Long-Run Impacts of State Integration Policies:
Autonomy and Assimilation in the Democratic Republic
of Vietnam ∗
Mai Nguyen
†
April 2016
Abstract
The incorporation of peripheral groups into a central state is often viewed as an
essential part of the state-building process. While benefits may be conferred to states
that consolidate power, incorporation may have more ambiguous effects for groups
being integrated. In this article, I compare economic outcomes for ethnic minority
communities in Vietnam who were exposed to twenty years of autonomous rule with
those exposed to fully assimilationist policies. In contrast to many scholars that predict
positive returns to assimilation, I find that autonomous rule has a large positive effect
on present day living standards. Using a geographic regression discontinuity design,
I find an approximately 23% increase in household income among communities that
were within autonomous regions. This effect is robust to a variety of specifications
and functional form assumptions. Furthermore, analysis of public service delivery and
participation data reveals that the primary mechanism by which the autonomous region
policy affects contemporary economic development is through increased educational
attainment levels.
∗
I would like to thank Pablo Querubin, David Stasavage, Neal Beck, Saad Gulzar and Renard Sexton
for valuable comments and suggestions. I thank the Mekong Development Research Institute and United
Nations Development Programme in Vietnam for allowing me access to valuable data. I also thank Hannah
Simpson, Megan Metzger, Harsh Pandya, Drew Dimmery, Andrew Peterson, Maria Carreri and Emily West
as well as participants of the NYU Dissertation Seminar, NEWEPS-4 Conference and WESSI meeting for
providing helpful feedback.
†
New York University, Wilf Family Department of Politics, [email protected].
1
Introduction
A crucial part of the state formation process concerns the relationship between the central
state and peripheral regions, with potential policies ranging from complete autonomy for
outlying communities to strict assimilation. Previous scholarly work on state consolidation
has examined the incentives for and consequences of policies towards peripheral regions
from the perspective of the central state. In contrast, this article explores the implications
of autonomy versus assimilation for outlying communities themselves. In short, what are
the long-term political, social and economic implications of state integration on peripheral
groups?
I answer this question by examining a policy enacted by the Democratic Republic of Vietnam
(DRV) in the 1950s in an attempt to incorporate ethnic minority groups of the northern highlands into the newly formed state. After formation of the DRV, officials enacted a policy of
indirect rule that designated specific areas of autonomy for ethnic minorities. Ethnic minorities within these autonomous regions were granted self-governance and cultural preservation,
while ethnic minorities residing outside autonomous areas were subject to direct rule and assimilation by the ethnic majority Kinh. Under autonomous rule, ethnic minorities were given
the rights to solve local affairs, choose their own leaders and representatives, and keep the
use of native languages in political, economic and cultural life (Chung 1968). In autonomous
areas zonal assemblies, administrative committees and militia forces were created and controlled primarily by members of ethnic minority groups. Furthermore, policies were put into
place in autonomous areas that sought to safeguard cultural traditions of ethnic minorities.
This was most apparent in education policy: under autonomous rule, educational instruction
took place in ethnic minority languages (in addition to Vietnamese) and curriculums were
minority-tailored with courses in things such as ethnic literature and art (Kahin 1972). The
Autonomous Region (henceforth referred to as AR) policy lasted from the formation of the
DRV in 1954 until Reunification in 1975. The purpose of this analysis is to determine how
policies of autonomy versus assimilation affect long-term economic outcomes and by what
mechanisms this effect may function.
To identify the effect of the AR policy on contemporary economic outcomes, I leverage a
natural experiment. Drawn by French colonial cartographers, the pre-existing provincial
boundaries that determine if a given peripheral community received the AR policy or not
were drawn arbitrarily with respect to the outcomes of interest. Accordingly, communities
1
from the same ethnic minority group just on one side or the other of the AR boundary
received dramatically different policies with respect to integration, despite being otherwise
identical.
Using georeferenced household survey data I find that geographic location in an AR is positively associated with household income in 2012: being in a former AR increases current
economic performance. The effect remains significant and robust to a range of controls. To
the extent that assignment to the AR treatment is not completely random, the estimates
using standard OLS regressions are not causally identified. Therefore, I also employ a geographic regression discontinuity (RD) design. Using this approach, I am able to exploit
plausibly exogenous variation in AR treatment assignment at the boundary and identify its
effect on economic outcomes. I use a semi-parametric approach limiting analysis to samples
falling within various bandwidths around the AR boundaries and fitting smooth functions
of geographic location. Using this approach I find a long-run AR effect increases household
income by around 23% for subject areas. The effect is robust to a wide range of specifications using various functional forms and controls. This result shows that being subject to a
policy of autonomy during the nascent stages of state formation in north Vietnam increases
contemporary economic performance.
It would make intuitive sense why policies of autonomy could improve economic development
in the short term compared to policies of forced assimilation; however, the question is how
does autonomy come to affect long-term economic performance? That is, by what channels
do policies enacted in regards to incorporating peripheral groups affect economic outcomes
today? I examine three possible mechanisms: development of leadership capacity, local
governance and education. The AR policy could affect contemporary economic outcomes
through the improvement of the capacity of minority leaders and increased representation.
Previous studies have shown the effect of minority representation on policy choices (Pande
2003; Chattopadhy and Duflo 2004). Ethnic minorities in former ARs may be better represented today because ethnic groups were able to train leaders and build political networks
during the years the policy was still in place. Higher contemporary economic performance in
ARs then could be attributable to increased ethnic minority leadership capacity and representation in government. The AR policy could also have come to affect economic outcomes
by spurring the development of ethnic-based institutions that provide for more efficient local
governance and public goods provision (e.g. Acemoglu, Johnson and Robinson 2002; Nunn
2008; Banerjee and Iyer 2005; Dell 2010; Dippel 2014). Finally, the AR policy could have
contributed to increased economic outcomes by affecting educational attainment. If the ed2
ucation system in ARs raised achievement levels, the increased contemporary earnings could
be attributed to higher levels of educational attainment.
To tease out the mechanism for the long term income effect, I examine the effect of AR
policy on present day political participation and representation, public goods provision and
education levels. My results indicate that being in a former AR does not increase participation in People’s Committees, local branches of the Communist Party or the Vietnam
Fatherland Front. Furthermore, I do not find any evidence of long-term effects on public
goods provision between autonomous and non-autonomous regions; this indicates that the
AR policy does not affect income through increased local governance. I do find that those
residing in former ARs are much more likely to have finished primary school. These effects
are strongest for ethnic minority respondents who are above 40 years old, those who would
have been impacted directly by the AR policy. These results provide evidence in favor of an
education mechanism but not a representation nor a local governance mechanism, suggesting
that autonomy improves economic outcomes by fostering human capital.
This study contributes to the ongoing scholarly debate in the social sciences on state formation, ethnic inequality and economic development. The literature on state consolidation often
regards the integration of peripheral regions as a positive development, with the formal state
improving welfare outcomes for “ungoverned” areas through stability, public goods provision
and urban market access. The results from the AR policy in Vietnam suggest that assimilation instead puts minorities at an economic disadvantage relative to dominant groups.
The results provide important evidence for the debate on ethnic inequality in multi-ethnic
societies, suggesting that under certain circumstances disadvantaged groups can do better
with autonomy as opposed to assimilation. Similarly the education mechanism illustrates
the importance of building human capital in minority communities as a means of escaping
the poverty trap.
Most studies looking at ethnic minority economic development tend to focus on the disparities
in living standards between ethnic groups and only examine the proximate determinants such
as geographic endowments, lack of access to credits and markets, and social norms (Van de
Walle and Gunewardena 2001; Baulch et al. 2007; Baulch et al. 2012; Imai and Gaiha 2011).
This study, to the best of my knowledge, is one of the first quantitative analyses of the effect
of historical institutions on contemporary ethnic minority economic performance.
There are several reasons that my are relevant beyond the specific case of the DRV. There
are ongoing debates in multi-ethnic countries around the world regarding partial and full au3
tonomy for minority zones, such as for minority groups in Myanmar, South Sudan, Iraq, and
Turkey, and indigenous communities in numerous Latin American countries. Second, Vietnam has a politically empowered majority ethnic group, and numerous smaller and typically
marginalized ethnic minority groups, similar to many other contexts. Lastly, as a postcolonial and post-conflict state, Vietnam is grappling with state integration with constraints
that reflect many developing and conflict-affected countries: how do you consolidate a society
that includes embedded inequalities and societal lines in part inherited from outsiders?
The rest of the paper is organized as follows: Section 2 explores our theoretical understanding of state integration of peripheral areas. Section 3 provides a brief background of the
Autonomous Region policy in the DRV. Section 4 describes the data and measurements
used as well as the estimation framework employed to examine the impact of the AR policy.
Section 5 shows the baseline results of examining autonomy and income. Section 6 provides
evidence on mechanisms, and section 7 concludes.
2
State Integration: Beyond the “Civilizing Mission”
Many discussions of state incorporation are based on a state-centered approach that emphasizes the costs and benefits of integrating peripheral areas from the standpoint of the
central state, tending to overlook the impact on the populations being incorporated. That
is, the literature concerning state formation, with a few exceptions, often ignores the individual strategic reactions and welfare implications produced by encroachment of the central
state apparatus on peripheral populations. This tendency stems from the assumption that
integration of different populations into a centralized state system is desirable in as much as
states can provide social and economic stability. Incorporation of peripheral groups is typically styled as economic and social development to assist in lifting these populations from
“barbarism” and allowing them to partake in the security and monetary benefits conferred
by modern central states. However, much evidence points to the idea that being under state
rule may in fact be harmful to these groups and that the disadvantages from being confined
to central authority is what actually drives these populations to seek refuge in the peripheries
far from the locus of state power.
