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Income convergence dynamics inASEAN and SAARC blocsSakiru Adebola Solarina, Elsadig Musa Ahmeda & Jauhari Dahalanb

a Faculty of Business, Multimedia University, Melaka, Malaysiab School of Economics, Finance and Banking, University UtaraMalaysia, Sintok, MalaysiaPublished online: 03 Mar 2014.

To cite this article: Sakiru Adebola Solarin, Elsadig Musa Ahmed & Jauhari Dahalan (2014) Incomeconvergence dynamics in ASEAN and SAARC blocs, New Zealand Economic Papers, 48:3, 285-300,DOI: 10.1080/00779954.2013.874399

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Income convergence dynamics in ASEAN and SAARC blocs

Sakiru Adebola Solarina*, Elsadig Musa Ahmeda and Jauhari Dahalanb

aFaculty of Business, Multimedia University, Melaka, Malaysia; bSchool of Economics,Finance and Banking, University Utara Malaysia, Sintok, Malaysia

(Received 8 June 2013; accepted 6 December 2013)

This paper examines whether convergence of real income exists among theAssociation of South East Asian Nations (ASEAN) and South Asian Association forRegional Cooperation (SAARC) countries for the period covering 1970–2009.Univariate Lagrange Multiplier (LM) unit root tests with structural break(s) areemployed to check for the incidence of stochastic convergence, which is necessary forconditional convergence as proposed in the neoclassical model. We further examinethe presence of b-convergence, which is considered as the sufficient requirement forconditional convergence. Test results suggest convergence among ASEAN members,with the absence of convergence in SAARC member countries.

Keywords: income convergence; ASEAN; SAARC; structural breaks

JEL Classifications: C22; O47; O57

1. Introduction

The neoclassical growth model suggests that the wide gap of living standards, which ini-

tially separates the poor and rich nations, will disappear over time. In other words, coun-

tries that are originally poor should have faster growth rates relative to the originally rich,

so that their income levels will eventually converge. The theoretical proposition is pre-

mised on several assumptions including the postulation that with the passage of time, pro-

duction technology which was exclusive to prosperous economies will be available to the

developing nations. Moreover, capital per worker is assumed to be less in poor econo-

mies, implying higher marginal products of capital. In search for a higher rate of return

on capital, savers in many economies will direct their fund, at the expense of rich econo-

mies, to the poor states, wherein capital stocks are expected to grow quickly even if

domestic savings rates are very low. Beyond the ability to deflate the possible risk for the

outbreak of political tensions and hostilities among countries, economic integration is

likely to heighten the pace of technology spillover and capital mobility. In recent times,

several economic blocs have been formed to enhance inter-country and inter-regional

activities.

Starting with Baumol (1986), the convergence of income has attracted considerable

attention among economists. The earliest empirics (such as Barro, 1991; Sala-i-Martin,

1996) share a similar feature of using cross-sectional techniques, which have been chal-

lenged in some quarters (for example, see Friedman, 1992). The vulnerability of cross-

sectional techniques generated another wave of literature on convergence of income that

employs time series procedures (see Bernard & Durlauf, 1995; Dawson & Strazicich,

*Corresponding author. Email: sasolarin@mmu.edu.my

� 2014 New Zealand Association of Economists Incorporated

New Zealand Economic Papers, 2014

Vol. 48, No. 3, 285–300, http://dx.doi.org/10.1080/00779954.2013.874399

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2010; Strazicich, Lee, & Day, 2004, among others). Time series evidence has been

largely based on advanced countries, with most studies usually in support of income con-

vergence. Research works dedicated to developing countries are not as widespread as lit-

eratures on developed countries. For example, to our knowledge, the few studies on the

Association of South East Asian Nations (ASEAN) and South Asian Association for

Regional Cooperation (SAARC) with time series orientation are Lim and Mcaleer

(2004), Lee, Lim, and Azali (2005), Chowdhury (2004) and Jayanthakumaran and Lee

(2008, 2013).

This paper considers convergence of income for nine ASEAN and eight SAARC

countries for the period 1970–2009. Although there are many economic blocs, ASEAN

and SAARC are among the most important integration efforts within the Asian continent

with the reduction of regional income inequality high among their agenda. SAARC is an

organisation of the countries making up the largest group of people in the world and, as a

result, is supposed to have the largest sphere of influence than any other regional organi-

sation. With a population of more than 1.653 billion, nearly one quarter of the world pop-

ulation lives in these eight member countries, which are believed to have the potential to

become an area of great prosperity based on the idea of economic integration among the

member countries. The region accounted for 40% of the total population in Asia and con-

tributed 10% of the Asian Gross Domestic Product (GDP) in 2011 (United Nations,

2013). On the other hand, ASEAN has about 600 million inhabitants and accounts for 8%

of the aggregate Asian GDP. With the integration of its economy in process, ASEAN is a

major player in Asian economy and its role is expected to be the biggest after China and

India. In a bid to achieve their objectives, regional trade agreements (RTAs) such as

ASEAN Free Trade Area (AFTA) and SAARC Preferential Trading Agreement (SAPTA)

have been introduced over the past two decades. The ASEAN and SAARC nations have

had differing levels of success in regard to integration. While SAARC still remains to be

seen by itself and the world as a successful and vibrant socio-economic regional organisa-

tion, ASEAN has experienced some degree of economic cooperation, stability and

prosperity.

