Determinants of Intra-ASEAN Migration - IA de Investigación especializada en el MIT

Determinants of Intra-ASEAN Migration
∗
MICHELE TUCCIO

International labor mobility in Southeast Asia has risen drastically in recent
decades and is expected to continue increasing with the establishment of the
Association of Southeast Asian Nations (ASEAN) Economic Community in
2015. This paper looks at the determinants of the movement of workers and
ﬁnds three structural factors that will likely drive further intra-ASEAN migration
in the coming years: (i) demographic transition, (ii) large income differentials
between economies, y (iii) the porosity of borders. A microfounded gravity
model is estimated in order to empirically analyze the main determinants of intra-
ASEAN migration in the period 1960–2000. Results suggest that the movement
of migrants between Southeast Asian economies has mostly been driven by
higher wages and migrant social networks in destination economies, así como
natural disasters in origin economies.

Palabras clave: ASEAN, determinants, international migration, push and pull factors
JEL codes: F22, J61, O15, 053

I. Introducción

En décadas recientes, international labor mobility has played a prominent role
in shaping the socioeconomic landscape of East Asian economies. Desde el
1980s, high-performing economies in the Association of Southeast Asian Nations
(ASEAN) have attracted a growing diaspora of foreign workers from neighboring
economies at earlier stages of their development transition (Athukorala 2006).
Intra-ASEAN migration skyrocketed from 1.5 million to 6.5 million migrants
entre 1990 y 2013, representing almost 70% of ASEAN’s total migration
at the end of the review period (ILO 2014).

The magnitude of intra-ASEAN migration is expected to increase as the
ASEAN Economic Community, which was launched in 2015, seeks not only a more
integrated regional economic strategy, but also the free mobility of professionals
and skilled workers within the region. As ASEAN member states enter this new
integration era from very different economic starting points, the freer ﬂow of goods
and capital is likely to accelerate the movement of low-skilled workers. Firms
in higher-income economies with better access to infrastructure will raise their
competitiveness vis-`a-vis producers in lower-income economies, thereby increasing

∗Michele Tuccio: Economics Department, University of Southampton. Correo electrónico: m.tuccio@soton.ac.uk. The author
would like to thank Ahsan Butt for his excellent research assistance and Mauro Testaverde, the managing editor, y
anonymous referees for helpful comments. The usual disclaimer applies.

Asian Development Review, volumen. 34, No. 1, páginas. 144–166

C(cid:3) 2017 Asian Development Bank
and Asian Development Bank Institute

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DETERMINANTS OF INTRA-ASEAN MIGRATION 145

Cifra 1. Share of Individuals Who Identify as Citizens of Their Country of Origin and
as Citizens of the World

Fuente: World Values Survey. 2014. “World Value Survey Wave 5 and Wave 6.” http://www.worldvaluessurvey.org

the beneﬁts of migration to such markets (Martin and Abella 2014). Además,
economic differentiation across the region is progressively manifested in a mix of
skill shortages and surpluses among neighboring economies, which increases the
economic beneﬁts of international mobility (Manning and Sidorenko 2007).1

The rise in international migration in East Asia also reﬂects an increasing
trend in internationalization and cosmopolitanism, with more and more people
identifying as citizens of the world with global rather than national ties (Nejatbakhsh
2014). Recent data from the World Values Survey suggest that the share of people
who identify as citizens of the world has almost converged with the proportion of
individuals who see themselves as citizens of their country of origin (Cifra 1).2
Among those ASEAN economies participating in the survey, a remarkable 89% de
the population on average expressed that they considered themselves to be citizens
del mundo, a ﬁgure that reached as high as 96% y 97% of respondents in the
Philippines and Malaysia, respectivamente.

This growing sense of multiculturalism and cosmopolitanism within ASEAN
is reﬂected in the increasing desire to migrate that has been observed in recent
years at the global level. Clemenes (2011) found that over 40% of the adults in the

1A predecessor of the ASEAN Economic Community is the 2002 ASEAN Tourism Agreement, cual,
among other things, introduced visa-free travel between ASEAN member states (Wong, Mistilis, and Dwyer 2011).
This policy has led to the increased movement of workers across ASEAN economies. Facilitated by the removal of
restrictions on tourist travel, workers have often overstayed in destination economies while working in the informal
economía.

2Statistics provided in this paper are available for either the full set or selected subsets of ASEAN economies

included in each database.

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146 ASIAN DEVELOPMENT REVIEW

Cifra 2. Desired Migration Rates of College-Educated and Less-Educated Individuals
by Economy of Origin

Lao PDR = Lao People’s Democratic Republic.
Fuente: Docquier, Frederic, Giovanni Peri, and Ilse Ruyssen. 2014. “The Cross-Economy Determinants of Potential
and Actual Migration.” International Migration Review 48 (s1): S37–S99.

world’s poorest quartile of economies would like to migrate if the opportunity arose.
Docquier, Peri, and Ruyssen (2014) used Gallup World Poll data to identify the
percentage of people in a number of economies willing to emigrate abroad if given
the chance. The results reported in Figure 2 suggest that on average more than 12%
of ASEAN’s population over the age of 25 years old wanted to migrate in 2010.3

