SOCIAL AND ECONOMIC POLICY
WORKING PAPER
CONSIDERING CROSS-NATIONAL EQUITY
Children in Highland Populations in South-East Asia
Sólrún Engilbertsdóttir
Martin C. Evans
Ishani Shrestha
May 2013
UNICEF POLICY AND STRATEGY
Considering Cross-National Equity: Children in Highland Populations in South-East Asia
© United Nations Children’s Fund (UNICEF), New York, 2013
Cross-Sectoral Policy, Division of Policy and Strategy
UNICEF
3 UN Plaza, New York, NY 10017
This is a working document. It has been prepared to facilitate the exchange of knowledge and to stimulate
discussion.
The findings, interpretations and conclusions expressed in this paper are those of the authors and do not
necessarily reflect the policies or views of UNICEF or of the United Nations.
The text has not been edited to official publication standards, and UNICEF accepts no responsibility for errors.
The designations in this publication do not imply an opinion on legal status of any country or territory, or of its
authorities, or the delimitation of frontiers.
The editor of the series is Jingqing Chai of UNICEF Policy and Strategy Division. For more information on the series,
or to submit a working paper, please contact jchai@unicef.org
i
UNICEF SOCIAL AND
ECONOMIC POLICY
WORKING PAPER
May 2013
CONSIDERING CROSS-NATIONAL EQUITY
Children in Highland Populations in South-East Asia
Sólrún Engilbertsdóttir
Policy Analyst, Policy and Strategy, UNICEF
Martin C. Evans
Social Policy and Economic Analysis Specialist, Policy and
Strategy, UNICEF
Ishani Shrestha
Mt. Holyoke Intern, Policy and Strategy, UNICEF
Comments may be addressed by email to the authors:
sengilbertsdottir@unicef.org and mcevans@unicef.org
ii
ACKNOWLEDGEMENTS
We are grateful to the comments and suggestions made by Andrew Claypole, Beatrice Duncan,
Christina Popivanova, David Anthony, Etona Ekole, Jeffrey O’Malley, Jingqing Chai, Mahesh
Patel, Mizuho Okimoto-Kaewtathip, Thi Van Anh Nguyen, Lena Nguyen, Nicholas Rees, Nicola
Brandt, Valentina Calderon and Yoshimi Nishino.
The findings, interpretations and conclusions expressed in this paper are those of the authors
and do not necessarily reflect the policies or views of UNICEF or of the United Nations.
iii
Table of Contents
Executive Summary ................................................................................................................... vi
1. Introduction ......................................................................................................................... 1
2. Equity and Ethnicity ........................................................................................................... 2
3. Hill People of Southeast Asia ............................................................................................. 2
3.1 Viet Nam....................................................................................................................... 3
3.2 Lao PDR ....................................................................................................................... 5
3.3 Thailand ........................................................................................................................ 6
4.
Hill People Populations....................................................................................................... 7
4.1 Identifying Hill People in Survey Data ........................................................................ 8
4.2 Population and Sample Sizes ........................................................................................ 9
4.3 Household Size and Composition............................................................................... 11
4.4 Locational Characteristics .......................................................................................... 12
5.
Hill People and Ethnic Equity Profiling ........................................................................... 12
5.1 Asset Quintiles ............................................................................................................ 12
5.2 Deprivation, MDGs and Child Well-Being Measures................................................ 13
a. Drinking Water ........................................................................................................... 14
b. Sanitation .................................................................................................................... 15
c. Nutrition...................................................................................................................... 15
d. Health.......................................................................................................................... 16
e. Education .................................................................................................................... 16
f.
Early Childhood Development ................................................................................... 17
6. Equity Monitoring and Target Setting .............................................................................. 18
6.1 Equity Target Option 1: Equality of Ethnic-Related Risk ................................................ 18
6.2 Equity Target Option 2: Achieving Fair Outcomes ............................................................ 20
a. Basing fairness on ‘average’ (mean) levels of incidence. .......................................... 20
b. Equalizing shares of deprivation to match population share. ..................................... 21
7.
Concluding remarks .......................................................................................................... 22
iv
Tables
Table 1. Difference in Hill People household size and composition ............................................ 11
Table 2: Children in households with unimproved sanitation in Viet Nam ................................. 19
Table 3: Hill People deprivation and population shares for water and sanitation ........................ 21
Figures
Figure 1: Population/children in poorest quintile % ..................................................................... 13
Figure 2: Children in households with unimproved sanitation ..................................................... 15
Figure 3: Children 0-4 yrs stunted % ............................................................................................ 15
Figure 4: Children under 5 yrs who have received no vaccination............................................... 16
Figure 5: Children aged 12 to 14 not progressed to secondary education % ................................ 17
Figure 6: Children not attending early childhood education programme % ................................. 17
v
Executive Summary
In line with UNICEF’s equity focus this paper discusses and demonstrates approaches to the
empirical profiling of children in ethnic minorities. Using an equity lens, our analysis
demonstrates how survey data can be used in child deprivation profiling to identify the ‘most
disadvantaged’. Ethnic minority children, like all other children, are entitled without
discrimination to all the rights enshrined in the Convention on the Rights of the Child and other
relevant international human rights instruments. Investing in better information on children from
minority communities means improving our understanding of ethnic classifications, alongside
issues of human and economic development.
Our research addresses the challenge of using Multiple Indicator Cluster Survey (MICS) data to
drill down to potentially small sub-groups of the population. The approach moves ethnic
analysis from one based on aggregated profiles that tend to present just two groups, the ‘ethnic
majority’ and ‘ethnic minorities’, to a more nuanced approach that addresses equity issues
between ‘ethnic minorities’. We focus on children from Hill People minority communities
across three countries in South East Asia: Viet Nam, Laos and Thailand. By looking at a
common ethnic cluster of populations, Hill People, we address how to consistently identify,
measure and report equity issues for ‘indigenous peoples’ (using the UN definition that covers
Hill People of SE Asia) and thus of cross-national ethnic minorities as well as national
populations.
The audience for this paper is primarily those who need to identify equity issues for ethnic
minorities and other populations in order to accurately assess needs, differences in needs and
design programme responses and determine resource allocations. In particular, the paper is a
resource for country level Situation Analysis profiles conducted by UNICEF and other UN sister
organisations, and similar profiling exercises undertaken by national government departments
and NGOs. At its simplest we demonstrate how to use more detail in locally available data to
identify the most disadvantaged children.
This paper presents three country analyses alongside each other which are designed to be an
exemplar that can be replicated in other countries concerned with child focused ethnic minority
profiling. It provides UNICEF and other child rights partners and governments with a useful tool
for equity related targeting for programming purposes. In addition, focusing on a cross-national
ethnic minority group provides an opportunity for inter-regional learning and inter-country cooperation for addressing inequities.
Our findings demonstrate three important areas of ethnic minority profiling:
1)
The importance of rich profiling for a comprehensive understanding of ethnically based
inequities, going beyond comparing the majority population against a single aggregate ethnic
minority group
vi
2)
Robust methods and approaches to profiling small cross-national sub-groups (within the
specified limitations of survey design) which can be adopted more widely in child focused ethnic
profiling work
3)
The potential of inter-country learning and cooperation for addressing cross-national
ethnic inequities
In terms of the empirical results from this approach, we find for the three countries, children
from Hill People communities have consistently worse outcomes (in water, sanitation, nutrition,
health, education and early childhood development) than children from the ethnic majority, and
also worse outcomes than children from other ethnic minorities (except in Laos, where children
from other minority groups sometime have the worst outcomes). The evidence indicates that Hill
People children are well placed as a group to benefit from equity re-focus based on ethnicity.
The paper encourages cross-national sharing of good policy and programming practices in
overcoming the challenges children of Hill People communities face.
vii
1.
Introduction
UNICEF’s refocus on equity in recent years requires improved identification and analysis of
disadvantaged groups of the population, in order to re-prioritise programming to meet the needs
and address underlying inequities of these disadvantaged groups. This paper considers ethnic
equity issues as they pertain to Hill People, a cross-national ethnic minority group living in the
upland regions across many countries in mainland South-East Asia. We focus on a crossnational ethnic minority group for three reasons. First, although ethnic identity and inequity are
commonly linked, they are not always distinguished by national borders. Other studies in Latin
America have identified cross-national indigenous populations for specific profiles of poverty
and deprivation (UNICEF/CEPAL, 2010)1 and in Europe the Roma community have similarly
been the subject of cross-national concern (UNICEF, 2011). Second, inter-regional learning and
inter-country co-operation may be needed to identify the needs and approaches of common
interest in communities that are not only cross-national but also straddle national border zones.