The objective of this paper is to compare the effectiveness of the regions’ integration

efforts, in terms of convergence of income that has been achieved. Regional trade and

investment reforms tend to allocate resources internally among member nations, in

response to the elimination of quotas and tariffs in sectors that are traditionally protected

(Jayanthakumaran & Lee, 2013). With committed RTA, income convergence is likely to

occur among countries which possess cultural and geographical links (Freund, 2000) and

especially through integration (Silvestriadou & Balasubramanyam, 2000). This study

contributes to the existing studies on convergence in the ASEAN and SAARC regions in

three respects. First, we contribute to the literature by including more countries in the two

blocs than any of the existing papers. All the states in the two regions are now actively

involved in the integration process and therefore excluding any deserving country from

the analysis may prejudice the results. Prior exercises have largely blamed insufficient

data for including the fraction of the total members in their studies (Jayanthakumaran &

Lee, 2013). We are not constrained by this factor and consequently consider 17 of the

maximum 18 countries in this study. The second contribution of the current paper lies in

investigating the stationarity properties of the original income series before embarking on

the examination of the difference series’ stationarity properties. Previous literatures have

overlooked this important step. Within the stochastic environment, if the original income

series are stationary, there is no possibility of convergence among them (as they are at dif-

ferent levels) so that any conclusion of convergence on the difference series becomes

286 S.A. Solarin et al.

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invalid (Carlino & Mills, 1993; Cunado & Perez de Gracia, 2006a). Lastly, this is the first

endeavour to implement the Lee and Strazicich (2003, 2004) unit root tests procedure, to

verify stochastic convergence in the regions. The Lee and Strazicich (2003, 2004) unit

root tests are reliable and not affected by size distortions, in contrast to the Lumsdaine

and Papell (1997) stationarity tests utilised in previous studies (Lee & Strazicich, 2001).

The rest of this paper is organised as follows. Section 2 presents the literature review.

Section 3 provides the overview of integration efforts in ASEAN and SAARC countries

while the methodology is reviewed in Section 4. Empirical findings are discussed in Sec-

tion 5 and, finally, Section 6 presents with the conclusion of the study.

2. Literature review

There are at least three likely scenarios of convergence in the literature, which include no

convergence, unconditional (absolute) convergence and conditional convergence.1 An

absence of convergence captures the situation in which poor countries fail to catch up

with the rich ones, over time. The validity of the Solow model becomes questionable in

such a case. Unconditional convergence implies that income level in poor countries will

get closer to the rich countries so that, in the long run, disparity in the level of develop-

ment among the countries will disappear. This involves running a regression involving

per capita income growth and initial income, without the inclusion of conditioning varia-

bles. For unconditional convergence to exist, the regression must produce a negative rela-

tionship between the two series. In this case, convergence is expected to hold, even if the

countries under observation are different in terms of policies, savings rates, population

growth rates and access to technology. The notion of unconditional convergence implies

that there is only one equilibrium level to which all economies approach (Islam, 2003).

Baumol (1986) confirmed unconditional convergence for a sample of 16 Organisation for

Economic Co-operation and Development (OECD) countries for the 1870–1979 study

period. Conditional convergence suggests that initially deprived countries will catch up

with rich countries in terms of development, if they do not differ in characteristics such

as savings rates, population growth rates and access to technology. In the case of condi-

tional convergence, equilibrium differs by the economy, and each particular economy

approaches its own but unique equilibrium (Islam, 2003). Barro (1991), Mankiw, Romer,

and Weil (1992) and Sala-i-Martin (1996) confirmed conditional convergence in industri-

alised countries.2

The preceding literatures share the similar feature of utilising cross-sectional techni-

ques, which has been widely challenged by scholars. For instance, Friedman (1992) dem-

onstrated that the negative relationship between the initial levels of income and growth in

cross-country regressions do not adequately represent the concept of convergence. Fur-

ther, Quah (1993) revealed that such negative relationship is subjected to various deduc-

tions, which include a stable variance in cross-sectional distribution of incomes. Bernard

and Durlauf (1996) showed cross-sectional techniques as biased towards rejecting the

null of no convergence, and they cannot differentiate between local and global conver-

gence hypotheses.

Due to these criticisms, the recent studies apply time series methods to verify

income convergence. Carlino and Mills (1993) and Loewy and Papell (1996) investi-

gated convergence in per capita income of eight regions in the USA for the 1929–1990

period with their findings showing evidence for convergence in the regions. Bernard

and Durlauf (1995) probed per capita convergence in a sample of 15 OECD countries

for the 1900–1987 period, and the paper was unable to find evidence for convergence.

New Zealand Economic Papers 287

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Li and Papell (1999) evaluated the possibility of stochastic convergence among 16

OECD countries for the period 1900–1991 and observed convergence for most coun-

tries. Strazicich et al. (2004) exploited the two-break unit roots test of Lee and Strazi-

cich (2003) to investigate the occurrence of per capita income convergence in 15

OECD countries for 1870–1994. Test results provided substantial support for conver-

gence. Dawson and Sen (2007) and Dawson and Strazicich (2010) probed the conver-

gence hypothesis for real per capita incomes of 29 countries from 1900 to 2001. Both

papers revealed substantial evidence for convergence of the per capita incomes. Cunado

and Perez de Gracia (2006b) examined the existence of real convergence of some Cen-

tral and East European countries towards Germany and the USA during the period

1950–2003. Test results showed that the catch-up process occurred during the 1990s to

2003 period for Poland, the Czech Republic and Hungary towards Germany and only

for Poland towards the US economy.

