Migrant Networks and Trade: The Vietnamese Boat People as a

Transcription

Migrant Networks and Trade:
The Vietnamese Boat People as a Natural Experiment
Christopher Parsons
∗
Pierre-Louis Vézina
†
September 17, 2013
Preliminary - Comments welcome!
Abstract
The role of migrant networks in reducing the information frictions that inhibit
international trade has been discussed extensively. Yet the causality from migration
to trade creation has not been conclusively established. This paper provides cogent
evidence of the causal pro-trade effect of migrants by drawing upon the exodus of
the Vietnamese Boat People to the US. This episode represents an ideal natural
experiment as it combines a large immigration shock with a concurrent trade
embargo in tandem with an exogenous allocation of Vietnamese migrants across
US States. Following the lifting of the trade embargo in 1994, exports to Vietnam
were higher and more diversified from those US States with larger Vietnamese
populations, itself the result of larger refugee inflows 20 years earlier. A 10%
increase in a Vietnamese State population is associated with a ratio of export to
Vietnam over GDP that is 1.9% higher. Importantly, we find low-skilled migrants
to be as instrumental as the high-skilled in fostering trade.
JEL classification: F13
Keywords: Migrant Networks, Vietnam, Natural Experiment.
∗
Department of International Development, University of Oxford, Queen Elizabeth House, 3 Mansfield
Road, Oxford OX1 3TB, United Kingdom. E-mail: [email protected].
†
Department of Economics, University of Oxford, Manor Road Building, Manor Road, Oxford OX1
3UQ, United Kingdom. E-mail: [email protected]
1
Introduction
Despite decades of globalization, a myriad of trade costs, both formal and informal,
still inhibit international trade. Recent theoretical and empirical advances have singled
out information frictions as important factors shaping the world trade network and
highlighted that policies that reduce information frictions differ substantially from policies
that reduce traditional trade costs (e.g. Chaney (2011); Allen (2012). In this paper we
wish to bring back attention to the role of immigration policy in lowering such trade
frictions and argue that immigrants are a key component in realizing gains from trade.
The role of migrant networks in shaping world trade patterns has been extensively
studied in the last two decades. The empirical literature draws heavily upon the work of
Gould (1994), Greif (1993) and Rauch and Trindade (2002) who argued that immigrants’
contacts and knowledge of home-country markets and institutions lowers the costs of
trading across international borders. A large empirical literature has since shown that
migration and trade patterns are highly correlated in various settings and the fact that
migrants beget bilateral trade has been accepted into the orthodoxy (Felbermayr et al.,
2012). Yet the causality from migration to trade hasn’t been conclusively established.
This paper redresses this shortcoming by providing cogent evidence from a natural
experiment.
We draw upon a unique period in human history, i.e. the exodus of the Vietnamese
Boat People to the US. Following the Fall of Saigon in 1975 and ensuing conflicts,
hundreds of thousands of refugees, i.e. the Boat People, fled Vietnam to escape violence.
Those that survived scattered across the world, although the ultimate destination of the
vast majority was the US.1 Between 1975 and 1994 under the auspices of the Indochina
Migration and Refugee Assistance Act, the Orderly Departure Program, the Refugee Act
1980 and the Humanitarian Operation Program; hundreds of thousands of Vietnamese
refugees were distributed throughout the country as policymakers, drawing on the Cuban
lesson of the past, were keen to avoid the development of significant refugee agglomerations.
1
Estimates vary quite widely, but according to ? 1.4 million fled to the US, 260,000 to China, 200,000
to Canada, 185,000 to Australia and 130,000 to France.
2
Meanwhile, the US also exerted a trade embargo on Vietnam, from 1975 until 1994, in
defiance of the communist government.
The exodus of the Vietnamese Boat People thus combines a large influx of migrants
to the US - the first wave of which was exogenously dispersed across US States - in parallel
with a lasting trade embargo. These events constitute an ideal natural experiment to test
the causal link between the Vietnamese Boat People and US-Vietnam trade following
the lifting of the trade embargo in 1994. Figures 1 and 2 pictorially demonstrates our
identification strategy. Figure 1 plots the immigration waves of Vietnamese to the US
(dotted line), with three spikes corresponding to the Fall of Saigon, the Sino-Vietnamese
War, and the US’ welcoming policies. As clearly seen, these massive immigration shocks
preceded the opening up of trade with Vietnam in 1994, which led to a rise in US
exports to Vietnam (bold line), which itself was further promoted by a US-Vietnam trade
agreement in 2001 and Vietnam’s entry into the WTO in 2007. Figure 2 shows that the
random allocation of the first wave of refugees in 1975 is indeed strongly correlated with
the location of Vietnamese migrants in the US in 1995, the first year after the lifting of the
trade embargo. We therefore use the exogenous allocation of the first wave of migrants as
an instrumental variable to insulate our results from any endogenous migration decisions
of Vietnamese migrants, whereby individuals might move to those States with the best
trading opportunities. The chronology of events in addition to the exogenous dispersion
of the first wave of Vietnamese refugees in 1975 across US States allow us to establish a
causal link from migrant networks in 1995 to trade creation from 1995 to 2010.
We find that US States with larger Vietnamese populations, measured in levels
or as shares of State populations, total migrant stocks and Asian migrant stocks, are
associated with more exports to Vietnam during the period 1995-2010, whether exports
are expressed in levels or as shares of State GDP or total exports. Our results in levels
- the most comparable with the existing literature - suggest that a 10% rise in the
Vietnamese population of a particular US state is associated with an 7.5% rise in that
State’s exports to Vietnam, an estimate greater by a factor of five when compared to
recent meta-analysis estimates (Genc et al., 2011).2 Our results are robust to controlling
2
While Vietnamese networks may have created both export and import opportunities in the US,
3
for income per capita, remoteness from US export ports and for export structure. We
further find that Vietnamese migrants networks are associated with a larger number
of industries with positive exports, i.e. the extensive margin, and that the pro-trade
effect of immigrants is greatest for differentiated products, as opposed to goods sold
on organized markets, a recurrent finding in the literature (e.g. Rauch and Trindade
(2002)). Examining individual export industries separately, we find the largest pro-trade
effect on beverages and tobacco products, followed by agricultural products and fish.
Furthermore, we document new evidence showing that migrant networks amplify the
protrade effect of Vietnam’s WTO accession. Drawing upon the rich micro data from
the US Census, our results further show no particular gender favors trade creation, that
less educated immigrants exert a greater pro-trade effect than the more highly educated
and interestingly that the ethnic-Chinese Vietnamese facilitate US exports to Vietnam
more than ethnic-Vietnamese compatriots; by a factor of ten. Disaggregating our results
by occupation, we find migrants in precision, production, craft and repair, managerial,
engineers and scientists and other professional occupations have the strongest pro-trade
effects.
To further qualify our results, we examine counterfactual scenarios that simulate
how large the export flows to Vietnam would have been should refugee inflows into the
corresponding US States have been lower. To this end, we focus upon the top 10 States
that hosted the largest shares of refugees, in terms of the State populations in 1975, and
construct for each State a synthetic image, i.e. a weighted average of those States with
at least 3 times fewer refugees. The weights are calculated such that the synthetic image
is as similar as possible to the State in question in terms of both export structure and
income per capita (see Abadie et al. (2010) for the synthetic-control method). These
simulations show that on average, across these 10 States, exports to Vietnam would have
been 3.5 times less should refugees flows have been 7 times smaller.
Our paper demonstrates a clear causal link from immigration to export. This strengthens
a too-often forgotten benefit of immigration, namely that migrants help the flow of
we focus upon the export-creating effect of immigrants since this better isolates the welfare-enhancing
channel from the product-preference channel of the network’s pro-trade effect (Gould, 1994). We also
document the import-creating effect of immigrants however.
4
information between countries and thus help in realizing gains from trade.
The following Section provides an overview of the trade-migration literature, detailing
the problems that this paper addresses.
This is then followed in Section 3, which
establishes the foundations of our natural experiment by elucidating an historical account
of the pivotal refugee programs implemented by the US and the UNHCR to address the
crisis of the Vietnamese Boat People and the trade embargo imposed on Vietnam by
the US. Section 4 presents our empirical model, while Section 5 outlines the data used
in the study. Our results are then presented in Section 6, which in turn allow us to
simulate counterfactual experiments so as to quantify how much trade creation would
have occurred in the absence of Vietnamese (Boat People). Finally Section 7 concludes.
2
Literature Review
The empirical trade-and-migration literature’s theoretical foundations draw heavily upon
the work of Greif (1993)) who provides a compelling theoretical model demonstrating
how ethnic networks serve to beget trade flows by surmounting commitment issues
through communal sanctions in weak institutional environments. Another important
theoretical contribution is that of Casella and Rauch (2002) whom further emphasize
the role of business and social networks in the functioning of markets with incomplete
information, i.e. when informal trade barriers are high. The seminal papers by Gould
(1994) and Rauch and Trindade (2002) are the most vaunted that test these types of
linkages empirically. Gould examines the trade-migration nexus between the US and
its trading partners and distinguishes two competing mechanisms via which migrants
may foster trade; a preference channel by which migrants in their country of destination
increase demand for goods produced in their country of origin and an information channel,
the economically-relevant, necessarily welfare-enhancing channel, through which migrants
lower the transaction costs of trade. Rauch and Trindade, abstracting from any preference
effects, rather examine the trade-creating role of Chinese networks between countries
other than China and identify a network effect by showing that networks facilitate trade
5
mostly in differentiated products, characterized by information asymmetries, rather than
in goods sold on organized exchanges.
A prolific literature has since blossomed from these earlier empirical contributions. It
has examined the links between trade and migration in a variety of geographical settings;
between single countries and multiple trading partners, Head and Ries (1998), between
multiple countries, Felbermayr and Toubal (2012), between US States and foreign trading
partners, Peri and Requena (2009) and within countries, Briant et al. (2009). Genc et al.