Using aggregate data from Gallup surveys for 154 economies for 2010–2012,
Esipova, Rayo, and Pugliese (2011) construct a Potential Net Migration Index to
measure the number of adults who would like to move permanently out of an
economy minus the estimated number who say they would like to move into the
same economy as a proportion of the total adult population. They found that the only
ASEAN economies where the net ﬂows of migration would be positive are Singapore
and Malaysia. If all individuals who aspire to move either to or from Singapore
and Malaysia did so, their adult populations would increase by about 129% y
12%, respectivamente. The numbers of people aspiring to move in and out of Thailand
would roughly balance each other out, while for the remaining ASEAN economies,
unimpeded international migration would likely reduce the adult population. En
particular, if all individuals wishing to migrate in and out of an economy were able

3There is, sin embargo, great heterogeneity across economies and education levels. College-educated individuals
are twice as likely to aspire to emigrate because of the (eventual) greater payoff of moving abroad. While Indonesians
and Thais have relatively lower aspirations to emigrate than those in other ASEAN economies, almost 40% de
high-skilled Cambodians and Filipinos are willing to engage in cross-border migration. In the case of the Philippines,
the desire to emigrate is highest among people aged 15–34 years old, residents of urban areas, and more educated
individuals (McKenzie, Theoharides, and Yang 2014).

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DETERMINANTS OF INTRA-ASEAN MIGRATION 147

to do so, the adult population would decline by about 31% in Cambodia, 14% en el
Philippines, 9% in the Lao People’s Democratic Republic (Lao PDR), y 5% cada
in Myanmar and Viet Nam (Esipova, Rayo, and Pugliese 2014).

What is behind these large (actual and potential) movements of people? Qué
are the determinants of international migration within ASEAN? There is need for
a better understanding of the drivers of intra-ASEAN migration as labor mobility
increasingly impacts Asian economies. This paper aims to tackle these critical
issues by reviewing the existing literature on international migration in ASEAN and
providing new insights through the analysis of data. Además, a microfounded
gravity model is borrowed from the trade literature and adapted to estimate the main
push and pull factors driving cross-border migration ﬂows.

Our ﬁndings suggest that large income and demographic differentials between
ASEAN economies are likely to continue sustaining high levels of labor mobility
in the years ahead. Además, the porous borders that separate ASEAN member
states might also contribute to boosting low-skilled, undocumented migration.

The remainder of the paper is structured as follows. Section II presents
the linkages between individual characteristics and migration decisions. A set
of structural factors that are likely to sustain intra-ASEAN migration ﬂows is
discussed in section III. Section IV introduces the speciﬁc characteristics of sending
and receiving economies as key determinants. A gravity model for migration is
introduced in section V and its econometric results are presented in section VI.
Section VII concludes.

II. Migration Decisions and Individual Characteristics

A migrant’s decision to move is inﬂuenced by both supply and demand
factores. Economic and noneconomic incentives shape the supply side of international
migration, encouraging individuals to engage in cross-border movements.
En cambio, the need of immigrants in the destination economy as well as the
immigration policies in place represent the demand side. An individual would
therefore choose to migrate if the expected utility of living abroad is greater than
the payoff of staying in the home economy (net of migration costs).

Individual characteristics, such as education and sex, inﬂuence both the supply
and demand sides of migration. Consider a representative individual h facing the
choice between staying in her home economy i or moving to a foreign economy j.
The differential between wages at destination (w j ) and wages at origin (Wisconsin ) would
be one of the main push factors affecting the probability of individual h to emigrate.
Similarmente, the unemployment rate at the destination affects the probability of ﬁnding
a job after migrating. Sin embargo, in both the origin and destination economies wages
and unemployment rates are a function of the individual skill level (sh) y género
(gh). Por eso, women and men, as well as low-skilled and high-skilled individuals,
have different propensities to migrate based on their personal characteristics.

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148 ASIAN DEVELOPMENT REVIEW

Labor markets in different destinations also need different types of foreign
workers. Por ejemplo, most destination economies have gender-segregated labor
markets, with migrant women concentrated in domestic and caregiving work and
men in construction, agricultura, and trade. Since the second half of the 20th century,
there has been an increasing trend of female migrants from economies such as the
Philippines, Indonesia, y (more recently) Myanmar to ASEAN’s fastest-growing
economies of Singapore and Malaysia (Cortes and Pan 2013). With regard to female
migration in the last few years, both sending and receiving economies have seen
shifting patterns due to changes in the balance of power between ASEAN member
estados. Destination economies often grant temporary visas for women to work as
domestic helpers because of the increasing number of women earning wages in
the formal sector (Yeoh, Huang, and Gonzales III 1999). The magnitude of these
ﬂows is massive. Por ejemplo, each year around 100,000 women emigrate from
the Philippines to work as domestic helpers and caregivers (Cortes and Pan 2013),
while in Singapore in 2000 there was one foreign maid in every eight households
(Yeoh, Huang, and Gonzales III 1999).

This paper uses several microlevel surveys from ASEAN economies
to estimate the proportion of women among current emigrants (Cifra 3).4
Curiosamente, more than half of all emigrants from Indonesia are female and
approximately half of all emigrants from Cambodia and the Philippines are women.
As argued by Lim and Oishi (1996), there are several distinctive features of the
East Asian economic landscape that can help explain the recent feminization of
migration ﬂows. Primero, the supply of East Asian female migrants has been very
ﬂexible relative to men in East Asia and women in other regions of the world.
East Asian women have responded rapidly to changing demand in foreign labor
markets, which is partly due to low levels of discriminatory gender norms and high
female labor force participation rates in their home economies. Segundo, ASEAN
economies have seen the rise of a large immigration industry that facilitates both
legal and undocumented female migration. Tercero, women, especially young women,
are more likely than men to rely on informal social networks and chain migration,
following their relatives or friends who are already employed abroad. The steady
enlargement of the diasporas of Cambodians, Filipinos, and Indonesians in host
economies has the effect of encouraging other women to follow.