In reference to the highland minorities in the Southeast Asian Massif, Michaud (2000b) notes
that these peripheral populations can be seen as ”refugees displaced by war and choosing
to remain beyond the direct control of state authorities, who sought to control labor, tax
4
productive resources, and secure access to populations from which they could recruit soldiers,
servants, concubines and slaves” (11). This sentiment is echoed by Scott (2009), who argues
that when conditions of servitude and economic subjugation became overwhelming, subjects
would move to the periphery to distance themselves from the state: “the economic, political
and cultural organization of such people is, in large part, a strategic adaptation to avoid
incorporation in state structures” (39). The implication from both authors is that being a
part of the central state apparatus is welfare-reducing for these populations. It is important
to note not all people are harmed by living under central state rule: many people may find
the security and economic benefits outweigh the costs of state encroachment. But for many
reasons—possibly, due to cultural disparities or differential treatment under state rule—many
people living on the periphery found that being outside of state reach was more beneficial
for them and chose to distance themselves from central state power. With the advent of
numerous technological innovations that reduce the cost of state expansion, these areas that
were previously ungoverned or at the periphery are now unable to escape state control. To
the extent that they are no longer able to distance themselves from the central state, what
happens to peripheral groups when they inevitably become integrated?
Direct rule and assimilation has long been the favored policy to incorporate peripheral groups
and the primary method by which to raise the economic performance of minority groups.
French authorities of Indochina viewed the colonial undertaking as a “civilizing mission”
both culturally and economically, that is, the purpose was the making over of non-European
peoples in the image of “civilized” Europeans (Lewis 1962). Similarly, many members of the
Kinh majority from the time of independence held the belief that if prosperity was to be
achieved, the “minority peoples should overcome their age-old economic, cultural and social
backwardness” (Chung 1968: 18).
However, it is unclear whether assimilation should be viewed as the only and best policy.
The emphasis on assimilation policies stems from ethnocentric perspectives that fail to take
into account ethnic differences in preferences, skills and behaviors. Assimilationist policies
(especially if they are forced) could be very harmful for the long-term welfare of a group to
the extent that groups will be forced into a sector in which they do not have a comparative
advantage. For example, forcing ethnic minorities to adopt a lowland model of monocrops of
fruit or wet rice cultivation may not be sustainable given that they tend to live in highland
remote areas with less access to high inputs of fertilizer and pesticides (The World Bank
2009). The end result will be that ethnic minorities will be unable to catch up to “majority
levels of success.” This may also contribute to the high levels of ethnic inequality in Vietnam
5
today. 1 Here, higher levels of state encroachment would prove to be welfare-reducing to
subject communities.
Alternatively, policies of autonomy may produce positive long-term economic outcomes in the
sense that minority groups would be able to build local institutions and strategies of economic
development suited to their own needs and strengths. This idea is related to arguments in
favor of decentralization. Greater local authority in decision-making (both politically and
fiscally) can improve the efficiency of public service delivery because government outputs
can be adjusted depending on local needs (Besley and Coate 2003). Oates (1972) argues:
“the tailoring of outputs to local circumstances will, in general, produce higher levels of
well-being than a centralized decision to provide some uniform level of output across all
jurisdictions” (130). Furthermore, decentralization creates competition for capital and labor,
which leads to improved governance outcomes (Tiebout 1956; Inman and Rubinfeld 1997).
Centralized decision-making may be more appropriate in certain contexts: when spillovers
are possible and there is no heterogeneity in preferences, centralized provision of public goods
is more efficient (Oates 1972). Centralization can also exploit economies of scale better in the
construction of overhead facilities, but these economies of scale are less important in local
management and maintenance (Bardhan 2002). This notion is furthered by Malesky (2014):
recentralization in Vietnam increased public service delivery for things that were important
to central leaders, but did not impact and even decreased public service delivery for things
that local populations found more important. Autonomy and decentralization would allow
for more effective local governance catered towards ethnic minority interests, in turn raising
living standards and long-term economic outcomes for ethnic minorities living within the
autonomous regions.
One can also think about autonomous regions as a type of “ethnic enclave,” a topic that has
received a great deal of attention in the economics literature on immigration. Scholars are
divided about the effect of such enclaves (geographic locations of high ethnic concentration)
on labor market outcomes. On one side it is argued that the presence of ethnic enclaves prevents the adoption of important host-country or majority-based skills (Xie and Gough 2011).
However, ethnic enclaves may be beneficial because they represent a network that increases
the opportunities for gainful trade by disseminating information on economic opportunities
1
There are stark differences between the Kinh majority and ethnic minorities in terms of poverty rate:
ethnic Kinh experience a poverty rate of 10 percent while the average for all other ethnic groups is 52 percent
(The World Bank 2009). Additionally, vulnerability (defined as the probability of falling into poverty from
one time period to the next) is much higher for ethnic minorities at approximately 62 percent compared to
the Kinh majority at 7 percent (Imai and Gaiha 2011).
6
(Edin et al. 2003; Damm 2009).
3
The Autonomous Region Policy in the DRV
Under imperial rule in Vietnam during the 18th century, ethnic groups other than lowland
Kinh were on the periphery of state control and largely left to handle their own affairs. By
1802, most of the mountainous areas in the north had fallen into the court of Hue’s political
domain, however, only very nominally. Many ethnic tribal groups such as the Tho (now
Tay), Nung, Man and Meo (now H’mong) lived under their own local chiefs and would only
occasionally present tribute to Hue (Woodside 1971). Peripheral and mountainous districts
were given distinct names (chau) to differentiate them from standard districts (huyen) headed
by Kinh mandarins (Michaud 2000a: 337). A large proportion of territory of the North was
classified as remote and administrative networks were only marginally operational (Dang
Phuong-Nghi 1969).
Similarly, during the French colonial era ethnic groups of the highlands (termed Montagnards by French colonial administrators) were largely left alone except when it came to issues
directly related to French interests. For much of the colonial era the French only acknowledged Kinh and Chinese as important ethnic identities; whereas, other ethnic tribal groups
living in the high regions were considered primitive and typically classed as looters or bandits
(Michaud 2000a: 344).
Ethnic minority groups of the highlands did not become truly important to colonial authorities and majority highlanders until the First Indochina War. During this time, wartime
alliances with ethnic minorities became vital amidst growing unrest fomented by Vietnamese
nationalists and Communists against the French colonial regime. In the aftermath of 1945
August Revolution, French authorities attempted to regain control of northern territory and
the support of ethnic highlanders by allying with the White Tai of Song Chau Tai. The
Viet Minh and communist cadres also attempted to gain ethnic minority support by offering
lower taxes in minority areas, providing supplies and opening schools that taught in minority
languages (McElwee 2004: 191). After a series of military blunders, the French managed to
alienate a large number of ethnic groups who then defected to the Viet Minh: “when the
Battle of Dien Bien Phu finally took place in spring of 1954, many Black Tai from Son La
and many White Tai, Hmong, Yao, and Khmu from the Sip Song Chau Tai, not counting the
Thos [Tay] and other montagnards from east of the Red River already enrolled in the Viet
7
Minh’s forces, had made themselves available to the Communists” (Michaud 2000a: 353).
The ultimate success of the 1945 revolution and the Dien Bien Phu victory could not have
been possible without support from the ethnic minorities (Ibid.).
[Figure 1 about here.]
Once the Democratic Republic of Vietnam was established in July of 1954, the communist
leaders adopted a new policy towards ethnic minorities. The goal of the newly formed
government was to reward ethnic allies and consolidate the political gains made among
the minorities of the northern highland region (Michaud 2000a: 354). Borrowing from the
Chinese model towards national minorities, two autonomous regions were created: the ThaiMeo Autonomous Region (later renamed Tay Bac) and the Viet Bac Autonomous Region.
Figure 1 shows a map of the AR boundaries. The Tay Bac AR was established by decree on
May 7, 1955 and encompassed an area equivalent to three provinces (Lai Chau, Son La and
Nghia Lo) between part of the Red River Valley to the east, the Laotian border to the west
and the Yunnan Province to the North (Moseley 1975: 157-158). The area had a population
of about 500,000 and included over 25 different ethnic minority groups (Ibid.). The Viet
Bac AR, with a population of 1.5 million, was created on August 19, 1956, incorporating
five provinces (Ha Giang, Cao Bang, Tuyen Quang, Bac Thai and Lang Son) from the Red
River Valley to the province of Kwangsi (Ibid.: 158).2
The land borders of Vietnam (along with many other countries in the Southeast Asian
Massif) are artificial creations of the colonial period: the boundaries drawn under French
colonialism in Indochina were largely unrelated to the cultural, geographical and racial elements, which shaped the peoples and governments of its constituent parts (St. John 1988).
During imperial Vietnam, conceptions of boundary were centered on local geography and
sovereignty within the context of divine kingship, and the limits of a realm were defined
vaguely in terms of allegiance of outlying villages to the center of the kingdom rather than
by a central authority (Ibid.). French administrative reorganization of Indochina resulted
in a strong centralized leadership but not political nor administratively homogenous entities (Dommen 2002). French minority policy for the mountainous regions of Indochina is
described as a colonial divide-and-rule policy guided by ad hoc considerations (Salemink
2003). After Independence, the DRV established the AR policy and selected provinces for
inclusion that had large populations of ethnic minorities. However, because the policy was
2
Additionally, the central government intended to create a third autonomous region encompassing the
provinces of Lao Cai and Yen Bai between the Tay Bac and Viet Bac regions; however, the plan was
abandoned in 1959 (Ginsburgs 1962).
8
based on arbitrary French colonial borders, many ethnic groups were split across boundaries.
Decisions on which areas to include in the ARs appears to have been made haphazardly:
Ginsburgs (1963) describes one of the regions as being “an artificial and heterogeneous agglomeration of disparate tribes, lacking a definite ethnic rationale for its existence other than
the mere negative fact that minority groups inhabited the territory.”