(2011), in their meta-analysis of 45 studies that examine the trade-migration nexus, argue
that on average a 10% rise in immigrants is associated with a 1.5% rise in bilateral trade.
The two most prominent issues that the literature seeks to address are the extent to
which a causal link can truly be established from migration to trade and in identifying
the underlying mechanisms. Our paper speaks to both.
In a recent review of the trade-and-migration literature, Felbermayr et al. (2012)
highlight that a natural experiment is the most convincing way to establish causality from
migration to trade and that any such offering is conspicuously missing to date. Issues of
endogeneity emerge due to concerns about reverse causality, i.e. whether migrants beget
trade or vice-versa and with regards to omitted factors such as unmeasurable cultural
affinity between two countries that might drive both trade and migration.
To deal with potential omitted-variable biases, studies have sharpened their geographical
focus, moving from examining trade between countries to investigating export patterns
across regions within a country. These developments attenuate the bias that might
otherwise be created by cultural affinity between trading partners, which is most likely to
be defined at a national level. For example, Dunlevy (2006) focused upon export patterns
across US States, Peri and Requena (2009) across Spain’s regions and Bratti et al. (2013)
across Italy’s. An alternative approach to deal with potential omitted-variable bias is
to move to panel data analysis (as opposed to relying upon cross-sections). Indeed the
proper inclusion of country or region fixed effects (or multilateral resistance terms in a
structural gravity model specification Anderson and Wincoop (2003)) have been shown
to be particularly relevant Felbermayr et al. (2010). Nevertheless these developments do
6
not entirely account for issues of simultaneity.
To deal with reverse causality, authors have adopted a variety of approaches,3 although
the most common is to identify suitable instruments, which also address concerns of
omitted variable bias and measurement error if indeed they are suitable. Drawing upon
the seminal work of Altonji and Card (1991) and Card (2001), Peri and Requena (2009)
and Bratti et al. (2013) instrument changes in immigrants at the sub-national level by
applying the net growth of immigrants at the national level to historical sub-regional
immigrant stocks to generate a time-varying and region-varying instrument. This approach
is not free from criticism however, as recently documented by Aaron and Levy (2013).4
Other studies have proposed various instruments for migration. To study the impact
of migration on foreign investment, Javorcik et al. (2011) use passport costs in the origin
country. In his study of migrant networks in Switzerland, Vézina (2012) adds visa policies
and migration sources in neighboring countries to the instrument mix. Sangita (2013)
proposes a similar instrument based on the variation in destination country citizenship
laws, i.e. the number of years of residency required in order to obtain citizenship, arguing
that such changes are exogenous to changes in trade, investment, business and political
climate. While these studies refine the causal link, they fail to convince unanimously due
to remaining doubts about the validity of the instruments. Indeed, it is not clear that such
instruments pass the exclusion restriction since both visa policies and bilateral trade flows
might both be driven by unobserved cultural and historical factors. Passport costs, on
the other hand, is not always a strong instrument. As noted by Felbermayr et al. (2012),
the most convincing method for addressing such endogeneity concerns between trade and
migration is through studying a natural experiment. To the best of our knowledge, our
paper is the first to do so.
The second aspect of the literature which has attracted the most interest is in terms
of distinguishing underlying the mechanisms by which migrants beget trade. Earlier
3
Gould (1994) argues that immigration occurs before the onset of trade and hence reverse causality
is not a concern.
4
These authors argue that such instruments might additionally capture persistent sub-regional
characteristics and are thus not strictly excludable. Moreover, historical migrant stocks could have
direct effects on trade growth 20 years later, rather than only through recent migration.
7
contributions concentrate upon discriminating between Goulds original information and
preference channels (Gould, 1994). Most studies focus on a single nation and its trading
partners, regressing imports and exports on the bilateral stocks of immigrants, relying
upon an identification strategy that assumes that the preference channel, i.e. nostalgia
trade, does not affect exports but only imports, unlike the information channel.5
Other papers instead build upon the insights of Rauch and Trindade (2002), restricting
attention to the transaction-cost mechanism and further distinguishing between information
and contract-enforcement mechanisms. Their identification strategy draws on the Rauch
(1999) classification of goods, which quantifies the informational content embodied in
various types of goods. Homogenous goods, such as gold or oil are sold on organized
exchanges and require little specific information to be traded. Reference-priced goods
such as chemical products have their prices quoted in trade publications and hence
require some though not much good-specific information. Other goods are classified
as differentiated and are the most information-intensive. Rauch and Trindade (2002)
show that Chinese networks are mostly correlated with trade in differentiated products,
thus highlighting the market-information channel6 and this result has subsequently been
replicated, for example by Briant et al. (2009).
To identify the contract-enforcement mechanism, Dunlevy (2006) shows that the
pro-trade effect of migrants across US States is stronger, the higher the corruption level
in the origin country. The idea here is that corruption is associated with issues of trust and
thus migrant networks can substitute for institutions. Furthermore Dunlevy demonstrates
that this effect is stronger when the language in the origin country is neither English nor
Spanish, the two most common native languages. As market information is more difficult
to obtain across linguistic boundaries, he thus provides evidence that migrant networks
bridge situations of incomplete information. In a similar vein, White and Tadesse (2008),
drawing upon World Values and European Value Surveys, construct measures of cultural
distance show that while trade declines as cultural distances between trading partners
5
As stressed by Parsons (2012), more satisfying identifications that rely upon cross-country data
instead regress unidirectional trade flows on both immigrant and emigrant stocks.
6
Rauch and Trindade (2002) argue that the contract-enforcement mechanism should equally apply
across all types of goods.
8
increases, migrants partially offset this effect.
Peri and Requena (2009), drawing upon the Chaney (2008) distorted gravity model
of trade, report that immigrants in Spain typically affect exports mostly through the
extensive margin. Vézina (2012), reports a similar finding in the context of Switzerland.
This suggests that migrants lower the fixed costs of exporting, associated with information
and market penetration, rather than the variable costs associated with transport and
tariffs.
To delve deeper into the mechanisms at play, authors have commonly examined
immigrant characteristics in relation to the overall pro-trade effect of immigration, focusing
upon the skill level, as defined by visa category, education level or occupation. Head and
Ries (1998) find that immigrants that entered Canada on the Family and Independent
visa classes exert the greatest pro-trade effect, while refugees have a negligible effect on
trade.7 Gould (1994) includes the ratio of skilled and unskilled immigrants in his analysis
and asserts that relative skills do not have a significant impact on immigrant-links.
Conversely, Felbermayr and Jung (2009), find in their panel study that the pro-trade
effect of high-skilled migrants is more than double that of the overall effect of migrants.
Aleksynska and Peri (2011) examine migrants occupations, specifically focusing upon
immigrants in the OECD employed in management positions, which they argue are those
most likely to establish business connections. They find that the pro-trade effect of these
migrants is larger than non-business network migrants - by a factor of ten and that
this classification is superior to a stricter definition based on education, but that when
both definitions are combined, it is the highly-educated in management positions that
underpin the trade-migration nexus.
By drawing upon rich micro-data and a natural experiment, our study contributes to
many of the issues from across the literature. Before turning to our empirical strategy,
we document the historical background that underpins our identification strategy.
7
Similarly, White and Tadesse (2010), find for the US, that refugees have a considerably smaller
pro-trade effect in comparison with immigrants entering the labor market or for purposes of family
reunification.
9
3
Historical Overview
Following the Fall of Saigon in 1975, Le Duan, then General Secretary of the Communist
Party of Vietnam vehemently purged those that had previously supported the US-backed
Vietnamese South, forcing many, especially military officers, into ’re-education camps’,
escape from which was punishable by death, or else to work in ’New Economic Zones’
i.e. agricultural collectives. More than one million people were held in captivity while
hundreds of thousands of others fled overland and by sea, relying on watercraft, often their
fishing boats, hence giving rise to their name, ’The Boat People’, which already by 1979
numbered more than four hundred thousand. In the same year, Vietnam again found itself
in conflict, this time with China, aggrieved by the December 1978 Vietnamese invasion
of Cambodia, which subsequently flexed its military muscles and invaded Vietnam in a
display of solidarity with its Khmer ally. This precipitated further persecution of the
entire and sizeable ethnic-Chinese populous in Vietnam, who were mandated to work in
labor camps at Vinh Bao and Nghe An or else flee the country.8
Those Vietnamese that were allowed and/or able to leave - often after several failed
attempts - fled overland to Cambodia and Laos (and then often onto Thailand) in the
case of the Southern Vietnamese - as opposed to their Sino-Vietnamese compatriots
whom instead largely fled overland to Southern China - or else headed for the open
seas, to international waters and busy shipping lanes; where they were preyed upon by
Thai pirates.9 The fortunate were rescued by ship crews and taken to refugee camps in
Hong Kong; although the overwhelming majority were destined for neighboring countries,
predominantly Malaysia, Thailand, Indonesia and the Philippines, the so-called ’first
asylum countries’ where they typically faced squalid conditions; rape, beatings and
torture and often arduous waits in refugee camps established by the UNHCR before
onward travel to Western countries for resettlement.
8
According to Zhou and Bankston (1998) the ethnic Chinese were persecuted both because they
were considered Bourgeoisie and because the Hanoi Government remained convinced that the Chinese
Government was trying to create a ’5th column’ of secret sympathizers, which culminated in protracted
persecution and numerous attacks upon them Duiker (1989).
