policy (TRESP) is a double-

blind peer reviewed biannual international journal published in June and

December. The journal is managed by the Research Committee under the

supervision of the Academic Affairs Division of the Faculty of

Economics, Thammasat University. Our editorial board and review panel

comprise of academicians and practitioners across various areas of

economic and social policies. The goal of the journal is to provide up-to-

date practical and policy-oriented analysis and assessment of economic

and social issues, with particular focus on Asia and the Pacific region.

However, research findings from other parts of the world that are relevant

to the theme of the journal may be considered.

Aims & Scope

Our journal is dedicated to serve as a platform for debate and critical

discussion pertaining to the current issues of public policy. The outcome

of such research is expected to yield concrete policy implications. Some

of the targeted issues include urban and regional socio-economic

disparities, ageing society, healthcare, education and welfare policies,

environmental and natural resources, local communities, labor migration,

productivity, economic and political integration, political economy,

macroeconomic instability, trade and investment, fiscal imbalances,

decentralization, gender issues, behavioral economics and regulations;

and law and economics. The journal makes its best effort to cater a wide

range of audience, including policymakers, practitioners in the public and

business sectors, researchers as well as graduate students.

Articles should identify any particular issue concisely, address the

problems of the research explicitly and supply sufficient empirical data or

strong evidence and substantial argument to support the discussion of

policy initiatives asserted by the author( s) . Theoretical and applied

papers are equally welcome provided their contributions are policy-

relevant.

Advisory Board

Sakon Varanyuwatana, Thammasat University, Thailand

Medhi Krongkaew, National Institute of Development Administration, Thailand

Arayah Preechametta, Thammasat University, Thailand

Duangmanee Laovakul, Thammasat University, Thailand

Editor-in-Chief

Euamporn Phijaisanit, Thammasat University, Thailand

Associate Editors

Pornthep Benyaapikul, Thammasat University, Thailand

Phatta Kirdruang, Thammasat University, Thailand

Editorial Board

Kirida Bhaophichitr, Thailand Development Research Institute, Thailand

Brahma Chellaney, Center for Policy Research, New Delhi, India

Aekapol Chongvilaivan, Asian Development Bank, Manila, Philippines

Ian Coxhead, University of Wisconsin-Madison, United States

Tran Van Hoa, Centre for Strategic Economic Studies, Victoria University, Australia

Emma Jackson, Bank of England, UK

Prajak Kongkirati, Faculty of Political Science, Thammasat University, Thailand

Somprawin Manprasert, Faculty of Economics, Chulalongkorn University, Thailand

Gareth D. Myles, Tax Administration Research Centre, University of Exeter, UK

Songtham Pinto, Bank of Thailand, Thailand

Pathomdanai Ponjan, Fiscal Policy Office, Ministry of Finance, Thailand

Nattapong Puttanapong, Faculty of Economics, Thammasat University, Thailand

Sasatra Sudsawasd, National Institute of Development Administration, Thailand

Maria-Angeles Tobarra-Gomez, University of Castilla-La Mancha, Spain

Soraphol Tulayasathien, Fiscal Policy Office, Ministry of Finance, Thailand

Editorial Assistants

Darawan Raksuntikul

Sorravich Kingsuwankul

Panit Buranawijarn

Editorial and Managerial Contact

c/o Mrs. Darawan Raksuntikul

Thammasat Review of Economic and Social Policy (TRESP)


2 Prachan Road, Bangkok 10200, Thailand

Tel. +66 2 696 5979

Fax. +66 2 696 5987

E-mail: [email protected]


Volume 2, Number 2, July – December 2016

Editorial Introduction 1

ARTICLES

Democracy and Growth: Global Causal Evidence for

Heterogeneous Political Regimes and Economic and Social

Policy 6

Tran Van Hoa

On Income Inequality and Population Size 24

Thitithep Sitthiyot and Kanyarat Holasut

South-South Trade Growth Prospects and Policy

Implications 50

Panit Buranawijarn


Volume 2, Number 2, July - December 2016

1

Editorial Introduction

Following the success of our first issue in December

2015, this issue consists of the topics on democracy and

growth, inequality and population size, and south-south trade

considerations.

The nexus between democracy and growth is an

important issue in economics and political economy,

generating an extensive body of literature discussing

definitions of democracy and the nature of its causality.

Empirical studies, however, have so far proven inconclusive.

The first article of this issue, “Democracy and Growth:

Global Causal Evidence for Heterogeneous Political Regimes

and Economic and Social Policy”, by Tran Van Hoa

contributes to the literature through a simultaneous equation

model to introduce circular causality between democracy,

growth, and income based on conventional democracy-

growth causality hypotheses. The paper uses a data set from

2008 for 162 countries. The model employed is a three-

simultaneous-equation model of democracy, growth and per

capita real income based on conventional hypotheses for

open economies to introduce circular causality. The article

provides empirical evidence to support the hypotheses

linking democracy and growth. The findings confirm bi-

directional causality for overall data, and for full and flawed

democracies, but is mixed for countries with less democratic

institutions. Policy implications suggest the relevance of

democratic institutions for promoting growth. However, care

should be taken in data selection and drawing conclusions of

causality. Regarding the issues on income inequality, economists

have long used Gini Coefficient as a measurement of income

inequality. The degree of income inequality and size of

population can be expected to have some kind of a



2

relationship. However, there is yet a study that examines an

appropriate degree of income inequality as measured by Gini

Coefficient for a country given the population size. High

degree of income inequality can cause economic, social and

political disruptions (i.e. adverse impacts on growth and

poverty, concentration of economic and political power, etc.)

which in turns favour the rich and prohibit social mobility.

On the other hand, low income inequality is detrimental in its

own way- equality of income generates no incentive to take

lucrative actions, which further lead to poor initiatives and

slow technological progress. Other social problems like riots

and protests may ensue. The authors, Thitithep Sitthiyot and

Kanyarat Holasut, hypothesized that there ought to be an

optimal level of income inequality to avoid these adverse

effects. They postulate that the degree of social, economic

and political diversities for any country is reflected by

population heterogeneity in that country. This study uses

income inequality and population data of 69 countries in

2012 from the World Bank. The relationship between the

level of income inequality (Gini Coefficient) and natural

logarithm of population size is found to be non-linear, which

can be best described by a second-degree polynomial

function. About one-fifth to one-third of countries in the

sample have Gini Coefficients close to appropriate values

while those of the other two-third to four-fifth are either too

high or too low. The finding of this article recommends

policy makers to take into account targeted Gini Coefficient

prior to any attempt to reduce or raise income inequality. The

paper posits that for a given level of population, countries

that achieve targeted level of income inequality are more

likely to attain higher economic growth, compared with those

which are far from their appropriate level of income

inequality.



3

On trade growth amongst developing nations, the share

of the trade in goods exported by these nations has grown

rapidly over the past two decades, fueled in large part by

China’s rapid growth. Though many developing countries

still face various issues in conducting trade, the share of

South-South trade is increasing in times of instability and

uncertainty in developed economies. The South-South

cooperation represents the collaboration between developing

countries across various dimensions including politics,

economics, trade, investment and technology. The third

article, “South-South Trade Growth Prospects and Policy

Implications” by Panit Buranawijarn, focuses mainly on one

aspect, trade, and through a review of the data and literature,

explores the characteristics, motivations, and effectiveness of

South-South trade. The article focuses on the involvement of

China and India in South-South Trade due to the large roles

that they play in both Asia and the Global South. Though

there are theoretical justifications for reducing trade barriers

between developing countries, factors such as the wide range

of developing countries and the unbundled structure of

production and the trade in intermediate goods makes it

difficult to determine whether South-South trade is more

beneficial compared with trade orientations. On the other

hand, there are many reasons why more advanced developing

countries such as China may encourage the South-South

Cooperation agenda through investment and developmental

aid for political and security reasons. Policy-wise, in the face

of economic and political uncertainties in the West, and given

the long-standing difficulties of the WTO Doha Development

Round, developing countries may see advancing South-South

trade as providing greater stability. However, making the best

use of South-South Cooperation and Trade for development

will depend on the circumstances of each individual country.



4


(TRESP) is our newly constructed biannual double-blind peer

reviewed international journal published in June and

December. The Faculty of Economics, Thammasat

University and the Editorial Team of TRESP seek to provide

an effective platform for reflecting policy-oriented

perspectives that links the academic and policymaking

community. Having devoted to our ‘knowledge-for-all’

philosophy so as to drive our society forward, the Faculty

decided that TRESP published in an open access model. For

further information and updates on this journal, or to submit

an article, please visit our website at www.tresp.econ.tu.ac.th.

Euamporn Phijaisanit

Editor-in-Chief



5



6

Democracy and Growth: Global Causal Evidence

for Heterogeneous Political Regimes and

Economic and Social Policy

Tran Van Hoa

Research Professor and Director

Vietnam and East Asia Summit Research Program

College of Business

Victoria University

Australia

[email protected]



7

ABSTRACT

The relationship between democracy and growth is of great

importance to development of economic and social well-

being policy but its directional causality is still generating

lively debate conceptually and empirically. The paper

introduces a simple simultaneous-equation model of

democracy and growth for open economies and uses global

data and system estimation to provide new evidence on

democracy-growth causality and importantly the effects of

different democratic institutions on it for strategic economic

and social policy analysis. The findings confirm democracy

causes growth globally but this causality is mixed for

countries with heterogeneous political regimes. Regime-

specific policy is therefore recommended for appropriate

decision-making.

Keywords: Democracy and growth, Lipset/Aristotle and

virtuous cycle, heterogeneous political regimes,

simultaneous-equation modelling.

JEL Classification: O10, O40, P16



8

1. Introduction

The nexus between democracy (political freedom and

equality for all) and growth (real income per head or living

standard and its rate of change) is an important issue in

economics and political economy and with relevance to

economic and social well-being policy. It has generated a

large theoretical and empirical literature and ongoing lively

academic and policy-making debates. The debates range from

the definition of democracy arising from the immensely

influential polyarchy concept of Dahl (1970) and the

causality of democracy and growth (Rigobon & Rodrik,

2005; EIU, 2015). Equally important is the fact in the current

empirical literature that the findings to verify this nexus have

also been mixed and sometimes controversial (Barro, 1996;

Persson & Tabellini 2007; Acemoglu et al., 2008; Narayan et

al., 2011; Acemoglu et al., 2014).

Explanations for the variation of findings and

suggestions for improvement in empirical study are

numerous. They include the neglect of relevant variables and

their nonlinear relationships (Barro, 1996), omission of key

control variables that simultaneously affect both growth and

democracy (Acemoglu et al., 2008), heterogeneous political-

economic development paths of the countries in the sample

(Persson & Tabellini 2007), and importantly, possibly a lack

of circular causality hypothesis between democracy and

growth (Barro 1996; Acemoglu et al., 2008). These are the

current gaps on an important global issue that require further

study and verification for meaningful economic and social

policy study.