Differences in deprivation profiles for such cross-national groups may represent differences in
national policy and practice. This means that the approaches that seem to work better for a
certain community in one country may well hold important lessons for neighbours with similar
underlying constraints of remoteness and topography. This paper does not provide such
comparative cross-national policy analysis, but rather the results highlight the importance of such
future analysis. Third, measuring success in reducing inequities can be improved if done crossnationally. Consistent measures of inequity and targeting approaches for reducing inequities
allow a clearer understanding of common and different factors, rather than relying solely on
country-level measures and approaches for very similar interventions and circumstances.
UNICEF’s programming for such communities may thus benefit from consistent cross national
approaches to ethnic inequity related issues.
UNICEF’s equity approach leads to some of the following questions on measurement:



How to consistently and accurately identify ethnic population sub-groups
How to robustly identify and measure inequity in potentially small sub-groups of the
population
How to set targets for redressing ethnic inequity
This paper focuses on these empirical questions of identification, measurement and target setting
and thus can provide useful guidance to UNICEF’s Monitoring Results for Equity (MoRES)based approach, as well as other monitoring frameworks. The aim of this paper is therefore not
only to provide an overview of children belonging to a particular cross-national ethnic minority,
but also demonstrate methods and approaches to profiling small sub-groups of the population
that can be adopted more widely. We consider the circumstances and characteristics of children
in ‘Hill People’ communities in three out of the many countries in continental South-East Asia in
which they live: Viet Nam, Laos and Thailand.
1
UNICEF/CEPAL (2010) Porbreza Infantial en América Latina y el Caribe, Santiago: CEPAL & UNICEF
1
2.
Equity and Ethnicity
When considering the drivers of national child level disparities, ethnic inequity is a prominent
feature of disparity analysis. However, in many countries there are several ‘ethnic minority’
groups and using an ‘ethnic minority’ aggregate group to profile inequity can hinder an
appreciation of how heterogeneous ethnic minorities often are, as well as hinder a comprehensive
understanding of ethnically based inequity. Ethnic minority communities diverge from the
ethnic majority population in different ways, and treating them in an aggregate can, for example,
mix high income minorities with poor minorities, as well as highly deprived children with less
deprived.
However, once the need to separately assess ethnic minorities is acknowledged, it leads to
problems of accurate identification of these various minorities. Reporting on, for example, all
the 49 ethnic groups currently identified in Laos is complicated, hence some sort of aggregation
is necessary. A major empirical problem is how to consistently and accurately draw ethnic
identity from survey data, such as MICS, DHS or other household surveys. National statistical
offices may have ethnic definitions that differ from these surveys, as well as different
conventions on aggregating small groups. Some of these approaches may reflect politicised
definitions of racial or ethnic difference and must be carefully considered before being used in
profiling and analysis: some groups may be assimilated into the majority2 and some groups
assigned to an ‘other’ category, for instance. In this paper our approach explores and
exemplifies a consistent analysis that clearly defines ethnic groups, within the specified
limitations of survey design.
3.
Hill People of Southeast Asia
Hill People refer to communities with common characteristics in South-East Asia, but go by
many names and languages and cultures. Collectively they can be known as ‘Hill tribes’,
‘Montagnards’ (especially in the Central Highlands of Vietnam), ‘Southeast Asian Massif
populations’ and ‘Highland ethnic minorities’. 3 The majority live above an elevation of 500
meters, across many countries and an area of approximately 2.5 million square kilometres
(approximately the size of Western Europe). They are extremely diverse, geographically
dispersed and politically fragmented communities with linguistic, cultural and religious
differences. Their many linguistic and cultural identities include for instance the Akha, BodoFor instance in Malaysia, where the so-called ‘Bumiputera’ majority definition conflates indigenous and nonindigenous Malay ethnicities and includes those of mixed Malay ethnicity, and is distinguished from ‘Indian’ and
‘Chinese’ minorities. Recent UNDP analysis shows that indigenous groups, subsumed within the ‘Bumiputera’
definition are amongst the very poorest populations in Malaysia (United Nations Country Team, 2011 The
Millennium Development Goals at 2010)
3
Other countries inhabited by Hill People populations are, India (north), China (south) and other similar groups live
in Afghanistan Kyrgyzstan, Pakistan and Tajikistan.
2
2
Kachari, Lahu, Karen, Hmong Mien, Mizo and Lisu who are all Tibeto-Burman peoples who
migrated over recent centuries into the areas from southern China and Tibetan regions, as well as
groups who speak Malayo-Polynesian, Tai, and Mon–Khmer based languages.
Hill People are recognised as being distinct from lowland living communities in several
important ways. Lowland communities, while diverse, generally share a common language and
culture and have developed and maintained the dominant social institutions in national political
environments. Hill People do not share that heritage, and historically persistent conflicts exist
between highland and lowland groups over many issues, including land ownership, language and
cultural preservation, access to education and resources, as well as political representation.
The commonality across Hill People is they are ethnic and cultural political minorities and live
on both the topographic and social fringes of society, in elevated and rugged terrain. In these
terrains they have tried to preserve their local cultures from state control and influence of
lowland majorities4. They are mostly non Buddhist/Confucian in religious beliefs and
traditionally animist and shamanist, but in some areas they have adapted to major religions such
as forms of Christianity. Their economic systems do not rely on paddy rice or industrial
production (which the majority group most commonly relies on), instead their systems
traditionally ranged from hunting and gathering, forest horticulture, swidden farming and upland
rice growing, and trade with lowland communities – particularly in forest and mineral products
(gems and silver especially). Prior to prohibition, traditional agricultural activity also involved
opium poppy production.5
Our analysis focuses on Laos, Thailand and Viet Nam as all these countries have household
survey data from the Multiple Indicator Cluster Survey (MICS) from 2005/6, and all countries
participated in the MICS4 round allowing for potential further analysis. We now turn to consider
the position of Hill People profiling in these countries
3.1Viet Nam
Most ethnic, social and economic inequity profiling to date in Viet Nam has compared all ethnic
minorities against the Kinh majority (and often with the Chinese ethnic group aligned with the
majority Kinh group), and not explicitly identified Hill People.
Poverty profiling has demonstrated that ‘ethnic minorities’ living in the Northern and Central
Highlands (and thus disproportionately Hill People) have substantially higher risk of poverty
than other ethnic minorities.6 While the Vietnamese government has directed significant
resources and designed specific programmes aimed at ethnic minorities, as well as officially
prohibiting discrimination against ethnic minorities, there is a persistent lag in development and
4
Scott, J. (2009) The Art of Not Being Governed. New Haven:Yale University Press.
Michaud, J. (2006). Historical Dictionary of the Peoples of the Southeast Asian Massif
6
World Bank (2009) Country Social Analysis Ethnicity and Development in Vietnam: Summary Report. Washington
DC: The World Bank.
5
3
longstanding societal discrimination against Hill People. Their higher poverty risk and lower
agricultural productivity is often ascribed to ‘backwardness’ by the majority. The issue of land
rights and relocation has affected Hill People in Viet Nam, many of whom have lost productive
gains from land for several reasons, such as programmes of ‘sedentarisation’ and the loss of
customary land, as well as resettlement of Hill People villages.
As said, remoteness in upland areas is one distinguishing feature of Hill People. However, Viet
Nam analysis has shown that the independent roles of remoteness and topography can only partly
explain differences in poverty causation and inequality, and thus factors relating to ethnicity play
a large part.7 Detailed survey and assessment of ethnic differences focus on low assets (both in
physical and human development terms); barriers to access for education, healthcare8, labour
market and commerce; very low migration rates to urban centres; poor cultural appropriate in the
design of anti-poverty and other programmes; and the lack of social and political voice.9 Recent
profiles of ethnic minorities in Viet Nam suggest that other rurally located minorities such as
Cham and Khmer communities have experienced some narrowing of the gap with the Kinh
majority, however for highland minorities, and especially those in the Central Highlands, the gap
has widened. Industrialization and foreign direct investment are mostly concentrated in the major
cities where the Kinh ethnic majority mostly resides and therefore benefit the most from the
associated rapid economic growth.10 Development projects in the rural and remote areas have
also been largely dominated by ethnic majority based finance for migrant settlers and
commercial agricultural projects.