The administration of these autonomous regions were meant to follow the ideals set forth in
resolutions of the communist party’s First National Congress in 1935 3 : “each nationality
of the Union will enjoy, in addition, the right to autonomy, that is, the right to solve local
affairs, to use its mother tongue in its political, economic and cultural life, and to choose its
own leaders in political and economic affairs” (Chung 1968: 12).
In 1955 and 1956, multiple presidential edicts solidified the autonomy policy and outlined
the administration of autonomous regions.4 The ARs were to be modeled under a system
of “democratic socialism” with central authority coming from a zonal people’s council and
corresponding administrative committee. Some functional matters that fell under the jurisdiction of local AR authorities include: the right to open schools and assign personnel, issue
special ordinances, and form its own military detachments or security forces for maintenance
of order and defense of the area. In regards to financial matters, the AR central council and
committee would manage the local finances—as in, control income and expenditures—but
part of the revenue had to be deposited in the Central State Bank. Finally, the preservation
of every nationality in terms of lifestyle and beliefs was legally enshrined: it became forbidden to use administrative fiat or coercion to bring about any changes in the customs and
habits of any nationality. Furthermore, the public and private use of each ethnic groups own
language would not be impinged. In short, autonomous regions were free to set out their
own social and economic development plans, insofar as they did not interfere with the goals
of the nation-wide central state plan.5
These ideals of cultural preservation and self-governance were further codified in the 1960
Constitution. Within autonomous zones, the constitution outlines the rights of ethnic mi3
Communist leaders originally advocated for the right to self-determination for minority peoples and
the possibility of declaring a separate state; however, after gaining power national leaders became more
circumspect of the idea of independent states for minorities and instead adopted the policy of autonomy
under a unified, multinational state (see Michaud 2000a for discussion).
4
Presidential Decree no. 230: Resolution on the Creation of the Thai-Meo Autonomous Zone (1955).
Presidential Decree no. 268: Resolution on the Creation of Autonomous Region of Viet-Bac (1956).
5
See Ginsburgs 1962 and Ginsburgs 1963 for more detailed discussion of government administration in
the DRV.
9
norities to appropriate representation in government 6 , administer local finances, public
security and statues 7 , and preserve or reform their own national cultures 8 .
In practice it is unclear whether the tenants outlined in the constitution were carried out
fully due to the paucity of available administrative records from the time period. However,
ethnographic accounts show that the ideals of self-governance and cultural preservation were
enforced at least at a very basic level. In autonomous areas zonal assemblies, administrative
committees, and militia forces were created (McElwee 2004: 192). Additionally, state-wide
policies were adapted at the local level in autonomous regions according to the needs of the
ethnic minorities. One example of this is the organization of cooperatives (under collectivization policies the DRV had began to enact as steps towards a larger socialist goal): the
size, character and steps in establishing cooperatives varied dependent upon the conditions
of the different minority groups in the autonomous regions (Kahin 1972: 585).
Representation was also higher for ethnic minorities in the autonomous regions. Members of
minority groups occupied almost all important administrative positions in the Viet Bac and
Tay Bac Autonomous Regions as well as in the central DRV administration (Kahin 1972:
586). In 1959 it was reported that in the Tay Bac region the people’s council was made up
of 139 delegates belonging to 17 nationalities and the administrative committee was made
up of 24 members belonging to 11 nationalities (Ginsburgs 1963: 203). Similarly, the in the
Viet Bac region, the administrative council included 17 people representing 15 nationalities
(Ibid.).
Finally, cultural preservation was advocated for in the autonomous regions, especially within
the education system. Educational instruction in autonomous regions was in ethnic minority languages for the formative years or primary school; whereas, outside of these areas
courses were taught solely in Vietnamese. Additionally, the minority-tailored curriculum in
autonomous regions included courses given on the culture of the minority groups including
literature and music (Kahin 1972: 584).
It is important to note that although the central government of the DRV had a seemingly
friendly attitude towards ethnic minorities, the policies did not stem from purely altruistic
motives. Cultural preservation was valued; however, the majority Kinh did not value the
actual cultures of ethnic minorities. During this time period, the common attitude was that
6
Constitution of the Democratic Republic of Vietnam 1960, Article 93.
Ibid., Article 94 and 95.
8
Ibid., Article 3 and 96.
7
10
upland peoples and ethnic minorities were “backwards” and inferior to the Kinh majority
(Michaud 2000a; McElwee 2004). 9 Policies enacted by the regime toward ethnic minorities
of the highland region were double-sided. Autonomous regions were granted to consolidate
gains made in regards to the northern high region and prevent uprisings from ethnic minorities. The ultimate goal would become “attaching these ethnicities to mainstream Vietnamese
society, making the Marxist-Leninist revolution triumphant across Vietnam” (Michaud 2006:
233). Indeed, Ginsburgs (1962) notes:
...looking for a proper way to handle the thorny problem of the mountain people,
Hanoi tacitly acknowledged from the very start that it would have to proceed with
extreme circumspection and, as a result, heavily emphasised throughout a gradual and thoroughly pragmatic approach, seeking to bring about desired changes
in the existing tribal patterns in line with its own ideological plans primarily
by means of a concerted campaign of propaganda and political indoctrination
ostensibly devoid of any overt element of pressure or force. This per se constituted perhaps the best possible evidence, and confession, of the precariousness
of Hanoi’s foothold in and the uncertainty of its influence over the traditionally
centrifugal border areas, a predicament which the regime itself did not fail to
recognise and take into careful consideration when devising a long-range policy
for resolving the potentially explosive issue of the country’s ethnic minorities
(218).
After the Communists’ final victory in the Second Indochina War and reunification in 1975,
the ARs were no longer considered necessary and were dissolved (Michaud 2006). All regions became subject to central communist rule in the Socialist Republic of Vietnam, and
central government authorities could begin their work to fully assimilate all ethnicities into
mainstream Vietnamese society.
4
Research Design
In order to determine the effect of the AR policy, I test the impact of being in an AR on
economic outcomes today. Specifically, I examine the impact of ARs on current household
income and wealth levels.
9
The cultural stereotype of backwardness of ethnic minorities persists today and was the basis for many
(ultimately unsuccessful) development programs (Asian Development Bank, 2002).
11
4.1
Estimation Framework
I employ two estimating strategies in order to measure the impact of the AR policy on
current economic outcomes. The first strategy involves using an OLS regression to estimate
the association between being in a former AR and household income today. I flexibly control
for unobservable differences in group dynamics by including ethnic group fixed effects. This
specification allows me to compare households with the same ethnic background but under
different integration policies. The basic regression form is as follows:
yiec = β0 + β1 AutonomousRegionc + β2 Xiec + αe + iec
(1)
y is the outcome variable for household i in ethnic group e residing in commune c, Autonomous Region is an indicator variable for whether or not the commune was located in an
AR, X is a vector of covariates including demographic variables and geographic characteristics, α is a set of ethnic group fixed effects and is the error term. The inclusion of ethnic
group fixed effects allows me to account for any unobservables that vary at the group level.
This basic specification allows me to examine the differences in outcomes between treatment and control groups. However, there may be concerns with selection on unobservables
that are not adequately accounted for using an OLS regression. If certain areas or groups
were strategically selected for to be included in the ARs then treatment and control groups
may not actually be comparable.10 For this reason I also employ a geographic regression
discontinuity (RD) design to estimate the effect of AR treatment. The AR treatment is a
deterministic function of longitude and latitude, making this specification a multidimensional
discontinuity. The geographic RD design allows for more credible causal inference because
variation in treatment at the discontinuity is “as good as random.” Ideally, I would employ
a nonparametric approach so as to not rely on functional form assumptions; however, nonparametric approaches tend to be difficult because they require good estimates of outcome
means in small neighborhoods of the discontinuity (Angrist and Pishke 2009). Therefore, I
follow Dell (2010) and use a semiparametric RD approach that restricts the sample to fall
within various neighborhoods around the discontinuity. This method allows me to distinguish between the treatment effect of the ARs from smooth functions of geographic location
(Ibid.). The regression equation for the geographic RD is similar to equation (1) and is as
10
This is of particular concern in the context of the DRV as provinces were chosen based largely on the
fact that some of the bigger ethnic minority groups resided in those areas.
12
follows:
yiec = γ0 + γ1 AutonomousRegionc + γ2 f (GeographicLocationiec ) + γ3 Xiec + αe + iec (2)
where y is the outcome variable for household i in ethnic group e residing in commune c.
Autonomous Region is an indicator variable for whether or not the commune was located
in an AR. Next, f (GeographicLocationiec ) is the RD polynomial that controls for smooth
functions of geographic location (Dell 2010; Angrist and Pishke 2009). X is a vector of
covariates including demographic variables and geographic characteristics and is the error
term. Again I use ethnic group fixed effects, allowing me to compare households with the
same ethnic background close to the AR boundaries.
Identification under a geographic RD design requires that variation in treatment near the
discontinuity is assigned as if from a randomized experiment (Lee and Lemieux 2010). This
assumption is plausible in the context of the DRV, given that at the local level AR borders
were drawn arbitrarily. Because these boundaries are arbitrary and do not seem to follow any
geographic or demographic considerations at the local level, individual units just inside and
outside of the AR boundaries can be considered comparable. Relatedly, the RD design would
be invalidated if individuals can precisely manipulate the assignment variable or selectively
sort across the treatment threshold (Lee and Lemieux 2010). This potential violation is
especially pertinent in geographic RD designs as individuals are more able to sort precisely
and move across geographic boundaries (Keele and Titiunik 2014). This appears to be
less of a problem in the context analyzed here because ethnic minorities historically have
low levels of migration. Ethnic minorities report very low levels of mobility: in a survey
of migration, only 18 percent of ethnic minorities report having ever venture outside of
their home province (The World Bank 2009). Additionally, analysis of the 2009 Population
and Housing Census shows that ethnic minorities have much lower levels of migration than
their Kinh counterparts: only 2.2% of ethnic minorities made a move during the five years
preceding the census, and of those who did move, half made short-distance (intra-provincial)
moves (Lam 2012).