To address these major gaps in the empirical literature,

the paper develops a simple multi-equation model with

conventional testable causal postulates that are

comprehensively based on the current democracy-growth



9

causality hypotheses for open economies. Significantly, the

model also assumes circular causality in the form of a

simultaneous-equation model to address the possible multi-

directional impact or virtuous cycle hypothesis between

democracy, growth and income (see also Rigobon & Rodrik,

2005).

For empirical study with cross-sectional data reflecting

thus implicitly long-run or equilibrium-state outcomes, the

paper uses the 2008 international data for 162 countries and

system estimation to provide evidence on the democracy and

growth relationship, and importantly, on this relationship for

four non-overlapping component regimes of these countries

on the hypothesis that different democratic regimes may be

characterised by different causality and therefore require

different policy (see detail below). The 2008 data are used on

the observation that 2008 was the start of the slowing down

of the decades-long democratisation process globally (EIU,

2008) and also known as democratic recession (Diamond,

2008), and the emergence of the global financial crisis

resulting in a sharp and protracted recession that could

threaten democracy in some parts of the world.

The paper’s findings confirm that bi-directional causality

exists between democracy and growth for the 162 countries

combined, and that this causality is mixed for different

groups of countries with heterogeneous political regimes and

thus requires regime-specific policy. Some analysis with

economic and social policy implications is then briefly

discussed.

2. The Model and Its Features

A simple three-simultaneous-equation model of

democracy, growth and per capita real income, based



10

importantly on the key conventional and testable postulates

for open economies in the current literature and specifically

addressing the major specification and circular causality

issues above, can be written arbitrarily in implicit form as (𝑌, 𝐷, 𝑌𝐻, 𝐸𝐹, 𝑋𝑌) = 0. After normalising for three key variables (𝑌, 𝐷 𝑎𝑛𝑑 𝑌𝐻) and using the usual stochastic linear

form1, it can be written as

𝑌 = 𝛼1 + 𝛼2𝐷 + 𝛼3𝑌𝐻 + 𝛼4𝐸𝐹 + 𝛼5𝑋𝑌 + 𝑢1 (1)

𝐷 = 𝛽1 + 𝛽2𝑌 + 𝛽3𝑌𝐻 + 𝛽4𝐸𝐹 + 𝛽5𝑋𝑌 + 𝑢2 (2)

𝑌𝐻 = 𝛿1 + 𝛿2𝐷 + 𝛿3𝑌 + 𝛿4𝐸𝐹 + 𝛿5𝑋𝑌 + 𝑢3 (3)

Where

𝑌 is growth (rate of change in real GDP per capita),

𝐷 is democracy composite index,

𝑌𝐻 is real GDP per head or, approximately, initial income,

𝐸𝐹 is economic freedom composite index, and

𝑋𝑌 is exports/GDP or trade intensity.

𝑢1, 𝑢2 𝑎𝑛𝑑 𝑢3 are the error terms or omitted variables with conventional cross-country and cross-equation correlation.

As for its structural specification, the model conceptually

encompasses and addresses the main testable hypotheses of

growth, democracy and income and their circular causality in

the literature. These hypotheses include more specifically, (a)

the Barro’s (1996) hypothesis of democracy affecting growth

𝐷𝑌 (D causes Y) and also income 𝐷𝑌𝐻; (b) the Lipset/Aristotle hypothesis (Acemoglu et al., 2008) of growth

1 A log form (Acemoglu et al., 2014) may be inappropriate as Y can be

negative as a result of a financial crisis or recession



11

and income affecting democracy 𝑌𝐷 and 𝑌𝐻𝐷; (c) the

virtuous cycle hypothesis of D-Y circular causality (𝐷 <=>𝑌) (Jaunky, 2013), and (d) depending on their empirical findings, the sceptic, compatibility and conflict hypotheses

(Narayan et al., 2011). In addition, as the model is for open

economies, it allows for the testable hypotheses of (i) the

effect of trade (exports) intensity representing a country’s

level of openness or globalisation on growth and income;

𝑋𝑌𝑌 and 𝑋𝑌𝑌𝐻 (Acemoglu et al., 2008), and on

democracy, 𝑋𝑌 𝐷, and as political and economic freedoms may be jointly correlated, of (ii) economic freedom on

growth and income, 𝐸𝐹 𝑌 and 𝐸𝐹𝑌𝐻 (Azman-Saini et al., 2010).

As the model of three structural and jointly dependent

equations for 𝑌, 𝐷 and 𝑌𝐻, it should be estimated

appropriately by a system method such as the three-stage

least-squares (3SLS) or the generalised method of moments

(GMM) incorporating factors or instruments that are, for econometric parametric estimation consistency, both

exogenous and simultaneously affect growth, income and

democratic processes (Barro, 1996; Acemoglu et al., 2008,

2014). Nonlinearity can be introduced into the model by

simply using the polynomials of 𝑌, 𝐷 and 𝑌𝐻 as additional

determinant variables (see Barro, 1996 for this suggestion).

An important focus of the paper is that it is assumed that

variation in democracy-growth causality may exist due to the

heterogeneous characteristics from a political economy

perspective of the in-sample countries as measured by their

various levels of democratic institutions or dictatorship

(Persson & Tabellini, 2007; EIU, 2008; Acemoglu et al.,

2014). This proxy aspect of deepening democratic institutions

as a major contribution to economic success is the paper’s

major focus for empirical testing in a structural system

framework and for evidence-based policy analysis.



12

In addition, as a generalisation of Acemoglu et al. (2008,

2014)’s modelling-by-IVs strategy, the IVs in our model may

include influencing IV indicators such as population, the

country’s world GDP share (to allow for country size

weight), and export share (to allow for the effect of trade

intensity or level of openness). These IVs must satisfy the

relevance and exogeneity criteria as required for

econometrically asymptotically consistent system estimates

of identified equations. For pragmatic reasons that also

satisfy the econometric requirements, the IVs in our model’s

three-stage least-squares estimation are simply polynomials

of the jointly dependent variables (see Johnston & DiNarno,

1997).

3. The Data and Estimation Issues

The whole data are cross-sectional for 2008 and for a

sample of 162 countries. The data for Y and YH are from the

US-Department of Agriculture-Economic Research Service

database. The data for exports and GDP are retrieved from

the United Nations Explorer datasets. The countries’ export

shares (X/GDP) are calculated from these data. Democracy

index (D) is obtained from the Economist Intelligence Unit

(EIU) online, and economic freedom index (EF) from the

Heritage Foundation. Acemoglu et al. (2014) have provided

further discussions on the reliability of these indexes and

their alternatives.

As we use the concept of heterogeneous political

institutions for testing the potential variation of democracy-

growth causality, we adopt the EIU (2008) classification of

these institutions and data availability in empirical study. The

four non-overlapping subsamples of the 162 countries with

differential democratic institutions as defined by the EIU

(2008) are based, for each country, on the average score (0-



13

10) of 60 indicators in five categories reflecting democracy:

electoral process and pluralism, civil liberties, the functioning

of government, political participation, and political culture.

The index values for the four regimes are: full democracies

(8-10), flawed democracies (6-7.9), hybrid regimes (4-5.9),

and authoritarian regimes (below 4). As described earlier, the

main motivation of this division is to shed more light on the

hypothesis that democracy-growth causality is potentially

affected by the countries’ stages of democratic processes

(Acemoglu et al., 2014) and also to provide potential and

appropriate regime-specific prescriptions. More specifically,

these four regimes and their number of included countries

are: full democracies (30 countries), flawed democracies

(50), hybrid regimes (36), and authoritarian regimes (51).

These regimes represent almost all of the world’s population.

We note that the selected sub-sampling may not be optimal

but it simply represents one useful definition of democratic

states with available data that provides, as an advantage over

its alternatives, considerable differentiation of scores even

among developed countries (EIU 2008). This definition has

been usefully adopted in the paper to empirically study the

diversity of democracy and growth causality for economic

and social policy analysis.

4. Empirical Findings and Political Economy Policy

Implications

The model (1) - (3) for testing bi-directional causality

between democracy, growth and income has been estimated

by the 3SLS method based on the whole sample of 162

countries and separately for the four sub-samples as

described above. While ‘pure or clean’ IVs with economic-

theoretic relevance and statistical exogeneity features for

system estimation are theoretically desirable for obtaining



14

asymptotically consistent parameter estimates, they are

elusive (Bazzi & Clemens, 2013) in empirical studies due to

the inherent Marshallian or Haavelmo interdependence

characteristics of economic activities. Extensive discussions

of major issues with IVs and remedial recommendations in

practice for acceptable estimation and analysis have been

provided in the literature (see for example Murray (2006),

Acemoglu (2010), Bazzi and Clemens (2013), and Acemoglu

et al. (2014), among others). In the paper, a number of

combinations of economically relevant IVs and their

polynomials had been experimented with and tested for

exogeneity. The final accepted IV proxies satisfying the

relevance and exogeneity econometric criteria are, for

pragmatic and illustrative-system-estimation reasons, simply

the polynomials of the variables in the model. The simple use

of endogenous variable polynomials (or lags with time series

data) as appropriate IVs have been suggested as satisfying the

relevance and exogeneity requirements for asymptotically

consistent system estimation in the econometric literature

(see Johnston & DiNardo, 1997; Wooldridge, 2009). The

final findings, conditional on these IVs, are reported in Table

1.

When the whole sample of 162 countries was used for

estimation ignoring thus the political-economic heterogeneity

among these countries, the findings confirm the validity of

the hypotheses of Barro (𝐷𝑌 and 𝐷𝑌𝐻), Lipset/Aristotle

(𝑌𝐷 and 𝑌𝐻𝐷) and virtuous cycle (𝑌 <=> 𝐷) (Jaunky,

2013). In other words, democracy itself contributes

significantly to improving growth and living standard, and

higher economic growth and income in these countries also

promote deepening democratic institutions. Interestingly, the

countries’ export intensity or openness has no statistically

significant effect on growth, democracy or income, and free-

market environment is found to enhance democracy



15

(confirming the link between economic freedom and political

freedom) and not growth or income. The findings from the four separate classes of regimes

show, however, the diversity of democracy-growth causality

for heterogeneous democratic institutions. First, for full-

democracy economies which consist of mainly developed

economies, the findings almost mirror the causality found in

the overall sample for growth, democracy and income and the

positive impact of economic freedom, and the insignificance

of openness. Second, for flawed democracies (where some

major South East Asian countries such as Indonesia,

Malaysia, the Philippines, Thailand and some South Asian

countries such as India and Sri Lanka belong), bi-directional

causality between growth, democracy and income is also

found, but, significantly and unlike full democracy regimes,

economic freedom does not promote democracy but it

enhances income for this group. Third, for hybrid regimes,

the diversion from the overall findings for causality appears

prominent. For example, democracy appears to hinder growth

and weakly impacts on income. Growth and especially

income also have only weak effects on democracy. While

economic freedom has no significant effect on democracy

and income, the level of openness however strongly increases

income for this group. Finally, for authoritarian regimes, an

interesting observation is that, unlike the overall and other

regimes, all included key variables are statistically significant

but with sometimes opposite causality. More specifically,

democracy affects growth but reduces income, and growth

promotes democracy but higher income hinders it. For the

countries in this regime, openness assists growth but not

income, and more economic freedom enhances democracy

and income but not growth.