9
According to the UNHCR, over 250,000 refugees died on the open sea ”as a result of storms, illness,
and starvation, as well as kidnappings and killings by pirates” (111th Congress, 2nd Session, House
Representatives 5th May 2010)
10
As shown clearly in Figure 1, the exodus of the Vietnamese to the US consisted
of three distinct waves, although debate exists with regards to their precise timing and
overlap. According to Zhou and Bankston (1998) the Boat People predominantly entered
in (the first) two waves, the first that peaked in 1978 and the second in 1982. The third
wave largely comprised those arriving on the basis of family reunification.10
Passed by President Gerald Ford on 23 May 1975, the signing of the Indochina
Migration and Refugee Assistance Act, as well as facilitating the entry of the first wave of
Vietnamese refugees to the US, marked a watershed moment in America’s stance toward
admitting Asian refugees; the previous policy of which was to resettle Southeast Asian
migrants in other nations, that although safer than their own, were not the US. Some
130,000 Indochinese refugees of which 125,000 were Vietnamese, brought by the 7th Fleet,
entered the US under the special status bestowed upon them under the Act. On arrival
to the US, these refugees were allocated to one of four reception centers: Camp Pendleton
in California, Fort Indiantown Gap in Pennsylvania, Fort Chaffee in Arkansas and Eglin
Air Force Base in Florida, at which time they were interviewed and assigned to various
sponsors, including amongst others, religious organizations. Following the closure of these
camps between September and December 1975, the first wave of Vietnamese Boat People
was deliberately dispersed around the US in an attempt to avoid a similar agglomeration
of refugees which had occurred in the case of the Cuban exodus following the Mariel
Boatlift (see below).
Following an international conference in Geneva in 1979, aimed at solving the crisis
of the Boat people, many Western countries pledged to resettle far greater numbers. In
the same year, amidst worldwide condemnation at the plight of the Vietnamese exodus,
the Orderly Departure Program was established, with the signing of a memorandum
of understanding between the communist Vietnamese regime and UNHCR, to allow
Vietnamese to legally emigrate on the basis of family reunion and on humanitarian
grounds. Lasting until 1994, the aim of the program was to resettle Vietnamese refugees
10
In fact the very first influx of Vietnamese to the US, around the time of the Fall of Saigon, comprised
Vietnamese exiles, as opposed to Boat People, those that had worked and fought with the US during
the protracted conflict, consisting of military personnel, business owners, professionals i.e. the upper
echelons of Southern Vietnamese society.
11
around the world, although the US was by far the largest recipient.
The Orderly
Departure Program predominantly facilitated the departure of Southern Vietnamese
officers and military personnel domiciled in re-education camps together with their families.
By the mid-1990s, estimates suggest that over two hundred thousand Vietnamese entered
the US under the auspices of the Orderly Departure Program.
In 1980, the US Congress passed the Refugee Act - the most comprehensive piece of
refugee legislation in US history - into Law, which revised the provision of the Hart-Celler
Act of 1965 that only admitted refugees into the US in limited proportions relative to the
overall number of immigrants. From 1980 onwards the numbers of refugees allowed entry
into the US was therefore independent of other considerations and hundreds of thousands
were accepted that had previously lived in Southeast Asian refugee camps, constituting
many of those that entered the US during the second wave.
The third and final wave of Vietnamese, which began in the late 1980s comprised
family members of Vietnamese-Americans, former re-education camp detainees and Amerasian
children. The Amerasian Homecoming Act was passed in the US in 1988, the effect of
which was to lift quotas on Amerasian immigration and reduce the requirement to enter
the US to ostensibly very little. Under this Act, the US Government was directed to
bring as many Amerasians to the US as possible. Until the passing of the Act, the
physically distinct Amerasians, the sons and daughters of Vietnamese women and US
service personnel; had been subjected to impoverished lives in their country of birth.
Although some were admitted as early as 1975, before 1988 only 6,000 Amerasians
(together with 11,000 relatives) had succeeded in leaving for the US (under the provisions
of the Orderly Departure Program). By 1993, the situation had changed, with a further
17,000 Amerasian children and 65,000 family members resettled in the US under this
Act. The final important piece of legislation passed by the US Congress to aid the
Vietnamese was the Humanitarian Operation Program 1989. In that year, the US and
Vietnamese Governments agreed for former and current detainees in re-education camps
to be allowed to depart for the US, the ultimate consequence of which was the arrival of
a further 70,000 Vietnamese. Post-1990 the majority of Vietnamese immigrants to the
US largely comprised political prisoners and their families.
12
Whereas the US Government went to quite extraordinary lengths to facilitate inward
movements of Vietnamese Boat People to the US, their stance with regards the movement
of goods between the two nations was quite the reverse. Under the auspices of the
1917 ’Trading with the Enemy Act’ and the ’Export Administration Act’ 1969, the
US widened trade sanctions, ostensibly a complete trade embargo, from its previous
focus on the North of Vietnam, which had been in place since 1964, to the entire
country, following the military conquest of Saigon in 1975 by the Communist North.
On 3 February 1994, President Clinton lifted the trade embargo at a time of increased
lobbying by private domestic firms keen to do business in Vietnam; arguing in favor of
normalizing the relationship between the two nations following a sustained effort by the
Hanoi Government to assist US forensic teams locate and identify over 2,000 US service
personnel that were still listed as Missing In Action at that time. A normalization
of diplomatic relations ensued in 1995, with the upgrading of the liaison offices to full
embassy status, while in 2000, a bilateral trade agreement was signed between the two
countries, which came into force in December 2001. The trade agreement mutually
extended Most-Favored-Nation status, de facto resulting in Vietnamese imports to the
US facing an average tariff of 3% as opposed to the previous 40%; while concurrently
tariffs remained on average around 13% for US products in Vietnam. On 11 January
2007, Vietnam acceded to the WTO, becoming its 150th member.
4
Empirical Strategy
In this section we carefully describe the natural experiment that allows us to identify
the causal pro-trade effect of migrant networks. The natural experiment combines the
fact that the first significant wave of Vietnamese Boat People to the US was exogenously
allocated across US States and the fact that the complete trade embargo of Vietnam
by the US was in force up until 1994, i.e. during the whole period over which the vast
majority of Vietnamese entered the US. Since we focus on immigrants that arrived prior to
the lifting of the trade-embargo (i.e. before 1994), we can conclusively insulate our results
from concerns of reverse causality. Furthermore, the exogenous allocation of Vietnamese
13
immigrants in 1975 further allows us to effectively instrument the 1995 migrant stock
to militate against further endogeneity concerns. Indeed, the most important aspect
of the distribution of Vietnamese refugees in 1975, is that the Boat People themselves
had little to no say as to where they could reside, such that their location decision
was exogenous. According to a statement made by Kenneth Fasick, Director of the
International Division of the US General Accounting Office, before The Subcommittee
on Immigration, Refugees, and International Law, Committee on The Judiciary of the
US House of Representatives on the 16th May 1979:
”To avoid the kind of geographic concentration experienced with the Cuban refugees,
an effort was made at the time of the initial resettlement wave in 1975-76, to distribute
the refugee population throughout the US.”
In the words of the Sociologist Ruben G.Rumbaut (1995):
”...goal of resettlement through reception centers was to disperse refugees to ’avoid
another Miami’...Consequently the initial resettlement efforts sought a wide geographic
dispersal of Vietnamese families.”
According to Zhou and Bankston (1998),
”...the US Government and the voluntary agencies working mainly under government
contracts oversaw their resettlement and in most cases decided their destinations... The
effort to minimize impact [on America Society] led initially to a policy of scattering
Southeast Asians around the country...the early attempts at dispersion gave rise to Vietnamese
communities in such places as New Orleans, Oklahoma City, Biloxi, Galveston and
Kansas City, that had previously received few immigrants from Asia.”
THIS IDENTIFICATION STRATEGY IS SIMILAR TO LUNDQVIST IN JPE:
We thus use the exogenous allocation of Vietnamese refugees in 1975 as an instrument
for the stock of Vietnamese migrants across US states in 1995, the year from which the
US started exporting to Vietnam. Figure 6 shows across the US the concentrations of
Vietnamese by State, as well as the 28 metropolitan areas that hosted more than 5,000
Vietnamese in 1995 (the top metropolitan areas are also listed in Table 13). Although
14
concentrations persist, most notably in California and Texas, the figure demonstrates
the wide dispersion of the Vietnamese across the country. While many of the largest
cities feature in this figure, it is worth emphasizing that many populous cities do not, for
example, San Antonio, Jacksonville, Indianapolis and Columbus. Most importantly, as
shown in Figure 2, this distribution in 1995 was in large part determined by the initial
allocation of refugees in 1975. The correlation between the two data series is 0.98, giving
us reason to believe that our instrument will subsequently be strong.
11
To further guard against scale effects i.e. larger States export greater amounts since
they are home to greater numbers of migrants; we normalize both exports and our
immigrant stock variables, the former by total exports and State GDP and the latter
by total immigrants or State population. Our regression takes the following form:
Xi = β0 Vi + β1 Ci + i
(1)
Where Xi is the average normalized exports of State i to Vietnam from 1995 to
2010, Vi is the (normalized) stock of Vietnamese migrants in 1995 and Ci is a set of
control variables. The βs are parameters to be estimated and is the error term. Mi is
instrumented by the stock of refugees in 1975.
We include three control variables: income per capita, as rich States may be more
likely to export more differentiated products to Vietnam, a measure of export-structure
similarity with Vietnam’s import basket from the US, to control for differences in export
structures that could explain export performances and a measure of trade costs, i.e.
remoteness from US customs ports.
To construct the export-structure similarity index, we take the inverse of the Euclidean
distance between the State’s export vector, defined as its export share by industry and
Vietnam’s import vector. More precisely, for each State the index is defined as:
11
Internal movements of the Boat People did occur in the years after 1975, especially to California, as
made clear by the statement of Kenneth Fasick:
”Nevertheless, there is a substantial concentration of Indochinese refugees in California resulting from
refugee movements there for reasons of family ties, warmer weather, better job opportunities, and a larger
refugee community.”