4.2
Data
Household income and wealth data are taken from household living standards survey collected by the Committee for Ethnic Minorities and United Nations Development Programme
13
(UNDP) in 2012.11 The survey provides a broad range of information on the socioeconomic
status of ethnic minorities. The benefits of this survey are the oversampling of mountainous
and remote areas, thereby providing the most comprehensive and complete dataset on ethnic
minorities in Vietnam, and the georeferencing of households (using GPS coordinates). I am
able to use the GPS coordinates of households to measure the Euclidean distance to the AR
boundary.12 The measure of real income used is calculated by totaling household income
from all productive activities13 and adjusting for inflation. I then take the total, adjust it
for household size and take the natural log to create the primary outcome variable, Log Real
Income Per Capita.
AR boundaries are extracted using digitized maps from Michaud (2000a) and historical military atlases.14 Maps are georeferenced and AR boundaries are matched on to modern day
district borders. Extraction of boundaries is further corroborated with lists of provinces and
districts included in each AR from Moseley (1975) and Kahin (1972). Exogenous geographic
characteristics are calculated using 30 arc second resolution Shuttle Radar Topography Mission (SRTM) elevation data.15 Geographic characteristics are calculated for each household
by overlaying the georeferenced survey data and SRTM elevation data. Using this data I am
able to calculate the Elevation, Slope 16 and Terrain Ruggedness 17 for each household. When
using data that does not include the geolocation of the household, I aggregate up and use
the mean area-weighted elevation, slopeand terrain ruggedness of each commune.18
Covariate data were collected from a variety of archival sources from the colonial era. De11
The survey is entitled the the 2012 Program 135-II Endline Survey. A corresponding baseline survey was
conducted in 2007. The surveys collect data for the entire country; however, the analysis will be restricted
to households residing in north Vietnam (north of the 17th parallel).
12
For households that fall near both ARs, I use the Euclidean distance to the nearest boundary point. For
households in which I do not have precise GPS coordinates, I use the commune centroid as the geographic
location.
13
Including income from farm and non-farm activities, overseas and domestic remittances, and renting out
land.
14
Indochina Atlas, published by the Directorate of Intelligence, Office of Basic and Geographic Intelligence,
U.S. Central Intelligence Agency, retrieved from Perry-Castaneda Library Map Collection of the University
of Texas at Austin.
15
Elevation data accessible from the CGIAR-Consortium for Spatial Information (2008).
16
Slope is calculated with the first order derivative of the elevation at a location, to determine the steepness
relative to the 8 surrounding pixel values, and is measured in degrees.
17
Terrain ruggedness uses the ruggedness index value, calculated for every location, by summarizing the
change in elevation within the 3 by 3 pixel grid. The ruggedness index is measured in meters and is classified
as follows: level (0-80m), nearly level (81-116m), slightly rugged (117-161m), intermediately rugged (162239m), moderately rugged (240-497m), highly rugged (498-958m) and extremely rugged (959-4397m) (Riley
et al. 1999).
18
All spatial analysis and GIS data preparation are completed using open source QGIS software.
14
mographic data were taken from the 1947 edition of the Statistical Yearbook of Indochina.19
The primary demographic variable used is Population Density which measures the number
of inhabitants per square kilometer. To measure pre-treatment economic levels, data on tax
revenue was collected from the archives of the Residence Superieure in Tonkin and Annam.20
Tax Revenue is the total amount of property and personal income tax collected in 1937. Population density and tax revenue data are only available at the province level, making them
very coarse measures. Nevertheless, these variables provide valuable pre-treatment demographic and economic information. Finally, information on the Number of Government Posts
was collected by georeferencing and digitizing colonial era transport maps.21 The digitized
maps were overlayed with administrative boundary shapefiles and the number of government
posts were counted for each commune.
Data used for analysis of mechanisms come from the Provincial Governance and Public Administration Performance Index (PAPI), collected by the Centre for Community Support
Development Studies (CECODES) and UNDP. The PAPI is a survey of 50,000 Vietnamese
citizens measuring their experiences with various dimensions of governance, corruption and
public administration. The PAPI data is used to measure representation and local governance outcomes. Political representation is measured by determining if respondents have
ever served in the People’s Committee, in the leadership of the local Communist Party organization or in the leadership of the Vietnam Fatherland Front (VFF).22 Local governance is
measure by examining public service delivery and access to basic infrastructure. The Public
Service Delivery variable is based on dimension 6 of the PAPI index and is a scaled rating
of citizen experience of public service delivery under four categories: public health, public
education, infrastructure, and law and crime. The public service delivery scale is from 1 to
10 with 10 representing the highest level of public service delivery experience. Infrastructure
is an aggregate index of household access to basic goods such as electricity, clean water,
roads and sanitation services.23 Finally, Primary Education is a dichotomous variable that
19
Annuaire Statisque de l’Indochine published by the Service de la Statistique Generale of the government
of Indochina. Reliable data from the Tonkin region of Indochina became sparse and unreliable after this
edition due to violence as part of the First Indochina War.
20
Collection housed at the Archives Nationales d’Outre-Mer in Aix-En-Provence, France.
21
Carte Routiere du Tonkin, 1935. Made available by the National Library of France Department of Maps
and Plans. gallica.bnf.fr
22
The Vietnam Fatherland Front is a political alliance organization under the leadership of the Communist
Party of Vietnam charged with the roles of supervising government organizations and nominating candidates
for election, amongst other activities.
23
See the PAPI 2013 Full Report for documentation and full explanation of survey methodology and
measurement, available at http://papi.vn/en/documents-and-data-download.html.
15
indicates whether or not a respondent completed primary school.
Table 1 presents summary statistics for households used in the analysis.24 Columns 1 and
2 provide the means of pre-treatment covariates for households residing in non-autonomous
and autonomous regions, respectively. Finally, column 3 tests for the differences in group
means. Households located in ARs tend to be located in areas with higher levels of elevation,
slope (or steepness), and terrain ruggedness. Furthermore, non-autonomous areas tend to
have higher numbers of government posts, population density and tax revenue during the
colonial era. This is unsurprising considering the AR policy was enacted to target ethnic
minorities who traditionally reside in the highland mountain regions that are far from Hanoi,
and therefore, centers of colonial power.
[Table 1 about here.]
In order for a geographic RD approach to be warranted, all relevant factors must vary
smoothly at the discontinuity threshold. In order to test this assumption, I examine each
pre-treatment variable at the discontinuity in figure 3. Each graph presents the local averages
of each outcome, in two kilometer wide bins, plotted against the distance from the AR
boundary (negative distances indicated location outside an AR, while positive distances
indicate location inside an AR). Additionally, each graph is overlayed with a smoothed
linear polynomial and 95 percent confidence intervals based on raw data on either side of the
boundary cutoff. None of the graphs indicate significant jumps in pre-treatment variables
at the discontinuity. Nevertheless, in all specifications I control for these geographic and
demographic characteristics.
[Figure 2 about here.]
5
Autonomy and Economic Performance
5.1
Baseline Results
I begin by presenting baseline results using an OLS regression looking at the relationship
between the autonomous zone indicator and contemporary economic outcomes. Table 2
presents the results from this baseline regression. The dependent variable for all columns is
24
Descriptive statistics for all variables used in analysis can be found in the appendix.
16
the log of real household income per capita. The first column presents results of a basic regression of income on autonomy, the second includes controls for all pre-treatment covariates
and finally, the third column presents results including boundary fixed effects.
[Table 2 about here.]
The point estimates for log real household income per capita are positive and statistically
significant at the 5% level for all specifications including controls as well as boundary fixed
effects. This result shows that a long-run AR effect increases real household income by
between approximately 21% to 23%. Table 2 shows that the AR effect increases household
economic performance in 2012.
The basic OLS specification allows me to examine the differences in outcomes between treatment and control groups, but it does not allow me to account for selection on unobservables.
Therefore, I turn to using a geographic regression discontinuity specification. Table 3 presents
the regression results using the RD specification with various control functions of geographic
location. Panel A shows results using a linear polynomial in latitude and longitude. The
preferred specification uses geographic location as measured in latitude and longitude; however, I present results in panels B and C that use other measures of geographic location to
show results are robust to different control functions. Panel B give results using a linear
polynomial in distance to Hanoi and panel C shows results using a linear polynomial in distance to an AR boundary.25 Column 1 limits the sample to households falling within 100km
of the AR boundary, column 2 to 75km, column 3 to 50km and column 4 presents results
using a Imbens and Kalyanaraman (I-K) data-driven optimal bandwidth (2012).26
Point estimates are higher than those in the OLS specification and remain positive and
statistically significant at the 5% level for columns 1, 2, and 3 and at the 10% level for
column 4 using the linear polynomial in latitude and longitude. Similarly, six out of eight
specifications are statistically significant at the 10% level or better using the linear polynomial
in distance to Hanoi or distance to AR boundary. Coefficients become less precisely estimated
at the smallest bandwidth around the AR boundaries.27 However, the point estimates remain
25
As a robustness check, table A.3 in the appendix presents results using a quadratic polynomial. I limit
my specifications to only linear and quadratic polynomials because higher order polynomials have implicit
weights that are not attractive, results based on higher order polynomial regressions are sensitive to the order
of the polynomial approximation, and conventional inference has poor properties in settings with higher order
polynomial approximations (Gelman and Imbens 2014).
26
These specifications are equivalent to local linear regressions with pre-defined bandwidths around the
discontinuity (Imbens and Lemieux 2008).
27
This may be attributable to the small sample size.
17
fairly stable in magnitude across specifications. The results show that the AR treatment
increases real household income by approximately 23% in the long term (on the conservative
end).
[Table 3 about here.]