16



17

As democracy and growth are crucial components of

economic and social well-being, the findings appear to have

important related policy implications. First, for total (162

countries) and as mirrored by full-democracy (30 countries)

findings, the world’s population seems to enjoy the mutual

benefits of positive growth, income and democracy

relationships while in fact only 14.4 per cent of its population

enjoys this beneficial causality environment and its

affordability. Economic and social policy that is based on the

total or aggregate data findings as reported by the majority of

studies in this area and used by policy-makers is therefore at

least misleading. Second, while half of the world’s

population lives in a democracy of some sort, our evidence

shows that for flawed democracy countries (50 countries or

35.5 per cent of the population and concentrating in Latin

America, Eastern Europe, and to a lesser extent in Asia), a

disturbing result is that a policy of more economic freedom

has no impact on deepening democracy which, according to

the EIU survey, was still generally characterised by low

political participation and weak democratic culture (EIU,

2008). Interestingly, the same result is also found for hybrid

regimes.

Third, significantly for hybrid regimes (36 countries or

15.2 per cent which together with authoritarian regimes

dominate in the countries of the former Soviet Union), the

relationships between democracy, growth and income are

weak, and the only economic and social policy that is

compatible with our significant findings and enhances

income is related to more openness. This policy may have

obstacles however due to the geo-political situation of these

countries and the conflicting influence of Russia and the

West. The weak relationships could also be attributed to the

‘colour revolution’ during the period being petering out.

Fourth, paradoxically for authoritarian regimes (51 countries



18

or 34.9 per cent), the empirical findings are, unlike for other

regimes, statistically and uniformly more robust, due to

perhaps the wide differentiation of the democracy index

scores among the regime members. For these members, any

policy is, according to our findings, complex and needs

careful balancing as it always involves minuses and pluses.

For example, a policy of more democracy and more openness

will promote growth but will reduce income, and a policy of

more economic freedom will promote democracy and higher

income but will reduce growth.

5. Conclusion

To address the gaps in the empirical literature on

democracy and growth causality, a simple structural

simultaneous-equation model of democracy, growth and

income with major relevant determinants for open economies

in the world is developed to provide empirical evidence to

their causality and with a special focus on the effects of

heterogeneous democratic institutions. This evidence is

useful to develop appropriate economic and social policy

analysis as democracy and growth are crucial components of

economic and social well-being. The findings confirm the bi-

directional causality for overall data and full and flawed

democracies, but are mixed for countries with less

democratic institutions. The study shows the relevance of

these institutions on promoting growth and also that caution

is required in interpreting causality from overall global panel

data and in developing appropriate economic and social

policy. As an example, an average global democracy index of

5.55 in the scale from 0 to 10 was recorded for both 2008 and

2015 even though the latter is more in the age of anxiety with

more diverse country-specific scores (EIU, 2015).

Endogenous switching regime modelling in the time-series



19

domain may be a further related interesting research with

available data but it is in another perspective (Jochmann &

Koop, 2014).



20

References

Acemoglu, D. (2010). Theory, General Equilibrium, and

Political Economy in Development Economics. Journal

of Economic Perspectives, Vol. 24, No. 3, pp. 17-32.

Acemoglu, D., Johnson, S., Robinson, J. A. and Yared, P.

(2008). Income and Democracy. American Economic

Review, Vol. 98, No. 3, pp. 808-42.

Acemoglu, D., Naidu. S., Restrepo, P., and Ronbinson. J. A.

(2014). Democracy Does Cause growth, NBER

Working Paper Series No. 20004. Retrieved from

http://www.nber.org/papers/w20004 .

Azman-Saini, W.N.W., Baharumshah, A.Z. and Law, S.H.

(2010). Foreign Direct Investment, economic Freedom

and Economic Growth: International Evidence.

Economic Modelling, Vol. 27, pp. 1079-1089.

Barro R. J. (1996). Democracy and Growth. Journal of

Economic Growth, Vol. 1, pp. 1-27.

Bazzi, S and Clemens, M A. (2013). Blunt Instruments:

Avoiding Common Pitfalls In Identifying the Causes of

Economic Growth. American Economic Journal:

Macroeconomics, Vol. 5, No. 2, pp. 152-186.

Dahl, R. A. (1970). Polyarchy. New Haven: Yale University

Press.

Diamond, L. (2008, March-April). “The Democratic

Rollback”. Foreign Affairs. Retrieved from

https://www.foreignaffairs.com/articles/2008-03-

02/democratic-rollback



21

Economist Intelligence Unit (2008). “Index of Democracy”.

Retrieved from

http://graphics.eiu.com/PDF/Democracy%20Index%20

2008.pdf

Economist Intelligence Unit (2015). “Democracy Index”.

Retrieved from

http://www.yabiladi.com/img/content/EIU-Democracy-

Index-2015.pdf

Jaunky, V. C. (2013). Democracy and Economic Growth in

Sub-Saharan Africa: A Panel Data Approach,

Empirical Economics, Vol. 45, pp. 987-1008.

Jochmann, M. and Koop, G. (2014). Regime-switching

Cointegration. Studies in Nonlinear Dynamics and

Econometrics, Vol. 19, No. 1.

Johnston, J. and DiNardo, J. (1997). Econometric Methods,

4th Ed, New York: McGraw-Hill.

Murray, M. P. (2006). Avoiding Invalid Instruments and

Coping with Weak Instruments. Journal of Economic

Perspectives, Vol. 20, No. 4, pp. 111-132.

Narayan, P. K., Narayan, S. and Smyth, R. (2011). Does

Democracy Facilitate Economic Growth or Does

Economic Growth Facilitate Democracy? An Empirical

Study of Sub-Saharan Africa. Economic Modelling,

Vol. 28, pp. 900-910.

Persson, T. and Tabellini, G. (2007). The Growth Effect of

Democracy: Is It Heterogeneous and How Can It Be

Estimated?, NBER Working Paper Series No.13150.

Retrieved from http://www.nber.org/papers/w13150

http://graphics.eiu.com/PDF/Democracy%20Index%202008.pdf

http://graphics.eiu.com/PDF/Democracy%20Index%202008.pdf

http://www.yabiladi.com/img/content/EIU-Democracy-Index-2015.pdf

http://www.yabiladi.com/img/content/EIU-Democracy-Index-2015.pdf



22

Rigobon, R. and Rodrik, D. (2005). Rule of Laws,

Democracy, Openness and Income: Estimating

Interrelationships. Economics of Transition, Vol. 13,

No. 3, pp. 533-564.

Wooldridge, J. M. (2009). On Estimating Firm-level

Production Functions using Proxy Variable Control for

Unobservables. Economics Letters, Vol. 104, No. 3, pp.

112–114.



23



24

On Income Inequality and Population Size

Thitithep Sitthiyot

Director

Public Debt Policy Research Division

Policy and Planning Bureau

Public Debt Management Office

Ministry of Finance

Thailand

[email protected]

Kanyarat Holasut

Associate Professor

Department of Chemical Engineering

Faculty of Engineering

Khon Kaen University

Thailand

[email protected]

Corresponding author and submitted as an independent author. The

contents of this article do not reflect the authors’ affiliations. The authors

are grateful to Suradit Holasut for initiating the idea and for valuable

suggestions. The authors also thank two anonymous referees for their

useful comments and criticisms. All errors rest with the authors.



25

ABSTRACT

The pursuit of having an appropriate level of income

inequality should be viewed as one of the biggest challenges

facing academic scholars as well as policy makers.

Unfortunately, research on this issue is currently lacking.

This study is the first to introduce the theoretical concept of

targeted level of income inequality for a given size of

population. By employing the World Bank’s data on

population size and Gini coefficient from sixty-nine countries

in 2012, this study finds that the relationship between Gini

coefficient and natural logarithm of population size is

nonlinear in the form of a second degree polynomial

function. The estimated results using regression analysis

show that the majority of countries in the sample have Gini

coefficients either too high or too low compared to their

appropriate values. These findings could be used as a

guideline for policy makers before designing and

implementing public policies in order to achieve the targeted

level of income inequality.

Keywords: Income Inequality, Gini Coefficient, Population

Size

JEL Classification: D31, D63, J19



26

1. Introduction

It is widely agreed among academic scholars and

practitioners that the most commonly used measurement of

income inequality is Gini coefficient. While the theoretical

value of Gini coefficient lies between zero and one, in

practice, the minimum and maximum values the Gini

coefficient could possibly attain are zero and (P-1)/P, where

P is the number of population. This could be illustrated by

using an example of a hypothetical country. If a country has

only one population, then there is obviously no income

inequality and the value of Gini coefficient would be zero.

That is the minimum value of Gini coefficient this country

could attain. However, as the number of population gets

larger, say, 2, 3, 5, 8, …, or P, and only one person has all the

income while others have none, a situation of perfect income

inequality, the maximum value of Gini coefficient for this

hypothetical country to attain would be 1/2, 2/3, 4/5, 7/8, …,

or (P-1)/P, respectively.1 In practice, the value of Gini

coefficient, therefore, should be greater than zero but less

than (P-1)/P.

The above example indicates that, theoretically, there

should be an association between the degree of income

inequality as measured by Gini coefficient and the size of

population. This is consistent with Deltas (2003) who argues

that the Gini coefficient of a small population would be

smaller than that of a larger one generated by the same

stochastic process. Equivalently, removing members of a

population at random would tend to lower the estimated Gini

coefficient of that population. Deltas also notes that, for any

1 This could simply be calculated geometrically by dividing the area

between the 45-degree line and the Lorenz curve by 1/2.



27

given level of intrinsic inequality, as expressed by income

generating function, a reduction in the sample size would

lead to a reduction in inequality as measured by the Gini

coefficient. In addition, countries with small populations and

less diverse economies tend to report small Gini coefficients

whereas a much higher Gini coefficient are expected for

countries with economically diverse large populations (“Gini

Coefficient”, 2016).