15
1
qP
(2)
2
(Xk − Mk )
where Xk is the State’s export share in industry k (28 industries of the NAICS
classification) and Mk is Vietnam’s share of imports from the US in industry k.
To construct the remoteness measure we take a weighted distance from each State
centroid to every Customs Port (see Figure 4), where the weights are US exports to
Vietnam from the ports. The logic here is that the further the States from the customs
ports exporting to Vietnam, the higher the trade costs. More precisely, the remoteness
of each state is defined as:
1
P Xi
(3)
Di
where Xi are the custom port i exports to Vietnam and Di is the distance in kilometers
from the State’s centroid to custom port i.
Unless indicated otherwise, variables are taken in logs.
5
Data
Trade data are taken from the Foreign Trade Division of the US Census Bureau. Exports
are disaggregated into 28 product categories, according to the 3-digit NAICS (North
American Industry Classification System) from 2002 to 2010 and the 2-digit SIC (Standard
Industrial Classification) from 1995 to 2001 (see Appendix). We match the SIC categories
to NAICS for our category-level regressions, although in most regressions we use aggregate
export data, taking the mean over 1995-2010, since we are interested in the cross-State
variation, as per our identification strategy. The main US exports to Vietnam in absolute
terms over the period were transportation equipment and food and kindred products,
while leather and forest products are important in relative terms (see Table 1).
The 1975 refugee location data are obtained from a US General Accounting Office
16
Report to Congress (General, 1977).12 It provides the numbers of refugees resettled by
State as of 31st December 1975, importantly the final day of the month of the last camp
closure, the implementation of which militates against internal migratory movements
confounding our results. Migration data for the year 1995 are taken from the US 2000
Census, drawing upon the question that asks respondents their place of residence five
years hence. In other words, we only include in estimation those migrants that remained
in the US up until the year 2000 and importantly only include those that migrated to the
US prior to 1994, to ensure that their decision to migrate could not have been based on
the prospect of initiating trade with Vietnam. These anonymous micro data, obtained
from the (The Integrated Public Use Microdata Series (IPUMS-USA)) provide detailed
information about migrants’ education, occupation, ethnicity, languages and gender. The
cities with the largest Vietnamese populations in 1995 were San Francisco, Los Angeles
and Houston (see Figure 6 and Tables 13 and 14). The data for our control variables,
i.e. State GDP and population are taken from the US Bureau of Economic Analysis.
Summary statistics are provided in Table 2.
6
Results
Before turning to our baseline results, a few words on the validity of our instrumental
variable. We instrument each variant of our Vietnamese network variable by the stock
of the 1975 Vietnamese refugees. As shown in Figure 2, the distribution of Vietnamese
in 1995 was in large part determined by the exogenous allocation of refugees in 1975;
the correlation between the two data series is 0.98. To confirm the validity of our IV
in each regression, we display the Cragg-Donald F statistics and the Kleibergen-Paap
test p-values in all our tables. The Kleibergen-Paap test examines whether the excluded
instrument, i.e. 1975 refugees, is correlated with the endogenous regressors, conditional
on the control variables. P-values below 0.1 suggest that we can reject the null hypothesis
that the equation is not identified, thus confirming that our instrument is statistically
12
The report is available for download here: http://www.gao.gov/assets/120/118759.pdf
17
significant.13 The Cragg-Donald F statistic provides an indication as to whether our
instrument is strong or weak, the latter arising when the instrument is correlated with the
endogenous regressor but only weakly, thus affecting the performance of the IV estimator.
To asses the weakness of our instrument we need to compare these F statistics with the
Stock-Yogo critical values for the Cragg-Donald F-statistic with one endogenous regressor
(Stock and Yogo, 2002).14 As a rule of thumb, an F-statistic above 10 indicates that the
IV is acceptable.
Our baseline results, using OLS as well as IV-2SLS regressions, are presented in Table
3. We find a positive and significant migrant-network trade-creating effect on exports
across both measures of export performance, i.e. exports to Vietnam as a share of total
exports and as share of GDP, as well as across three measures of migrant networks;
Vietnamese as a share of total migrants, Vietnamese as share of population and simply
the total number of Vietnamese in levels. Our IV results suggest that a 10% increase
in the Vietnamese network raises the ratio of exports to Vietnam over GDP by 1.9%.
Similarly, if the Vietnamese stock as a share of the State population is 1% higher, the
ratio of exports to Vietnam over GDP is about 239% higher.
Columns 1-6 of Table 4 examine the network effect on the extensive margin of
exports. Here we define the extensive margin of exports as the number of 3-digit NAICS
categories in which exports to Vietnam are positive, divided by the total number of
categories exported by that State; again to account for scale effects. We find a positive
and significant effect, suggesting that a 10% increase in Vietnamese migrants increases
the share of categories exported by 2.6%. This effect may appear small, but recall that
export categories are defined quite broadly, meaning this finding is a strong indication
of a network effect on the extensive margin of exports. Columns 7-12 of Table 4 provide
additional results, whereby our left-hand side variable is simply the (non-normalized)
total exports to Vietnam. In this case we find that a 10% larger Vietnamese network
13
The test is essentially the test of the rank of a matrix: under the null hypothesis that the equation is
under-identified, the matrix of reduced form coefficients on the excluded instrument has rank=K where
K is the number of endogenous regressors.
14
These are 10% maximal IV size 16.38, 15% maximal IV size 8.96, 20% maximal IV size 6.66, and
25% maximal IV size 5.53. An F statistic above 16.32 ensures a minimal bias.
18
results in an increase in exports to Vietnam of 7.5%.
To further confirm the validity of our results, we perform a number of preliminary
robustness exercises. Firstly, we take exports to Vietnam as a share of Vietnam-style
exports as our dependant variable as an alternative normalization procedure. Vietnam-style
exports are a State weighted-average of exports, where the weights are the share of
Vietnam’s import from the US in each NAICS category. Hence, Vietnam-style exports
are an export basket that mimics the products that Vietnam imports from the US. Results
in Table 5 confirm that even in this specification that controls even more conservatively
for export differences across States the results hold. Secondly, we take Vietnamese
migrants as a share of Asian migrants, rather than total migrants or population. The idea
here is that Asian migrants may be driving the correlation rather than specifically the
Vietnamese. The results in Table ?? confirm that in all IV regressions, the results hold for
any measure of export performance. Finally, in Table 7 we examine whether Vietnamese
immigrants also foster imports to the US from Vietnam. While import data by State are
unavailable, we have imports by 30 US customs ports that we assign to States. While
investigating the impact on imports is less interesting since we also capture a preference
effect for home goods, i.e. nostalgia trade, it is interesting from a developing country
perspective, i.e. Vietnam reaching the US market. We find a strong effect, whereby a
10% increase in Vietnamese increases imports as a share of GDP by about 5%, confirming
the additional preference effect above and beyond any information channel.
6.1
Heterogeneity across Industries
In Table 9 we present our results when we disaggregate our baseline results by NAICS
categories. These regressions are estimated on the basis of taking exports as a share of
total US exports within each category, as a share of the State’s industry GDP and by
taking migrants as a share of total migrants and of the total population. We find robust
positive and significant effects for most industries. The effect is strongest for Agricultural
products and Beverages and Tobacco Products and insignificant for homognous goods
such as oil and gas, and mineral and ores. The coefficients are standardized (beta
19
coefficients) to ease comparison across columns. The average of the four columns’ estimates
are depicted in Figure 5. We further aggregate exports according to Rauch’s classification,
by matching each NAICS code to a Rauch category (see Table 15). In line with the
existing literature, we only find a robust pro-trade effect for differentiated products,
confirming previous findings which suggest that migrant networks operate through providing
market information across international borders (Table 8).
6.2
Heterogeneity across Immigrant Types
We proceed by exploring how various migrant characteristics influence the pro-trade
effect, the results from which are summarized in Table 10. We begin by estimating
our baseline regressions separately for males and females, in this case taking the total
migrant stock as equivalent to the population shares, in both cases implementing our
total stock of Vietnamese refugees in 1975 as our IV. Although we find across all four
export-performance measures that the pro-trade effect is marginally higher for women
these differences are not statistically significant. Turning to the ethnicity of migrants, we
test whether ethnic-Chinese Vietnamese have a larger effect than their ethnic-Vietnamese
compatriots, not least since ethnic-Chinese have previously been touted as representing a
key driving force in global trading patterns (Rauch and Trindade, 2002). The difference
is startling, since our estimates suggest that ethnic-Chinese Vietnamese have a stronger
pro-trade effect by a factor of ten. Turning to the level of English of Vietnamese migrants
we find that those who speak good English fail to foster trade more than the those who
do not; quite to the contrary, suggesting it is those immigrant ties to the homeland
that matter most for trade. Finally, we examine migrants’ skill level as defined by both
education level and occupation. We define an immigrant as high-skilled should they have
received a tertiary education level or higher. Interestingly, we find, contrary to existing
studies, for example Aleksynska and Peri (2011), that in fact it is the low-skilled that
most influence bilateral trade patterns. Turning to specific immigrant occupations, we
disaggregate the 1990 Census Bureau Occupational Classification 1-digit coding, which
originally comprises 7 categories into 9, splitting out Management, Professional and
20
Related Occupations into Managerial, Engineers and Scientists and Other Professionals.
Our results from our regressions run across these occupational categories are presented
in Table 11 and Figure 6. The results indicate that Vietnamese migrants in Precision,
Production, Craft and Repair occupations, as well as those with Managerial, Engineers
and Scientists and Other Professional occupations have the strongest pro-trade effects.
Those in the military have no significant effect.