The 2008 Viet Nam Household Living Standard Survey showed only modest progress in
reducing poverty levels among ethnic minority populations, which fell from 52.3 per cent in
2006 to 49.8 per cent in 2008. This is much less than the reduction seen in the poverty rate of the
Kinh population (down from 10.3 to 8.5 per cent). Children belonging to ethnic minority groups
are particularly at greater risk of being poor compared to children from the Kinh/Chinese ethnic
majority, and this is especially the case in rural areas.11 The 2011 Viet Nam MICS demonstrates
substantial ethnic disparities; ethnic minority children are three times as likely as Kinh/Hoa
children to die before their first and fifth birthdays, and likewise there are large disparities
between the nutritional status of ethnic minority children as compared to ethnic majority
children, and one in every four Vietnamese living in ethnic minority households defecate in the
open.12
7
Epprecht M., Müller D. and Minot N (2011) Annals of Regional Science Vol 46, #2, pp 349-368.
Swinkels R. and C. Turk (2006) Explaining Ethnic Minority Poverty in Viet Nam: a summary of recent trends and
current challenges, mimeo, Washington DC: The World Bank
9
World Bank (2009) op-cit.
10
Baulch B., Hung T. Pham and B. Reilly (2007) Ethnic minority and household welfare in Viet Nam: Empirical
Evidence from 1993 to 2004, London/Brighton: DfiD & Institute of Development Studies.
http://www.dfid.gov.uk/r4d/PDF/Outputs/ESRC_DFID/60423-ethnicity_household_welfare_vietnam.pdf
11
MOLISA and UNICEF (2008) Children in Viet Nam – who and where are the poor?
12
General Statistical Office (GSO), Viet Nam Multiple Indicator Cluster Survey 2011, Final Report, 2011, Ha Noi,
Viet Nam
8
4
An evaluation of various government programs to support ethnic minorities suggests that they
have been insufficient and often poorly targeted towards ethnic minorities, as well as poorly
matched to their specific needs of language and culture, for example only one out of seven
vocational training projects and two out of five housing projects focus on the specific needs of
ethnic minorities13.
3.2 Lao PDR
Lao PDR is among the poorest South-East Asian countries and its 5 million population is very
ethnically diverse. Forty nine distinct ethnicities with around 200 ethnic subgroups are spread
across four broader ethno-linguistic family groups: the majority group of Lao-Tai, who are 67%
of the population, the Mon-Khmer, 21%, and Hill People from the Hmong-Lu Mien (8%), and
the Chine-Tibetan (3%) linguistic groups.14 A simpler and cruder classification frequently used
in the past and to this day remains in unofficial categorisation, splits the population by elevation:
lowland, middle land and highland dwellers. This rough categorisation means that the Lao-Thai
live in the productive paddy-rice growing and more urbanised lowlands, the Mon-Khmer in the
midland rural areas, and Hill People in the highlands. These simplistic divisions reflect and
reinforce widely held appreciation of ethnic and cultural difference between settled lowland
paddy rice growers and hill-living dry rice growing, swidden and sometimes nomadic Hill
People communities.
Laos government policy on redressing ethnic inequalities since the 1980s has placed emphasis on
assimilation through schemes such as resettlement of communities to be nearer government
services and facilities, to stop opium production, to improve security, to promote ‘nation
building’ and to reduce levels of swidden agriculture. In many ways the Lao approach to
highland and Hill People can be seen as the opposite to Viet Nam’s – to move the inhabitants to
lower lying areas rather than sponsoring lowland people to migrate to the highlands. Since 2003,
one half of Laos districts have been ‘priorities’ for development in an attempt to narrow ethnic
and regional disparities but results have been mixed, and moving highland people to lower lying
and more crowded places has often increased problems of vector borne and infectious disease,
reduced access to assets and increased poverty risk as well as heightening land disputes in the
destination areas.15
Most recent and thorough analysis of ethnic differences in poverty have compared the Lao-Thai
majority to the remaining aggregate group of ‘ethnic minorities’.16 Older analysis shows Hill
People poverty headcounts in 2002/03 at 45% for Hmong-Mien and 40% for Chine-Tibet
Jones R., Tran Thi Hanh, Nguyen Anh Phong and Truong Thi Thu Trang (2009) A Mapping Exercise – Poverty
Reduction Programmes and Policies in Viet Nam
14
King E and van de Walle D (2012) Laos: Ethno-linguistic Diversity and Disadvantage in Hall G and Patrinos H
(eds) Indigenous Peoples, Poverty and Development, Cambridge: Cambridge University Press.
15
Baird I and Shoemaker B (2007) Unsettling Experiences: Internal Resettlement and International Aid Agencies in
Laos, Development and Change, 38(5) pp 865-888.
16
King and van de Walle (2012) op-cit.
13
5
language groups, much higher than the 29% for the Lao-Thai majority, but at lower levels than
the Mon-Khmer group, 54%.17 Detailed decomposition of underlying differences for ethnic
disparities in poverty incidence in Laos support findings in Viet Nam: that Hill People’s poverty
is partly explained by lower access to productive land, larger family size and poorer
infrastructure but that their efficient use of lower productive land and other scarce natural
resources compared to lowland agriculturalists and this protects them from many poverty
shocks.18 More generally, Laos ethnic minorities are less educated, partly a reflection of lack of
access to both primary and secondary schools, and in rural areas ethnic minority children spend
less time at school per day compared to their ethnic majority counterparts. Ethnic minorities also
have a higher incidence of temporary health problems and are less likely than the ethnic majority
to seek treatment for health ailments, reflecting both limited access and demand for health
services among ethnic minorities in Lao PDR.19 20 The percentage of underweight children below
the age of five is also higher among ethnic minorities, for the Hmong- Mien it is 37% and for the
ethnic majority it is 34.3%.21 Ethnic minorities generally have less land the ethnic majority in
Laos, and produce crops between two fifths to one quarter less per capita22.
3.3 Thailand
The position of Hill People (known as ‘Hill Tribes’ or ‘Highlanders’ in Thailand) as a distinct
sub-group of ethnicities minority is clearly recognized by the Thai government, and programmes
have been in place since the mid-1970s to address their social and economic development. There
are several distinct communities: The Karen, Hmong, Mien, Akha, Lahu, Yao, Lua H’tin,
Khamu and Lisu, who together make up some 800-900,000 people. However, population counts
are uncertain as registration of individuals, households and ‘villages’ for official Thai local
administration is not consistent due to a range of factors.23 Many in these communities have
‘stateless’ identity as they have not registered or obtained Thai citizenship. This gives rise to
distinct and separate treatment in terms of civil and political rights and increases the risk of both
exclusion from social services (with identity cards needed to access health and education) and
exclusion from limits placed on geographical mobility within the country. ‘Non-citizens’ are
prohibited from traveling outside their home districts without prior permission from the district
17
Engvall A. (2006) Ethnic Minorities and Rural Poverty in Lao PDR (background paper for World Bank Poverty
Assessment Report), Stockholm: Stockholm School of Economics (mimeo).
18
Engvall (2006) op-cit and van de Walle D. and Gunerwardena D (2001) Sourcs of Ethnic Inequality in Viet Nam,
Journal of Development Economics, Vol 65 pp 177-207.
19
World Bank (2006) Lao PDR Poverty Assessment Report From Valleys to Hilltops — 15 Years of Poverty
Reduction, Washington DC: The World Bank
http://unpan1.un.org/intradoc/groups/public/documents/apcity/unpan035358.pdf
20
King and van de Walle (2012) op-cit
21
World Bank (2006) op-cit
22
ibid
23
Aguettant J (1996) Impact of Population Registration on Hilltribe Development in Thailand, Asia-Pacific
Population Journal, Vol 11 #4 pp47-72.