In a similar way, the educational attainment of migrants can partly explain
bilateral international migration ﬂows. The positive or negative selection of migrants
es, on one hand, due to self-selection mechanisms, y, por otro lado, due to
skill-selective immigration policies in place in destination economies (Docquier and
Machado 2016). In a macro perspective, economies of origin frequently specialize

4These surveys include the Cambodia Socioeconomic Survey (2012), Indonesia Family Life Survey (2007),
Malaysia Labor Force Survey (2010), Philippines Labor Force Survey (Julio 2010), Thailand Socioeconomic Survey
(2009), and Viet Nam Household Living Standard Survey (2012).

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DETERMINANTS OF INTRA-ASEAN MIGRATION 149

Cifra 3. Share of Women among Current Working-Age Emigrants by Economy of Origin

Fuentes: Cambodia National Institute of Statistics. 2012. “Cambodia Socio-Economic Survey.” International Labour
Organization. http://www.ilo.org/surveydata/index.php/catalog/341; RAND. 2007. “Indonesia Family Life Survey
2007.” http://www.rand.org/labor/FLS/IFLS.html; Department of Statistics. 2010. “Labor Force Survey.” Government
of Malaysia. https://www.statistics.gov.my/index.php?r=column/ctheme&menu_id=U3VPMldoYUxzVzFaYmNk
WXZteGduZz09&bul_id=NHUxTlk1czVzMGYwS29mOEc5NUtOQT09; Philippines Statistical Authority. 2010.
“Labor Force Survey 2010.” https://psa.gov.ph/statistics/survey/labor-force/lfs/2010; National Statistical Ofﬁce. 2009.
“Thailand Household Socio-Economic Survey 2009.” Ministry of Information and Communications Technology.
http://catalog.ihsn.org/index.php/catalog/1486; General Statistics Ofﬁce. 2012. “Household Living Standard Survey
2012.” Government of Viet Nam. http://www.gso.gov.vn/default_en.aspx?tabid=483&idmid=4&ItemID=13888

in supplying migrants with a speciﬁc skill, while labor markets in host economies
often require different skills or levels of education. Por ejemplo, although Singapore
has typically adopted a two-pronged policy for less-skilled and professional migrant
workers, the government’s willingness to recruit high-skilled migrants has recently
resulted in a reduction in work permits for the less skilled and a corresponding
increase in the share of permits for foreign professionals (Yap 2014).

By looking at the differences in educational attainment between emigrants
and natives by economy of origin, Cifra 4 conﬁrms the heterogeneous skill patterns
of ASEAN emigrants.5 Almost two-thirds of migrants from the Philippines hold a
tertiary degree, while on average less than one-third of the general population is
a university graduate. This positive selection of migrants is in part due to the fact
that most Filipino workers migrate to Organisation for Economic Co-operation
and Development economies, which require higher educational levels, and in part
due to a speciﬁc government strategy. As discussed by Tullao, Conchada, y
Rivera (2014), the Government of the Philippines encourages university graduates

5In line with previous literature, we assume that migrants’ skills can be at least partially captured by their
level of educational attainment. Cross-economy and/or economy-level information on the real skill levels of workers
are currently not available for most economies. Among others, Beine, Bertoli, and Fern´andez-Huertas Moraga (2015)
and McKenzie and Rapoport (2010) adopt a similar approach and we refer to them for further discussion on the issue.

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150 ASIAN DEVELOPMENT REVIEW

Cifra 4. Share of Working-Age Population with a University Degree by Economy of Origin

to meet international standards by improving the quality of their education through
certiﬁcation measures, often in partnership with destination economies such as
Canada.

En cambio, Thailand resorts to labor immigration to meet industry needs,
especially for lower-skilled jobs (ADBI, ILO, and OECD 2014). This partly
explains why Cambodian emigrants, who typically migrate to Thailand, appear
to be negatively selected. Similarmente, despite a gradual improvement in educational
attainment in recent decades, Indonesian emigrants appear to be mostly unskilled
and employed in the agriculture, transportation, and housekeeping sectors (Kuncoro,
Damayanti, and Isfandiarni 2014).

III. Structural Determinants of Intra-ASEAN Migration

Although individual characteristics help us better understand international
migration ﬂows, not all individuals with certain characteristics decide to migrate;
and even among emigrants, not everybody chooses the same destination. Alguno
migration corridors are nearly empty while others experience large bidirectional
ﬂows. Typically, the major origin economies in ASEAN are Indonesia, Myanmar,
and Viet Nam, which all have relatively lower income levels. En cambio, Malasia,

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DETERMINANTS OF INTRA-ASEAN MIGRATION 151

Table 1a. Major Migration Corridors in ASEAN, 2000–2010

Rank Origin Economy Destination Economy Migration Flows

Indonesia
Malasia
Myanmar
Myanmar
Viet Nam
Tailandia
Viet Nam
Lao PDR
Indonesia
Viet Nam

Malasia
Singapur
Tailandia
Malasia
Cambodia
Cambodia
Malasia
Tailandia
Singapur
Tailandia

1
2
3
4
5
6
7
8
9
10
ASEAN = Association of Southeast Asian Nations, Lao PDR = Lao People’s
Democratic Republic.
¨Ozden, C¸ a˘glar et al. 2011. “Where on Earth Is Everybody? El
Fuente:
Evolution of Global Bilateral Migration 1960–2000.” The World Bank
Economic Review 25 (1): 12–56.