5.2
Alternative Specifications
Several different tests were carried out to explore the robustness of my results. The first
addresses heterogeneous effects by subgroup. One potential concern is that the results may
be driven by changes in economic opportunities for the ethnic majority group (Kinh). If
integration of these formerly peripheral regions means an increased availability of natural
resources and land, then increased incomes could just be a product of increased Kinh exploitation of new economic opportunities. Results could then be driven by idiosyncratic
Kinh entrepreneurial and migration patterns rather than by any real effect of being in an
autonomous area. In order to test possibility, I perform a subgroup analysis to determine
who actually benefited from the AR policy. Table 4 presents results of the baseline and geographic RD analysis split up by ethnic minority status. Panel A presents results for ethnic
minorities only, while panel B presents results for the ethnic majority Kinh only. For the
geographic RD specifications in columns 2-5, the control function used is a linear polynomial
in latitude and longitude.
Analysis shows that the effect on income is driven primarily by ethnic minorities. The
point estimates for ethnic minorities are all positive, fairly stable across different bandwidth
specifications and statistically significant at the 10% level or better. The point estimates for
ethnic Kinh are large but vary widely depending on the bandwidth used and are statistically
insignificant. These results suggest that the AR effect on income is not due to changes in
majority Kinh economic situations, but rather a result of direct effect on ethnic minorities.
[Table 4 about here.]
Table 5 presents two other specifications using the baseline regression as well as geographic
RD design with linear polynomials in latitude and longitude and accounting for possible
confounding variables. One potential confounding factor is the presence of development
programs. If households residing in former ARs are more likely to be beneficiaries of targeted development programs, then increases in contemporary economic outcomes may be
18
attributable to the presence of these programs rather than to any long-run effects of the
AR policy. I account for this possibility by examining the presence of the Socio-Economic
Development Programme for the Most Vulnerable Communes in Ethnic Minority and Mountainous Areas, or Program 135 for short.28 The outcome measure for development program
is a dichotomous variable, coded as a 1 for households residing in communes that were beneficiaries of Program 135 and 0 for those residing in communes not assisted by the program.
[Table 5 about here.]
Panel A of table 5 presents the results of analyzing the effect of being in an AR and probability of being a Program 135 beneficiary. Under the baseline OLS specification the point
estimate on autonomy is negative and statistically significant at the 10% level. However,
this effect goes away using the geographic RD design—effects are not statistically significant
with all bandwidths used. Being in an AR does not affect the probability of being a Program
135 beneficiary accounting for pre-treatment covariates and geographic location. These results signal that the effect of the AR policy on income cannot be attributed to differences in
development programs.
Another important factor to examine is the effect of the Vietnam War (or “the American
War”). During the time in which the AR policy was in place, the DRV, assisted by the Soviet
Union amongst other communist allies, was fighting a protracted conflict with the Republic
of Vietnam (South Vietnam), aided by the United States and other anti-communist forces.
While most of the fighting involving ground forces took place in South Vietnam, the United
States Air Force carried out an extensive campaign of aerial bombardment that targeted
many areas in the DRV (Clodfelter, 1995). By March of 1965, U.S. forces were sending
aircrafts against the DRV daily: approximately 25,000 sorties were dropped in 1965 and by
1967 that number had skyrocketed to 108,000 (Turley 2009).
The long term economic impacts of conflict are ambiguous: many scholars argue that conflict suppresses economic development due to destruction of human and physical capital (e.g.
Collier et al. 2003), while others contend that war may have a growth-inducing effect stemming from the development of stronger government institutions in the post-war period (e.g.
Acemoglu and Robinson 2006, Tilly 1975, Tilly 1992, Slater 2005).29 Remaining agnostic
28
Program 135 was established in 1998 and aimed to increase ethnic minority living standards by “promoting production and access to basic infrastructure, improving education, training local officials and increasing
institutional capacity-building” (Quan 2008).
29
For a more thorough discussion of the effects of internal conflict on economic development see Blattman
and Miguel 2010.
19
on the direction of the impact of war on economic outcomes, differential rates of bombing
between AR and non-AR region could have resulted in differential changes in economic outcomes, thus, confounding the results presented above. To test this hypothesis, I examine
whether being in an AR affected the amount of bombing received. Vietnam War bombing
data come from Miguel and Roland (2008).30 The Bombing Intensity variable is measured
as the total number of bombs, missiles and rockets dropped per square kilometer, measured
at the district level. Panel B of table 5 presents the estimated effects of being in an AR
on bombing intensity. Again, column 1 presents results using a baseline linear regression,
while columns 2-5 present results under the geographic RD specification using a linear polynomial in latitude and longitude as the control function and limiting the sample to various
bandwidths. All point estimates are small and statistically insignificant in all specifications,
suggesting that the differential effects on income cannot be attributed to the impacts of war.
[Table 6 about here.]
Table 6 includes additional robustness tests using matching and a placebo check. Matching
methods are useful to control for the potential confounding influence of pre-treatment covariates by reducing imbalance between treatment and control groups (Iacus et al. 2011).
Essentially, pre-processing data via matching prunes observations so that distributions of
covariates in the groups are more similar, therefore making treatment and control groups
are more comparable (Ibid.). For this analysis I used Coarsened Exact Matching (CEM) to
balance on all pre-treatment geographic and demographic variables31 and re-ran the baseline
regression on only matched observations. Results using the matching procedure is presented
in column 2. The point estimate is slightly smaller than the baseline without matching
(shown for convenience in column 1), but remains statistically significant at the 5% level.
Column 3 presents results using a placebo test, whereby I arbitrarily redraw the AR boundaries.32 Since it is not the actual boundary, we should expect no effect for the placebo
treatment on economic outcomes. The point estimate on a baseline regression of log real
household income per capita on the placebo treatment is small and not statistically signifi30
Raw data come from the Combat Activities-Air (CACTA), South East Asia (SEADAB), and Combat Naval Gunfire (CONGA) databases. For more details on how data were collected and gathered see: http://emiguel.econ.berkeley.edu/assets/miguel_research/18/_Appendix2__Long-Run_
Impact_of_Bombing_Vietnam.pdf.
31
For more detailed explanation of matching procedure see Iacus et al. 2011 as well as Blackwell et al.
2009)
32
In this case, I created an artificial boundary by moving the actual AR boundaries 50km inwards, meaning
those observations that were in ARs but were within 50km of the boundary were now coded as not being in
an AR area.
20
cant. This result supports the identification strategy used and indicates that my results are
measuring the effect of the AR policy.33
6
Mechanisms
How is it that autonomy or decentralization can come to affect long-term economic performance? Stated differently, by what channels do policies enacted in regards to incorporating
peripheral groups affect economic outcomes today? In this section I explore several possible
mechanisms by which the AR policy comes to affect contemporary economic development:
representation, ethnic-specific institutions and education. This section uses data concerning
participation and local governance from PAPI for the year 2013.
6.1
Leadership and Representation
One possible mechanism by which the AR policy affects present day economic outcomes
is through increased representation and improving the capacity of minority leaders. The
benefits of representation stem from the basic assumption that legislative capture by the
majority adversely affects the policy interests of minority groups; therefore, putting ethnic
minorities in positions of power may increase the probability of pro-minority policies to be
enacted (Pande 2003). Although it is unclear whether descriptive representation necessarily
leads to substantive representation in developed countries, such as the U.S. (Cameron, Epsten
and O’Halloran 1996; Soroka and Wlezien 2008) there is some evidence that representation
does affect policy outcomes in some developing countries. In a study of reservations in India,
Chattopadhy and Duflo (2004) find that reservation affects policy choices; in particular,
reservations for women affect policy decisions in ways that seem to better reflect women’s
preferences. Similarly, Pande (2003) finds that political reservation for scheduled castes
and scheduled tribes in India has contributed to the observed rise in targeted redistribution
towards these groups. In the Vietnamese context, better long term economic performance
could be a result of increased minority representation in ARs.
The effect of representation in ARs can manifest in present day outcomes through development of leaders. This idea is related to the literature concerning political dynasties in which
33
Table A.2 in the appendix further checks this by running the geographic RD specifications using the
placebo treatment. All point estimates statistically insignificant.
21
power begets power. When an individual holds more power, it becomes more likely that she
will create or continue a political dynasty, that is, political power is self-perpetuating (Dal Bo
et al. 2009). Although political dynasties generally refer to familial relationships, the logic
can be extended to a group context. Creation of political elites in the past can contribute to
increased likelihood of representation now amongst minority groups. If ethnic minorities in
former ARs are more likely to be represented by co-ethnics today, then economic differences
could be attributed to more pro-ethnic minority policies proliferated by minority leaders.
To test the plausibility of leadership as a mechanism, I examine the long-run impact of AR
policy on the likelihood of an ethnic minority serving as a political representative. If the
theory about increased minority representation holds true as a mechanism, then we should
see positive effects of political participation from being in a former AR. In table 7, I present
results of this analysis. Column 1 shows estimates using a baseline linear regression. Columns
2 and 3 present the results limiting the sample to households falling within 50km an AR
boundary as well as using the I-K optimal bandwidth, respectively. The control function used
in the geographic RD specifications is a linear polynomial in latitude and longitude. Panel A
looks at the likelihood of serving in the People’s Committee, panel B looks at the likelihood
of holding a leadership position in a local Communist Party organization, and finally, panel
C looks at the likelihood of holding a leadership position in the Vietnam Fatherland Front.
The results in table 7 show that the AR effect is most likely not operating through increased
leadership capacity or representation. In fact, the point estimates in panel A—being all
negative and statistically significant at the 10% level or better—suggest that ethnic minorities
who reside in former ARs are less likely to serve in a local People’s Committee. Coefficients in
panels B and C are all statistically insignificant, indicating that autonomous treatment does
not affect current day likelihood of being a local Communist Party leader or participating as
part of the Fatherland Front. The results provide evidence that the AR effect is not working
through the mechanism of leadership or representation.