6
office or outside their home provinces without permission from the provincial governor. Those
without cards may not travel at all and have difficulty accessing any services, owning land, and
accessing bank credit.
There are few recent sources of published data on Hill People’s poverty or other deprivations in
Thailand. The 2001 World Bank Poverty Assessment Report gives no ethnic breakdowns of
poverty incidence, but confirmed that factors associated with Hill People were linked to higher
risk: being in North East and North regions, rural, of low education status and with small landholdings.24 The most recent Human Development Reports for 2003, 2007 and 2009 all discuss
various issues concerning Hill Peoples’ rights and development but provide no ethnic
breakdowns of poverty or Human Development Indicators, and their discussion of ethnicity
focuses on issues of migrants and refugee populations that include Hill People in part. A
specialized survey in 2006 by UNESCO and the Bureau of Social Development found more than
30% of Hill People did not have citizenship and that lack of knowledge of rights or language
problems explained 50% of the low birth registration. Those children without official citizenship
were 73% less likely to enter primary school compared to their citizen peers and 94% less likely
to enter secondary school. Overall, when compared to ethnic majority Thais living in the same
areas, Hill People were approximately 95% less likely to enter primary school. Underlying
economic discrimination resulted in Hill Peoples being between 16% (Lahu) and 93% (Mien)
less likely than the ethnic Thai majority to have land ownership rights.
4.
Hill People Populations
While Hill People communities are ‘minorities’ when considered in national populations they
actually represent significant cross-national populations in Southeast Asia. For example, the
Hmong community total around 5 million in Asia, almost equal to the population of Lao PDR.25
Overall, Hill People in the South-Eastern portion of the Asian landmass total to around 80
million.26 Hence, some care is needed in considering how national ‘ethnic minorities’ link to
considerable cross-national populations of similar cultures and ethnicities.
Of the three countries we focus on in this report, the largest, in terms of population, is Viet Nam,
where the 2009 Population and Housing Census shows a total population of 85.8 million, of
which the Kinh majority was 86%. Fifty three ethnic groups make up the remaining 14%, of
which the larger ethnic groups are Thai: 1.6 million (1.8%); Muong: 1.3 million (1.5%); and
Mong: 1.1 million (1.2%).27
The 2005 Lao PDR census reports a total population of 5.6 million and identified 49 different
ethnic groups. The majority, 55%, were Lao-Thai and Hill People such as the Hmong, comprise
24
World Bank (2001) Thailand Social Monitor: Poverty and Public Policy, Washington DC: The World Bank.
Michaud, J. (2006). op-cit
26
ibid
27
http://www.gso.gov.vn/default_en.aspx?tabid=515&idmid=5&ItemID=10799
25
7
8% of the population and the Khamu, who are an ethnic minority group that mainly resides in
middle altitudes in the north, comprise 11% of the population.28
The 2010 Thailand census reported a total population of 65.5 million29 but there is no
information on ethnic minorities in the English census report30. Estimates of Hill People
population numbers are uncertain as previously discussed, but other sources such as the FAO,
report 3,527 Hill People villages in 20 provinces of Thailand comprising more than 750 thousand
people. This suggests Hill People are around 1% of the whole population. The largest Hill
People group in Thailand is Karen (46 percent), followed by Hmong (16 percent) and Lahu (11
percent).31 From these census numbers we estimate that 19% of Laos’, 11% of Viet Nam’s and
1% of Thailand’s populations are of Hill People ethnicity.
4.1 Identifying Hill People in Survey Data
We now turn to address the first of our empirical questions outlined earlier, “How to
consistently and accurately identify ethnicity-related population sub-groups” when profiling
child level disparities for UNICEF equity profiling. Our previous overview of Hill People
populations in the three countries gives us good grounds to base our equity profiling to identify
children in Hill People populations as potentially being among the ‘most disadvantaged’. But
how far are we able to take forward such equity concerns about children in Hill People
communities using national MICS survey datasets? MICS datasets all have ethnic identifiers
(based on languages spoken in the household), but each national dataset has differing
interpretations of groupings of ethnic and linguistic identities.
The three country level MICS datasets produced different problems and solutions to identifying
Hill People:


In the Thai dataset, a category for ‘Hill tribes’ was already defined as a specific identity
(alongside Cambodian (Khmer), Lao, Myanmar, Chinese and Thai).
In Lao PDR data, the ethnicity flags identified just four groups: ‘Mong’, ‘Khamu’, ‘Lao’ and
‘other’. Tabulations showed distributions by region that put the majority of ‘Mong’ in the
North along with the Khamu group, but when the definitions were matched to more detailed
breakdowns of ethnic and linguistic groups, there were two main problems in interpreting
ethnic difference. Firstly, the ‘Khamu’ definition could well refer to the Lao practice of
distinguishing between ‘midlanders’ (or Lao Theung) and ‘highlanders’ (Lao Sung) and thus
including Khamu within a ‘Hill Tribe’ grouping could confuse a local readership. We also
knew from the earlier literature review that poverty rates were higher for the Khamu than
Hmong groups and thus conflating them into a single group may obscure clear analysis.
28
http://www.nsc.gov.la/Products/Populationcensus2005/PopulationCensus2005_chapter1.htm
http://popcensus.nso.go.th/en/
30
http://popcensus.nso.go.th/upload/popcensus-08-08-55-E.pdf
31
http://www.fao.org/docrep/004/ak216e/ak216e04.htm
29
8

Secondly, there were other smaller communities of Hill People such as the Akha, Mien and
Lahu that were not separately identified but subsumed within the ‘other ethnicity’ group. In
the absence of clear ethnic identifiers, we chose to use the best proxies available in the data
and drew Hmong (Mong) communities and all the ‘other ethnicity’ communities that lived in
the North region into a combined group of ‘Hill People’, and separately identified the Khamu
community. Our results should be interpreted bearing in mind the uncertainties that spring
from this optimal but unsatisfactory classification. A comparison of these groups to the
national level documentation from the Statistical Office and other sources seemed to suggest
that large errors would be minimal.
The Vietnam MICS had less aggregated and more accurate identification of ethnic
communities. We used the specified ethnicity flags to compare with ethnographic and other
profiling materials such as location flags such as region and district to attribute ‘Thai’, ‘Kho
Mu’, ‘H’Mong’, ‘Dao’, ‘Gia-Rai’, ‘Bana’, ‘Xo Dang’, ‘Mnong’, ‘Bru’, and ‘Khang’ groups
to Hill People status and left the remaining ethnic communities in a residual ‘other minority
ethnic groups’ category once Kinh and Chinese communities had been aggregated into the
‘majority ethnic group’.
These different types and levels of data difficulties reinforce the recommendations made recently
by the World Bank Country Social Analysis in Viet Nam which apply to other countries in
South-East Asia, “More and better information is needed on minorities, from how they are
classified by ethnic group to where they are located in the country to their levels of economic
development. …….. Poor classification and overly general data can lead to inaccurate targeting
of resources, while more detailed local data can help identify the most vulnerable.”32
4.2 Population and Sample Sizes
Consideration of ethnic equity issues relies not only on the sub-group characteristics and correct
identification but also on the underlying population sizes and how these are captured in survey
data. Hill People are small minorities within in each country and thus lead to potential ‘small
numbers’ problems in survey data. This is particularly problematic when considering indicators
of child deprivation and wellbeing where the specific age-groups for measuring, for example,
immunization coverage, enrollment in programmes and education may result in small samples
compared to ‘all children’ for such groups. This leads to potential problems in obtaining
consistent measurement (for instance for MDGs) for small population sub-groups The problem
across the three countries considered in this paper is worst for Thailand, where MICS3 survey
data indicates that 0.6% of the individual sample is from Hill People communities, less than
would be expected to match Census profiles. Even the very large overall sample size for MICS3
in Thailand of over 137,000 individuals means that only around 750 are of Hill People ethnicity,
and, once we start looking at children by age-groups to capture health and education and other
32
World Bank (2008) op-cit p. 5
9
deprivations, then sub-samples become very small indeed. This is less of a problem for Laos and
Viet Nam where MICS3 samples of Hill People are 4,444 (13.3% of survey sample) and 4,594
(12.6% of survey sample) respectively.