6.3
Vietnamese Networks, the US-Vietnam Trade Agreement
and Vietnam’s WTO Accession
In this section we focus upon how the pro-trade effect of migrant networks differed before
and after two trade-policy events, i.e. the US-Vietnam free-trade agreement in 2001 and
the entry of Vietnam into the World Trade Organization (WTO) in 2007. We run a panel
regression with a policy dummy interacted with migrant networks to examine whether
the trade creation effects of these policy changes were higher in those States that hosted
greater numbers of Vietnamese migrants. Specifically, we run the following regression:
Xit = αi + γt + β1 W T Ot + β2 W T Ot × Vi + β3 Cit + it
(4)
Where αi and γt are State and year fixed effects, W T Ot is a dummy variable that
switches from zero to one in years after WTO accession (or after the trade agreement
is enforced). We focus upon the six-year period around policy changes. Vi is the stock
of Vietnamese migrants in 1995, normalized by both State populations or total migrant
stocks. Cit is a set of control variables including GDP and income per capita. A positive
β2 would suggest that the trade-creation effect of the policy change are significantly
higher in States with larger Vietnamese networks in 1995. We instrument W T Ot × Vi
with W T Ot × 1975 refugees. The corresponding results are presented in Table 12 which
suggest that migrant networks did indeed amplify the export creation following Vietnam’s
accession to the WTO. In those States with the largest migrant networks, WTO accession
resulted in an additional boost to exports by a factor as high as 5, an effect illustrated
21
in Figure 7. Conversely, we find no significant effect across States with smaller networks.
Interestingly, we find no evidence that there was any significant trade creation following
the signing of the US-Vietnam Free-trade Agreement. One plausible explanation for this
finding is the fact that Vietnam’s surge in imports began in the mid-2000s (see Figure
1).
6.4
Synthetic Simulations
For a final robustness check, we simulate the export path of the top 10 US States (in terms
of Vietnamese per capita) should those States have received around 3 times fewer refugees
in 1975. For each State’s exports to Vietnam as a share of GDP, we construct a synthetic
version that is a weighted average of the variable in other States where the numbers
of Vietnamese refugees are at least 3 times smaller. The weights are generated so that
the differences in export shares across each industry (as well as differences in income per
capita) between States are minimized. Each State is thus compared to a synthetic version
of itself, similar in terms of income per capita and export structure, but with far fewer
Vietnamese refugees (see Abadie et al. (2010) for a detailed review of the technique).
Figure 9 displays the cases of Texas, California, Minnesota, Hawaii, Washington and
Kansas, six States among the top 10, according to the number of Vietnamese as a share
of population. Figure 9 shows that, with the exception of Hawaii, the export performances
of these States are far higher as when compared to their synthetic image, especially post
2005. In 2010, Texas’ exports to Vietnam accounted for 0.0004% of GDP. Without its
important refugee intake, our counterfactuals suggest exports from Texas to Vietnam
would have been four times smaller, i.e. 0.0001% of GDP. In the cases of California and
Kansas, exports would have been 5 times smaller. For Minnesota, exports would have
been about 60% lower. We find on average for these 10 states that exports to Vietnam
would have been 3.5 times lower should refugee flows have been about 7 times smaller
(the average size in the synthetic image).
22
7
Conclusion
Using the exodus of the Vietnamese Boat People as a natural experiment we establish
a clear causal impact from migrant networks to trade. To this end, we exploit the
exogenous allocation of refugees across US States as an instrument for immigrant stocks
in 1995 and examine the effect of the latter on exports in the 15 years following the
lifting of the trade embargo in 1994. We find a strong pro-trade effect across many
alternative specifications, measuring migrant networks in levels or else as shares of State
populations or State migrant stocks. In our benchmark regression a 10% increase in
the Vietnamese network is associated with a rise in the ratio of exports to Vietnam
over GDP of 1.9%. Controlling for export structure, we further show that for a State
like California, where the Vietnamese account for 1.15% of the population, exports to
Vietnam, at 0.0005% of GDP, would have been 5 times lower had the original Vietnamese
refugee flow been 3 times smaller. Additionally we find evidence that the pro-trade effect
of migrant networks, true to their reputation (Rauch and Trindade, 2002) is strongest for
ethnic-Chinese Vietnamese and particularly strong for beverage and tobacco products.
Our paper is therefore the first to provide evidence from a natural-experiment of the
causal relationship between migrant networks and international trade thereby addressing
an issue that has lingered over two decades of empirical research.
Taking a broad
perspective, our results importantly provide evidence of the positive long-term economic
benefits of immigration, i.e. export creation and gains from trade, which policymakers
might be encouraged to consider.
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27
4
100
Figure 1: Vietnamese Boat People and US Exports to Vietnam
Fall of Saigon, 1975
Amerasian Homecoming Act, 1988
Humanitarian Operation Program, 1989
40
2
60
Sino−Vietnamese War, 1979
3
80
Vietnam joins WTO, 2007
20
1
Trade agreement, 2001
0
0
Trade ban lifted, 1994
1970
1980
1990
2000
Inflow of Vietnamese migrants (thousands)
US exports to Vietnam ($ billions, right axis)
Sources: US Census 2000 and USITC.
28
2010
Figure 2: Vietnamese Migrant Stock in 1995 vs. Refugees in 1975
12
CA
Vietnamese migrants in 1995
6
8
10
TX
MA
UT
NV
MS
WA
VA
FL
NY
LA
IL
MN
PA
GA
ORMD
NJ
NC
CO
OK
HI
AZ
OH
KS MI MO
IA
CT
TN
AL
IN
NE
WIAR
SC
KY
NM
DC
AK
RI
NH
DE
VT WV
ID
ME ND
SD
MT
4
WY
4
5
6
7
8
Vietnamese refugees in 1975
9
10
Note: The circles are proportional to the State’s average exports to Vietnam as a
share of GDP during 1995-2010. Sources: See Section 5
29
30
Over 75,000
25001 - 75000
10001 - 25000
5001 - 10000
Up to 5,000
States
Denver
Austin
Houston
Dallas
Oklahoma City
Tampa
Orlando
Atlanta
New Orleans
St. Louis
Chicago
Minneapolis
Note: Circles are proportional to Vietnamese migrant populations.
Over 50,000
10001 - 50000
Up to 10,000
Metropoles
San JoseStockton
Sacramento
San Francisco
Los Angeles
San DiegoPhoenix
San Bernardino
Portland
Seattle
Figure 3: Vietnamese Migrants in 1995
Washington
Philadelphia
Boston
New York
31
5%-7.5%
2.5%-5%
Up to 2.5%
Over 7.5%
!
!
!
!
USA Trade Share
!
!
NEW ORLEANSMOBILE
!
CHARLOTTE
!
!
!
!!
!
TAMPA
!
HOUSTON-GALVESTON
MIAMI
!
LAREDO
!!
DALLAS-FORT WORTHCHARLESTONSAVANNAH
!
!
ST. ALBANS
PORTLAND
! !
BUFFALO
MILWAUKEE
!
CHICAGO
BOSTON
!
DETROIT
!
!CLEVELAND NEW!YORK
BALTIMORE
!
ST. LOUIS
!!WASHINGTON
!
NORFOLK
MINNEAPOLIS
!
DULUTH
!
PEMBINA
!
Note: Circles are proportional to total exports to Vietnam from the district port.
NOGALES
!EL PASO
!
SAN DIEGO
!
!
GREAT FALLS
LOS ANGELES
SAN FRANCISCO
!
!
COLUMBIA-SNAKE
!
SEATTLE
Figure 4: US Customs Districts
Table 1: Export Products - 1995-2010
NAICS
Exports to
Share of Description
Vietnam (‘000$) US exports
316
380000
1.34% Leather & Allied Products
113
210000
1.28% Forestry Products, Nesoi
321
470000
1.05% Wood Products
311
2600000
0.76% Food & Kindred Products
312
220000
0.57% Beverages & Tobacco Products
910
790000
0.52% Waste And Scrap
111
1600000
0.40% Agricultural Products
114
92000
0.26% Fish, Fresh/chilled/frozen & Other
336
3200000
0.20% Transportation Equipment
322
350000
0.20% Paper
325
1900000
0.17% Chemicals
333
1700000
0.16% Machinery, Except Electrical
327
110000
0.14% Nonmetallic Mineral Products
313
97000
0.12% Textiles & Fabrics
112
13000
0.11% Livestock & Livestock Products
331
370000
0.11% Primary Metal Mfg
334
1700000
0.10% Computer & Electronic Products
990
120000
0.10% Special Classification Provisions
335
260000
0.09% Electrical Equipment, Appliances
315
38000
0.08% Apparel & Accessories
314
18000
0.08% Textile Mill Products
326
150000
0.08% Plastics & Rubber Products
332
190000
0.07% Fabricated Metal Products, Nesoi
339
270000
0.07% Miscellaneous Manufactured Commodities
920
36000
0.06% Used Or Second-hand Merchandise
337
16000
0.05% Furniture & Fixtures
511
3300
0.05% Newspapers, Books & Other Published
323
26000
0.05% Printed Matter And Related Products
212
39000
0.04% Minerals & Ores
324
36000
0.01% Petroleum & Coal Products
211
722
0.00% Oil & Gas
32
Figure 5: The Pro-Export effect of the Vietnamese by Industry
Agricultural Products
Beverages & Tobacco Products
Used Or Second−hand Merchandise
Furniture & Fixtures
Fish, Fresh/chilled/frozen & Other
Transportation Equipment
Waste And Scrap
Fabricated Metal Products, Nesoi
Forestry Products, Nesoi
Minerals & Ores
Paper
Wood Products
Food & Kindred Products
Textile Mill Products
Petroleum & Coal Products
Leather & Allied Products
Livestock & Livestock Products
Plastics & Rubber Products
Electrical Equipment, Appliances
Miscellaneous Manufactured Commodities
Primary Metal Mfg
Special Classification Provisions
Nonmetallic Mineral Products
Printed Matter And Related Products
Textiles & Fabrics
Newspapers, Books & Other Published
Apparel & Accessories
Oil & Gas
Machinery, Except Electrical
Computer & Electronic Products
Chemicals
Published Printed Music And Music
−.5
0
.5
1
1.5
Vietnamese network effect on US exports
Note: This Figure is based on regression results of Table 9.