[Table 7 about here.]
6.2
Local Governance
The political economy literature cites historical institutions as a prominent determinant
of economic development today. Economic performance depends on the organization of
society: institutions that ensure secure property rights for a broad cross section of society
22
are essential for economic growth; whereas, extractive institutions discourage investment and
economic development (Acemoglu and Robinson 2012; also see North and Weingast 1989;
North and Thomas 1973). Institutions are vital because they affect local governance and
public goods provision. Examining the persistent effects of the mita policy in Peru, Dell
(2010) finds the creation of an institution that provided land tenure contributed to long
term economic outcomes: the presence of large landowners provided a stable land tenure
system that encouraged public goods provision in non-mita districts. Additionally, Dippel
(2014) finds that forced coexistence of Native American tribal bands in the United States
decreases income on reservations today by affecting local governance.
Local level institutions that are ethnic-based can provide can provide for better local governance and public goods allocation geared towards the specific needs of ethnic minorities.
Ethnic-specific institutions can be instrumental in assigning property rights and resolving disputes as well as providing mechanisms of accountability for local leaders (Herbst 2000). This
in turn, contributes to increased efficacy of local governance and provision of public goods.
Furthermore, Michalopoulos and Papaioannou (2012) argue that ethnic societies with strong
political institutions have more success in getting concessions both from colonial powers and
from national governments after independence. Decentralization and cultural preservation
within ARs may affect current economic outcomes through the formation of ethnic-specific
institutions. Under cooperativization in the ARs 34 , management committees, composed of
ethnic minorities, were created to allocate collectively owned land, farming implements and
draught animals (Chung 1958: 156). The ethnic institutions created during the time period
of ARs can impact current economic performance by affecting governance at the local level
and allowing ethnic minorities to leverage power in regards to the central government.
I use public service delivery data from PAPI to explore the feasibility of the local governance
mechanism. I run a series of analyses examining the impact of AR treatment on public
service delivery and infrastructure in 2013 using the same baseline geographic RD procedure. If the mechanism by which the AR effect operates is through local level institutions,
we would expect a positive effect of autonomous treatment on public service delivery and
infrastructure.
[Table 8 about here.]
Table 7 presents the results of analysis on local governance. Results using the public ser34
Agricultural cooperativization was introduced in DRV in 1959-1960. The collectivization of production
means continued after Reunification until the Doi Moi Policy of economic reform in 1986.
23
vice delivery index as the dependent variable are presented in panel A, while results for
infrastructure are shown in panel B. Again, column 1 shows estimates using a baseline linear
regression. Column 2 presents the results limiting the sample to households falling within
50km an AR boundary and column 3 uses the I-K optimal bandwidth. All of the point
estimates for both public service delivery and infrastructure are relatively small and not statistically significant. These results indicate that the AR effect does not operate via a local
governance channel.35
6.3
Education
There exists a large literature that examines the connection between education and income.
The vast majority of this research concludes that there are positive returns to increased educational attainment both at a micro- and macro-level: individuals with more schooling tend
to have higher lifetime earnings (e.g. Angrist and Krueger 1991; Duflo 2001)36 and countries
with higher levels of educational tend to have higher levels of economic growth (Krueger and
Lindahl 2001; Barro 2013). The positive effect of autonomous treatment on income could
be a result of differential schooling systems, and therefore, disparate educational attainment
levels between those residing inside and outside of ARs. There seems to be some evidence
to suggest that education systems did differ between treated and untreated areas. Inside
autonomous regions primary school instruction was conducted in ethnic minority languages
(in addition to the majority language), while outside of these regions instruction took place
solely in Vietnamese (Kahin 1972). The subject matter of primary school instruction also differed between autonomous and non-autonomous regions for ethnic minority students (Ibid.:
584). If the education system in autonomous regions contributed to more students achieving
higher levels of schooling, then increased contemporary income from AR treatment could be
attributed to educational attainment.
To test this mechanism, I examine the long-run impact of AR policy on educational attainment. Specifically, I examine whether or not being in an AR contributed to the likelihood of
the head of household having completed primary school. Table 9 presents the results of this
analysis. Column 1 shows the results using a baseline OLS regression: the point estimate is
35
Note that the analysis only addresses contemporary levels of governance. It is possible that during the
time the AR policy was in effect, local governance did improve but non-AR and AR areas just converged
in terms of public service delivery or infrastructure after the policy ended. However, without detailed data
concerning governance at a local level during that period, I am unable to test this hypothesis.
36
See Card 1999 for a review of research in the field of education and earnings.
24
positive and statistically significant at the 5% level, indicating that autonomous treatment
increases the likelihood of primary school completion. Going beyond this, I can examine
precisely who benefited the most from the AR policy in terms of schooling. Using the demographic information available for each household head, I can decompose the sample by
ethnic minority status and age cohort. This type of sub-sample analysis is useful because I
am able to isolate those people who would have been alive during the time the AR policy was
in place and would have been directly affected by it. Columns 2 and 3 examine education
outcomes for ethnic minorities, while columns 4 and 5 look at just ethnic Kinh. Columns 3
and 5 limit the sample to include only those over the age of 40 (at the time the survey was
taken) for each group. Point estimates for ethnic minorities are both positive and statistically significant; whereas, the specifications for Kinh only are both statistically insignificant.
These results indicate that only ethnic minorities benefited from the AR policy, in terms of
increasing schooling levels. Furthermore, the effect of autonomous treatment on educational
attainment appears to be primarily driven by ethnic minorities over the age of 40 (column
3). Results using the geographic RD design are similar and presented in the appendix (tables
A.3 and A.4). The point estimate for the baseline regression indicates that among ethnic
minorities who were alive when the AR policy was in place, those who resided in ARs were
roughly 16 percent more likely to have completed primary school.
[Table 9 about here.]
Analysis of education data suggest that the AR policy had positive effects on individual levels
of schooling that the effect of autonomous treatment on long term economic outcomes may
be a result of increased educational attainment. Unfortunately, I am unable to determine
whether these schooling outcomes are due to institutional or cultural factors. It is possible
that higher attainment levels stem from increased quality of instruction in autonomous regions. However, it is equally possible that cultural considerations may factor into the decision
to send children to school. Previous studies have shown that forced assimilation policies, in
the form of language restrictions, may result in a cultural backlash whereby ethnic minorities
further isolate themselves from the majority (Fouka 2014). Educational attainment could
be affected by the AR policy then if ethnic minorities were more or less likely to send their
children to school given there perceptions about cultural preservation. Without any data on
cultural perceptions of schooling or the precise details of educational instruction at the time,
I am unable to disentangle these two mechanisms. Nonetheless, these findings underscore
the importance of education in increasing standards of living for ethnic minorities
25
7
Conclusion
In this paper I combine geographic data on the location of AR boundaries and household
survey data of ethnic minorities to examine the impact of the AR policy on long-term
economic outcomes. Using a geographic RD design, I document that a long-run AR effect
increases household income by around 21% for subject areas. The effect is robust to a
wide range of specifications using various functional forms and controls and shows that
being subject to a policy of autonomy during formation of the modern Vietnamese state
affects contemporary economic performance. Furthermore, examination of participation and
public service delivery data reveals that the primary channel by which AR treatment affects
economic outcomes today is through the increase in educational attainment.
It is important to note that the practice of indirect rule adopted in the case presented
here is a far cry from that of allowing an independent state or fully autonomous territory;
however, even with minimal levels of autonomy in place, there was enough evidence to show
long term economic benefits of the AR policy. The insights garnered from this analysis are
applicable to many contexts outside of the former DRV. Within the region, there remain
large swaths of loosely governed areas along the Southeast Asian Massif that the constituent
countries of Myanmar, Thailand, Vietnam, Laos and Cambodia will need to address. As
these central states continue to grow and develop, they will be continually confronted with
how to incorporate the numerous ethnic minority groups of the highlands into the state fold.
Extending beyond the region, ungoverned or weakly controlled state spaces exist all over
the world from Somalia to Colombia to Afghanistan and Pakistan; these ungoverned spaces
are especially pertinent as they may also pose threats to international security (Clunan et
al. 2010). As these central states attempt to consolidate their power, it is important to
understand the long term effects of state integration policies.
There are several ways to improve this analysis for future research. First, there needs to be
collection of finer grained and detailed data on ethnic minority populations. Most datasets
documenting economic development in Vietnam fails to adequately account for the ethnic
minority experience. The dataset used here is the first of its kind to provide a more comprehensive look at ethnic minority welfare; however, it is still limited in its scope and size.
Additionally, there should be examination of alternate mechanisms that connect AR treatment to modern economic outcomes. Considering the importance of norms and rules of
interaction to ethnic identity, it would be interesting to examine how policies of autonomy
26
versus assimilation affect social outcomes and the transmission of cultural preferences. Finally, future research should address questions such as at what point do economic effects of
incorporation policies disappear? Do they ever? What policies may be enacted to reduce
the potentially harmful effects of state integration?
Despite its limitations, the findings of my analysis are important in showing that policies
adopted by the state in an attempt to integrate former “peripheral” groups have impacts for
long-term economic outcomes, even after they are abolished. The results provide an extension
to Scott (2009) and Michaud (2000b), and show that increased state encroachment under
direct rule and forced assimilation may be harmful and allowing for some level of autonomy
is welfare-maximizing for ethnic minority groups. Additionally, my research sheds light on
the study of ethnic minority economic development by moving beyond proximate causes and
exploring the historic differences in ethnic minority experience with the state that impact
living standards today. Finally, I contribute to the literature on ethnic integration by showing
the need to examine policies and institutions of integration in understanding the economic
trajectory of minority individuals today.
27
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33
Figure 1: Map of Autonomous Regions in DRV, 1955
Notes: Autonomous Region boundaries are shown in dark purple and overlayed
on modern provincial borders (shown in gray).