One visible feature of the previous papers is the inclusion of developed countries in

their samples. There are also research works that have focused solely on developing

countries, which are not only closely similar in terms of the level of development, but

also have some degree of economic integration efforts. Galvao and Reis Gomes (2007)

tested for income convergence in 19 Latin American countries during a 1951–1999

study period. Test results revealed substantial evidence in favour of conditional conver-

gence in the selected countries with greater evidence for convergence when the sample

was separated into South and Central America. Cunado and Perez de Gracia (2006a)

examined the occurrence of per capita income convergence in 43 African countries for

the period 1950–1999. Overall, the study was able to find limited evidence for conver-

gence, when the benchmark was either the African average or the US economy. Cunado

(2011) examined the real convergence hypothesis of 14 Organization of the Petroleum

Exporting Countries (OPEC) using data for the period 1950–2006. The study was only

able to find evidence of catch-up with the US economy for the case of Indonesia and

for Angola in the last years of the sample. Solarin and Sahu (2013) probed the inci-

dence of per capita income convergence in 11 African Financial Community franc

countries in Africa towards various benchmarks for the 1961–2010 period, where the

test results demonstrated limited convergence among the countries.

Separable across methodology inclinations, there are few studies of the convergence

hypothesis in ASEAN and SAARC. Ismail (2008) utilised the panel cross-sectional tech-

niques to explore convergence of income in five ASEAN countries for the period of

1960–2004. Test results provided evidence for convergence in these economies. How-

ever, Chowdhury (2005) investigated convergence of per capita income in the same

ASEAN countries during 1960–2001, but failed to support the hypothesis. For SAARC

countries, Chowdhury (2004) examined convergence in seven SAARC countries (with

the exception of Afghanistan) for the period 1960–2000. The paper failed to establish

convergence in these economies.

Lim and Mcaleer (2004) examined convergence in five ASEAN countries for 1965–

1992. The paper was unable to find convergence in these countries. Lee et al. (2005)

probed convergence of income in the same five ASEAN countries and Japan during the

period of 1960–1997. The findings of Lee et al. (2005) revealed income divergence

between each ASEAN country and Japan, with the exception of Singapore. Jayanthaku-

maran and Lee (2008, 2013) examined the convergence of income in five ASEAN coun-

tries and five SAARC countries separately. Applying the Lumsdaine and Papell (1997)

method, convergence was found in the ASEAN countries, without any evidence for

income convergence among the SAARC countries.

288 S.A. Solarin et al.

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3. Overview of ASEAN and SAARC

ASEAN was established in August 1967 in Bangkok by the five original member coun-

tries, namely, Indonesia, Malaysia, Philippines, Singapore and Thailand. The other mem-

bers that later joined the association are Brunei, Vietnam, Laos, Myanmar and Cambodia.

With an appreciable level of success, several initiatives were launched in the region

including preferential trade agreement in 1977 and unilateral economic restructuring, fol-

lowing chronic economic downturns in the early 1980s (Jayanthakumaran & Lee, 2013).

In 1992, ASEAN leaders introduced the AFTA to increase investment and economic

growth of participant countries, and increasing the region’s competitive advantage as a

production base geared for the world market (Ching, 2008; Yusop, 2009). The overall

impact of AFTA has generally been positive and is expected to remain as such in the

future, as regional integration provides many opportunities in various forms (Yusop,

2009). Signed immediately after AFTA, the Common Effective Preferential Tariff

scheme was introduced to reduce tariff rates for all relevant products to a 0%–5% range,

through normal and fast-track approaches. The reduction of tariffs was found to have sig-

nificant effect in increasing the bilateral exports of ASEAN members (Hapsari &

Mangunsong, 2006). Overall, regionalism in the ASEAN bloc has led to some appreciable

levels of economic benefits and income convergence. Following a sharp decline in 1998

due to the Asian financial crisis, the average GDP per capita of ASEAN member states

had increased from USD 965 in 1998 to USD 2533 in 2009. In 2009, the least developed

countries in ASEAN – Cambodia, Laos, Myanmar and Vietnam economies – grew (at a

rate of 4.9%) faster than the other six members (which grew at 1%). They were less

affected by the 1997 Asian financial crisis, managing to grow by 5.7% in 1998 when the

other six members contracted by 8.8%, and their collective share to ASEAN GDP also

increased from less than 6% in 1998 to above 9% in 2009 (Pitsuwan, 2010).

The SAARC was established in 1985 and includes Afghanistan, Bangladesh, Bhutan,

India, Maldives, Nepal, Pakistan and Sri Lanka. The essence of the bloc is to create insti-

tutional and regulatory mechanisms that make optimum use of inter-regional trade and

social and political development, which ultimately lead to a regional economic growth. It

was perceived that SAARC, through accelerated economic growth and social develop-

ment programmes, would promote the collective self-reliance of the region, thereby con-

tributing to mutual trust and appreciation. Recognising that a preferential trading

arrangement is the first step towards higher levels of trade and economic cooperation,

member nations conceived the idea of SAPTA in December 1991 to encourage mutual

trade and the economic cooperation among the Contracting States.3 However, most of the

measures in the arrangement were never implemented which led to the introduction of

South Asian Free Trade Area (SAFTA) in 2006. One of the frameworks in SAFTA that

was designed to close the development gap among SAARC countries was the introduc-

tion of two sets of trading conditions, with the stricter condition for the developing coun-

tries – India, Pakistan and Sri Lanka – and the lighter condition for least developed

countries – Bhutan, Bangladesh, Maldives and Nepal. The impact of SAFTA is yet to be

substantially felt by the members of the bloc. Unlike the ASEAN countries, trade between

the SAARC states has remained limited despite the fact that all are located within a close

proximity of one another and all are part of the World Trade Organization (Thapar, 2006).