33
2
2.5
Figure 6: The Pro-Export effect of the Vietnamese by Occupation
Military
Precision, Production, Craft & Repair
Service
Technical, Sales & Administrative Support
Operators, Fabricators & Labourers
Managerial
Engineers & Scientists
Other Professionals
Farming, Forestry & Fishing
−1
0
1
2
Vietnamese network effect on US exports
3
Note: This figure is based on regressions in column(1) of Table 11.
WTO effect on Vietnam−share of US exports
0
1
2
3
WTO effect on Vietnam−share of US exports
−.5
0
.5
1
1.5
Figure 7: The Combined Vietnam-migrants-WTO-Accession Effect on US Exports across
States
4
6
8
10
ln (Vietnamese in 1995)
12
0
Thick dashed lines give 90% confidence interval.
Dotted line is a kernel density estimate of network.
.05
ln (Vietnamese share of migrants in 1995)
Thick dashed lines give 90% confidence interval.
Dotted line is a kernel density estimate of network.
Note: This figure is based on regressions in columns(2) and (4) of Table 12.
34
.1
0
0
.0002
.0002
0
0
.0002
.0003
Washington
1995
2000
2000
Kansas
2005
synthetic Kansas
2005
2010
35
.0001
.00015
.0002
.0004
2005
.00005
Exports to Vietnam / State GDP
.0001
Texas
.00015
1995
2000
.0001
.0003
1995
.00005
.0001
0
0
.0002
.0003
.0001
.0002
.0003
.0004
.0001
.0005
.0004
Figure 8: Synthetic Controls
synthetic Texas
2010
1995
California
synthetic Washington
2010
1995
1995
2000
Minnesota
2000
2000
Hawaii
synthetic California
2005
2005
synthetic Hawaii
2005
2010
synthetic Minnesota
2010
2010
2005
2010
1995
2005
2010
Income per capita
35000
40000
45000
synthetic California
25000
30000
50000
40000
1995
2000
2005
2010
1995
2000
Minnesota
2005
2010
synthetic Minnesota
35000
30000
25000
25000
30000
Income per capita
35000
40000
40000
synthetic Washington
1995
2000
Kansas
2005
2010
synthetic Kansas
20000
Income per capita
2000
California
60000
synthetic Texas
30000
20000
40000
45000
2000
Washington
Income per capita
35000
Income per capita
25000
1995
Texas
20000
30000
35000
30000
25000
20000
Income per capita
40000
Figure 9: Synthetic Controls - Income per capita
1995
2000
Hawaii
36
2005
synthetic Hawaii
2010
Table 2: Summary Statistics
Obs
Mean Std. Dev.
Min
Max
GDP (Million $)
51 246748
297667 22518 1672301
Income per capita
51
35383
5877 27108
58523
Pop
51 5532596
6183150 494300 34000000
Export structure
51
0
1
-3.19
2.02
Remoteness
51
-13.64
0.39 -14.62
-12.45
Exports to Vietnam (’000$)
51
33400
70700
306
444000
Share of total exports
51
0.15%
0.12% 0.02%
0.57%
Share of GDP
51
74.31
84.66
7.90
523.20
Nb of NAICS exported to Vietnam
51
12.58
6.35
2.00
27.31
Share of NAICS exported
51
0.43
0.21
0.10
0.92
Total migrants
51 679535
1494611 16058 9261300
Vietnamese migrants
51
15782
50747
85
358205
Vietnamese refugees 1975
51
2369
3987
81
27199
Males
51
7944
25136
8
177198
Females
51
7838
25615
67
181007
Ethnic Vietnamese
51
12644
38865
22
272129
Ethnic Chinese
51
1831
8240
0
59026
Low-skilled
51
2882
9428
18
67009
High-Skilled
51
11369
36927
52
260184
Good English
51
10900
34239
66
240740
37
38
51
0.214
0.746
(0.566)
-0.192
(0.273)
0.124
(0.110)
-17.74***
(6.138)
12.41**
(5.273)
51
0.147
13.52
0.00287
1.041*
(0.619)
-0.197
(0.241)
0.0759
(0.102)
-21.14***
(6.594)
21.75**
(10.75)
51
0.223
-0.0292
(0.559)
-0.0472
(0.201)
0.187*
(0.106)
-7.634
(5.478)
142.3***
(33.33)
51
0.214
10.31
0.0207
51
0.170
0.129*
(0.0643)
-0.131
0.123
(0.602) (0.602)
-0.0109 -0.0564
(0.197) (0.261)
0.186*
0.164
(0.0987) (0.114)
-6.156
-10.15
(6.105) (6.125)
179.9**
(79.76)
Exports to Vietnam share of exports
(2)
(3)
(4)
(5)
51
0.169
271.7
7.54e-05
0.143**
(0.0616)
0.0989
(0.590)
-0.0430
(0.244)
0.161
(0.108)
-9.824
(6.012)
(6)
51
0.263
-0.459
(0.874)
-0.453
(0.358)
0.150
(0.139)
2.013
(9.907)
16.04***
(4.769)
(7)
51
0.176
13.52
0.00287
-0.0543
(0.829)
-0.461
(0.320)
0.0840
(0.135)
-2.654
(8.988)
28.89**
(12.18)
51
0.234
-1.388
(0.881)
-0.292
(0.445)
0.231
(0.146)
14.02
(9.627)
157.0**
(61.78)
51
0.205
10.31
0.0207
-1.609*
(0.908)
-0.213
(0.475)
0.230*
(0.136)
17.24*
(9.490)
238.8**
(93.43)
51
0.290
0.232***
(0.0664)
-1.380*
(0.801)
-0.214
(0.388)
0.190
(0.151)
13.38
(8.038)
Exports to Vietnam share of GDP
(8)
(9)
(10)
(11)
51
0.285
271.7
7.54e-05
0.190***
(0.0621)
-1.305*
(0.785)
-0.256
(0.363)
0.197
(0.143)
12.37
(8.073)
(12)
Note: Robust standard errors in parenthesis. *** p<0.01, ** p<0.05, * p<0.1. Odd-numbered columns are OLS estimations, even-numbered IV-2SLS.
1975 Vietnamese refugees is the IV.
Observations
R-squared
Cragg-Donald F
Kleibergen-Paap p-val
Constant
Export structure
Remoteness
Income per capita
Vietnamese
Vietnamese share of pop
Vietnamese share of migrants
(1)
Table 3: The Pro-Trade Effect of Vietnamese Migrants in the US
39
51
0.247
0.531
(0.621)
-0.479***
(0.167)
0.0727
(0.0703)
-13.22*
(7.181)
7.253**
(3.007)
83.62**
(33.77)
13.52
0.00287
51
51
0.253
1.578**
0.0767
(0.756)
(0.625)
-0.498** -0.394*
(0.249)
(0.199)
-0.0982
0.109*
(0.128)
(0.0645)
-25.29*** -7.294
(8.064)
(7.189)
40.48***
(12.30)
10.31
0.0207
51
-0.602
(0.653)
-0.151
(0.474)
0.107
(0.0841)
2.591
(6.554)
334.7***
(126.8)
51
0.727
0.277***
(0.0314)
-0.194
(0.332)
-0.200
(0.156)
0.0587
(0.0459)
-3.976
(3.478)
Exports to Vietnam’s extensive margin
(2)
(3)
(4)
(5)
51
0.727
271.7
7.54e-05
0.266***
(0.0309)
-0.175
(0.322)
-0.211
(0.143)
0.0607
(0.0432)
-4.235
(3.375)
(6)
51
0.284
0.927
(1.575)
-1.238**
(0.510)
0.255
(0.183)
-11.44
(19.20)
26.30***
(7.862)
(7)
13.52
0.00287
51
3.695*
(2.167)
-1.289**
(0.595)
-0.197
(0.318)
-43.38*
(22.14)
114.2***
(35.17)
(8)
51
0.330
-0.837
(1.581)
-0.888
(0.700)
0.387**
(0.178)
11.74
(18.90)
346.3***
(110.2)
10.31
0.0207
51
-2.453
(1.700)
-0.310
(1.336)
0.382*
(0.205)
35.28**
(16.90)
944.2***
(297.3)
Exports to Vietnam
(9)
(10)
51
0.718
0.769***
(0.0856)
-1.283
-0.973
-0.459
(0.501)
0.247*
(0.144)
16.49
(9.838)
(11)
51
0.717
271.7
7.54e-05
0.750***
(0.0809)
-1.248
(0.934)
-0.478
(0.466)
0.251*
(0.136)
16.02*
(9.481)
(12)
Note: Robust standard errors in parenthesis. *** p<0.01, ** p<0.05, * p<0.1. Odd-numbered columns are OLS estimations, even-numbered IV-2SLS.
1975 Vietnamese refugees is the IV.
Observations
R-squared
Cragg-Donald F
Constant
Export structure
Remoteness
Income per capita
Vietnamese
(1)
Table 4: The Pro-Trade Effect of Vietnamese Migrants in the US - 2
Table 5: Results taking Exports to Vietnam as a share of US Vietnam-Style exports
Exports to Vietnam as a share of Vietnam-style US exports
(1)
(2)
(3)
(4)
(5)
(6)
12.55**
(5.846)
19.65*
(10.07)
141.2***
(31.14)
Vietnamese
Income per capita
Remoteness
Export structure
Constant
Observations
R-squared
Cragg-Donald F
0.844
(0.563)
-0.0442
(0.279)
-0.117
(0.116)
-14.10**
(6.072)
1.068*
(0.591)
-0.0483
(0.250)
-0.154
(0.105)
-16.68***
(6.425)
0.0670
(0.558)
0.0996
(0.203)
-0.0539
(0.112)
-3.981
(5.399)
51
0.141
51
0.100
13.52
0.00287
51
0.146
162.5**
(70.97)
0.128**
(0.0597)
0.00942
0.218
(0.591) (0.588)
0.120
0.0905
(0.188) (0.265)
-0.0541 -0.0765
(0.105) (0.119)
-3.143
-6.474
(5.857) (5.842)
0.129**
(0.0568)
0.217
(0.572)
0.0912
(0.248)
-0.0767
(0.114)
-6.457
(5.676)
51
0.143
10.31
0.0207
51
0.091
271.7
7.54e-05
51
0.091
Note: Robust standard errors in parenthesis.