34
Figure 2: Smoothness in Covariates
Notes: Each of the panels above is a graph of local averages of the outcome
plotted against distance to the AR boundary. Each outcome is a pre-treatment
covariate and includes elevation, slope, terrain ruggedness, population density,
number of government posts and tax revenue. Each dot represents the unconditional mean in bins of two kilometers by the distance from AR boundary.
Negative values indicate locations outside of an AR, while positive values indicate locations within an AR. The solid line corresponds to the predicted values
of a local linear polynomial smoother on each side of the threshold, and dashed
lines indicate 95 percent confidence intervals.
35
Table 1: Summary Statistics
Mean
Non-Autonomous Autonomous
(1)
(2)
GIS Measures
Elevation
Slope
Terrain Ruggedness
Colonial Measures
Number of Government Posts
Population Density
Tax Revenue
Other
Percent Minority
Observations
Difference
(3)
280.21
(400.84)
89.93
(0.21)
187.40
(194.64)
576.47
(394.63)
89.98
(0.08)
305.60
(174.39)
-296.26***
(23.23)
-0.05***
(0.01)
-118.20***
(10.64)
0.12
(0.53)
69.00
(115.05)
237.09
(230.61)
0.04
(0.24)
18.60
(10.72)
97.36
(41.37)
0.08***
(0.02)
50.41***
(4.04)
139.74***
(8.27)
77.88
(41.55)
97.21
(16.49)
-19.33***
(1.64)
452
823
1275
Notes: Columns 1 and 2 report the means and standard deviations in parentheses. Column 3 presents the differences of group means between the first two columns with standard
errors in parentheses. *p < .1, ** p < .05, *** p < .01
36
Table 2: Autonomy and Household Income: Baseline Regression
Dependent Variable: Log Real Income Per Capita
(1)
(2)
(3)
Autonomous
0.215**
0.232**
0.229**
(0.099)
(0.095)
(0.107)
R-squared
0.104
0.108
0.114
Controls
Ethnic Group F.E.
Boundary F.E.
Observations
Clusters
No
Yes
No
1267
228
Yes
Yes
No
1267
228
Yes
Yes
Yes
1267
228
Notes: Robust standard errors are clustered at the commune level
and shown in parentheses. The unit of analysis for all columns is
the household. Controls include elevation, slope, terrain ruggedness,
population density, number of government posts and tax revenue.
*p < .1, ** p < .05, *** p < .01
37
38
Yes
Yes
1028
198
Yes
Yes
857
167
Yes
Yes
739
149
0.262*
(0.136)
0.138
Yes
Yes
604
130
0.179
(0.145)
0.160
Notes: Dependent variable is log real income per capita. Robust standard errors are clustered at the commune level
and shown in parentheses. The unit of analysis for all columns is the household. All regressions include controls
for elevation, slope, terrain ruggedness, population density, number of government posts and tax revenue. The I-K
bandwidth distance is 37.71 km.
*p < .1, ** p < .05, *** p < .01
Controls
Ethnic Group F.E.
Observations
Clusters
Panel C: Linear Control Function in Distance to Boundary
Autonomous
0.223*
0.232*
(0.120)
(0.131)
R-squared
0.127
0.138
0.148
(0.140)
0.162
Panel B: Linear Control Function in Distance to Hanoi
Autonomous
0.236**
0.235*
(0.103)
(0.119)
R-squared
0.129
0.139
0.259**
(0.127)
0.138
0.237*
(0.134)
0.181
I-K Bandwidth
(4)
Regression Discontinuity
< 100km of bound
< 75km of bound
< 50km of bound
(1)
(2)
(3)
Panel A: Linear Control Function in Latitude and Longitude
Autonomous
0.283**
0.288**
0.312**
(0.118)
(0.122)
(0.126)
R-squared
0.135
0.153
0.164
Table 3: Autonomy and Household Income: RD Specification
39
Yes
Yes
0.272
(0.442)
0.125
123
50
Yes
Yes
0.631
(0.386)
0.197
122
49
0.309**
(0.122)
0.095
906
184
< 100km of
bound
(2)
Yes
Yes
0.474
(0.383)
0.280
113
43
0.325***
(0.124)
0.112
744
156
Yes
Yes
0.221
(0.441)
0.273
104
37
0.325**
(0.130)
0.123
635
138
Regression Discontinuity
< 75km of
< 50km of
bound
bound
(3)
(4)
Yes
Yes
0.108
(0.513)
0.331
95
33
0.246*
(0.127)
0.145
509
119
(5)
I-K Bandwidth
Notes: Dependent variable is log real income per capita. For the regression discontinuity specifications in columns
2-5 the control function used is a linear polynomial in latitude and longitude. Robust standard errors are clustered at
the commune level and shown in parentheses. The unit of analysis for all columns is the household. All regressions
include controls for elevation, slope, terrain ruggedness, population density, number of government posts and tax
revenue. The I-K bandwidth distance is 37.71 km.
*p < .1, ** p < .05, *** p < .01
Controls
Ethnic Group F.E.
R-squared
Observations
Clusters
Panel B: Ethnic Kinh
Autonomous
Panel A: Ethnic Minorities
Autonomous
0.258***
(0.092)
R-squared
0.069
Observations
1144
Clusters
214
(1)
OLS
Table 4: Alternative Specifications I
40
Yes
Yes
Yes
Yes
Yes
Yes
0.129
(0.230)
0.212
620
125
-0.063
(0.056)
0.123
746
149
Yes
Yes
0.239
(0.238)
0.234
558
117
-0.071
(0.065)
0.115
611
130
(5)
I-K Bandwidth
Notes: Dependent variable in panel A is an indicator variable for if the household resides in a commune that is a
beneficiary of Program 135 and the dependent variable for panel B is the total number of bombs dropped per square
kilometer during the Vietnam War. For the regression discontinuity specifications in columns 2-5 the control function
used is a linear polynomial in latitude and longitude. Robust standard errors are clustered at the commune level
and shown in parentheses. The unit of analysis for all columns is the household. All regressions include controls
for elevation, slope, terrain ruggedness, population density, number of government posts and tax revenue. The I-K
bandwidth distance for panel A is 31. 30 km and the I-K bandwidth distance for panel B is 42.47 km.
*p < .1, ** p < .05, *** p < .01
Yes
Yes
0.094
(0.230)
0.219
706
135
Panel B: Dependent Variable – Bombing Intensity
Autonomous
-0.083
0.081
(0.207)
(0.217)
R-squared
0.165
0.218
Observations
851
773
Clusters
160
150
Controls
Ethnic Group F.E.
-0.074
(0.054)
0.134
864
167
Regression Discontinuity
< 75km of
< 50km of
bound
bound
(3)
(4)
< 100km of
bound
(1)
(2)
Panel A: Dependent Variable – Program 135
Autonomous
-0.088*
-0.060
(0.051)
(0.053)
R-squared
0.095
0.134
Observations
1275
1035
Clusters
228
198
OLS
Table 5: Alternative Specifications II
Table 6: Alternative Specifications III
Autonomous
OLS
Matching
(2)
0.178**
(0.087)
Baseline
(1)
0.232**
(0.095)
Placebo
R-squared
Controls
Ethnic Group F.E.
Observations
Clusters
0.108
Yes
Yes
1267
228
0.105
No
Yes
581
None
Placebo
(3)
0.097
(0.086)
0.103
Yes
Yes
1267
228
Notes: Dependent variable is log real income per capita. Robust standard
errors are clustered at the commune level and shown in parentheses for
columns 1 and 3. The unit of analysis for all columns is the household.
Regressions in columns 1 and 3 include controls for elevation, slope, terrain ruggedness, population density, number of government posts and tax
revenue. *p < .1, ** p < .05, *** p < .01
41
Table 7: Autonomy and Political Leadership and Representation
OLS
Regression Discontinuity
< 50km of bound
I-K Bandwidth
(1)
(2)
(3)
Panel A: Dependent Variable – Served in People’s Committee
Autonomous
-0.056**
-0.068*
-0.070*
(0.024)
(0.038)
(0.038)
R-Squared
0.025
0.080
0.087
Observations
1086
588
523
Clusters
69
45
43
Panel B: Dependent Variable – Leadership in Local CP
Autonomous
0.004
0.016
(0.022)
(0.032)
R-Squared
0.012
0.023
Observations
1086
588
Clusters
69
45
-0.006
(0.029)
0.032
523
43
Panel C: Dependent Variable – Leadership in Fatherland Front
Autonomous
-1.822
3.360
(1.909)
(3.470)
R-Squared
0.012
0.023
Observations
1086
588
Clusters
69
45
-0.048
(0.115)
0.119
200
17
Controls
Ethnic Group F.E.
Yes
Yes
Yes
Yes
Yes
Yes
Notes: Dependent variable.... The sample for all specifications are restricted to ethnic minority
households only. Robust standard errors are clustered at the commune level and shown in parentheses. The unit of analysis for all columns is the household. All regressions include controls for
elevation, slope, terrain ruggedness, population density, number of government posts and tax revenue. The I-K bandwidth distance is 42.98 km for panel A, 38.60 km for panel B and 42.88 km for
panel C. *p < .1, ** p < .05, *** p < .01
42
Table 8: Autonomy and Local Governance
OLS
Regression Discontinuity
< 50km of bound
I-K Bandwidth
(1)
(2)
(3)
Panel A: Dependent Variable – Public Service Delivery
Autonomous
0.041
-0.131
-0.256
(0.103)
(0.165)
(0.172)
R-Squared
0.098
0.127
0.160
Observations
4018
2224
2057
Clusters
124
69
64
Panel B: Dependent Variable – Infrastructure
Autonomous
0.069
(0.091)
R-Squared
0.236
Observations
4018
Clusters
124
Controls
Ethnic Group F.E.