The Integrated Programme of Action (IPA), which involves nine areas of cooperation,

constitutes the core of the SAARC process from which regional cooperation could take

off. Although it underwent numerous changes, the nature of activities carried out under

the IPA has been beneficial from the regional perspective only to a limited extent.

New Zealand Economic Papers 289

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Following the recommendation of an Independent South Asian Commission on Poverty

Alleviation, the governments in the region committed to the eradication of poverty in

South Asia by year 2002 through an Agenda of Action. However, this objective was never

realised and the target date has been shifted several times (Lama, 2010). Overall, the inte-

gration efforts over the years have not been very fruitful due to incessant inter-state con-

flicts and uncooperative stance of member states, ethnic tensions, imbalance of power

among member states, preference for bilateral as against multilateral agreements, human

rights abuses and corruption (Jayanthakumaran & Lee, 2013; Thapar, 2006). The SAARC

as a regional body has little to show in terms of matching with its foundational objectives

and in terms of reaching its benefits to the people and institutions in the region (Lama,

2010).

4. Data and econometric methodology

Data for the 17 Asian countries under consideration were extracted from the Penn World

Tables 7.0, which has the benefit of providing purchasing power parity data. The coun-

tries include Brunei, Cambodia, Indonesia, Laos, Malaysia, Philippines, Singapore, Thai-

land and Vietnam for ASEAN countries. Myanmar is the only ASEAN country left out

due to insufficient data. SAARC countries under consideration are Afghanistan, Bangla-

desh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka. The study employs yearly

series of per capita real GDP (rgdpch variant, in line with Galvao & Reis Gomes, 2007)

ranging from 1970 through to 2009. The current study does not consider the 1960s

because of several factors. First, data of that period are not available for most countries in

these regions. Second, the period was associated with (potential) conflicts with no con-

crete effort for economic integration in the two blocs. Singapore became independent

from Malaysia in 1965, while Bangladesh separated from Pakistan in 1971. There were

three major wars that took place between India and Pakistan, namely, in 1947, 1965 and

the Bangladesh Liberation War (which also involved Bangladesh) in 1971. From 1962 to

1966, an undeclared military conflict between Indonesia and Malaysia was a major source

of tension in the ASEAN region (Ewing-Chow, 2010).

The initial value and growth rate of per capita GDP in ASEAN and SAARC countries

are presented in Table 1. According to the convergence hypothesis, countries with rela-

tively higher (or lower) initial value of GDP will have lower (or higher) growth rate. Con-

sidering the ASEAN countries, we observe that Brunei has the biggest initial per capita

income (at USD 59,124.46) and the lowest growth rate at (�0.37%) for the entire sample

period 1970–2009. Countries with relatively lower initial per capita real GDP such as

Vietnam (at USD 569.47), Laos (at USD 632.69) and Indonesia (USD 859.04) grew at a

relatively higher growth rate – 4.34%, 3.90% and 4.16%, respectively. Singapore and

Malaysia have relatively high initial income (at USD 6806.20 and USD 2095.73, respec-

tively) and also high growth rates (5.15% and 4.48%, respectively). However, evidence

shows that their recent growth rates (2000–2009) are among the lowest (2.55% and

1.75%), with their initial real per capita income among the highest in the region at USD

38,278.21 and USD 9705.86, respectively. This signifies support for convergence in the

ASEAN countries. Considering the SAARC countries, insufficient evidence was observed

as the countries with relatively lower initial per capita such as Nepal (USD 686.06) and

Bangladesh (USD 794.51) have relatively lower growth rates (1.51% and 1.59%, respec-

tively). Although Maldives has relatively lower initial per capita and relatively higher

growth rate, recent statistics (2000–2009) show relatively higher initial per capita (at

USD 3132.30) and relatively higher growth rate (at 4.27%). Due to the significance of the

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Table1.

Realper

capitaincomein

ASEANandSAARCmem

ber

countries.