This brings us to the second of our major empirical questions outlined earlier: “How to robustly
identify and measure inequity in potentially small sub-groups of the population?” We employ
three approaches to ensure that our profiling recognizes the problems of small sub-samples



Using population weights for all profiling but being careful to acknowledge a) small
underlying numbers and b) that population weights are not designed to make ethnic subgroup’s representative, but are usually based on sampling frames and strata based on
region, district or urban/rural populations. For instance, using population weights in
Thailand reduces the proportion of Hill People from 0.6% in un-weighted to 0.3% in
weighted proportions of the total population. For all of the analysis presented in this
paper we use population weights.
Showing statistical significance of small sub-samples is crucial when reporting simple
profiling results – for instance, it is not robust to report the proportion of Hill People
children aged 12-14 who are married in Thailand because the underlying sample for this
age group is below 10 observations. We use statistical tests, t-tests, to ensure that small
sample sizes are large enough to report significant profiles (that they are not showing
results that could have occurred randomly).
Comparing sub-groups to show ‘significant difference’ is key to equity profiling: to
demonstrate that children in Hill People communities have, for example, different rates of
immunization, school progression and malnutrition when compared to the ethnic
majority, and, perhaps, when compared to other minorities. However, comparing subgroup populations of different sample sizes means that each estimate has different level
of significance. We therefore show the 95% confidence intervals that are either side of
the point estimate when comparing Hill People to other population sub-groups. This
allows a distinction between cases where the 95% confidence intervals overlap (thus
frustrating any finding of significant differences) and those cases where differences are
robust and reliable.
Even when we adopt such careful profiling practices there remains the problem of how to
interpret differences that are found between Hill People minorities and other populations. How
far do differences reflect different characteristics rather than issues of human rights, such as
different access to or treatment by public services is always wise to bear in mind. For example,
are Hill People communities different in the way they form households and families, as well as
their particular location and environmental situations?
10
4.3 Household Size and Composition
Hill People live in relatively larger households when compared to ethnic majority households, as
shown in table 1: the mean household size of Hill People in Viet Nam is 6.1, compared to 4.9 for
the Kinh majority. In Lao PDR, mean household size for Hill People is 7.7 compared to 6.1 for
Lao majority but overlapping confidence intervals suggest that differences with other minorities
are not significant. In Thailand, mean household size for Hill People is 4.5 compared to 4.3 for
the ethnic majority but the wider confidence intervals for the small sub-group mean that it could
be between 4.3 and 4.6 and thus not statistically different from the majority.
Considering children only, Hill People households, on average, have larger numbers of children
than the ethnic majority. Hill People households in Viet Nam have 2.8 children on average as
opposed to 1.7 for the Kinh majority; in Lao PDR, 4.4, compared to 2.7 for the Lao-Thai
majority and in Thailand 1.6 compared to 1.4 for the Thai majority. Larger numbers of children
between Hill People and other ethnic minorities are significant in Viet Nam and in Laos but only
when comparing with Khamu minority; otherwise overlapping confidence intervals mean that
clear differences between Hill People and’ other minorities’ in Thailand and Laos are not
discernible.
Larger numbers of children on average is accompanied by having higher incidence of household
with children in their communities. 94% of Hill People households in Viet Nam have children
compared to 83% of the Kinh majority; in Lao PDR, 98% do so compared to 94% of the Lao
majority. In Thailand, no difference is discernible; 72% of both Hill People and Thai majority
households have children.
Children in Hill People communities are younger on average than ethnic majority children,
children’s mean age in Viet Nam is 8.0 years, compared to 9.0 years in the Kinh ethnic majority
households; in Laos 7.8 compared to 9.0 for Lao and in Thailand, 8.0 compared to 8.8.
Table 1: Difference in Hill People household size and composition
Mean number of household members
Viet Nam
95% CI
Laos
95% CI
Thailand
95% CI
Hill People
6.1
6.0 – 6.2
7.7
7.6 – 7.8
4.5
4.3 – 4.6
Other minorities
5.1
5.1 – 5.2
7.7
7.5 – 7.8
4.2
4.1 – 4.4
Khamu minority
--
--
6.8
6.7 – 6.9
--
--
Majority
4.9
4.9 – 4.9
6.1
6.0 – 6.1
4.3
4.3 – 4.3
Mean number of children per household
Hill People
2.8
2.8 - 2.9
4.4
4.4 - 4.5
1.6
1.5 – 1.8
Other minorities
1.9
1.9 -2.0
4.3
4.2 – 4.4
1.4
1.3 – 1.6
Khamu minority
--
--
3.5
3.5 – 3.6
--
--
Majority
1.7
1.7 -1.7
2.7
2.7 – 2.7
1.4
Average child age by ethnic group
11
1.4 -1.4
Hill People
8.0
7.8 – 8.3
7.8
7.7 – 8.1
8.0
7.3 – 8.8
Other minorities
9.1
8.8 – 9.5
7.8
7.6 – 8.0
7.3
6.5 – 8.2
Khamu minority
--
--
8.2
8.1 – 8.5
--
--
Majority
9.0
8.9 – 9.1
9.0
8.9 – 9.2
8.8
8.7 – 8.9
In short, Hill People communities have larger households, with more and younger children, than
the ethnic majorities.
4.4 Locational Characteristics
We do not have the ability from MICS data to empirically capture good measures of
‘remoteness’ for Hill People, for instance the distance of communities from paved and unpaved
roads, from health facilities, from schools of different types and levels. We have already seen
from the early summary discussion that there are restrictions on mobility and migration for Hill
People in all three countries combined with policies of relocation and ‘sedenterisation’. Location
is a key issue to understanding underlying ethnic differences not just because of underlying
geographical characteristics of remoteness and topography, but also due to policy reasons
related to service provision in such locations and to relocation of populations in and out of them.
In Viet Nam, only 0.7% of Hill People live in ‘urban’ designated areas, compared with 23% of
the majority ethnic population. In Lao PDR the same comparison is 1.3% compared to 22% and
in Thailand, it is 0.03% compared to 30%. Some care is needed in interpreting the actual
urbanity of Hill People because they may travel to trade in market towns, that may or may not be
designated as ‘urban’ areas, and there may be ‘illegal’ settlement in provincial towns (or cities
such as Chiang Mai in Thailand) that is not captured in survey sampling. But the overall position
is quite clear. Not only are Hill People predominantly rural, they are also in based in hilly terrain
and at distance from formal employment opportunities, access to financial services, trade and
from social and education service hubs.
5.
Hill People and Ethnic Equity Profiling
Are Hill People the ‘most disadvantaged’ in terms of ethnic equity in these countries? To answer
this we compare the incidence of several UNICEF programme-related deprivations across ethnic
communities, with Hill People distinguished from ‘other minorities’ and the ethnic majority
group in each country. For all the following analysis we use data from Multiple Indicator
Cluster Surveys (MICS) for the three countries from the year 2006.
5.1 Asset Quintiles
12
Figure 1 shows the proportion of all ethnic
communities that are in the poorest quintile of
asset holdings (at the individual level) for all
three countries. There is a clear ethnic propoor gradient across all three countries with
Hill People concentrated in the poorest
quintile.33 The starkest concentration is in
Viet Nam, where 88% of Hill People are in
the poorest quintile, as opposed to 12% of
those belonging to the majority ethnic group
and 62% for other ethnic minorities.
Similarly, in Thailand, 69% of Hill People are
in the poorest asset quintile, far higher than
other ethnic minority groups, 28%, and the
majority Thai ethnic group, 19%. In Lao
PDR, Hill People are highly over-represented
in the poorest quintile, 38%, but not more so
than other ethnic minorities, also 38%, and
less so than the Khamu minority, 49%.
However, all Lao minorities are overrepresented compared to the Lao majority
ethnic community of whom only 5% of are in
the poorest quintile.
Figure 1: Population/children in poorest quintile %
Ethnic inequity is more pronounced when children (aged 0-17 inclusive) are considered; we see
that the proportion of children from Hill People populations in the poorest asset quintile rises to
very high levels. In Viet Nam, 90% are in the poorest asset quintile; in Thailand, 75% (with 95%
confience intervals of 68% and 82%, so we can not definitely say that there is a higher
proportion than adults), and in Lao PDR 39%, while 51% of the Khamu minority children are in
the poorest quintile. Part of the explanation for these higher proportions is the previously
explained demographic profile of Hill People: they have more children in larger households as
well as having low levels of assets.