*** p<0.01, ** p<0.05, *
p<0.1. Odd-numbered columns are OLS estimations, even-numbered IV-2SLS. 1975
Vietnamese refugees is the IV.
40
41
51
0.148
0.285
(0.172)
0.725
(0.636)
-0.102
(0.303)
0.150
(0.117)
-15.25**
(6.409)
51
0.028
14.47
0.00559
0.720*
(0.405)
1.287
(0.856)
0.0240
(0.315)
0.0935
(0.107)
-18.33**
(7.286)
51
0.203
0.414**
(0.172)
-0.428
(0.978)
-0.324
(0.378)
0.178
(0.147)
4.912
(10.72)
51
0.073
14.47
0.00559
0.956**
(0.425)
0.273
(1.026)
-0.167
(0.370)
0.107
(0.150)
1.081
(10.85)
51
0.247
14.47
0.00559
51
51
0.067
14.47
0.00559
51
0.650*
(0.376)
1.291
(0.804)
0.152
(0.314)
-0.138
(0.109)
-14.14**
(7.095)
Exports to Vietnam
share of Viet-style
(7)
(8)
0.250* 1.339*** 0.281*
(0.134)
(0.368) (0.164)
0.627
2.037*
0.812
(0.678)
(1.041) (0.628)
-0.402** -0.0860 0.0445
(0.170)
(0.309) (0.309)
0.0773
-0.0655 -0.0895
(0.0671) (0.132) (0.123)
-12.36
-20.06* -11.53*
(7.722)
(10.66) (6.393)
Extensive
margin
(5)
(6)
Note: Robust standard errors in parenthesis. *** p<0.01, ** p<0.05, * p<0.1. Odd-numbered columns are OLS estimations,
even-numbered IV-2SLS. 1975 Vietnamese refugees is the IV.
Observations
R-squared
Cragg-Donald F
Constant
Export structure
Remoteness
Income per capita
Vietnamese share of Asian migrants
Exports to Vietnam Exports to Vietnam
share of exports
share of GDP
(1)
(2)
(3)
(4)
Table 6: Results Regressing Vietnamese Migrants as a Share of Asian Migrants as the Dependent Variable
42
76.35**
(33.84)
-3.177
(2.152)
25.30
(22.02)
558.5**
(266.2)
30
0.269
-2.426
(2.238)
17.86
(23.09)
405.3**
(149.9)
0.469***
(0.173)
-1.818
(1.753)
8.381
(17.72)
30
0.255
0.527***
(0.166)
-1.990
(1.758)
9.659
(17.82)
-0.723
(2.969)
10.93
(31.20)
54.05
(36.52)
30
0.139
-3.979*
(2.417)
45.48*
(24.78)
395.3*
(239.2)
30
0.253
IV estimates
0.332
(0.212)
-3.017
(2.140)
33.50
(21.81)
30
0.150
Observations
30
30
30
30
30
30
R-squared
0.231
0.252
0.068
0.252
0.143
Cragg-Donald F
8.921
6.106
77.86
8.921
6.106
77.86
0.0133 0.0623
0.00159
0.0133
0.0623
0.00159
Note: Robust standard errors in parenthesis. *** p<0.01, ** p<0.05, * p<0.1. 1975 Vietnamese refugees is the IV.
Constant
Income per capita
Vietnamese
1.423
(2.961)
-23.51
(30.83)
30
0.134
Observations
R-squared
Constant
0.259
(2.679)
-9.957
(27.77)
28.60**
(13.38)
Income per capita
Vietnamese
Imports from Vietnam share of GDP
(4)
(5)
(6)
OLS estimates
30.58**
(13.46)
427.2***
(141.4)
0.427**
(0.206)
-1.295
-4.136*
-3.296
(2.822) (2.374)
(2.085)
17.59
47.03*
35.57
(29.37) (24.49)
(21.46)
Table 7: US Imports from Vietnam: The Nostalgia Effect
Imports from Vietnam share of imports
(1)
(2)
(3)
30
6.106
0.0623
8.921
0.0133
-0.974
(0.807)
8.087
(8.228)
323.0**
(129.9)
30
0.231
-0.0841
(0.981)
-0.740
(10.09)
141.4***
(41.42)
30
1.686
(1.453)
-20.14
(15.14)
44.16***
(17.00)
30
0.139
0.871
(1.104)
-10.66
(11.43)
10.73**
(4.670)
30
0.539
77.86
0.00159
0.271***
(0.0691)
-0.189
(0.577)
-1.699
(5.851)
30
0.542
0.295***
(0.0622)
-0.258
(0.551)
-1.188
(5.730)
Extensive margin
(7)
(8)
(9)
43
51
0.322
10.31
0.0207
51
0.123
13.52
0.00287
1.060
(1.085)
-0.895***
(0.332)
0.245
(0.159)
-21.53*
(11.09)
55.11***
(18.00)
51
0.273
10.31
0.0207
455.6***
(176.3)
-1.907*
(1.116)
-0.422
(0.659)
0.525***
(0.129)
16.43
(10.80)
13.52
0.00287
51
3.908**
(1.677)
-0.526
(0.630)
-0.428
(0.264)
-55.79***
(15.07)
45.27**
(22.39)
51
0.075
10.31
0.0207
374.3*
(191.1)
1.471
(1.506)
-0.138
(0.539)
-0.198
(0.203)
-24.61
(16.59)
51
0.040
13.52
0.00287
-2.040
(1.502)
-0.526
(0.515)
-0.312
(0.249)
14.82
(16.91)
23.53
(21.89)
51
0.071
10.31
0.0207
194.6
(175.7)
-3.307**
(1.650)
-0.324
(0.611)
-0.192
(0.207)
31.03*
(18.11)
Reference-priced goods
share of exports
share of GDP
(5)
(6)
(7)
(8)
46
0.112
10.08
0.00816
-2.829**
(1.385)
-0.385
(0.491)
-0.422**
(0.196)
16.44
(12.61)
12.07
(21.41)
46
0.184
9.138
0.0266
98.06
(155.2)
-3.538***
(1.261)
-0.271
(0.476)
-0.367**
(0.153)
25.52*
(13.30)
46
0.112
10.08
0.00816
-2.543
(3.047)
-0.401
(0.680)
-0.295
(0.266)
19.40
(29.51)
45.97
(33.11)
46
0.149
9.138
0.0266
373.4
(246.1)
-5.241**
(2.371)
0.0350
(0.669)
-0.0849
(0.268)
53.97**
(22.53)
Organized-exchange goods
share of exports
share of GDP
(9)
(10)
(11)
(12)
Note: IV-2SLS estimates. 1975 Vietnamese refugees is the IV. Robust standard errors in parenthesis. *** p<0.01, ** p<0.05, * p<0.1.
Observations
R-squared
Cragg-Donald F
Constant
Export structure
Remoteness
51
0.363
13.52
0.00287
251.2***
(87.92)
1.287*
-0.349
(0.666)
(0.642)
-0.463*
-0.203
(0.250)
(0.229)
0.128
0.282***
(0.0952)
(0.101)
-27.70***
-6.777
(6.559)
(6.305)
Income per capita
30.38***
(8.650)
Differentiated goods
share of exports
share of GDP
(1)
(2)
(3)
(4)
Table 8: The Pro-Trade Effect across Product Categories - Rauch
44
Vietnamese as a share of pop
Share of total exports Share of GDP
0.85
0.89
0.42
0.40
0.56
0.44
0.61
0.57
0.21
0.19
0.57
0.38
0.44
0.49
0.64
0.78
0.24
0.31
0.45
0.46
0.12
0.30
0.41
0.49
0.51
0.43
0.48
0.47
0.24
0.34
0.39
0.51
0.14
0.12
0.41
0.41
0.33
0.29
0.33
0.35
0.54
0.51
0.14
0.19
0.12
0.18
0.37
0.44
0.60
0.56
0.59
0.60
0.31
0.38
0.22
0.31
0.56
0.59
0.66
0.60
0.30
0.35
Note: Standardized beta coefficients of IV 2SLS estimation. 1975 Vietnamese refugees is the IV. Bold ones are significant at least at the 10% level.