Yes
Yes
0.001
(0.134)
0.229
2224
69
-0.117
(0.141)
0.242
1991
62
Yes
Yes
Yes
Yes
Notes: The dependent variable for panel A is public service delivery, which is based on dimension
6 of the PAPI index. The dependent variable for panel B is infrastructure, an aggregate index of
household access to electricity, clean water, roads and sanitation services. Robust standard errors
are clustered at the commune level and shown in parentheses. The unit of analysis for all columns is
the household. All regressions include controls for elevation, slope, terrain ruggedness, population
density, number of government posts and tax revenue. The I-K bandwidth distance is 42.03 km for
panel A and 15.71 km for panel B. *p < .1, ** p < .05, *** p < .01
43
Table 9: Autonomy and Primary Education
Autonomous
R-Squared
Observations
Clusters
Controls
Ethnic Group F.E.
Full
Sample
(1)
0.048**
(0.022)
0.210
4018
124
Yes
Yes
Ethnic Minorities
All
Ages 40+
(2)
(3)
0.111*
0.167**
(0.060)
(0.075)
0.237
0.389
1086
69
Yes
Yes
624
63
Yes
Yes
Ethnic Kinh
All
Ages 40+
(4)
(5)
-0.001
0.001
(0.015)
(0.018)
0.002
0.004
2932
116
Yes
Yes
2014
110
Yes
Yes
Notes: Dependent variable is primary school education. Robust standard errors are
clustered at the commune level and shown in parentheses. Column 1 presents results for
the full sample, columns 2 and 3 restrict the sample to ethnic minorities only and columns
4 and 5 restrict the sample to only ethnic Kinh. The unit of analysis for all columns is
the household. All regressions include controls for elevation, slope, terrain ruggedness,
population density, number of government posts and tax revenue. *p < .1, ** p < .05,
*** p < .01
44
A
Appendix
Table A.1: Summary Statistics I
Variable
Log Real Income Per Capita
Autonomous
Number of Posts
Population Density
Tax Revenue
Elevation
Slope
Terrain Ruggedness
Longitude
Latitude
Distance to Hanoi
Distance to Boundary
Program 135
Bombing Intensity
Mean
8.39
0.65
0.07
36.47
146.89
471.45
89.96
263.7
105.22
21.93
160.33
52.92
0.37
0.71
Std. Dev. Min.
1.01
3.7
0.48
0
0.37
0
73.09
10.89
156.21
32.24
421.26
6
0.14
87.3
190.35
1
0.86
103.46
0.82
20.2
69.42
2.98
41
0.09
0.48
0
0.98
0
Max.
13.63
1
3
557.99
717.55
1777
90
1005.47
107.86
23.32
297.8
143.96
1
8.12
N
1267
1275
1275
1275
1275
1275
1275
1275
1275
1275
1275
1275
1275
851
Table A.2: Summary Statistics II: PAPI Data
Variable
Mean
Served in People’s Committee
0.03
Leadership in Local Communist Party
0.05
Leadership in Local Fatherland Front
0.57
Public Service Delivery Index
7.17
Infrastructure
2.03
Primary Education
0.91
45
Std. Dev.
0.17
0.22
22.13
0.68
0.49
0.29
Min.
0
0
0
4.53
0.70
0
Max.
1
1
999
9.21
2.84
1
N
4075
4075
4074
4075
4075
4075
46
Yes
Yes
1028
198
Yes
Yes
857
167
Yes
Yes
739
149
0.260*
(0.137)
0.138
Yes
Yes
604
130
0.174
(0.140)
0.160
Notes: Dependent variable is log real income per capita. Robust standard errors are clustered at the commune level
and shown in parentheses. The unit of analysis for all columns is the household. All regressions include controls
for elevation, slope, terrain ruggedness, population density, number of government posts and tax revenue. The I-K
bandwidth distance is 37.71 km.
*p < .1, ** p < .05, *** p < .01
Controls
Ethnic Group F.E.
Observations
Clusters
Panel C: Quadratic Control Function in Distance to Boundary
Autonomous
0.216*
0.237*
(0.122)
(0.129)
R-squared
0.127
0.138
0.166
(0.149)
0.162
Panel B: Quadratic Control Function in Distance to Hanoi
Autonomous
0.244**
0.251**
(0.107)
(0.126)
R-squared
0.129
0.140
0.264**
(0.132)
0.138
0.193
(0.153)
0.221
I-K Bandwidth
(4)
Regression Discontinuity
< 100km of bound
< 75km of bound
< 50km of bound
(1)
(2)
(3)
Panel A: Quadratic Control Function in Latitude and Longitude
Autonomous
0.260**
0.251*
0.209
(0.123)
(0.128)
(0.130)
R-squared
0.136
0.154
0.174
Table A.3: Autonomy and Household Income: RD Specification II
47
Yes
Yes
1207
216
Yes
Yes
1023
189
Yes
Yes
584
105
-0.056
(0.123)
0.134
Yes
Yes
464
90
-0.109
(0.132)
0.156
Notes: Dependent variable is log real income per capita. Robust standard errors are clustered at the commune level
and shown in parentheses. The unit of analysis for all columns is the household. All regressions include controls
for elevation, slope, terrain ruggedness, population density, number of government posts and tax revenue. The I-K
bandwidth distance is 42.03 km.
*p < .1, ** p < .05, *** p < .01
Controls
Ethnic Group F.E.
Observations
Clusters
Panel C: Linear Control Function in Distance to Boundary
Placebo
0.125
0.087
(0.084)
(0.088)
R-squared
0.104
0.094
0.031
(0.140)
0.174
Panel B: Linear Control Function in Distance to Hanoi
Placebo
0.144
0.132
(0.089)
(0.093)
R-squared
0.102
0.097
0.042
(0.129)
0.146
0.064
(0.173)
0.176
I-K Bandwidth
(4)
Regression Discontinuity
< 100km of bound
< 75km of bound
< 50km of bound
(1)
(2)
(3)
Panel A: Linear Control Function in Latitude and Longitude
Placebo
0.207
0.157
0.097
(0.128)
(0.134)
(0.166)
R-squared
0.110
0.096
0.147
Table A.4: Placebo Check: RD Specification
48
Yes
Yes
Yes
Yes
0.000
(0.017)
0.003
2376
93
Yes
Yes
-0.007
(0.018)
0.003
2201
87
0.153**
(0.069)
0.253
817
56
0.060**
(0.026)
0.195
3018
93
Yes
Yes
-0.026
(0.022)
0.009
1636
66
0.108*
(0.058)
0.310
588
45
0.056**
(0.025)
0.232
2224
69
Regression Discontinuity
< 75km of
< 50km of
bound
bound
(3)
(4)
Yes
Yes
-0.040
(0.024)
0.013
1323
52
0.047
(0.038)
0.231
383
35
0.009
(0.031)
0.147
1706
53
(5)
I-K Bandwidth
Notes: Dependent variable is primary school education. Robust standard errors are clustered at the commune level
and shown in parentheses. Panel A presents results for the full sample, panel B restricts the sample to ethnic minorities
only and panel C restricts the sample to only ethnic Kinh. The unit of analysis for all columns is the household. All
regressions include controls for elevation, slope, terrain ruggedness, population density, number of government posts
and tax revenue. The I-K bandwidth distance is 29.38 km. *p < .1, ** p < .05, *** p < .01
Controls
Ethnic Group F.E.
R-Squared
Observations
Clusters
Panel C: Ethnic Kinh
Autonomous
-0.001
(0.015)
0.002
2932
116
0.151**
(0.066)
0.247
843
58
Panel B: Ethnic Minorities
autonomous
0.111*
(0.060)
R-Squared
0.237
Observations
1086
Clusters
69
R-Squared
Observations
Clusters
0.063**
(0.024)
0.198
3219
99
< 100km of
bound
(2)
0.048**
(0.022)
0.210
4018
124
Panel A: Full Sample
Autonomous
(1)
OLS
Table A.5: Autonomy and Education: Alternate Specifications I
49
Yes
Yes
Yes
Yes
0.007
(0.020)
0.007
1627
89
Yes
Yes
0.000
(0.021)
0.006
1497
83
0.246***
(0.084)
0.369
442
51
0.082***
(0.030)
0.231
1939
93
Yes
Yes
-0.018
(0.025)
0.013
1103
63
0.168**
(0.064)
0.442
339
40
0.069**
(0.028)
0.290
1442
69
Regression Discontinuity
< 75km of
< 50km of
bound
bound
(3)
(4)
Yes
Yes
-0.035
(0.032)
0.019
889
51
0.147**
(0.054)
0.411
220
30
0.039
(0.035)
0.214
1109
53
(5)
I-K Bandwidth
Notes: Dependent variable is primary school education. Results are limited to age cohort of 40 years and above.
Robust standard errors are clustered at the commune level and shown in parentheses. Panel A presents results for
the full sample, panel B restricts the sample to ethnic minorities only and panel C restricts the sample to only ethnic
Kinh. The unit of analysis for all columns is the household. All regressions include controls for elevation, slope,
terrain ruggedness, population density, number of government posts and tax revenue. The I-K bandwidth distance is
29.38 km. *p < .1, ** p < .05, *** p < .01
Controls
Ethnic Group F.E.
R-Squared
Observations
Clusters
Panel C: Ethnic Kinh
Autonomous
0.001
(0.018)
0.004
2014
110
0.249***
(0.081)
0.368
455
53
R-Squared
Observations
Clusters
Panel B: Ethnic Minorities
Autonomous
0.164**
(0.075)
R-Squared
0.389
Observations
591
Clusters
62
< 100km of
bound
(2)
0.087***
(0.029)
0.239
2082
99
(1)
OLS
0.072***
(0.027)
0.272
2605
124
Panel A: Full Sample
Autonomous
Age Cohort: 40+
Table A.6: Autonomy and Education: Alternate Specifications II