543,238
225,661
201,417
79,176
43,857
36,048
35,317
31,721
21,772
14,439

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Table 1b. Major Migration Diasporas in ASEAN, 2010

Rank Origin Economy Destination Economy Migration Stocks

Indonesia
Malasia
Myanmar
Viet Nam
Tailandia
Lao PDR
Myanmar
Viet Nam
Indonesia
Singapur

Malasia
Singapur
Tailandia
Cambodia
Cambodia
Tailandia
Malasia
Malasia
Singapur
Malasia

1
2
3
4
5
6
7
8
9
10
ASEAN = Association of Southeast Asian Nations, Lao PDR = Lao People’s
Democratic Republic.
Fuente: ¨Ozden, C¸ a˘glar et al. 2011. “Where on Earth Is Everybody? The Evolution
of Global Bilateral Migration 1960–2000.” The World Bank Economic Review
25 (1): 12–56.

1,316,973
842,899
637,383
148,516
122,071
100,380
99,718
93,215
81,324
61,993

Singapur, and Thailand have absorbed most intra-ASEAN migration in recent
años, given their need for workers to ﬁll fast-growing labor markets (Tables 1a
and 1b).6 According to Martin (2007), foreigners constituted about 5% of the Thai
workforce in 2007 and about 10% of the working-age population in Malaysia in 2010
(Del Carpio et al. 2015). At the top-end of the distribution lies Singapore, cual
represents an extreme case of labor markets in which one of every three employed
persons was a foreigner in 2014 (Ministry of Manpower 2015).

6Tables 1a and 1b are based on the World Bank’s Global Migration Database, which is a comprehensive
collection of data on the stock of international migrants by country of birth and citizenship, as enumerated by
population censuses, population registers, nationally representative surveys, and other ofﬁcial statistical sources. Por
definición, illegal migration is not fully taken into account in such a database. Por eso, important migration routes for
undocumented foreign workers may not be reported.

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152 ASIAN DEVELOPMENT REVIEW

In addition to individual characteristics, three main structural factors appear
to be driving labor migration in ASEAN: (i) the demographic transition underway in
most East Asian economies that affects the supply and demand of labor, producing
additional migration opportunities and challenges; (ii) income differentials between
economías, which eventually represent the greatest pull forces for migrants; (iii)
the penetrability of porous borders, which can explain the high prevalence of
undocumented migration in some ASEAN economies.

Much of East Asia’s economic expansion in recent decades is linked to the
region’s demographic changes (Bloom and Finlay 2009). Since the aftermath of the
Second World War, “Asia has exploited the catch-up potential with such enthusiasm
that it has produced one of the fastest and most dramatic demographic transitions
ever” (Bloom and Williamson 1998, 424). A sharp decline in child mortality rates
has been accompanied by an increase in life expectancy and a rapid decrease in total
fertility rates over the years. Como resultado, all ASEAN economies saw an increase
in the size of their working-age population between 1965 y 2010, which further
fueled already swift economic development.

We adopt a Shapley decomposition approach to quantify the extent to which
aggregate economic growth in ASEAN member states has been linked to changes
in the employment rate, productivity, and the demographic dividend over the last
2 décadas. This technique allows for describing changes in per capita value added
through the growth in each of its components (see Gutierrez et al. 2009 for a careful
explanation of the methodology).7 Using data from the ILO and the World Bank
for the period 1990–2010, we ﬁnd that demographic change accounted for almost
one-ﬁfth of total income growth in ASEAN member states over the last 2 décadas
(Cifra 5).8 In some economies, such as Singapore and Indonesia, the increase in
the share of the working-age population has been even more pronounced (Ahsan
et al. 2014).

Sin embargo, things are changing in East Asia. The favorable demographics
that have been contributing to rapid economic growth for the past 50 years are
quickly shifting. ASEAN’s population is becoming older as average life expectancy
increases and fertility rates decline, which will eventually lead to a contraction in
relative size of the working-age population. Projections for the next 3–4 decades
show labor forces in several economies shrinking dramatically, which will pose
important challenges to sustaining economic growth (ILO 2014). Además, el
dependent population in the future will mainly comprise the elderly, que lo hará

7Following the Shapley decomposition method, gross domestic product per capita y (aggregate value added
Y divided by the total population N) can be written as y = Y
A
norte , where E is total employment, A is the
norte
working-age population, and N is the total population. Such a relationship can be also written as ¯y = ¯ω + ¯e + ¯a,
where ¯ω refers to changes in output per worker, ¯e captures changes in the employed share of the working-age
población, and ¯a is the demographic change.

= Y
mi

mi
A

8Per capita value added comes from the World Bank’s World Development Indicators and its change has been
calculated as the growth rate between 1990 y 2010. Similarmente, the working-age population (World Development
Indicators) and the total number of employed people (ILOSTAT) are exploited to calculate changes over 2 décadas.