Period

1970–2009

1970–1979

1980–1989

1990–1999

2000–2009

Country

Initial

value

Growth

rate

Initial

value

Growth

rate

Initial

value

Growth

rate

Initial

value

Growth

rate

Initial

value

Growth

rate

ASEANcountries

Brunei

59,124.46

�0.37

59,124.46

5.70

99,274.46

�5.67

54,182.90

�0.82

49,495.10

�0.69

Cam

bodia

1095.22

1.64

1095.22

�6.19

561.85

3.04

736.03

3.86

1067.70

5.85

Indonesia

859.04

4.16

859.04

6.44

1597.19

3.94

2344.20

2.45

2919.94

3.79

Laos

632.69

3.90

632.69

2.25

784.81

3.62

1104.87

2.70

1437.41

7.02

Malaysia

2095.73

4.48

2095.73

7.43

4227.52

3.76

6062.04

4.98

9705.86

1.75

Philippines

1574.93

1.63

1574.93

3.24

2160.38

�0.33

2067.54

1.64

2411.09

1.97

Singapore

6806.20

5.15

6806.20

7.80

14,349.33

4.91

22,980.80

5.34

38,278.21

2.55

Thailand

1575.89

4.25

1575.89

4.55

2442.27

6.25

4454.07

2.77

5761.76

3.43

Vietnam

569.47

4.34

569.47

1.54

656.58

3.70

941.84

5.94

1675.00

6.19

SAARCcountries

Afghanistan

858.01

2.32

858.01

�0.46

802.70

�1.01

704.81

�4.08

382.83

14.83

Bangladesh

794.51

1.59

794.51

�0.88

715.44

1.25

809.08

2.04

987.43

3.94

Bhutan

837.89

4.71

837.89

0.62

885.55

6.85

1645.48

5.50

2786.16

5.86

India

886.24

3.51

886.24

1.44

1018.26

3.30

1407.72

2.87

1858.87

6.42

Maldives

730.92

4.94

730.92

3.25

982.39

7.90

2056.99

4.35

3132.30

4.27

Nepal

686.06

1.51

686.06

0.23

699.12

2.23

867.40

2.18

1075.12

1.41

Pakistan

1148.17

1.92

1148.17

2.39

1450.73

2.91

1931.24

�0.31

1858.22

2.68

SriLanka

1123.35

3.37

1123.35

2.61

1451.33

2.72

1896.46

4.16

2849.22

3.97

Source:PennWorldTables7.0.Thefiguresarein

theiroriginalseries

with‘Initialvalue’

referringto

thevalueofper

capitaincomeatthebeginningoftheperiodandgrowth

rateisthe

incomegrowth

ratewithin

each

period.

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policy implications of convergence, graphical inspection is too crude and a more formal

investigation is required.

5. Methods

This study follows the time series procedure of Carlino and Mills (1993), which com-

prises two steps to verify conditional convergence. The first step involves the investiga-

tion of the existence of stochastic convergence (equivalent to convergence in growth

rate) with the use of per capita income of a country relative to average per capita income

in each region. The existence of stochastic convergence implies that shocks to the income

of a given country relative to the cross-sectional average will be temporary. Stochastic

convergence can be tested as follows:

yit ¼ ln GDPit=XIi¼1

GDPit=I

!" #ð1Þ

Here the relative income of country yit is the ratio of per capita income of country i to the

ASEAN or SAARC’s average. I refers to the sample size. Unit root testing is performed

on the relative income yit to decide the presence of stochastic convergence. Failure to

reject null hypothesis of unit root demonstrates the case in favour of stochastic conver-

gence. According to Carlino and Mills (1993), the convergence of per capita incomes

through time requires the following: (1) that shocks to a region’s per capita income are

temporary (stochastic convergence) and (2) that initially poor regions tend to catch up to

the initially rich regions (cross-sectional convergence). In other words, rejecting null

hypothesis of a unit root is merely a necessary, but not sufficient, condition for condi-

tional convergence, which is only established when stochastic convergence and b-conver-

gence exist (Galvao & Reis Gomes, 2007).

The second step involves the verification of b-convergence, which is satisfied if the

countries with initial incomes beneath the average income grow faster than countries

with initial incomes higher than the average income.

yit ¼ xi þ bit þ eit ð2Þ

Here eit is the error term that fulfils the classical assumptions i.e. zero mean and constant

variance. For b-convergence to exist, the growth rate(s) of yit must be positive (negative),

provided the initial value(s) of yit is negative (positive). In other words, xi and bi must

generate opposite signs.

Several unit root tests inclusive of the routinely used augmented Dickey–Fuller

(ADF) test are available in the literature to inspect stochastic convergence. Reliance on

ADF test has been questioned because it ignores the existence of possible structural

breaks. Perron (1989) demonstrated that the power to reject a unit root declines when

the time series concerned is stationary around a structural break. As an alternative, Per-

ron (1989) introduced a unit root test that incorporates dummy variables to permit one

exogenous or known break point. Later papers improved the test to allow for unknown

structural break(s), which is (are) determined endogenously from the data. Popular

among these papers include those of Zivot and Andrews (1992) and Lumsdaine and

Papell (1997), who introduced unit roots with one and two endogenously determined

structural breaks, respectively. Zivot and Andrews’ (1992) test involves selecting the

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structural break at a point in which the t-statistic testing the null of a unit root is the

most negative. Lumsdaine and Papell (1997) simply replicated this idea, providing for

two break points.

One important concern with utilising the tests by Zivot and Andrews (1992) and

Lumsdaine and Papell (1997) is the assumption of no break(s) under the unit root null,

in which their critical values were derived accordingly. Thus, the alternative is

‘structural breaks are present’, which indicates the likelihood of a unit root with break

(s). Therefore, the rejection of the null does not essentially mean rejection of unit root

per se, but would mean rejection of unit root without breaks (Lee & Strazicich, 2003).

Moreover, Lee and Strazicich (2001) demonstrated that the assumption of no break

under the null in endogenous break tests causes the test statistic to diverge and lead to

significant rejections of the unit root null when the data-generating process (DGP) is a

unit root with break(s).