5.2 Deprivation, MDGs and Child Well-Being Measures
Keeping our focus on children, the following analysis of some of the main pillars of child wellbeing (that are directly linked to UNICEF programme activity) illustrate the ethnic equity
33
The Wealth Index is a composite measure of cumulative living standard of a household, calculated using data on
household’s ownership of selected assets, such as televisions and bicycles, materials used for housing construction,
and types of water access and sanitation facilities. Generated with a statistical procedure known as principal
components analysis, the Wealth Index places individual households on a continuous scale of relative wealth
13
position for Hill People, namely and in order; water, sanitation, nutrition, health, early childhood
development and education. Unfortunately the sample size was too small to look at child
protection indicators, such as child marriage and birth registration. Where possible, we use
indicators that reflect international standards for dimensions for child well-being, such as the
Convention on the Rights of the Child, the World Summit for Children, and the Millennium
Development Goals. To be consistent and help interpretation we profile using ‘deprivations’, i.e.
the absence or lower quality of a desired state of well-being or the direct incidence of ‘negative’
indicators of child well-being. This means that ethnic inequity is captured in ‘higher’ scores for
minority ethnic communities such as Hill People when compared to other ethnicities.
a. Drinking Water
MDG 7 on environmental sustainability includes commitments to improve water and sanitation
facilities. The relationship between water and child health and survival is well established, where
unsafe drinking water severely impacts children’s health. The relationship between poverty and
poor access to improved34/safe source of drinking water is also well established.
In Viet Nam, 30% of Hill People children
compared to just 9% of Kinh/Hoa majority
80%
64%
59
children use unimproved drinking water
51
60%
51**
sources, but other ethnic minorities have
36
40% 30** 27
broadly similar disparity (27% to 9% (the
14
20%
majority)). In Thailand, 68% of Hill
9
5
People children use unimproved water
0%
sources compared to 5% of children from
the majority ethnic group. In Lao the
picture is almost reversed, where 59% of
children from other ethnic minorities use
VIET NAM
LAOS
THAILAND
(ave 12%)
(ave 50%)
(ave 6%)
unimproved drinking water source, and
** t-test significant at 0.05 or higher
51% of both Hill People and the ethnic
Figure 2: Children in households with unimproved drinking water
majority children use unimproved drinking
source
water source. A large percentage of both
the ethnic majority and Hill People children get their drinking water from unprotected wells,
which is considered an unimproved source of drinking water, while a large percentage of the
Khamu minority get their water from public stands which are considered an improved source of
drinking water, explaining why the Khamu have the best access to improved drinking water
source of all the ethnic groups.
34
Improved water source: Piped water into dwelling, plot or yard; public tap/standpipe; tubewell/borehole; protected
dug well; protected spring; rainwater collection. Unimproved water source: Unprotected dug well; unprotected
spring; cart with small tank/drum; bottled water; tanker-truck; surface water (river, dam, lake, pond, stream, canal,
irrigation channels). Bottled water is considered improved only when the household uses water from an improved
source for cooking and personal hygiene
14
b. Sanitation
100% 87**
72**
80%
84
67
53
60%
49
33
40%
13** 8
20%
0%
VIET NAM
LAOS
(ave 39%)
(ave 61%)
1
THAILAND
(ave 1%)
Poor access to improved sanitation35 is
linked to various child related illnesses,
most notably diarrhea which is one of the
main killers of children under five years.
Rural populations, such as Hill People,
generally have poorer access to improved
sanitation than urban populations, and this
is substantiated in these countries. In Viet
Nam 87% of Hill People children have
unimproved sanitation compared to 33%
for Kinh majority children. In Lao PDR
** t-test significant at 0.05 or higher
72% of Hill People children have
unimproved sanitation, while 49% of the
Lao majority have unimproved sanitation. The sanitation situation is worst for other ethnic
minority groups, where 84% of children have unimproved sanitation. The difference is not as
stark in Thailand, where 13% of Hill People children have un-improved sanitation, as opposed to
just 1% of the Thai majority.
Figure 3: Children in households with unimproved sanitation
A large percentage of Hill People children have no access to any kind of sanitation facility in
comparison to children from the ethnic majority across all three countries. In Viet Nam, 69% of
Hill People children have no access to any sanitation facility as opposed to 9% of Kinh majority
children. The disparities are less evident in Lao PDR but the percentage of Hill People children
without access to any sanitation facilities is still high, or 68%, and this is also high, or 43% for
children belonging to the majority ethnic group. More disturbingly, 84% of children from other
minority groups have no access to any kind of sanitation facility. In Thailand 10% (95%
confidence intervals between 4%, 16%) of Hill People children have no access to any kind of
sanitation facility as opposed to 1% of the ethnic majority children.
c. Nutrition
60%
49**
51
40%
49
31
18**
9
20%
12
0%
Insufficient nutrition in childhood has
been linked to stunted physical growth,
poorer learning outcomes, poorer health
and so forth. Malnutrition is clearly
linked to poverty.
Viet Nam has a separate General
Nutrition Survey and results by ethnicity
35
Improved sanitation: Flush toilet/latrine; VIP latrine; pit latrine with slab; composting toilet. Unimproved: flush to
elsewhere; pitLAOS
latrine without slab/open pit;THAILAND
bucket; hanging toilet/hanging latrine; no facilities, bush or field
(ave 41%)
(ave 12%)
** t-test significant at 0.05 or higher
Figure 4: Children 0-4 years stunted %
15
are not available36, however regional disparities that can be linked to Hill People populations
suggest higher rates of stunting compared to lowland majority ethnic areas. In Lao and Thailand
the MICS includes various anthropometric information, among them height for age (stunting)
which is indicative of long-term insufficient nutrient intake and frequent infections. In Lao
stunting rates of 49%, for Hill People children (aged 0-4), are higher than that of the Lao
majority (31%), but rates are even higher for other ethnic minorities (51%). In Thailand, stunting
rates appear to be highest for Hill People children at 18% but 95% confidence intervals at 8% to
28% show that these cannot be interpreted as significantly different from children from the
ethnic majority group (12%).
d. Health
Immunisation rates are an important measure of child well-being as over 60% of child deaths in
low income countries are attributable to infectious diseases, and the most effective prevention is
full immunization for all major diseases. The best immunisation indicator is based on a
denominator of children aged up to 23 months. But small sample sizes make this denominator
100%
problematic when considering small
73**
80%
ethnic sub-groups such as Hill People
55 58 51
60%
children. We therefore choose a larger
40%
age-cohort of those aged under 5 years to
14
12**
6
20%
8
assess those who have never received
7
2
0%
any vaccination. Again, overall rates of
-20%
immunisation vary, with higher coverage
in Viet Nam and Thailand compared to
Lao PDR. However, evidence of ethnic
VIET NAM
LAOS
THAILAND
disparity is clear. In Viet Nam, 12% of
(ave 4%)
(ave 58%)
(ave 8%)
**t-test significan at 0.05 or higher
Hill People children aged 0-4 have never
Figure 5: Children under 5 years who have received no vaccination
received any vaccination, compared to
7% for other ethnic minorities and 2% for
the ethnic majority. In Lao PDR, much lower overall coverage is even lower for Hill People
children, where 73% of children have never received any vaccination, worse than 55% for other
ethnic minorities and worse than 51% for the ethnic majority. For Thailand, again, the problem
of small numbers confounds an equity analysis as the numbers of those never vaccinated are
small and thus comparing rates for the different ethnic groupings cannot be done robustly.
e. Education
36
http://www.unicef.org/Viet Nam/resources_18459.html
16
Enrolment in compulsory primary education from the age of six37 is high across all groups in all
three countries, with little obvious
92
66**
87
difference between ethnic groups in
85**
100%
80%
40
enrolment and reported attendance. Of
57
60%
course, quality of schooling and
40% 25**
10
6
4
20%
subsequent drop out may differ
0%
ethnically in unobserved ways.