While there are empirical research examining the

relationship between income inequality and size of

population or size of state as well as other economic, social,

and political variables,2 the issue of what an appropriate

degree of income inequality as measured by the Gini

coefficient should be for a country given a population size

has yet to be explored by the existing literatures.3 According

to the income inequality and population data in 2012

compiled by the World Bank (2016a; 2016b), countries that

have similar values of Gini coefficient could have very

different population size. For example, Bhutan, with

population of only 743,711, has the Gini coefficient of 0.387

while Thailand, with population of 67,164,130, has a slightly

higher value of the Gini coefficient of 0.393. Does this imply

that income inequality in Bhutan is not much different from

that in Thailand? The same World Bank’s data also show that

countries that are similar in terms of population size could

2 For studies that focus on the issue of income inequality and size of

population or size of state, please see Streeten (1993), Commonwealth

Secretariat (2000), Bräutigam and Woolcock (2001), Alesina (2003), and

Campante and Do (2007). For those that investigate the relationship

between income inequality and other social, economic, and political

factors, please see Phongpaichit (2016) and references therein. 3 To the best of the authors’ knowledge, as of this writing, the authors

have found no study that investigates the appropriate level of income

inequality as measured by Gini coefficient for a given size of population.



28

have very different level of income inequality. For example,

Guinea, with population of 11,628,767, has Gini coefficient

of 0.337 whereas Haiti, with a slightly lower population of

10,288,828, has almost twice the value of Gini coefficient at

0.608. Based on these observations, can we conclude that

people of Guinea has more income equality than those of

Haiti?

Given that there are various economic, social, and

political factors that could have effects on income inequality

as investigated by earlier research,4 it is interesting to

examine the linkage between the degree of income inequality

as measured by Gini coefficient and the population size, and

find out empirically an appropriate value of Gini coefficient

given the size of population since no study has been

conducted thus far. With an exception of two extreme cases

of perfect income equality and perfect income inequality

regardless of population size, this study hypothesizes that a

country with small populations should have relatively lower

Gini coefficient than a country with large populations due to

the degree of economic, social, and political diversities as

already reflected by the size of population. This study views

that knowing the appropriate level of income inequality as

measured by Gini coefficient could benefit policy makers as

a starting point that can be used as a guideline prior to design

and implement public policies to tackle the issue of income

inequality or income equality.

This study is organized into five sections. Following the

Introduction, Section 2 discusses the logic of the appropriate

degree of income inequality. Section 3 explains research

methodology and data employed in this study. Section 4

4 See Streeten (1993), Commonwealth Secretariat (2000), Bräutigam and

Woolcock (2001), Alesina (2003), Campante and Do (2007), and

Phongpaichit (2016).



29

presents empirical findings and discusses the issue of targeted

level of income inequality. Finally, Section 5 concludes and

provides policy implications as well as suggestions for future

research.

2. The Logic of Appropriate Degree of Income

Inequality

High or extreme income inequality, theoretically, could

cause economic, social, and political disruptions in many

ways. Fuentes-Nieva and Galasso (2014) criticizes that

extreme economic inequality is damaging to society for

several reasons. It could have negative impacts on growth

and poverty reduction. Extreme economic disparity is also

worrying because of the pernicious impact that wealth

concentrations could have on equal political representation.

When wealth dominates public policymaking, the laws and

regulations are bent to favor the rich and often to the

detriment of the rest in the society. Equally alarming, public

opinion could be shaped and election outcome could be

affected by large-scale propaganda efforts through media the

rich own or can control (Raza, 2016). According to Fuentes-

Nieva and Galasso (2014), these could lead to the erosion of

democratic governance, the pulling apart of social cohesion,

and the vanishing of equal opportunities for all. Left

unchecked, the adverse effects of high or extreme income

inequality are potentially immutable, and will lead to

opportunity capture where the lowest tax rates, the best

education, and the best healthcare are claimed by the children

of the rich. This creates dynamic and mutually reinforcing

cycles of advantage that are transmitted across generations,

making process of social mobility even harder.

Whereas high or extreme income inequality is generally

perceived to have adverse effects on a society as a whole, it



30

should be noted that low income inequality or income

equality, in principle, could cause economic, social, and

political problems as well. Regardless of political regime a

country chooses to adopt, if everyone’s income is equal or

slightly different, there should be no incentives for people to

be creative or try to do things differently because no matter

how hard they try or what they do and/or invent, there will be

no extra benefits. A hypothetical example would be to

imagine that a brain surgeon doctor has the same monthly

salary as a garbage collector. In such a society, it is likely that

there would be labour shirking and/or free-riding problems.

The social and economic consequences would be poor

discipline and low initiatives among workers, poor quality

and limited selection of goods and services, as well as slow

technological progress (Soubbotina & Sheram, 2000). These

eventually could put the whole country into an incentive trap

which has negative impacts on productivity and economic

growth. In addition, for socialist, autocratic, or

nondemocratic countries, the time and monetary costs of top-

down monitoring and enforcement should be extremely high

in order to ensure that everybody has equal income or gets

the same ration.5 Except for the ruler or head of state, in a

society where people are forced to have the same wage or

ration, it is usually coupled with social and economic

problems that could give rise to protests, riots, and/or

political up-risings.

Based on the potential harmful effects of both high and

low income inequality on societies as discussed above, it

follows that a country where income inequality is too high

should lower her income inequality while a country that has

too low income inequality should increase her income

5 This excludes the ruler or head of state who typically has extremely

much larger share of income.



31

inequality in order to avoid such negative effects. Viewed

this way, the logic of an appropriate degree of income

inequality for a country could be established. The next task is

to find empirically an appropriate level of income inequality

for a country. This study hypothesizes that the appropriate

level of income inequality as measured by Gini coefficient

for a country should be positively correlated with population

size of that country. That is a country with small populations

should have relatively lower Gini coefficient than a country

with large populations. This is because it does not matter

whether a country is underdeveloped, developing, or

developed, if a country were to have only one population,

income inequality of that country as measured by Gini

coefficient would be zero. If a country were to have

population larger than one, the chance, that income inequality

as measured by Gini coefficient should rise, becomes higher

due to population heterogeneity.

Having established the logic of the appropriate degree of

income inequality and setting up hypothesis regarding the

positive correlation between the degree of income inequality

and population size, the next section explains research

methodology employed to test hypothesis whether there is

such a correlation. If so, what does the linkage imply about

the appropriate level of income inequality of a country?

3. Research Methodology

The degree of heterogeneity in social, economic, and

political factors, that could result in different income

inequality across countries, makes it difficult to find a

common set of variables that have similar effects for all

countries. It is hard to argue that Singapore with population

of 5.53 million should have the same social, economic, and

political factors affecting income inequality as those of China



32

with population of 1.37 billion.6 In addition, the number of

those factors may not be equal for both countries at a given

period of time. For these reasons, this study postulates that

the degree of social, economic, and political diversities for

any country could be reflected by population heterogeneity in

that country. In other words, the information regarding social,

economic, and political factors of a given country is already

compressed in the data on the number of population of that

country. This would allow us to examine the relationship

between the degree of income inequality as measured by Gini

coefficient and the size of population by employing ordinary

least squares regression,7 and to find out empirically the level

of income inequality as measured by Gini coefficient that is

appropriate for the size of population. To examine such a

relationship, this study employs income inequality and

population data of sixty-nine countries in the year 2012 from

the World Bank (2016a; 2016b).

The following section reports the empirical evidence of

the relationship between the level of income inequality as

measured by Gini coefficient and population size and

discusses the issue of an appropriate value of Gini coefficient

for a country given size of population.

6 The data on populations of Singapore and China come from the World

Bank (2016b). 7 It should be noted that the purpose of employing regression analysis is

to examine the correlation between income inequality as measured by

Gini coefficient and population size, not their causation. As argued in

Taleb ( 2012) , in a complex and multidimensional world, ‘ the notion of

“ cause” itself is suspect; it is either nearly impossible to detect or not

really defined.’



33

4. Empirical Results

Figure 1 illustrates scatter plots of the relationship

between levels of income inequality as measured by Gini

coefficient and natural logarithm of population size by taking

into account the possibility that if a country has only one

population, then the Gini coefficient must be zero.8 The

scatter plots indicate that the relationship between the two

variables should be positive. By employing curve fitting technique, this study finds

that the relationship between the level of income inequality

as measured by Gini coefficient and natural logarithm of

population size is nonlinear that can be best described by a

second-degree polynomial function.9 The following nonlinear

equation is therefore employed to estimate the relationship

between Gini coefficient and natural logarithm of population

size. Gini = + 1*ln(Pop) + 2*[ln(Pop)]2 + (1)

Where

= 0, 1 0, 2 0 and Gini = Gini Coefficient

ln(Pop)= Natural Logarithm of Population Size

= Error Term

8 A country with one population is included in the sample in order to

make the case more physically and mathematically realistic in the sense

that if there were such a country, then income inequality as measured by

Gini coefficient would have to be zero. This is always true regardless of

social, economic, and political background of that country. 9 The authors also tried a linear function, a third-degree polynomial

function, and a nonlinear function that includes natural logarithm of

population size and square root of natural logarithm of population size to

fit the data points but found that a polynomial function of degree two

yields the best fit. These results are available upon request.



34

Fig

ure 1

. Th

e R

elati

on

ship

betw

een

Levels

of

Incom

e I

neq

uali

ty

as

Measu

red

by

Gin

i C

oeff

icie

nt

an

d N

atu

ral

Logarit

hm

of

Pop

ula

tion

Siz

e



35

By using ordinary least squares estimator with

heteroskedasticity-consistent standard errors and covariance,

the estimated nonlinear relationship between Gini coefficient

and natural logarithm of population size is as follows:

Gini = 0.0304*ln(Pop) – 0.0005*[ln(Pop)]2 + (2)

The estimated results from equation (2) and from Table 1

below indicate that the coefficient on natural logarithm of

population size is statistically significant at 5 percent level

while that on natural logarithm of population size square is

statistically insignificant. The results confirm the hypothesis

of positive correlation between level of income inequality as

measured by Gini coefficient and natural logarithm of

population size. Adjusted R2 indicates that variations of

natural logarithm of population size and of natural logarithm

of population size square could explain variation of Gini

coefficient around 25 percent.

Table 1. Estimated Nonlinear Relationship between Gini

Coefficient and Natural Logarithm of Population Size

Explanatory Variable Coefficient P-Value

Constant

0

N/A

Natural Logarithm of

Population Size

0.0304

(5.26)

0.0000

[Natural Logarithm of

Population Size]2

-0.0005

(-1.36) 0.1785

Notes: Adjusted R2 = 0.2455; t-statistics are in parentheses; number

of countries = 69; total of observations = 70 including an



36

additional sample where a country has one population which would

result in the Gini coefficient to be zero.

Figure 2 and Figure 3 illustrate the scatter plots between

the estimated Gini coefficient and natural logarithm of

population size and between the estimated Gini coefficient

and natural logarithm of population size square respectively.