As a solution to the drawbacks noted with earlier tests, Lee and Strazicich (2003,

2004) proposed the Lagrange multiplier (LM) unit root test with endogenously deter-

mined structural break(s) in which the alternative hypothesis unambiguously implies

trend stationarity as follows:

Dyt ¼ d0DZt þ fSt�1 þ

Xpi¼1

xDSt�i þ mt ð3Þ

Here D is the first difference operator. S is a de-trended variable, with

St ¼ yt � cx � Zt dt; t ¼ 2; . . .; T : Expatiating on the symbols, d is a vector of the coeffi-

cients in the equation of Dyt on DZt and cx ¼ yt � Zt d; with y1 and Z1 depicting the first

observations of yt and Zt, respectively. mt is an error term that is assumed to fulfil the clas-

sical properties of a zero mean and finite variance. Zt is a vector of exogenous variables

characterised by DGP. Taking into consideration two-time changes in level and trend,

Zt ¼ ½1; t;D1t;D2t;DT1t;DT2t�0, where Djt ¼ 1 if t � TBj þ 1; j ¼ 1; 2; and 0 otherwise,

and also DTjt ¼ t if t � TBj þ 1; j ¼ 1; 2; and 0 otherwise. Position of TBj, which are breakdates, are given by λj ¼ TBj=T ; j ¼ 1; 2: If structural break (level and/or trend) is signifi-

cant, then Zt ¼ ½1; t;D1t;DT1t�0, where Djt ¼ 1 if t � TB þ 1 and 0 otherwise, and also

DTjt ¼ t if t � TB þ 1 and 0 otherwise.4 Generally, LMt ¼ Inf λ~tðλÞ is used in locating

the break dates, which minimises t (t-statistics) for the null hypothesis of unit root (f ¼0). Augmented terms of DSt�i; i ¼ 1; : : :; k are included to thwart the problem of serial

correlation in errors (see Lee & Strazicich, 2003, 2004).5

Providing for the dummies of structural breaks, b-convergence is re-specified as

yt ¼ h0 þ h1t þ h2D1t þ h3D2t þ h4DT1t þ h5DT2t þ et where x ¼ h0 þ h2 þ h3;b ¼ h1 þ h4 þ h5 depending on the presence of structural breaks. This is applied on rela-

tive incomes of countries which display stochastic convergence with two significant

breaks in level and trend. In estimating the b-convergence, for stochastic convergent

countries with one break, h3 ¼ h5 ¼ 0, and with no break, the paper further imposes

h2 ¼ h4 ¼ 0. As specified earlier xi and bi must produce opposite signs with significant

entries for b-convergence to exist.

6. Empirical findings

Table 2 reports the results of ADF and the Lee and Strazicich tests of each country’s per

capita income, alongside the averages of ASEAN and SAARC. ADF test results indicate

that the null of non-stationarity cannot be rejected in levels, for the series, at 10%

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significance level. A similar result was also obtained from Lee and Strazicich’s method at

the same level of significance. Two significant breaks were identified for all the series.

These outcomes generally prove that all the series achieve the first requirement of sto-

chastic convergence.

The unit root results of each country’s relative income to the regional average income

are presented in Table 3. Results for ASEAN countries are reported in the upper panel.

With the exception of Vietnam, all other countries fail to reject the existing of the unit

root in the series. Proceeding to Lee and Strazicich’s test(s), the null of unit root cannot

be rejected for Cambodia, Indonesia, Laos and Thailand, implying that these countries do

not possess stochastic convergence towards ASEAN’s average. Nevertheless, the null of

unit root is rejected for Vietnam, Brunei, Malaysia, Singapore and the Philippines, sug-

gesting that these countries do have stochastic convergence with ASEAN’s average.

Apart from the Philippines, which possessed a single significant structural break, two sig-

nificant structural breaks are detected in other countries. The results further indicate that

Table 2. Unit root tests of the original income series.

ADF Lee and Strazicich test

Country k t-stat k TB1 TB2 t-stat Break point(s)

ASEAN countriesBrunei 0 �2.352 1 1976 1994 �3.839 (0.2, 0.6)Cambodia 0 �2.655 1 1977 2005 �4.600 (0.2, 0.8)Indonesia 0 �2.343 3 1978 1997 �4.793 (0.2, 0.8)Laos 4 �0.707 0 1980 2004 �3.855 (0.2, 0.8)Malaysia 4 �1.140 2 1975 1993 �4.256 (0.2, 0.6)Philippines 4 �2.081 4 1979 1982 �4.674 (0.2, 0.4)Singapore 2 �1.939 1 1978 2000 �4.527 (0.2, 0.8)Thailand 4 �1.789 1 1987 1999 �3.223 (0.4, 0.6)Vietnam 0 �1.976 1 1977 1997 �4.927 (0.2, 0.8)ASEAN average 4 �2.142 2 1978 1988 �4.436 (0.2, 0.4)SAARC countriesAfghanistan 4 �0.501 1 1982 1991 �4.600 (0.4, 0.6)Bangladesh 0 �2.815 1 1981 1993 �4.609 (0.2, 0.6)Bhutan 0 �3.167 2 1979 2000 �4.136 (0.2, 0.8)India 4 1.469 3 1984 1998 �3.679 (0.4, 0.8)Maldives 3 �2.530 1 1980 2001 �3.517 (0.2, 0.8)Nepal 4 �2.244 2 1982 1997 �3.560 (0.4, 0.8)Pakistan 0 �1.285 1 1982 1998 �3.259 (0.4, 0.8)Sri Lanka 4 �1.939 2 1981 2002 �3.873 (0.2, 0.8)SAARC average 0 �2.870 1 1979 1995 �3.004 (0.2, 0.6)

Critical values for Lee and Strazicich (2003)0.4 0.6 0.8

Y 10% 5% 1% 10% 5% 1% 10% 5% 1%

0.2 �5.27 �5.59 �6.16 �5.32 �5.74 �6.41 �5.33 �5.71 �6.330.4 – – – �5.31 �5.67 �6.45 �5.32 �5.65 �6.420.6 – – – – – – �5.32 �5.73 �6.32

Note: TB is the estimated break points. Critical values in the lower panel of Table 2 are from Lee and Strazicich(2003). Critical values for ADF test obtained from MacKinnon (1996) are �4.03, �3.44 and �3.15 at the 10%,5% and 1% levels of significance, respectively, while the corresponding critical values for the Lee and Strazicich(2004) one-break tests are �5.05, �4.50 and �4.18, respectively.