However, when we consider an older
group of children, those aged between
the ages of 12 to 14 years who should
VIET NAM
LAOS
THAILAND (ave
have completed primary and be
(ave 68%)
10%)
(ave 5%)
** t-test significant at 0.05 or higher
attending lower secondary education,
Figure 6: Children aged 12 to 14 not progressed to secondary
we see significant ethnic disparities. In
education %
Viet Nam 25% of Hill People children
of this age have Primary education or lower as their highest level of education, compared to 4%
of the majority, suggesting huge differential fall out from schooling. In Lao, overall progression
to lower secondary schooling is less common for all ethnic groups, but even so, Hill People
children are more likely to have primary education or lower as their highest level of education,
85%, compared to the ethnic majority children, 57%; but other ethnic minorities seem to have
the greatest disadvantage at 92%. Results for Thailand are not statistically robust for the very
small Hill People samples of this age group.
f. Early Childhood Development
Early childhood is considered the most
critical period for children’s current
100%
86
66
62
and future well-being, and early
80% 69**
60%
childhood educational programmes can
39 35
38
40%
improve children’s cognitive and
20%
physical development. However, the
0%
implementation of such programmes
across the three countries differs very
greatly, with higher coverage in
Thailand and Vietnam across all
THAILAND
VIET NAM
LAOS
(ave 39%)
children than in Lao PDR. In terms of
(ave 39%)
(ave 92%)
** t-test significant at 0.05 or higher
ethnic disparity in provision, in Viet
Nam 69% of Hill People children do
Figure 7: Children not attending early childhood education
programme %
not attend early childhood education
(ECD) programmes as opposed to 35% of the Kinh majority children. In Lao PDR 98% of Hill
People children do not attend ECD programmes as compared to 86% of children of Lao majority
98** 99 97
37
http://stats.uis.unesco.org/unesco/TableViewer/tableView.aspx?ReportId=163
17
group. However, results for Thailand once again are not robust due to small sample sizes except
for the majority population where just 38% of Thai majority children do not attend ECD, as
opposed to rates to over 60% for ethnic minorities in general.
6.
Equity Monitoring and Target Setting
The evidence presented in this paper indicates that Hill People children are well placed as a
group to benefit from equity re-focus based on ethnicity across these three countries, and
potentially in other countries of South-East Asia. By separate and distinctly profiling Hill
People children and comparing them to majority ethnic populations we clearly demonstrate
aspects of inequity that are obscured when ‘all ethnic minorities’ are compared to the ethnic
majority. This is especially true for Viet Nam, where grouping different ethnicities into a Hill
People group shows that they are ‘most disadvantaged’ when compared to other ethnic
minorities as well as when compared to the ethnic ‘Kinh’ majority. In Lao and Thailand, where
‘Hill People’ ethnicity is recognized as more distinct than in Viet Nam, there is clear evidence of
ethnic inequity. But data problems partly frustrate clear profiling as less detailed ethnic
groupings in the Lao MICS data make it more difficult to profile ‘Hill People’ distinctly, and for
Thailand small sample sizes made it more difficult to profile children from Hill People
communities in terms of statistical robustness.
Having demonstrated a case for considering equity refocusing towards children in Hill People
communities, we now turn to look at the final question for this paper, outlined earlier: “How to
set targets for redressing inequity?” While the first step in any equity re-focus is to accurately
identify where inequity exists, there also needs to be a clear aim for refocused programming for
an equitable outcome. These may be medium term or long term targets, depending on how large
the inequity gap is to be narrowed and the volume and capacity of government programme
outputs. An ‘end-point’ defined in equitable terms is a helpful policy tool even if it takes years
or decades to reach it. However, defining an end-point equity outcome is not straightforward
and there are several potential approaches to setting equity targets. The different approaches
listed below are designed to be an exemplar that can replicated, by UNICEF and other partners,
in other countries concerned with child focused equity targeting based on ethnicity.
6.1 Equity Target Option 1: Equality of Ethnic-Related Risk
It is possible to think of an equity position for Hill People children based on ‘equality of ethnicrelated risk’. This approach attempts to reduce the incidence of deprivations and rights violations
that directly stem from factors that relate to ethnic identity rather than other factors. This
approach seeks to redress particular and systematic factors that explain ethnic differences, rather
than commonly occurring factors which may be due to, for example, low income or poor
education. These factors can affect all ethnic groups but are worse for the target ethnic group.
18
However, while this seems a sensible approach, we almost certainly lack a full picture on what is
driving unequal incidence across ethnic communities. For instance, how far are the current child
level inequities the result of discrimination and how far do they simply represent differences in
characteristics that are not necessarily linked to ethnic discrimination: differences in household
size and composition, fertility, location, and in characteristics such as adult literacy? One way of
thinking about the particular ethnic disparities in well-being that we have observed in the earlier
analysis is that these reflect ‘gross differences’ between Hill People and other populations. These
differences then result from a wider range of drivers that include a sub-set of factors that are a
net ‘ethnic penalty’ and that cannot be explained by other differences in characteristics with the
majority population. Such an approach would seek to ensure that Hill People children’s
enrolment in secondary education, risk of stunting and access to improved sanitation and safe
water etc. were equal to other groups when underlying characteristics were the same (such as
location, education of head of household etc.).
This approach is illustrated by looking
at simple consistent comparisons that
take into account two major factors that
can account for significant levels of
disparities, namely education levels and
location. Table 2 repeats the analysis
previously shown in Figure 2 but this
time shows the rates for all children who
have no access to improved sanitation in
Table 2: Children in households with unimproved sanitation in Viet Nam
Viet Nam, alongside the rates for children
who both live in rural areas and have mothers with no educational qualification. The table
shows that the gross differences between Hill People children and the ethnic majority are based
on higher overall values (an overall more deprived population) but the net differences between
Hill People and the majority narrow considerably, from a 54 percentage point difference (87%
compared to 33%) to a 47 percentage point difference (91% compared to 44%). At the same
time this example diminishes the perceived unfairness of targeting assistance on particular
ethnically identified groups that can be felt by similarly deprived people who are not in the
ethnic priority group, the Hill People group are still considerably worse off even when we
account for location and education of mother.
However, the advantages of such target setting for accurate parameters of disparities are offset
by data complexity and uncertainty to properly control for all the ‘non-ethnicity-related’ factors
of potential importance. Formulating ethnic based equity targets potentially relies on complex
assessments of household characteristics which may require collecting more information from
potential programme recipients. =Such an approach enables a clearer understanding of how
equity issues are particular to ethnic minority groups or are shared across other ethnicities –
including deprived children of the majority ethnicity. It more clearly demonstrates the trade-offs
19
between identifying inequity in purely ethnic versus other associated terms that are predictive of
low income or poverty. This could be crucially important when, UNICEF and other child rights
partners, are deciding how to re-orientate programming towards ‘recognizable’ sub-categories
based on distinct group characteristics rather than on underlying factors such as illiteracy, low
income or geographic location.
6.2 Equity Target Option 2: Achieving Fair Outcomes
A second and alternative approach to promoting equity, based on ethnicity, is to design
interventions aimed at achieving ‘fair’ outcomes. These outcomes would be expressed in simple
aggregate ‘gross’ terms in which an equitable end-point would be where deprivations and
violations were equally spread across the population and there are several alternatives in this
regard.
a.
Basing fairness on ‘average’ (mean) levels of incidence. This approach would set
targets that identify the difference between Hill People and the average position. This is the
approach taken, for example, by the ‘inequality of opportunity’ indices that have been developed
in Latin America and elsewhere to assess how far children have differential access to services
and social and economic rights38.
For such an approach the target is simple: to close the difference between the current inequitable
level of provision and the average. For example, for water and sanitation provision (previously
shown in Figures 1 and 2 above), it would imply that the provision of improved sanitation for
Hill People would have to grow by 9% in Thailand, 83% in Viet Nam and 18% in Lao PDR to
bring coverage up to average levels, and the provision of improved water by 50% in Thailand
and by 21% in Viet Nam, but with no remedial growth needed in Lao PDR as Hill People are at
or over the average position39.