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DETERMINANTS OF INTRA-ASEAN MIGRATION 153

Cifra 5. Aggregate Productivity, Employment, and Demographic Proﬁle of Growth
in ASEAN, 1990–2010

A = working-age population, ASEAN = Association of Southeast Asian Nations, E = total employment, N = total
población, and Y = value added.
Fuente: Banco mundial. 2016. “World Development
-development-indicators

Indicators.” http://data.worldbank.org/data-catalog/world

increase the ﬁscal burden of member states and crowd out investments (Ahsan et al.
2014).

Al mismo tiempo, a critical heterogeneity exists among ASEAN economies.
The labor forces in Cambodia, Indonesia, the Lao PDR, and the Philippines will
be powered by expanding pools of youth through 2050 (Cifra 6). Singapur,
Tailandia, and Viet Nam are expected to have much greater dependency rates by
entonces, with an over-65 population that will reach almost one-third of Thailand’s total
population in 2050 (Cifra 7). Como se ha mencionado más arriba, the population aging process is
due to a mix of rising life expectancy and declining fertility rates. In the relatively
higher-income economies of the region such as Singapore and Thailand, the fertility
rates have fallen as low as 1.2 y 1.6, respectivamente, which represent some of the
lowest fertility rates in the world ( ¨Ozden and Testaverde 2015). Large imbalances
in the age composition of the population across economies are likely to produce
shortages of workers in certain economies and an abundance in other.

It appears that international migration within East Asia can serve as a relief
mechanism to address demographic challenges. Given the geographic proximity to
one another of economies with either older or younger populations, intra-ASEAN
migration can ameliorate labor shortages in economies such as Thailand and
Singapore while providing migrants from labor-abundant economies new job
opportunities abroad. En suma, demographic changes have been and will continue
to be one of the principal determinants of international migration in ASEAN.

The large income and wage differentials between economies are a second
structural factor behind the rise of intra-ASEAN migration (Banco mundial 2014). En

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154 ASIAN DEVELOPMENT REVIEW

Cifra 6. Share of Youth (0–14 Years) in the Total Population

Lao PDR = Lao People’s Democratic Republic.
Fuente: United Nations Department of Economic and Social Affairs. 2013. World Population Prospects: El 2012
Revision. Nueva York: United Nations.

Cifra 7. Share of Elderly (65+ Años) in the Total Population

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Lao PDR = Lao People’s Democratic Republic.
Fuente: United Nations Department of Economic and Social Affairs. 2013. World Population Prospects: El 2012
Revision. Nueva York: United Nations.

hecho, although the average gross domestic product (PIB) per capita in ASEAN was
just above $24,000 en 2014 (constant 2011 international dollars at purchasing power parity), there is a great deal of variability within the region, with average incomes DETERMINANTS OF INTRA-ASEAN MIGRATION 155 Cifra 8. Income Differentials across ASEAN Economies l D o w n o a d e d f r o m h t t p : / / directo . mi t . ASEAN = Association of Southeast Asian Nations, GDP = gross domestic product, Lao PDR = Lao People’s Democratic Republic, PPP = purchasing power parity. Fuente: Banco mundial. “World Development Indicators.” http://data.worldbank.org/data-catalog/world-development -indicators as low as $3,093 in Cambodia and as high as $78,958 in Singapore (ILO 2014). The contrast is also striking if we look at average monthly wages, which range from $119 (constant 2005 prices at purchasing power parity) in the Lao PDR to $3,547
in Singapore in 2013 (ILO 2014). Además, wages in Thailand are three times
higher than in Cambodia, while wages in Malaysia are approximately three and a
half times those in Indonesia.

Cifra 8 shows the differences in GDP per capita within ASEAN. El
relatively higher-income economies of Brunei Darussalam, Malasia, Singapur,
y Tailandia (dashed lines) are all labor-receiving economies, while the relatively
lower-income economies (solid lines) of Cambodia, Indonesia, the Lao PDR, el
Philippines, and Viet Nam are labor-sending economies. Since potential migrants
aim at maximizing their expected utility by moving abroad, they tend to move to
destinations where they can improve their income and wealth. Como consecuencia, el
large wage and unemployment differentials among ASEAN economies are likely to
sustain large intraregional migration ﬂows up to a point in the future when wages
and employment rates converge across economies.

A third factor unique to intra-ASEAN migration is the porosity of its borders
(Chia 2006). Facilitated by weak border controls, irregular migration has become
an important feature of ASEAN labor mobility (Pempel 2006). The archipelagic
structure of a portion of the region with dispersed maritime borders facilitates the
undocumented movement of people (Tan and Ramakrishna 2004). The length of
shared borders across remote mountainous areas makes it difﬁcult to control and

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156 ASIAN DEVELOPMENT REVIEW

limit the inﬂow of illegal labor in other parts of the region (Bain 1998). Además,
irregular migration not only refers to those trespassing across borders without the
required documents, but also includes those who overstay on tourist visas, estudiantes
engaged in employment, regular migrants continuing beyond the contract period,
and individuals trafﬁcked in the sex industry (Wickramasekera 2002).

Given its very nature, quantifying the extent of irregular migration is a hard
tarea. Sin embargo, available estimates suggest that between 500,000 y 750,000 ilegal
migrants were residing in Thailand in 2000, mostly from neighboring Cambodia, el
Lao PDR, and Myanmar. Indonesians and Filipinos represented the vast majority of
el 1 million illegal migrants estimated to live in Malaysia in 1998 (Manning 2002).
Históricamente, irregular migration has been ﬁrstly tolerated and then sanctioned
by ASEAN governments (Battistella and Asis 1998). Despite the measures put in
lugar, illegal migration continues to be a recurrent feature of ASEAN economies.
An emergency ASEAN ministerial meeting was assembled in 2015 to strengthen
cooperation in the ﬁght against irregular migration and human trafﬁcking (ASEAN
2015).