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59% of the structural breaks are within the late 1970s and early 1980s, which are associ-

ated with recession in which most developed countries experienced severe global eco-

nomic downturn, and developing countries including those in the ASEAN region

witnessed commodities demand downturn. An approximate 24% of the structural breaks

were in the late 1990s, a period corresponding to the Asian financial crisis of 1997 and

the following recovery phase.

The findings for SAARC countries are reported in the lower panel of Table 3. The

results for the ADF test indicate the existence of the unit root for the SAARC countries.

However, the Lee and Strazicich test shows the existence of unit root for all SAARC

countries with the exception of Bhutan (at 10%). Overall, the findings are in contrast with

Lim and Mcaleer (2004), but confirm the assertion of Jayanthakumaran and Lee (2008,

2013) who indicated that stochastic convergence is present in most ASEAN countries,

but non-existent in SAARC countries. With the exception of Afghanistan, two structural

breaks are recorded for all the countries. More than 43% of the structural breaks were in

the late 1970s and early 1980s, a period coinciding with world oil crises and their after-

math effects on several countries, including South Asian countries.

In Table 4, b-convergence results of Brunei, Malaysia, Philippines, Singapore, Vietnam

and Bhutan are presented.6 These countries were established as stochastically convergent,

using the regional average. Findings show that these countries do not only produce signifi-

cant signs but also opposite signs as required to fulfil the b-convergence. Therefore, five

ASEAN nations – Brunei, Malaysia, Philippines, Singapore and Vietnam – conditionally

Table 3. Unit root tests of the difference income series.

ADF Lee and Strazicich test

Country k t-stat k TB1 TB2 t-stat Break point(s)

ASEAN countriesBrunei 0 �2.217 3 1978 1999 �5.757�� (0.2, 0.8)Cambodia 3 �2.789 3 1979 1993 �3.939 (0.2, 0.6)Indonesia 4 �1.575 2 1978 1996 �3.750 (0.2, 0.6)Laos 4 �2.595 1 1982 1997 �3.968 (0.4, 0.8)Malaysia 4 �0.783 3 1976 1994 �6.211�� (0.2, 0.6)Philippines 4 �2.138 3 1980 – �4.451� (0.2)Singapore 4 �0.663 3 1985 1999 �6.120�� (0.4, 0.8)Thailand 0 �1.161 3 1978 1995 �4.005 (0.2, 0.6)Vietnam 0 �3.735�� 1 1976 1982 –6.246��� (0.2, 0.4)

SAARC countriesAfghanistan 4 �0.638 1 1991 – �3.231 (0.6)Bangladesh 1 �2.190 2 1975 1984 �5.042 (0.2, 0.4)Bhutan 1 �2.332 1 1985 2003 �5.338� (0.4, 0.8)India 4 �0.063 2 1981 2000 �4.285 (0.4, 0.8)Maldives 3 �0.862 1 1982 2001 �3.994 (0.4, 0.8)Nepal 1 �1.815 1 1979 1999 �3.402 (0.2, 0.8)Pakistan 0 �2.035 0 1982 2001 �3.315 (0.4, 0.8)Sri Lanka 4 �2.686 4 1985 1999 �4.821 (0.4, 0.8)

Note: TB is the estimated break points. �, �� and ��� imply 1%, 5% and 10% levels of significance. Critical valuesfor Lee and Strazicich (2003) are reported in the lower panel of Table 2. Critical values for ADF test obtainedfrom MacKinnon (1996) are �4.03, �3.44 and �3.15 at the 1%, 5% and 10% levels of significance, respec-tively, while the corresponding critical values for the Lee and Strazicich (2004) one-break tests are �5.05,�4.50and �4.18, respectively.

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converge to the ASEAN’s average, while Bhutan is the only country that conditionally con-

verges to the SAARC’s average. The foregoing results appear to show some degree of con-

vergence in ASEAN economies. Since Bhutan is the single country that satisfies the

convergence criteria, this is an evidence of divergence in SAARC countries. These findings

confirm the findings of Chowdhury (2004, 2005) and Ismail (2008), but contrast the obser-

vations of Lee et al. (2005).

The lack of convergence among the SAARC countries should come as no surprise.

Despite the impressive success of India and the series of proposals to integrate the region,

South Asia as a whole is plagued by extreme poverty, immense income disparity and fun-

damental problem of infrastructure, energy and the environment. Several reasons are

responsible for the lack of convergence in the SAARC region. First, the uncertain rela-

tions and frictions between the two dominant powers in SAARC have prevented the bloc

from achieving its full potential of regional cooperation. While the ASEAN countries

have been able to resolve most of their political differences and concentrate on economic

cooperation, SAARC is still beset with conspicuous political and economic tensions. Sec-

ond, many SAARC countries prefer to pursue self-interest agenda at the cost of regional

economic cooperation. Third, there is a lot of heterogeneity in the structural transforma-

tion processes followed by SAARC countries (Bah, 2009; Jayanthakumaran & Lee, 2013;

Thapar, 2006).