In addition, the population sizes, the levels of actual income

inequality as measured by Gini coefficient, and appropriate

values of Gini coefficient estimated by this study for sixty-

nine countries in 2012 are shown in Table 2.

The empirical results from Table 2 show that there are

twelve out of sixty-nine countries that have the difference

between the estimated Gini coefficient and the actual Gini

coefficient by less than five percent.10 If the difference

between the estimated Gini coefficient and the actual Gini

coefficient is allowed to be less than ten percent, there are

twenty-three countries in this sample.11 This indicates that,

given countries’ population sizes, about one-fifth to one-

third of countries in the sample have Gini coefficients close

to their appropriate values while the other two-third to four-

fifth have either too high or too low Gini coefficients. As

explained in Section 2, too high or too low income inequality

could cause economic, social, and/or political difficulties in

the society. Therefore, countries that have high income

inequality should make an effort to reduce it whereas those

with low income inequality should try to increase it.

10 Those countries are Bulgaria, Cyprus, Estonia, Greece, Sri Lanka,

Lithuania, Montenegro, Mongolia, Portugal, Thailand, Turkey, and

Vietnam. 11 In addition to twelve countries listed in the previous footnote, there are

eleven more countries which are Spain, Guinea, Ireland, Italy, Lao PDR,

Luxembourg, Latvia, Mauritius, Philippines, Russian Federation, and

Democratic Republic of Congo.



37

Fig

ure 2

. Th

e R

ela

tion

ship

betw

een

Est

imate

d G

ini

Coeff

icie

nt

an

d N

atu

ral

Logarit

hm

of

Pop

ula

tion

Siz

e



38

Fig

ure 3

. Th

e R

ela

tion

ship

betw

een

Est

imate

d G

ini

Coeff

icie

nt

an

d [N

atu

ral

Logarit

hm

of

Pop

ula

tion

Siz

e]2



39



40



41



42



43

However, this does not mean that countries that have the

levels of income inequality as measured by Gini coefficient

equal or close to the appropriate levels should stay passive. It

is possible that, given approximately equal sizes of

population and Gini coefficients, the ratio of income share

held by the rich to the income share held by the poor in one

country is much higher than that of the other country. In this

case, the former country should come up with public policies

in order to reallocate income among populations by

increasing income of the poor and at the same time reducing

income of the rich in such a way that the targeted or

appropriate level of income inequality remains unchanged.

5. Conclusions, Policy Implications, and Suggestions for

Future Research

This study views that the pursuit of having an

appropriate level of income inequality should be considered

as one of the biggest challenges facing academic scholars as

well as policy makers. Unfortunately, technical and empirical

research on this particular issue are currently lacking. As a

result, most, if not all, policy attempts by governments

around the world to either reduce or raise the level of income

inequality (mostly reducing) are designed and implemented

without prior knowledge about targeted Gini coefficients in

mind. By employing the World Bank’s data on population

size to reflect the heterogeneity in economic, social, and

political factors as well as to level playing field among

countries and on Gini coefficient, the logic and empirical

findings of appropriate levels of income inequality as

measured by Gini coefficient for sixty-nine countries from

this study could be used as a guideline for policymakers

before designing and conducting public policies in order to

pursue the targeted level of income inequality. This study



44

conjectures that, for a given population size, countries that

achieve the targeted level of income inequality should

perform better in terms of economic growth and well-being

than those that are far away from their appropriate levels of

income inequality.

In addition, the issue of widening gap between income

(and/or wealth) share held by the rich and income (and/or

wealth) share held by the average population has recently

caught public attention. For example, according to Frank

(2011), heads of the largest corporations in the United States

of America at present earn four hundred times as much as

average workers, compared to forty times as much back in

1980s. Research conducted by Oxfam also indicates that, in

2015, the richest sixty-two people in the world own half of

global wealth (Reuben, 2016). While the main focus among

academic scholars and policymakers has been on the issue of

how to narrow the income (and/or wealth) gap between the

richest and the poorest, this study believes otherwise. It

hypothesizes that the root of the problem may not lie between

income (and/or wealth) gap of the richest and the poorest, but

rather that of the richest and the second richest. The

theoretical idea behind this is that when income (and/or

wealth) of the richest group gets larger than that of the

second richest group up to the point that passes a critical

threshold, it could make the second richest group feels that it

is unfair. It might also be possible that the richest group feels

that their economic, social, and/or political statuses are

threatened by the second richest group. The battle between

the two hegemonic groups could cause chaos in the society

mainly because both the richest and the second richest have

all the resources to influence government policies, to bend

laws, regulations, and constitutions, to create large-scale

propaganda and conflicts of memes among interest groups

and grassroot people, as well as to shape referendum or



45

election outcome. It is of interest to examine whether this

hypothesis is rejected or not. If not, then it is worth to find

out what an appropriate income (and/or wealth) gap between

the richest and the second richest groups that yields no

conflict between these two hegemonic groups for the good of

the society.

Moreover, it is of challenge to search for appropriate

gaps of percentage share of income among subgroups of

population in the society such that those who have lower

income feel wholeheartedly that it is fair and square for them

to have less income than those who earn more. These

interesting issues await future research.12

12 The authors thank Suradit Holasut for pointing out these issues.



46

References

Alesina, A. (2003). The Size of Countries: Does It Matter?.

The Journal of the European Economic Association, 1

(2-3), pp. 301-316.

Bräutigam, D. & Woolcock, M. (2001). Small States in a

Global Economy: The Role of Institutions in Managing

Vulnerability and Opportunity in Small Developing

Countries. WIDER Discussion Paper No. 2001/37.

Retrieved from

http://www.wider.unu.edu/sites/default/files/dp2001-

37.pdf

Campante, F. & Do, Q. A. (2007). Inequality, Redistribution,

and Population. KSG Faculty Research Working Paper

Series No. RWP07-046. Retrieved from

https://research.hks.harvard.edu/publications/workingp

apers/citation.aspx?PubId=4995&type=WPN

Commonwealth Secretariat. (2000). Small States: Meeting

Challenges in the Global Economy. Report of the

Commonwealth Secretariat/World Bank Joint Task

Force on Small States. Retrieved from

http://documents.worldbank.org/curated/en/267231468

763824990/Small-states-meeting-challenges-in-the-

global-economy

Deltas, G. (2003). The Small-Sample Bias of the Gini

Coefficient: Results and Implications for Empirical

Research. The Review of Economics and Statistics, 85

(1), pp. 226-234.

Frank, R. H. (2011). The Darwin Economy: Liberty,

Competition, and the Common Good. New Jersey:

Princeton University Press.



47

Fuentes-Nieva, R. & Galasso, N. (2014). Working for the

Few: Political Capture and Economic Inequality.

Oxfam Briefing Paper. Retrieved from

https://www.oxfam.org/en/research/working-few

Gini Coefficient. (n.d.). In Wikipedia. Retrieved July 7, 2016,

from https://en.wikipedia.org/wiki/Gini_coefficient

Phongpaichit, P. (2016). Commentary Note on Thailand’s

Current Inequality Situation and Its Prospects.

Thammasat Review of Economic and Social Policy, 2

(1), pp. 4-16.

Raza, S. A. (2016). r > g: Increasing Inequality of Wealth and

Income Is a Runaway Process. In 2016: What Do You

Consider The Most Interesting Recent [Scientific]

News? What Makes It Important?. Retrieved from

https://www.edge.org/annual-questions

Reuben, A. (2016, January 16). Wealth of Richest 1% ‘Equal

to Other 99%’. BBC News. Retrieved from

http://www.bbc.com/news/business-35339475

Soubbotina, T. P. & Sheram, K. A. (2000). Beyond Economic

Growth: Meeting the Challenges of Global

Development. Washington, D.C.: The World Bank.

Streeten, P. (1993). The Special Problems of Small

Countries. World Development, 21 (2), pp. 197-202.

Taleb, N. N. (2012). Antifragile: Things That Gain from

Disorder. New York: Random House.

The World Bank. (2016a). Gini Index (World Bank Estimate)

[Data file]. Retrieved from

http://data.worldbank.org/indicator/SI.POV.GINI

https://en.wikipedia.org/wiki/Gini_coefficient



48

The World Bank. (2016b). Population Ranking [Data file].

Retrieved from

http://databank.worldbank.org/data/reports.aspx?Code=

SP.POP.TOTL&id=af3ce82b&report_name=Popular_i

ndicators&populartype=series&ispopular=y



49



50

South-South Trade Growth Prospects and Policy

Implications

Panit Buranawijarn Candidate for MA (Economics)

Faculty of Economics

Thammasat University

Thailand

[email protected]

The contents of this article do not reflect the author’s affiliations. The

author thanks two anonymous referees for their comments and criticisms,

and Associate Professor Euamporn Phijaisanit, Thammasat University for

comments on an earlier version of this paper submitted for coursework.

All errors rest with the author.



51

ABSTRACT

South-South Trade, or more broadly South-South

Cooperation, is the collaboration between developing

countries of the Global South across various dimensions such

as political, economic, and social issues. This paper analyses

trends and developments in the trade between developing

countries in contrast to other orientations of trade, focusing

particularly on China and India. The paper looks at their trade

flows, as well as their other activities which fall under the

aegis of South-South Cooperation. Lastly, the literature on

South-South Trade is reviewed to study the motivation for

engaging and encouraging South-South Trade, as well as its

overall effectiveness. Policy recommendations for the

development of South-South Trade are made based on

evidence from the study.

Keywords: South-South Trade, China, India, economic

development

JEL Classification: F01, F10, F50



52

1. Introduction

Throughout history the integration and connectedness of

the world has ebbed and flowed; in modern times this

connectivity and globalisation has been enhanced by

advances in communications technologies that have left a

permanent mark on how the world communicates and does

business. However, the oldest force which has driven this tide

of interconnectedness is the trade between cities, regions and

nations. The wealth and exchange of information that

international trade brings to nations has determined their

success or failure throughout human history.

In economics, the basis for the championing of trade

between nations as a way to raise overall welfare in both rests

with Ricardo’s theory of comparative advantage. Subsequent

theories and models have sought to both build and improve

this idea, as well as attempting to prove and better

understanding the nature of trade empirically. Furthermore,

understanding trade also requires understanding the nature of

firms as recent developments have seen greater focus on the

role of networks, intra-firm trade, and the trade in

intermediates.

These theories and models are helpful in analysing

North-South trade where major differences exist in factor

endowments, or trade between developed countries which

have strong ‘gravitational’ pull towards each other. These

theories present motivations for trade which are purely

pecuniary, however other incentives for trade may also exist:

for example, the European Commission provides a list

benefits that developing countries may receive when

engaging in trade such as increased investment, knowledge

transfers and job creation1.