Among the reasons for the pervasive presence of undocumented migrants
in ASEAN, restrictive immigration policies that are often in contrast with labor
market needs in rapidly expanding destination economies play a key role (Abella
2000). Al mismo tiempo, extreme poverty and unemployment can push individuals to
look for opportunities elsewhere. Political instability and repressive policies toward
ethnic minorities can also encourage mobility (Wickramasekera 2002). Además,
the high costs of legal recruitment and the restrictive terms and conditions of
employment contracts in some economies such as Malaysia have led to resistance
among both employers and workers against the legal employment process for foreign
workers (Kassim 2002).

IV. The Role of Speciﬁc Features of Sending and Receiving Economies

The unique characteristics of both origin and destination economies are also
important drivers of international migration in ASEAN. Among the features of origin
economies that may lead individuals to engage in cross-border migration, political
instability, and civil conﬂicts can partially explain emigration from Myanmar in
recent decades. Ongoing developments are expected to shape future migration
patrones, with Myanmar’s political transition potentially leading to the eventual
reversal of some of these previous ﬂows (Banco mundial 2012).

Natural disasters and weather instabilities are also particularly relevant in the
Asian context. Asia was affected by nearly half of all natural disasters between 1990
y 1999, accounting for up to 70% of all lives lost (United Nations International
Strategy for Disaster Reduction 2004). Since the start of systematic reporting of
disasters in the 1960s, the number of calamities reported worldwide has been steadily
growing, while Asia still appears to be the continent most affected by natural

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DETERMINANTS OF INTRA-ASEAN MIGRATION 157

Figure 9a. Incidence of Natural Disasters by Continent, 1960–2014

Fuente: Centre for Research on the Epidemiology of Disasters. “EM-DAT: International Disaster Database.”
http://www.emdat.be/database

Figure 9b. Incidence of Natural Disasters in ASEAN, 1960–2014

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ASEAN = Association of Southeast Asian Nations.
Fuente: Centre for Research on the Epidemiology of Disasters. “EM-DAT: International Disaster Database.”
http://www.emdat.be/database

disasters—such as earthquakes, ﬂoods, volcanic eruptions, and hurricanes—with
almost 200 disasters in 2000 solo (Figure 9a). Indonesia, the Philippines, Tailandia,
and Viet Nam appear to be the most frequently affected economies, while Brunei
Darussalam, Cambodia, Malasia, and Singapore are the least affected (Figure 9b).
Natural disasters can force people out of their homes before or immediately
after an event due to the unforeseeable nature of most calamities. The impacts
on the socioeconomic conditions of forced migrants often create a vicious circle,
with poorer individuals being less able to cope with a disaster and ending up

158 ASIAN DEVELOPMENT REVIEW

more vulnerable than before. Asian economies also suffer disproportionately from
climate instability, while the persistence of natural disasters in certain areas can
impede development given the continuous need to overcome the impacts of such
calamities (Naik, Stigter, and Laczko 2007).

Por último, migration costs need to be taken into account in the analysis of the
main determinants of intra-ASEAN migration. The relative gain a migrant achieves
by moving abroad also depends on the physical and social distance between her
home economy and the destination economy (Fafchamps and Shilpi 2013). Mayor que
geographic distance between the two economies implies higher travel costs for the
initial move as well as for visits back home. Además, the further away the origin
and destination economies are from one another, the more costly it is to acquire
information ex ante about the foreign labor market (Mayda 2010).

Por esta razón, social networks play a key role in lowering migration costs
and facilitating ﬂows by correcting for the asymmetry of information that potential
migrants face (Munshi 2003, Beaman 2012). En décadas recientes, international
migrants in Asia have relied on their networks of social capital abroad in choosing
destinations (Hugo 2005). Social networks not only ease mobility but also help
migrants in adjusting to and integrating with socioeconomic conditions in the
receiving economy.

V. Gravity Model Analysis of Intra-ASEAN Migration

A. Metodología

As discussed in the previous sections, the choice of the optimal location
for migration is given by the comparison between the utility associated with each
ubicación: an individual will choose to live where the payoff is greatest, net of
any migration costs. The bilateral migration rate between two economies is thus a
function of the following:

migration rate = f (income differential, migration costs)

En particular, migration ﬂows are driven by the income and wage differentials
between the economy of destination j and the economy of origin i, (w j,t /wi,t ),
as well as the physical distance between the two economies (disti j ). Whether the
economies share a common border (conti j ) also inﬂuences the likelihood of bilateral
migration, especially in ASEAN where borders are porous and less monitored.
Finalmente, social networks, proxied by the lagged stock of migrants from economy i
in economy j (networki j,t−1), also affect mobility by lowering the monetary and
psychological costs of migrating.

To empirically estimate the impact of the aforementioned drivers on bilateral
migration ﬂows within ASEAN, we adopt a gravity model approach. Borrowed from

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DETERMINANTS OF INTRA-ASEAN MIGRATION 159

the trade literature, the gravity model speciﬁes trade as a positive function of the
attractive mass of two economies and a negative function of distance between them
(Lewer and Van der Berg 2008). Since migration is also driven by push and pull
factores, we adjust this framework in order to encompass migration ﬂows.