However, outcomes based on averages do need to be based on a clear understanding of the
overall population. For example, would sub-national differences have to be brought to a national
average as part of an overall approach to reducing equity to the average position, or could ethnic
disparities be reduced to reflect sub-national averages? In the case of Hill People there is the
cross-national issue in addition. Considering equity issues across countries for a cross-national
community would have to similarly consider the role of overall population composition and sizes
of ethnic communities that partly determine national averages. Our analysis clearly showed the
differences between a large sub-group and a small sub-group and their respective national
averages (such as when comparing Hill People disparities in Thailand and Lao PDR
respectively). Given that Hill People are a cross-national ethnic minority faced with similar
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Barros R., Ferreira F., Vega J and Chanduvi J (2009) Measuring Inequality of Opportunities in Latin America and
the Caribbean, Washington DC: The World Bank.
39
These are ‘growth’ targets, with the difference expressed as a percentage of the average position; absolute
numbers of sanitary installations etc would be the underlying numerical difference between hill people households
and the average at the household level
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inequities, setting targets that ensure comparison across differently apportioned populations and
framing targets that take into account differing population sizes may be preferable. This leads
us to suggest a second potential approach to ‘fairness’.
b.
Equalizing shares of deprivation to match population share. Table 3 shows the
comparisons of overall population share (the % of the child population that are in Hill People
communities) compared to the deprivation share (the % of the Hill People children that are
deprived) in both water and sanitation provision. This exemplifies the ‘population share’
approach to equity target setting40. In an equitable distribution of deprivation, any group would
experience a share of overall deprivation that was equal to its population share. However, table 3
illustrates inequity in the over-representation of Hill People children in water and sanitation
deprivation. Equity targets using this approach would seek to reduce any over-representation,
and thus reduce the ratio score to 1 or less. This means, for example, that Hill People children in
Thailand would have to have their share of sanitation deprivation lowered by a factor of 11.8, in
Viet Nam by 2.2 and in Lao PDR less appears to be needed to equal population shares.
Table 3: Hill People deprivation and population shares for water and sanitation
These population share based figures show the relative differences, between Thailand with very
high overall rates of improved water and sanitation in which Hill People have a very large
relative gap, and say Lao PDR that has overall lower provision of improved water and sanitation
but where Hill People are at a smaller relative disadvantage. We specifically recommend that
UNICEF and other partners consider using a population share approach when considering equity
refocusing, and suggest that this approach is particularly suitable for cross-national profiles of
equity. Calculating population shares is relatively simple and can be captured regularly in rounds
of MICS, DHS or other household surveys to establish progress.
Of course there are other approaches to targeting and considering equitable outcomes. Some
approaches aim for complete equality and narrowing the gap completely between the best and
worst off in some elements of deprivation, especially those that have fundamental and long
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By solely considering water and sanitation provision as an exemplar, allows us to use the whole population of
children aged 0-17 rather than smaller age-groups (thus we avoid the problem of small and missing numbers for
some of the other deprivation counts that we saw in our earlier analysis).
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lasting threats to child welfare and development, such as nutrition. If so, then using the average
as an end-point is inappropriate, and perhaps an intermediary target based on the average is an
entirely valid point on the way to full equality. If zero incidence (or close to it) of child
deprivations is also a long-term aim, then equalizing shares is also a valid short to medium term
objective. Such short to medium term objectives and targets can be well suited to government
expenditure cycles.
7.
Concluding remarks
At the outset of this paper we put forward three empirical questions on how to capture ethnic
group characteristics, how to profile disparities and inequity and how to set targets for ethnic
equity, using Hill People communities as an exemplar ethnic group across three Southeast Asian
countries. Our profiling and analysis showed how difficult it is to accurately and consistently
identify ethnic groups, particularly those who live across national boundaries where the need for
consistent definitions is perhaps greatest. Nonetheless, our analysis also showed that accurate
ethnic profiling is doable when detailed ethnic markers are included in household surveys and
sample sizes large enough to draw significant conclusions, such as in the Viet Nam MICS.
Having identified Hill People as best we could under the constraints of dataset definitions, it was
then possible to consider how such a ‘finer grained’ analysis of ethnic equity, compared to the
practice of comparing ‘ethnic minorities’ as an aggregate to the ethnic majority population. We
found that children in Hill People communities were always seriously disadvantaged when
compared to the ethnic majority across Viet Nam, Lao PDR and Thailand. We also found that
they were the ‘the most disadvantaged’ in comparison with all other ethnic communities in Viet
Nam and Thailand. The comparison in Lao PDR was not as clear due in part to the uncertainty
in ethnic identifiers.
Recommendations
As stated earlier, the audience for this paper is primarily those who need to identify equity issues
for ethnic minority/indigenous children in order assess priority areas for programme design and
resource allocation. We have demonstrated how to use more detail in locally available data to
identify the most disadvantaged. The paper can be considered a resource for country level
Situation Analysis of Women and Children, commonly undertaken by UNICEF, as well as other
UN sister organizations and national governments.
Some of the specific recommendations emerging from this paper are for these partners to
promote:
Use of disaggregated data: Data collection disaggregated by ethnicity remains an issue.
However, we have shown that MICS has real potential in providing extensive profiling not only
of ethnic minorities in general but specific groups of ethnic minorities. Data disaggregated by
ethnicity is imperative, without good data it is impossible for countries to know if the specific
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measures and policies aimed at certain ethnic minorities are actually improving their situation.
In countries such as Thailand where the MICS data does not allow to profile robustly certain
ethnic minorities, the emphasis should be on how to gather data on these minority populations
who historically have been among the most disadvantaged. UNICEF Thailand country office is
already considering this, with the implementation of an ‘Equity MICS’ that will emphasize
sampling frames and questionnaire instruments specially designed for in-depth analysis of
minority populations.
Clear transparent approaches to data analysis: Our analysis faced the problem, often found
when considering small sub-groups of the population, of small numbers. We were able to plan
for challenges regarding small sub-groups and meet them with a clear methodological approach
that invested in transparency. Given that empirical verification of equity issues for sub-groups is
a core issue for any equity refocus, we adopted clear statistical approaches to ensuring that out
analysis was robust – by reporting ‘t-tests’ and 95 percent confidence intervals to show where
statistical significance was assured and that differences between ethnic groups was ‘statistically
different’. This is good practice and should be adopted in all such future work. Interpretation of
results always requires care. There may be, for instance, group differences based on religion or
other reason that are not captured by ‘ethnic’ definitions. Analysis of such other potential drivers
of difference should be undertaken before any final determination of the profile of disadvantage
is made.
Consider cross-national equity issues: Our approach can be adopted in any national dataset to
profile ethnic disparities. However, additionally, the cross-country ethnic minority analysis has
the added potential to be adopted in other countries/regions to shed light on children living
marginalized ethnic minorities, and especially indigenous communities, that reside across
several countries, such as Roma populations in Europe, the Maasai in Kenya and Tanzania, the
Quechua in South America, and so forth. Such analysis is of relevance to UNICEF’s equity
focus, which emphasizes reviewing the equity focus of any child situation analysis. However, it
is worth considering whether cross-national equity be a concern at regional rather than country
level? The approach of this working paper was to analyse child well-being of certain groups
across national boundaries, bringing into question the effectiveness and relevance of UNICEF’s
current approach to profiling children within national boundaries. Do we miss out on
understanding equity to the fullest when we limit our analysis within national boundaries? How
do we ensure better targeted UNICEF programmes, which address inequities by serving these
disadvantaged populations across national boundaries? The Roma analogy may be useful in that
regard, as the Roma community have similarly been the subject of cross-national concern in
Europe. In December 2011 under the new European Framework for National Roma Integration
Strategies, the 27 member states of the EU were required to submit to the European Commission,
National Action Plans (NAPs) on Roma inclusion. A similar action plan addressing the
disadvantage Hill People children face in South Asia could be considered as a way forward.
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In Laos, Thailand and Viet Nam there are already in place, to a varying degree, social policies
and programmes that are meant to level the playing field, so that circumstances such as which
ethnic group you are born into do not influence a child´s life chances. However, without
additional policy action, Hill People children will have little chance to even out the inequality
lived by their parents. As long as Hill People ethnic minority children do not have access to, or
do not utilize, basic services that are considered critical for future advancement in life, inequality
of opportunity will persist.
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