1 Retrieved from

http://trade.ec.europa.eu/doclib/docs/2012/january/tradoc_148991.pdf



53

Building on this, South-South Trade, or more broadly

South-South Cooperation, is the collaboration between

developing countries across various domains including

politics, economics, social, cultural, environmental and

technical. Congruent to this is the notion of the Global South

which is made up of the world’s developing countries (and

hence South-South). The most concise definition for the term

‘developing country’ (and the definition this paper will

employ) is the World Bank’s classification of all countries

that are not high income, or below $12,476 income per

capita. This encompasses 138 of 217 ‘economies’ as the

World Bank defines them2. More concretely, what this

difference in income and development levels translates into

include deficiencies in hard and soft infrastructure like roads,

hospitals, and bureaucratic transparency, weak enabling

institutions for education, political involvement, and the rule

of law, and a poorly developed manufacturing or service

sector failing to provide jobs for skilled individuals. The

motivation for this paper is to understand how South-South

Trade has fitted into the development path of developing

countries, and what it may mean for the Global South as

whole in the future.

This paper studies the trends and developments,

motivations and policies behind South-South Trade through a

review of the literature and data. This will then be used to

formulate policy recommendations. The paper is structured as

a review of the literature which has been written on South-

South Trade, and is split into the following parts: first the

characteristics of South-South Trade are analysed, followed

by a discussion of the influence exerted by two major players

in the Global South, China and India, both in Asia and

2 Retrieved from http://data.worldbank.org/about/country-and-lending-

groups



54

beyond. The paper will then examine the effectiveness of

South-South Trade, as well as explore other non-economic

motivations for encouraging the growth of South-South

Trade. Lastly, the paper ends with a series of policy

implications and a conclusion based on the issues which have

been discussed.

2. Literature Review

This main body of the paper explores in the detail the

literature which has been written on South-South Trade and

its characteristics, as well as the importance of certain key

players in world trade and the Global South. Lastly, this

section explores the effectiveness of South-South Trade and

discusses some of the other potential motivations for

developing South-South Trade.

2.1. Characteristics of South-South Trade

To begin the discussion, it is important to paint a broad-

strokes picture of South-South Trade compared to world

trade. Figure 1 shows how exports by developing countries

has changed over time, against the back drop of world trade. Since 1995, total exports by developing countries has

grown modestly, mirroring overall global trends. Total

exports by developing countries, however, has grown faster

than South-South Trade indicating strong growth in exports

by developing countries to developed countries.



55

Fig

ure 1

. Exp

orts

by

develo

pin

g c

ou

ntr

ies,

1995

-2015

So

urc

e: U

nit

ed N

atio

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Co

nfe

rence

on T

rad

e an

d D

evel

op

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CT

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(20

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)



56

Table 1 breaks down exports of merchandise by region,

with the two major regions being Europe and Asia.

Furthermore, China is also the world’s largest exporter of

merchandise accounting for 12.7 per cent of the world’s total

merchandise exports in 2014.

Table 1. World merchandise exports by region/country in

2014

Percentage of world

merchandise exports

North America 13.5

South and Central America 3.8

Europe 36.8

Commonwealth of Independent States 4.0

Africa 3.0

Middle-East 7.0

Asia 32.0

China 12.7

India 1.7

Six East Asian traders 9.6

Source: World Trade Organisation (2015)

Breaking exports down further, at the individual country

level the second largest exporter is the United States,

followed closely by Germany. The largest exporter in terms

of dollar value in the Global South, aside from China, is

Mexico followed by Russia; India is the fourth largest

exporter in terms of developing countries and was globally

ranked 18th in 2015 (United Nations Statistics

Division/Comtrade, 2010). However, the outsized growth of

China and its influence on South-South Trade statistics has

led to some researchers crediting almost all the growth and



57

development in South-South Trade as being due to China

(Aksoy & Ng, 2014).

Table 2 below highlights the discrepancies between

developed and developing regions. Total manufacturing

exports in the world amount to 66.2 percent of the goods

trade (the remaining is divided between the trade in

agriculture, and fuels and mining), and the split between

regions is as previously described. What Table 3 shows,

however, is that as a share of their exports or imports,

developing regions (aside from Asia, and of course this

picture is distorted by wide differences in the region) depend

more on imports of manufactures while their exports are

mainly in other sectors.

Table 2. Share of manufactures in total merchandise

trade by region in 2014

Exports Imports

World 66.2 66.2

North America 67.6 75.0

South and Central America 25.5 65.3

Europe 74.8 68.5

Commonwealth of Independent States 22.4 75.6

Africa 20.7 72.1

Middle East 20.7 72.1

Asia 80.0 59.9

Source: World Trade Organisation (2015)

While it is easy to discuss international trade from a

macro perspective, it is also important to remember the ways

and means in which trade is conveyed around the world. In

the developed world, the network of logistics that can provide

consumers with next day (or even same day) delivery is taken

for granted, and it is only remarked upon when it fails. The

picture in the developing world is the complete opposite. The



58

World Bank’s 2014 Logistics Performance Index (LPI) paints

a stark picture of the compounding effect that poor

infrastructure and/or poor logistics service providers has on

developing countries. Furthermore, the border control

agencies in developing countries are often poorly equipped

and are unable to provide efficient clearing services, much

less delivering consistent timely outcomes. Arvis, Duval, Shepherd and Utoktham (2013) use data

from trade data from manufacturing and agriculture sectors in

178 countries over the period 1995-2010 to quantify this

effect: trade costs are sharply decreasing in income per

capita. Furthermore, while trade costs all over the world are

falling, they are falling slowest in the lowest income groups.

This has possibly dire consequences for their development,

and poses a significant barrier to their integration into global

trade. De (2006) investigates countries in Northern Asia and

demonstrates the direct effects that trade costs have on trade

volume, and how integration into the world economy is a

direct result of improving trade-related infrastructure and

services.

There is a myriad of reasons for this failure in closing the

logistics gap. Cadot and de Melo (2014) discuss the

experiences learned in the Aid for Trade programme and

provide an excellent insight into the problems that developing

countries face. Issues include the many non-tariff barriers

that developing countries run up against, for example the

inability to meet sanitary and phytosanitary (SBS) regulations

that developed countries impose on agricultural products,

while another issue analysed in the book is the poor

implementation of the programme due to fragmented

government and unclear lines of authority between ministries

in many developing countries.

One other issue that Cadot and de Melo bring up that has

direct relation to South-South trade is the failure in



59

realisation of the gains from unilateral liberalisation. In this

situation, a country undergoes liberalisation of its trade

policies, while neighbouring countries do not. This

disconnect in policy and lack of regional coordination

presents particular problems for the least developed and land-

locked developing countries which are highly dependent on

their neighbours as intermediaries for trade into and out of

the country. This lack of regional-level projects is where the

push for South-South Cooperation has a policy space, and

where an intra-regional push for greater cooperation between

neighbouring developing countries may yield benefits.

On the topic of regional cooperation, the failure of the

World Trade Organisation (WTO) in concluding the Doha

Round and the stop-go progress in negotiations since the

Ninth WTO Ministerial in Bali where signs of life seemingly

appeared over the issue of Trade Facilitation has cast doubt

on changes to the multilateral trading regime. Furthermore,

vulnerabilities and alarming weaknesses in global trade

growth and potential increases in protectionist policies

(Evenett & Fritz, 2016) have not been helped by the latest

crisis in the form of Brexit and the relationship between

members of the European Union. It is not surprising that

major exporters like China may be seeking to cultivate long-

term alternatives or simply diversify its pattern of trade.

2.2. Focus: China and India

China and India are two most populous countries in the

world, together comprising nearly 40% of the world’s

population. China, by some measures, is now the world’s

largest economy3 while India is perennially described as the

3 Retrieved from http://www.economist.com/news/finance-and-economics/21623758-chinas-back



60

next economic power. Both countries are also undertaking

policy changes designed to address what have been seen as

long term issues: India’s Prime Minister, Narendra Modi, was

elected on a platform of business-friendly policies (though

this has yet to yield significant changes), while President Xi

Jinping of China has been actively rooting out corruption in

the Chinese economic system.

While China and India are two of the leading countries

in the Global South (both are members of the eponymous

BRICS group of nations), relations have not always been

smooth: the Sino-Indian Border Conflict of 1962 still has

effects today with respect to the disputed Kashmir region.

Unrest in the region and border tensions with neighbouring

Pakistan has cemented this as an intractable problem of

sovereignty. Of course, it would be remiss to not mention the

increasingly tenuous and rapidly building issue that is the

South China Sea. How China handles these issues, and its

relationships with regional neighbours and partners, will set

the path for China on the world stage.

Having said the above, there are signs that economic ties

between China and India are improving, and if there is any

bilateral relationship that is likely to shape the course of

South-South Cooperation in the world, it will be the relations

between these two countries. China and India dominate the

economic and political landscape in the Asia-Pacific region.

Furthermore, their push for a South-driven development

process through initiatives such as the New Development

Bank and Asian Infrastructure Investment Bank in the face of

continued economic woes both at home and abroad is an

attempt to find an answer from the South to the global

economic malaise.

At present, however, both China and India are still

highly dependent on the developed world as trade partners.

Table 3 and Table 4 show China and India’s major trading



61

partners by share of trade flow. It is interesting to note that

China’s major partners on both the import and export side are

firmly in the North, and that while China registers as one of

India’s major partners for exports and imports, India is but

one of China’s minor partners.

Given the evidence, it is possible to see that, despite the

rhetoric coming from both countries on South-South

Cooperation, the two countries are still mostly dependent on

developed countries as export markets and import sources for

their production processes (for the time being). This can be

seen at the 2-digit SITC Rev.4 level; China is a major

importer of electrical machinery and parts, as well as raw

materials in the form of petroleum and its related products, as

well as metal ores and scrap. On the export side, China’s

major exports are telecommunications and related equipment,

electrical parts, and computer related products. Clothing and

apparel also remains a major export of China (United Nations

Statistics Division/Comtrade, 2016).

Table 3: China’s Major Trade Partners in 2015

Export Destinations Share (%) Import Sources Share (%)

USA 18.0 South Korea 10.4

Hong Kong 14.6 USA 9.0

Japan 6.0 Taiwan 8.6

South Korea 4.4 Japan 8.5

Germany 3.0 Germany 5.2

Vietnam 2.9 Australia 4.4

Source: United Nations Statistics Division/Comtrade (2016)

There is, however, an important caveat when discussing

China’s trade. China’s position as the leading manufacturer

and exporter of merchandise is due to its positioning in the

global value chain as the central assembly centre. This poses

an issue when analysing trade statistics as it is difficult to



62

determine China’s actual value added in the production

process, with the actual amount likely to be lower than

reported values in trade statistics, thereby flattering to

deceive China’s actual technological capabilities in

manufacturing (Xing, 2014). Having said that, Chinese firms

are unlikely to remain idle, a good example being the

smartphone industry. Though the Apple iPhone may be

China’s most famous smartphone ‘export’, domestic

manufacturers such as Huawei, OPPO, and Xiaomi are fast

growing in both sales and reputation (Kastrenakes, 2016).