Following Beine and Parsons (2015), our dependent variable is the number of
migrants from economy i in economy j as a ratio of natives from i who have chosen
not to migrate. Formalmente, let Ni,t be the native population in economy i at time t.
At each point in time, natives choose their optimal location among a set of possible
foreign destinations and their own home economy. Let Ni j,t be the size of the native
population of economy i moving to the optimal destination j and let Nii,t be the
size of the native population of economy i deciding to stay in their home economy
i. The bilateral migration rate between i and j is thus given by Ni j,t /Nii,t .

Datos

In order to compute Ni j,t , we exploit the World Bank’s Global Migration
Database, which includes bilateral migration data for 226 economies over the period
1960–2000 (see ¨Ozden et al. 2011 for a detailed description of the data set). Desde
information is provided on migration stocks for each decade, we compute migration
ﬂows from origin economy i to destination economy j as the difference in migration
stocks between two contiguous decades:9

Ni j,t = stocki j,t − stocki j,t−1

To recover Nii,t (the native population choosing not to migrate), we subtract
from the United Nations’ World Population Prospects data the total number of
immigrants in origin economy i, which in turn is calculated from the migration data
como

j
j=1 stock ji,t . Our main speciﬁcation will therefore be
(cid:4)

(cid:2)

(cid:4)

(cid:3)

= α0 + α1 ln

+ α2 ln

disti j

+ α3conti j + α4 ln

(cid:5)

(cid:6)

(cid:5)
networki j,t−1

(cid:6)

(cid:3)

Ni j,t
Nii,t

w j,t
Wisconsin,t

+ γi + γ j + γt + εi j,t

where time-invariant characteristics of the origin and destination economies are
captured by γi and γ j , respectivamente, and time ﬁxed effects are γt . Income differential
is measured as the ratio between destination and origin economy per capita GDP.

9This second-best procedure will unavoidably result in negative ﬂows as well (migration stocks declining
con el tiempo). This may be due to migrants returning home, moving to a third economy, or dying. De este modo, in constructing
this measure, we assume that both deaths and return migration are small relative to net ﬂows and we set negative
ﬂows equal to 0 (Beine, Bertoli, and Fern´andez-Huertas Moraga 2015). As argued by Beine, Docquier, and ¨Ozden
(2011), even though this procedure may be suboptimal, it provides a fairly accurate picture of migratory movements
during the period and it has become the standard approach in cross-economy studies on international migration (ver
Bertoli and Fern´andez-Huertas Moraga 2015, Beine and Parsons 2015, and Maurel and Tuccio 2016, among others).

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160 ASIAN DEVELOPMENT REVIEW

Data are taken from the version 8.1 of the Penn World Table (Feenstra, Inklaar, y
Timmer 2015).10 Distance (bilateral distance between the largest city in each of
the two economies weighted by the population share of each city in the economy’s
total population) and contiguity (a dummy variable equal to 1 if the origin and
destination economies share a common border) are taken from the CEPII’s Gravity
Dataset (Head, Mayer, and Ries 2010). Social networks are included to account for
diaspora effects and they are measured as the stock of migrants from origin economy
i in destination economy j at the beginning of the decade (data from the World Bank’s
Global Migration Database).

(cid:6)

Además, we augment the above speciﬁcation by including the share of
(cid:5)
in order to capture demographic
economy i’s population aged 15–29 years
youthi,t
push factors in the origin economy (Mayda 2010). A larger share of youth at the origin
implies more new entrants in the labor market at time t, thereby reducing employment
opportunities at home and increasing the payoff of moving abroad in search of
employment. The youth bulge is particularly relevant for ASEAN economies such
as Indonesia and Myanmar where almost one in every three individuals was between
the ages of 15 y 29 years old in 2000. Annual data on the youth population comes
from the United Nations’ World Population Prospects data. We compute decennial
intervals in order to match the time structure of the World Bank’s Global Migration
Database.

Because of the importance of calamities in driving migration ﬂows in ASEAN,
we also include the aggregate number of natural disasters (p.ej., earthquakes,
tsunamis, hurricanes, and volcanic eruptions) by origin economy in each decade
as an additional determinant. Information derives from the EM-DAT Database
produced by the Centre for Research on the Epidemiology of Disasters. Finalmente,
we introduce interaction terms between a dummy variable (with a value of 1 if the
economy of origin i is an ASEAN member state) and each migration determinant
in order to test whether ASEAN economies behave differently than the rest of the
world.

After putting together information from all of the aforementioned sources,
we come up with a data set covering 157 economies for the period 1960–2000. Todo
ASEAN member states are included in the analysis except for Myanmar.11

VI. Econometric Results

Results are presented in Table 2. Columna 1 shows the na¨ıve estimation
where the dependent variable is the bilateral migration rate as constructed above

10Although unemployment rates in both origin and destination economies are a major determinant in
cross-economy migration, a lack of historical data for the entire sample of economies does not allow the inclusion of
unemployment among the regressors.

11The lack of available data for Myanmar is a problem that needs to be addressed by policy makers.