7. Conclusion

The verification of per capita income convergence is not only a means of assessing the

validity of Solow growth model, but also of evaluating the success of economic integra-

tion efforts. This paper appraises the existence of convergence for ASEAN and SAARC

countries. In this study, we examine the stochastic convergence of income for 9 (out of

10 states) ASEAN and all (8) SAARC countries for the period 1970–2009. The contribu-

tions of this exercise include the application of Lee and Strazicich’s (2003, 2004) unit

root test procedures, the examination of the original income series before embarking on

the investigation of the difference series’ stationarity properties, and the inclusion of

more countries in our sample. The findings illustrate Brunei, Malaysia, Philippines, Sin-

gapore and Vietnam as having stochastic convergence towards the ASEAN’s average.

These countries also fulfil the sufficient condition criteria, implying the existence of con-

vergence in the ASEAN countries. For SAARC countries, it is observed that Bhutan

Table 4. b-convergence for ASEAN and SAARC countries.

Intercept and trend

Country x b

Brunei 2.126 �0.025Malaysia �1.437 0.006Philippines �1.463 0.003Singapore �0.206 0.017Vietnam �2.542 0.042Bhutan �0.076 0.003

Note: The Newey–West estimator is applied to correct for possible serial correla-tion and heteroscedasticity.

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singly shows stochastic convergence towards the SAARC’s average and also fulfils suffi-

cient condition criteria. This indicates a lack of convergence among SAARC countries as

observed earlier by Chowdhury (2004). Evidently, these results generally point out that

while convergence exists within the ASEAN countries, there is virtually no convergence

of income in the SAARC countries.

For the South Asian states to experience real convergence, it is suggested that the

political differences and lack of trusts between its members, especially between its two

largest economies, must be resolved. In other words, SAARC members have to tackle

contentious issues to reduce mistrust so as to establish an atmosphere conducive for coop-

eration and growth. These actions were undertaken by ASEAN countries in the 1970s and

1980s. Independent and sometimes self-interest bilateral dealings by member states are

mostly inimical in projecting SAARC as a united and effective entity and, as a result,

should be shun. If SAARC has to become successful and to emerge as a meaningful

regional bloc like ASEAN, some asymmetric initiatives, bold and decisive, by India are

encouraged (Jayaraman & Choong, 2012). Numerous structural breaks identified in this

study are coincidental with recession periods.

The study is not without its limitations. Quah (1993) and Friedman (1992) have

argued that convergence should be evaluated directly by investigating the variance of out-

put across countries i.e. sigma (s) convergence, as against evaluating convergence indi-

rectly through the b-convergence, which is a necessary, but not sufficient, condition for

(s) convergence. Our focus has been on b-convergence; for a better understanding of con-

vergence dynamics, future studies may investigate the nature of sigma (s) convergence in

the region. The likelihood of multiple structural breaks that might have existed during the

covered period has been overlooked by the current exercise and may qualify our findings

(see Kapetanios, 2005). With the use of structural break models, we have assumed that

the business cycles (movements between the periods of expansion and recessions of the

GDP) are instantaneous. However, GDP typically follows a cyclical behaviour, which is

gradual in nature and therefore can only be adequately represented in a non-linear func-

tional form (Beechey & €Osterholm, 2008). The methodology adopted in this paper to link

economic integration and income convergence is not exhaustive. There are better proce-

dures to adequately capture the relationship (Jayanthakumaran & Lee, 2008).

Notes

1. Any evidence for the existence of either unconditional (absolute) convergence or conditionalconvergence is an indication of b-convergence of output across countries. Another form of con-vergence is the sigma (s) convergence, which focuses on the dispersion of cross-country outputover time. According to Quah (1993) and Friedman (1992), convergence should be evaluateddirectly by investigating the variance of output across countries, as against evaluating conver-gence indirectly through the sign of b. Therefore, b-convergence is a necessary but not suffi-cient condition ofs-convergence. Despite the highlighted drawback, b-convergence continuesto enjoy most attention of convergence papers as it provides information regarding structuralparameters of growth models, whereas s-convergence usually does not provide such informa-tion (Islam, 2003).

2. Closely related to conditional convergence is the club convergence. However, it is not easy toempirically distinguish between the two concepts (Durlauf & Quah, 1999; Islam, 2003).

3. The arrangement was to ensure that all members provide duty-free access; exclusive tariff pref-erences or deeper tariff preferences for the export; the removal of non-tariff barriers; and theremoval, where appropriate, of para-tariff barriers of the goods generating from the least devel-oped member states.

4. There are specifications with break(s) in level(s) only. Sen (2003a) argued that specificationwhich provides for both breaks is better than specification with only break(s) in level(s). Sen

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(2003b) used Monte Carlo simulations to validate the superiority of specifications that providebreak(s) for both level(s) and trend(s).

5. To decide the lag length of k we apply the process suggested by Ng and Perron (1995). Begin-ning with an upper bound kmax on k, k ¼ kmax is selected if the existing lag is significant. If not,k is reduced by a unit the lag is significant. If none of the lags are significant, then k ¼ 0. In theempirical section, we set kmax ¼ 4 and employ the 10% value of the asymptotic normal distribu-tion, 1.645, to evaluate the significance of the last lag.

6. We report the b-convergence results of countries with stochastic convergence only.

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