Table 4: India’s Major Trade Partners in 2015

Export Destinations Share (%) Import Sources Share (%)

USA 15.2 China 15.8

UAE 11.3 Saudi Arabia 5.5

Hong Kong 4.6 Switzerland 5.4

China 3.6 USA 5.2

United Kingdom 3.4 UAE 5.2

Singapore 3.0 Indonesia 3.6

Source: United Nations Statistics Division/Comtrade (2016)

On the other hand, India’s trade profile is suggestive of a

country at a lower level of manufacturing development. Their

major export is refined petroleum and related products which

has arisen because of their strategic location linking the

Middle-East (the source of India’s unrefined oil) with the rest

of Asia (India’s other major exports include non-metallic

minerals, clothing and apparel, and textile yarns and fabrics).

Of note on the import side is the country’s voracious appetite

for gold which is both used as jewellery and a safeguard

against an ill-perceived financial system4. Given China’s role

4 Retrieved from http://www.economist.com/blogs/economist-explains/2013/11/economist-explains-11



63

as the largest producer of gold in the world, and given the

recent establishment of the Shanghai Gold Exchange

(Songwanich, 2016), there is a potential for issues to arise in

the future over the gold trade.

These trade profiles highlight the possible differing

priorities for China and India, and it remains to be seen if the

differences will bring them closer to engage in trade for their

mutual benefit, or if it will drive them apart.

2.3. South-South Cooperation: looking beyond trade

Trade, though important, is but one consideration for

countries in the Global South. China views South-South trade

as but one facet of its aid strategy along with technical

assistance and capacity building, investment in infrastructure,

and preferential trade agreements to name a few (OECD,

2012a). India, too, views South-South trade as part of a wider

cooperation strategy between developing countries designed

to enhance capabilities for self-development. Both China and

India have had a long history as donors; both China and India

were part of the Bandung Conference in 1955 which laid the

ground work for the Non-Aligned Movement, a part of which

lives on in the non-interference nature of aid rendered as part

of the South-South Cooperation framework (OECD, 2012b).

Initially, China focused its aid on neighbouring countries

sharing, at the time, similar political views such as North

Korea and Vietnam. After the Bandung Conference however,

China gradually expanded its aid programme eventually

stretching to include Western Asia, Africa, and Latin

America. Indeed, since 2009 China has been Africa’s largest

trading partner, and China’s aid to Africa can even

overwhelm domestic conditions; in 2008 China signed a deal

to provide a 6 billion US dollar loan to the Democratic



64

Republic of the Congo which had a GDP of 11.2 billion US

dollars in the same year (Sun, 2014).

India’s aid flows have mostly been targeted towards

countries in its vicinity such as Bhutan, Afghanistan,

Maldives, Nepal, and Sri Lanka. Like China, India has also

directed a significant portion of its aid to the African

continent. The majority India’s aid is focused around training

civil servants, engineers, and public sector managers, with

smaller amounts being directed towards concessional export

credits for purchasing Indian goods and services (OECD,

2012b). This aid focus towards generating business

opportunities for home country firms is also reflected in

Chinese aid which is designed to provide business

opportunities for Chinese state-owned firms. While recipients

of aid obviously benefit from these development projects and

assistance, it is also important to question the long-term

viability of an aid strategy where the focus is on providing

opportunities for home country firms rather than developing

the recipient country (Sun, 2014).

2.4. The effectiveness of South-South Trade: empirical

evidence

The focus of this literature review has revolved around

the significance of South-South trade. While the strong

empirical basis which links trade and economic growth is

acknowledged (indeed the push for South-South trade would

otherwise not make sense), as well as the success of export-

oriented policies that so benefited the Asian tigers from the

early 1960s to the 1990s, the literature on those topics will

not be restated here.

The narrative thus far has been one of North-North and

North-South flows driving world trade. Page (2004)

highlights the relative unimportance, thus far, of South-South



65

trade. She notes that the major markets for developing

countries all over the world are still in the North, and of the

South only India, and potentially China, are major trading

partners for most developing countries. Page does note,

however, that liberalising India’s high tariff rates could be

beneficial for other developing countries, but the chances of

this given India’s own status as a developing country are low.

There is also an empirical and theoretical basis for the

benefits that arise from increasing South-South trade; Ratna

(2009) documents the rise of South-South trade from 1990 to

2006, and highlights the channels through which South-South

trade can be a driving force for growth. Ratna makes these

claims by asserting that given the higher level of barriers in

the South, liberalising South-South trade has the potential to

generate more welfare compared to further liberalisation of

North-South trade. Secondly, developing countries provide

many of the intermediary goods used in final production, and

thus reducing trade barriers between countries in the South

will allow their goods to become more competitive price-

wise.

The trend of late in Official Development Assistance

(ODA) has also bolstered this: Aid for Trade now accounts

for roughly a third of all ODA (Cadot & de Melo, 2014).

Hühne, Meyer and Nunnenkamp (2014) show that Aid for

Trade has been beneficial for promoting South-South trade.

While their focus on South-South trade was to alleviate

endogeneity concerns in measuring North-South exchanges,

their conclusions show the benefit that developing countries

would gain from increased Aid for Trade flows.

Having said that, even though South-South trade was

envisioned to promote a more symmetrical exchange, things

have not always turned out that way. Udeala (2010) explores

the trade between Nigeria and China, and shows that trade

outcomes have been tilted in China’s favour, thereby



66

resembling the interaction between countries engaged in

North-South trade.

Furthermore, given the present small size of South-South

trade relative to other trade flows, the possible impacts are

hardly significant: Behar and Cirera (2010) employ gravity

models to show the positive impacts that trade liberalisation

in the form of the effect of free trade agreements on bilateral

trade. While they show that developing countries

unequivocally benefit from more liberalised trading regimes,

they are unable to come to a conclusion on whether engaging

in more South-South agreements would be beneficial to

developing countries. They come to this conclusion due to

their model’s inability to capture the perceived technological

benefits of engaging in North-South trade, compared to the

deeper economic and political ties engendered by South-

South trade.

2.5. Other motivations for South-South Trade

Beyond the reasons explored in the previous section,

there are other, non-economic, reasons for why countries are

promoting South-South Cooperation. China has ramped up its

efforts to be recognised on the world stage, through

economic, diplomatic, and military means. Examples of these

efforts include the promotion of the Renminbi and the

establishment of the Shanghai Gold Exchange, their

rapprochement with India and Russia, and on a somewhat

different note, the nexus of security, military, and power

issues that is the South China Sea. They are not, however, the

only players in the Global South trying to make their voice

heard: Putin’s Russia is again making a resurgence in global

politics, if not always for peaceful reasons. An agenda

pushing South-South Cooperation would certainly suit these

two countries who have recently reached an agreement for



67

increased natural gas imports. This deepening in Sino-

Russian ties is a potential worry for developed countries such

as Australia (which exports gas and coal to China) or

countries in the EU which depend on Russian gas imports

(Paton & Guo, 2014).

The continued failure of WTO members to bring a close

to the Doha Development Round has not improved the

situation. Instead, it has contributed to a proliferation of

Regional Trade Agreements (RTAs). These are free trade

agreements that are usually centred on a particular

geographical location, for example the Trans-Pacific

Partnership (TPP) which is part of the United States’ ‘pivot to

Asia’, as well as the Regional Comprehensive Economic

Partnership (RCEP) which covers the ASEAN group plus its

major economic partners minus the USA. While progress

with the TPP may be seen as a set-back for China, the pursuit

of increasing South-South Cooperation would help to

mitigate potential diversionary flows that arise from the TPP.

Newfarmer (2006) counts over 200 RTAs that are in force,

with the vast majority of RTAs being South-South, however

despite this proliferation in agreements, the magnitude of

South-South trade flows means that of the 30 percent of

world trade which happens between reciprocal RTA

members, most still involve the US or EU. However, given

the political uncertainties across the globe, with each region

experiencing its share of instability it is difficult to see what

path future developments may take. The extent to which

these uncertainties are affecting developed countries,

however, may help to push more developing countries to

further strengthen South-South ties in the near future.

There are two divergent views on what this increase in

regionalism means for world trade, coined as ‘stumbling

blocks’ or ‘building blocks’ by Jagdish Bhagwati (Frankel,

1997). The ‘stumbling block’ view imagines the formation of



68

a few major trading blocs with highly liberalised internal

trade, and relatively less liberalised external trade thereby

creating a cycle where trade occurs mostly between members

of the same trading bloc. The ‘building block’ view, on the

other hand, postulates that over time market pressures will

lead to an equalisation of prices and barriers, thereby

reaching an end-game of a fully open multilateral system

through plurilateralisation. This is of course under the

assumption that there aren’t political barriers to prevent this,

such as special interest groups within or between countries

that deliberately hinder efforts at integration.

Looking at South-South Cooperation through this

political lens, it is not difficult to see why major developing

countries such as China would seek to develop closer ties to

other countries part of the Global South. While China has a

history of foreign aid which goes back some 60 years, the

volume of aid has increased significantly in the last decade

(OECD, 2012a). Sun (2014) explores some of the reasons for

China’s expansion of aid in Africa: Sun states that while the

primary factor driving China’s investment in Africa is

probably due to the continent’s natural resources, China is

also seeking to bolster its security, political, and ideological

interests. One possible reason is the support that the African

voting bloc of 54 members in the United Nations General

Assembly brings (this is roughly a quarter of the votes in the

UN GA).

Not everyone views these developments in a positive

light however. Hanauer and Morris (2014) highlight some of

the negative impacts that China’s investment has had on

Africa, particularly stemming from China’s ‘hands-off, no-

interference’ approach to foreign policy. They characterise

this as having potential destabilising effects in the region,

through supporting corrupt practices and oppressive regimes.

It should be noted that the report is told from the perspective



69

of the United States’ security interests. Furthermore, the

authors envision China’s involvement as potentially freezing

out the United States’ opportunities on the region.

These geo-political considerations should thus be kept in

mind whenever evaluating the increased push for South-

South Cooperation.

3. Policy Implications for South-South Trade

The central question to answer here is, of course, should

developing countries push the agenda to deepen South-South

trade? The empirical evidence backs the view that South-

South trade can help promote economic growth and

development, though is this more effective than broad trade

liberalisation?

In 1993 Daniel Trefler used a Hecksher-Ohlin-Vanek

(HOV) model augmented with productivity differences to

show that the HOV theorem does, in fact, work empirically

on a general basis (Trefler, 1993). Before that however, the

HOV theorem was able to explain much of the trade flows

between North and South countries. This is both straight

forward and intuitive: developed countries in the North

would export their abundance in capital, while developing

countries would export based on their abundance in labour.