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DETERMINANTS OF INTRA-ASEAN MIGRATION 161

Mesa 2. Gravity Model of International Migration, 1960–2000

Income differential

Income differential × ASEAN

Distance

Distance × ASEAN

Contiguity

Contiguity × ASEAN

Social networks

Social networks × ASEAN

Share of youth at origin

Share of youth at origin × ASEAN

Natural disasters at origin

Natural disasters at origin × ASEAN

ASEAN

(1)
0.044
(2.68)∗∗∗
0.162
(5.62)∗∗∗
−0.470
(26.51)∗∗∗
0.028
(0.45)
0.454
(3.16)∗∗∗
0.000
(0.00)
0.296
(44.55)∗∗∗
0.051
(2.48)∗∗

(2)
0.044
(2.68)∗∗∗
0.161
(5.60)∗∗∗
−0.470
(26.51)∗∗∗
0.030
(0.48)
0.454
(3.16)∗∗∗
−0.005
(0.01)
0.296
(44.54)∗∗∗
0.052
(2.54)∗∗
0.027
(0.23)
0.448
(1.38)

−2.221
(3.75)∗∗∗
70,926

−1.639
(2.16)∗∗
70,926

(3)
0.105
(3.94)∗∗∗
0.276
(6.45)∗∗∗
−0.504
(19.59)∗∗∗
−0.181
(2.02)∗∗
0.166
(0.87)
0.997
(1.57)
0.274
(29.88)∗∗∗
0.029
(1.15)
−0.339
(1.32)
0.612
(0.87)
0.214
(3.53)∗∗∗
0.282
(2.38)∗∗
−0.123
(0.10)
34,674

norte
ASEAN = Association of Southeast Asian Nations.
Nota: ∗∗∗, ∗∗, and ∗ represent 1%, 5%, y 10% signiﬁcance levels, respectivamente.
Fuentes: Migration data come from ¨Ozden, C¸ a˘glar et al. 2011. “Where on Earth
Is Everybody? The Evolution of Global Bilateral Migration 1960–2000.” The
World Bank Economic Review 25 (1): 12–56; gross domestic product per capita
data come from Feenstra, Robert C., Robert Inklaar, and Marcel P. Timmer.
2015. “The Next Generation of the Penn World Table.” The American Economic
Revisar 105 (10): 3150–82; distance and common border dummies come from
Head, Keith, Thierry Mayer, and John Ries. 2010. “The Erosion of Colonial Trade
Linkages After Independence.” Journal of International Economics 81 (1): 1–14;
population data come from United Nations Department of Economic and Social
Affairs. 2013. World Population Prospects: El 2012 Revision. Nueva York: United
Nations; and information on natural disasters is taken from Centre for Research
on the Epidemiology of Disasters. “EM-DAT: International Disaster Database.”
http://www.emdat.be/database

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(cid:7)

(cid:8)(cid:8)

Ni j,t
Nii,t

. Income differentials appear to be signiﬁcantly and positively affecting
international migration, meaning that larger differentials between GDP per capita
in origin and destination economies attract more migrants. This relationship is
particularly important for ASEAN’s origin economies, whose coefﬁcient is almost
5 times larger than the coefﬁcient for the rest of the world.

162 ASIAN DEVELOPMENT REVIEW

Physical distance between two economies plays a signiﬁcant negative role
in shaping migration ﬂows, increasing migration costs and information asymmetry.
Por otro lado, sharing a common border is positively correlated with greater
migration rates, although this effect does not seem to be particularly different
for ASEAN economies than for the rest of the world. Finalmente, social networks
in destination economies have the expected positive and signiﬁcant sign since they
reduce migration costs and encourage mobility. También, as anticipated, this effect is
particularly relevant for ASEAN migrants, who have been shown to rely heavily on
relatives and friends abroad when engaging in the migration process (Hugo 2005).
Contrary to expectations, the population share of youth (15–29 years old) en
the origin economy did not appear to have any effect on migration rates between
1960 y 2000 (Columna 2). Perhaps this relationship is stronger today than it was in
the past as the youth bulge was previously less of an issue given more widespread
labor opportunities prior to the global ﬁnancial crisis. Por otro lado, natural
disasters in origin economies appear to have a signiﬁcant effect as a push factor of
emigrants abroad. The effect is particularly important in the ASEAN economies,
overall twice as large (Columna 3).

En suma, this simple empirical analysis using bilateral migration data conﬁrms
that income differentials between origin and destination economies are a key
driver of international migration in ASEAN economies. Similarmente, migration costs
appear to matter as well, with higher costs reducing the likelihood of engaging in
cross-border movements. Finalmente, as expected, natural disasters are an important
push factor globally and especially in ASEAN.

VII. Conclusions

This paper identiﬁed the main determinants of intraregional migration in
ASEAN. The ﬁndings suggest that migration ﬂows are likely to increase in the next
few decades as demographic changes bring imbalances across economies that will
require mobility in order to ﬁll the consequent labor shortages. Además, grande
income and wage differentials across economies will continue to play an important
role in attracting migrants as long as income inequalities persist across the region. On
the other side, porous borders will continue to encourage low-skilled, poor workers
to migrate toward higher-income economies.

In order to achieve ASEAN’s objective of creating a more thriving and
inclusive community, it is necessary for governments to take measures to liberalize
and regularize intraregional labor mobility. As stressed by Martin and Abella (2014),
the challenge will be for ASEAN economies to open their doors to low-skilled
migrants. This would reduce the magnitude of irregular cross-border movements
and eliminate the cost advantages enjoyed by those ﬁrms who illegally employ such
migrants over competing employers who do not.

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DETERMINANTS OF INTRA-ASEAN MIGRATION 163

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