Vietnamese as a share of migrants
NAICS Description
Share of total exports Share of GDP
111
1.07
1.12
112
0.53
0.50
113
0.71
0.55
114
Fish, Fresh/chilled/frozen & Other
0.77
0.71
211
Oil & Gas
0.27
0.24
212
Minerals & Ores
0.72
0.49
311
0.55
0.61
312
0.81
0.98
313
Textiles & Fabrics
0.30
0.40
314
0.57
0.57
315
0.15
0.38
316
0.52
0.61
321
Wood Products
0.65
0.54
322
Paper
0.60
0.59
323
Printed Matter And Related Products
0.31
0.43
324
0.49
0.64
325
Chemicals
0.18
0.15
326
0.51
0.51
327
0.41
0.37
331
Primary Metal Mfg
0.42
0.44
332
0.68
0.65
333
0.17
0.23
334
0.16
0.23
335
Electrical Equipment, Appliances
0.46
0.55
336
0.76
0.71
337
0.75
0.76
339
0.40
0.48
511
Newspapers, Books & Other Published
0.28
0.40
910
Waste And Scrap
0.70
0.74
920
Used Or Second-hand Merchandise
0.83
0.75
990
Special Classification Provisions
0.38
0.44
Table 9: The Pro-Trade Effect across Product Categories - NAICS
Table 10: The Pro-Trade effect by Gender, Ethnicity, Language and Skills
Exports to Vietnam Exports to Vietnam Extensive
Exports
share of exports
share of GDP
margin
to Vietnam
(1)
(2)
(3)
(4)
Females
55.12***
69.80***
73.25***
220.6***
(20.30)
(23.14)
(14.90)
(49.67)
Males
50.37***
63.79***
66.95***
201.6***
(19.42)
(21.37)
(14.23)
(47.41)
Ethnic Vietnamese
31.76**
40.22***
42.21***
127.1***
(12.39)
(13.64)
(9.016)
(30.50)
Ethnic Chinese
353.8***
448.1***
470.3***
1,416***
(111.8)
(145.8)
(149.1)
(371.7)
Bad English
79.33***
100.5***
105.4***
317.5***
(30.39)
(33.48)
(22.26)
(73.72)
Good English
39.52***
50.05***
52.53***
158.2***
(14.81)
(16.69)
(10.87)
(36.32)
Low skills
152.5**
193.1**
202.6***
610.2***
(62.83)
(75.28)
(58.23)
(187.2)
High skills
35.90***
45.46***
47.71***
143.7***
(12.96)
(14.37)
(8.877)
(29.74)
Note: Each coefficient is estimated in a separate regression using 1975 Vietnamese refugees as IV. Control
variables included: Income per capita, Remoteness, and export structure. Robust standard errors in
parenthesis. *** p<0.01, ** p<0.05, * p<0.1.
45
Table 11: The Pro-Trade Effect across Migrant Occupations
Occupation
Managerial
Share of total exports
0.35*
(0.19)
Engineers & Scientists
0.33**
(0.16)
Other Professionals
0.29**
(0.14)
Technical, Sales & Administrative Support
0.38
(0.23)
Service
0.48
(0.35)
Farming, Forestry & Fishing
0.25**
(0.11)
Precision, Production, Craft & Repair
0.55**
(0.21)
Operators, Fabricators & Laborers
0.36
(0.23)
Military
1.12
(0.84)
Share of GDP
0.47**
(0.21)
0.44**
(0.16)
0.39**
(0.16)
0.51**
(0.26)
0.63
(0.39)
0.33**
(0.12)
0.74**
(0.3)
0.48**
(0.28)
1.49
(0.95)
Extensive margin
0.65***
(0.14)
0.61***
(0.11)
0.54***
(0.12)
0.71***
(0.22)
0.89**
(0.38)
0.46***
(0.1)
1.03**
(0.46)
0.67**
(0.29)
2.09
(1.46)
Note: Each coefficient is estimated in a separate regression using 1975 Vietnamese refugees as IV. Control
variables included: Income per capita, Remoteness, and export structure. Robust standard errors in
parenthesis. *** p<0.01, ** p<0.05, * p<0.1.
46
47
Note: IV estimates with State fixed effects. WTO (FTA) × 1975 Vietnamese refugees is used as IV. Robust
standard errors in parenthesis. *** p<0.01, ** p<0.05, * p<0.1.
Exports to Vietnam share of exports
Exports to Vietnam share of GDP
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
FTA
-0.798
-0.198
-0.982
-0.383
(1.369)
(0.708)
(1.464)
(0.759)
WTO
-0.544
0.0403
-0.430
0.0897
(0.380)
(0.191)
(0.400)
(0.202)
FTA × Vietnamese share of migrants
0.138
0.136
(0.154)
(0.162)
WTO × Vietnamese share of migrants
0.124***
0.116**
(0.0426)
(0.0455)
FTA × Vietnamese share of pop
19.61
19.36
(21.88)
(22.78)
WTO × Vietnamese share of pop
17.49***
16.75***
(5.854)
(6.370)
Income per capita
0.647
-0.293
-1.027
-2.551
-4.016
-0.584
-5.554*
-3.157*
(5.137)
(1.884)
(4.375)
(1.836)
(3.489) (1.796)
(2.978)
(1.778)
GDP
-6.459**
-0.418
-6.296**
-1.070
(3.062)
(1.485)
(2.982)
(1.520)
Observations
304
304
304
304
304
304
304
304
R-squared
0.265
0.386
0.257
0.356
0.225
0.439
0.218
0.427
Cragg-Donald F
242.0
779.0
19.96
105.5
217.3
741.7
20.97
94.47
6.05e-06
0
0.000297
0
5.93e-06
0
0.000256
0
Table 12: the Pro-Trade Effect of Migrant Networks and Trade Policy Changes
Table 13: Top Vietnamese Metropolitan Areas - 1995
Metropolitan area
Los Angeles-Long Beach, CA
San Jose, CA
Houston-Brazoria, TX
San Francisco-Oakland-Vallejo, CA
Washington, DC/MD/VA
Dallas-Fort Worth, TX
San Diego, CA
Seattle-Everett, WA
New York-Northeastern NJ
Boston, MA-NH
Philadelphia, PA/NJ
Atlanta, GA
Sacramento, CA
Portland, OR-WA
Chicago, IL
Vietnamese
200,984
79,961
46,839
46,489
33,845
30,279
28,058
24,796
21,579
20,155
17,604
17,273
16,427
14,485
13,185
Metropolitan area
Vietnamese
Minneapolis-St. Paul, MN
12,222
Riverside-San Bernardino,CA
11,856
New Orleans, LA
10,636
Honolulu, HI
8,207
Denver-Boulder, CO
7,819
Oklahoma City, OK
6,102
Phoenix, AZ
5,985
Tampa-St. Petersburg-Clearwater, FL
5,596
St. Louis, MO-IL
5,237
Austin, TX
5,207
Stockton, CA
5,128
Orlando, FL
5,046
Wichita, KS
4,997
Charlotte-Gastonia-Rock Hill, NC-SC
4,511
Tacoma, WA
4,276
48
Table 14: The Vietnamese in the Unites States - 1995
State
California
Hawaii
Washington
Texas
Oregon
Massachusetts
Virginia
Louisiana
Kansas
Minnesota
Oklahoma
Colorado
Maryland
District of Columbia
Nevada
Utah
Georgia
Iowa
Pennsylvania
Arizona
Nebraska
Florida
Missouri
Connecticut
New Jersey
North Carolina
Alaska
Illinois
New York
New Mexico
Arkansas
Mississippi
Alabama
Michigan
North Dakota
Tennessee
Vermont
Delaware
Ohio
Rhode Island
South Carolina
Idaho
South Dakota
Kentucky
Indiana
Wisconsin
New Hampshire
Maine
West Virginia
Wyoming
Montana
Vietnamese % of pop % of migrants 1975 refugees
364192
1.15
4.40
30495
7767
0.65
3.48
2411
31103
0.57
5.72
5205
82142
0.43
3.26
11136
12411
0.39
5.18
2448
23890
0.39
3.18
1439
24566
0.37
4.79
5620
14947
0.34
11.70
3916
6794
0.26
5.90
1953
11483
0.25
5.71
4250
8055
0.24
6.74
3716
8995
0.24
3.07
2350
11773
0.23
2.57
2828
1240
0.21
1.80
613
3321
0.21
1.50
519
3763
0.19
3.11
964
13501
0.18
7.01
1622
5094
0.18
7.11
3352
20583
0.17
3.78
8187
7027
0.16
1.33
1444
2433
0.15
4.32
1418
20492
0.14
0.84
5237
7575
0.14
5.53
3154
4634
0.14
1.16
1304
10717
0.13
0.76
1918
9022
0.12
2.91
1334
721
0.12
1.70
94
13543
0.11
0.97
4675
20490
0.11
0.51
4749
1837
0.11
1.27
1047
2280
0.09
3.72
2127
2205
0.08
5.33
493
3368
0.08
3.60
1439
7578
0.08
1.70
2949
502
0.08
3.19
408
3777
0.07
2.91
1250
387
0.07
1.73
106
475
0.07
1.07
173
6961
0.06
2.07
3496
604
0.06
0.51
545
2162
0.06
2.06
926
666
0.06
1.10
421
361
0.05
2.59
604
1881
0.05
2.70
1174
2780
0.05
1.77
2175
2338
0.05
1.34
2461
511
0.04
0.98
171
486
0.04
1.15
376
361
0.02
1.46
268
89
0.02
0.60
143
123
0.01
0.60
360
49
Table 15: Matching NAICS to SIC and the Rauch goods classification
NAICS NAICS description
SIC
Rauch
111
1
w
112
2
w
113
8
r
114
Fish, Fresh/chilled/frozen & Other Marine Products 9
r
211
Oil & Gas
13
w
212
Minerals & Ores
10
w
311
20
n
312
21
n
313
Textiles & Fabrics
n
314
22
r
315
23
n
316
31
n
321
Wood Products
24
r
322
Paper
26
r
323
Printed Matter & Related Products, Nesoi
27
n
324
29, 12
w
325
Chemicals
28
r
326
30
n
327
14, 32
r
331
Primary Metal Mfg
33
r
332
34
n
333
35
n
334
38
n
335
Electrical Equipment, Appliances & Components
36
n
336
37
n
337
25
n
339
39, 3X
n
511
Newspapers, Books & Other Published Matter, Nesoi
n
512
Published Printed Music & Music Manuscripts
n
910
Waste & Scrap
91
n
920
Used Or Second-h& Merchandise
92
n
980
Goods Returned (exports For Canada Only)
n
990
Special Classification Provisions, Nesoi
99
n
Note: The Rauch column tags the categories as w=goods traded on an organized exchange (homogeneous
goods), r=reference priced, n=differentiated products. See Rauch (1999)
50

Migrant Networks and Trade: The Vietnamese Boat People as a

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