With this in mind, it is clear to see why most trade still occurs

along North-South lines.

On the other hand, the increased unbundling of the

production process may be a boon for the South-South

Cooperation agenda. Baldwin (2014) summarises the effects

on industrialisation of what he terms the second unbundling

in rather unflattering terms. While industrialisation is now

easier for developing countries, it is less meaningful as they

become a part of the production line. This reduces the

chances of knowledge transfers and spillovers as the



70

technologically demanding tasks remain in the North. Thus,

the benefits from engaging in North-South trade are reduced,

putting it on more even footing with benefits which may be

accrued from South-South trade flows.

Is there a policy space for South-South Cooperation in

this unbundling? The issue still is that countries in the South,

for the most part, lack the technological know-how and

capital stock of developed countries. It is unclear how

pushing for increased South-South Cooperation would

alleviate this problem. Instead the policy implication here

would still be the same message of developing local human

capital capabilities, thereby improving the capacity for

knowledge absorption and moving up the value chain.

If the reason for the South-South Co-operation agenda is

not economic, then we must refer back to the ‘Other’

motivations explored earlier. Indeed, the Financial Times, in

response to Krugman’s assertion that the TPP is insignificant,

claims that the economist is missing the point entirely. For

the United States, the deal is much more about fostering

tighter economic cooperation and enhancing their security

than it is about the economic gains from trade5. For now,

however, it still remains to be seen if the TPP will survive to

the point of ratification and enforcement by all member states

given the increasingly tenuous political situation in the

United States.

One aspect in which the TPP can be seen as

revolutionary is the inclusion of ‘FTA-plus’ or ‘Singapore

Issues’6. The successful completion and establishment of an

5 Retrieved from http://blogs.ft.com/the-world/2014/02/tanks-or-cars-why-krugman-is-missing-the-point-on-trade-deals/ 6 Introduced at the First WTO Ministerial in Singapore, these issues are

trade and investment, trade and competition policy, transparency in

government procurement, and trade facilitation.



71

RTA incorporating these issues could potentially act as a

model for similar agreements to be reached elsewhere.

However, many in the South (including China) view that they

are not sufficiently prepared to address these issues, not to

mention enforcing stringent laws on intellectual property

rights and domestically unpopular investor-state dispute

settlement mechanisms. Thus, viewing South-South

Cooperation as a collective bargaining block to slow down

these developments is another plausible consideration.

The discussion thus far has mostly focused around major

developing countries in the South, namely China and India.

The implications of increased South-South Cooperation are

very different for them compared to the vast majority of

developing countries who lack the economic and political

leverage to tilt proceedings in their favour. It should thus then

be hoped that the spectre of South-South Cooperation is not

used to drive a wedge between North-South trade.

What policy implications can be drawn from this? One

would argue that for the majority of developing countries, the

answer is not very different from standard export-oriented

economic development policies. However, as stated earlier

trade costs in the developing world are still the highest,

leaving a lot of room for improvement in this area. Focusing

on the issues that surround that first (for example improving

hard and soft infrastructure to lower trade costs, cutting

bureaucratic red tape) is a difficult enough challenge for

many developing countries. To take full advantage of the

possibilities that South-South Cooperation could bring,

however, means having products to sell. This involves

domestic development of industries and small businesses, as

well as the development of rural areas. An example of this

would be One Village One Product (OVOP)-style policies

run in countries such as Thailand and Malawi which are

based on the original (now defunct) rural development



72

programme in Oita, Japan (Kurokawa, Tembo & te Velde,

2010).

4. Conclusion

The development of South-South Cooperation will not

be the be-all end-all for economic growth, development and

the shape of world trade. While more of the share of

manufacturing and production may shift to the developing

world in the coming years, and indeed may even be

accelerated by continued weaknesses and instabilities in the

developed world, a lot of that will still be due to China

(ADB-ADBI, 2014). Having said that, even China is immune

from potential threats to its economy as its growth slows

down (Einhorn, 2016). This may present itself as an

opportunity for other developing countries (such as those in

South-East Asia) already part of global value chain, though

obviously, any economic troubles in China will have large

knock-on effects for global economy.

For the remaining developing countries, however, the

long and arduous road to economic development is still a

process that requires a multi-faceted and all-inclusive

approach. South-South Cooperation should be pushed for

what it can achieve, and that is increased freer trade among

developing countries, but the industrialisation and

development process will still require inputs and engagement

with developed countries. While South-South Cooperation

thrives through non-interference, developing countries will

need to understand that continued development, growth, and

stability will depend on reducing inefficiencies in the

domestic economy.

Furthermore, for countries dependent on aid from China

and India, a long and hard look is required to look at the

long-run demands for growth in the country. While



73

infrastructure developments and outside assistance provides

short-term opportunities for improvement, it must be backed

up by improving domestic conditions for job seekers and

local businesses. However, for developing countries

dependent on North-South trade, weaknesses in the global

economy engendered by domestic instabilities in many

developed countries should be a clear warning sign. Fostering

greater South-South ties, and improving domestic capabilities

to move up the value chain should be a priority for these

countries.

To conclude, South-South Cooperation presents many

potential benefits and pitfalls, and requires each individual

country to be aware of their own situation and what the best

way to make use of South-South Cooperation to better their

growth prospects may be.



74

References

Aksoy, A. & Ng, F. (2014). Increased export performance

and competitiveness of developing countries is mainly

a China story. Retrieved from

http://www.voxeu.org/article/south-south-trade-it-s-

mostly-china

Arvis, J-F., Duval, Y., Shepherd, B. & Utoktham, C. (2013).

Trade Costs in the Developing World. Poverty

Reduction and Economic Management Network Policy

Research Working Paper Series, No. 6309. Washington

D.C.: The World Bank.

Asian Development Bank-Asian Development Bank Institute

(2014). ASEAN, PRC, and India: The Great

Transformation. Tokyo: Asian Development Bank

Institute.

Baldwin, R. (2014). Trade and Industrialization after

Globalization's Second Unbundling: How Building and

Joining a Supply Chain Are Different and Why it

Matters, in Feenstra, R., and A. Taylor (eds)

Globalization in an Age of Crisis: Multilateral

Economic Cooperation in the Twenty-First Century.

Chicago: University of Chicago Press.

Behar, A. & Cirera, L. (2010). The impact of North-South

and South-South trade agreements on bilateral trade.

CSAE Working Paper Series, No. 2010-30. Oxford:

Centre for the Study of African Economies.

Paton, J. & Guo, A. (2014, November 10). Russia, China add

to $400 billion gas deal with accord. Bloomberg.

Retrieved from http://www.bloomberg.com/news/2014-

11-10/russia-china-add-to-400-billion-gas-deal-with-

accord.html



75

Cadot, O. & de Melo, J. (2014). Aid for Trade: What have we

learnt? Which way ahead? Washington D.C.: Center for

Economic and Policy Research.

De, P. (2006). Why Trade Costs Matter? Asia-Pacific

Research and Training Network on Trade Working

Paper Series, No. 7. Bangkok: United Nations

Economic and Social Commission for Asia and the

Pacific.

Einhorn, B. (2016, October 20). China’s housing bubble

wobble. Bloomberg. Retrieved from

http://www.bloomberg.com/news/articles/2016-10-

20/china-s-housing-bubble-wobble

Evenett, S. & Fritz, J. (2016). Global trade plateaus.

Retrieved from http://www.voxeu.org/article/global-

trade-plateaus

Frankel, J. (1997). Regional Trading Blocs in the World

Economic System. Washington D.C.: Peterson Institute

for International Economics.

Hanauer, L. & Morris, L. (2014). Chinese Engagement in

Africa. Nation Security Research Division, RAND

Corporation. Washington D.C.: RAND Corporation.

Hühne, P., Meyer, B. & Nunnenkamp, P. (2014). Does Aid-

for-Trade from the North promote South-South Trade?

Kiel Working Paper Series, No. 1918. Kiel: Kiel

Institute for the World Economy.

Kastrenakes, J. (2016, April 27). Lenovo and Xiaomi no

longer among top 5 smartphone makers. The Verge.

Retrieved from

http://www.theverge.com/2016/4/27/11521178/lenovo-

xiaomi-overtaken-in-smartphone-shipments



76

Kurokawa, K., Tembo, F. & te Velde, D. (2010). Challenge

for the OVOP Movement in Sub-Saharan Africa. JICA

Research Institute Working Paper Series, No. 18.

Tokyo: Japan International Cooperation Agency

Research Institute.

Newfarmer, R. (2006). Regional Trade Agreements: Designs

for Development in Newfarmer, R. (eds) Trade, Doha,

and Development: Window in the Issues. Washington

D.C.: The World Bank.

Organisation for Economic Co-operation and Development

(2012a). Trade-related South-South Co-operation:

China. Policy Dialogue on Aid for Trade. Paris:

Organisation for Economic Co-operation and

Development.

Organisation for Economic Co-operation and Development

(2012b). Trade-related South-South Co-operation:

India. Policy Dialogue on Aid for Trade. Paris:

Organisation for Economic Co-operation and

Development.

Page, S. (2004). South-South Trade in The Doha

Development Agenda Impacts on Trade and Poverty.

London: Overseas Development Institute.

Ratna, R. (2009). Promoting South-South Trade: Recent

Developments and Options. ARNeT Policy Brief

Series, No. 17. Bangkok: United Nations Economic and

Social Commission for Asia and the Pacific.

Songwanich, S. (2016, April 25). China’s new gold fix. The

Nation. Retrieved from

http://www.nationmultimedia.com/opinion/Chinas-

new-gold-fix-30284591.html



77

Sun, Y. (2014). Africa in China’s Foreign Policy.

Washington D.C.: Brookings Institute.

Trefler, D. (1993). International Factor Price Differences.

Journal of Political Economy, 101(6), 961-987.

Udeala, S. (2010). Nigeria-China economic relations under

the South-South Cooperation. African Journal of

International Affairs, 13(1), 61-88.

United Nations Conference on Trade and Development

(2016). Data retrieved October 10, 2016 from

http://unctadstat.unctad.org/wds/ReportFolders/reportF

olders.aspx

United Nations Statistics Division (2016). Data retrieved July

7, 2016, from http://comtrade.un.org/.

World Bank (2014). Logistics Performance Index:

Connecting to Compete 2014: Trade Logistics in the

Global Economy. Washington D.C.: The World Bank.

World Trade Organisation (2015). International Trade

Statistics 2015. Retrieved from

https://www.wto.org/english/res_e/statis_e/its2015_e/it

s2015_e.pdf

Xing, Y. (2014). Measuring Value Added in the People’s

Republic of China’s Exports: A Direct Approach.

ADBI Working Paper Series No. 493. Tokyo: Asian

Development Bank Institute.



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