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Decomposing the Ethnic Gap in RuralVietnam, 1993–2004Bob Baulch, Hung T. Pham & Barry Reilly

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To cite this article: Bob Baulch, Hung T. Pham & Barry Reilly (2012): Decomposing the Ethnic Gap inRural Vietnam, 1993–2004, Oxford Development Studies, 40:1, 87-117

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Decomposing the Ethnic Gap in RuralVietnam, 1993–2004

BOB BAULCH, HUNG T. PHAM & BARRY REILLY

ABSTRACT This paper examines and decomposes the gap in per capita expenditures betweenmajorityand minority ethnic groups in rural Vietnam between 1993 and 2004. Over this period, the realexpenditure gap between rural Kinh and Chinese-headed households and those headed by ethnicminorities increasedby14.6%.Approximately two-fifths of themeangap is found to be due todifferencesin household endowments (in particular demographic structure and education), and at least half due todifferences in returns to these endowments. Geographic variables explain less than one-fifth of the gap.Over half of the increase in themean gap is linked to temporal changes in unobservable factors, and lessthan a quarter to the majority’s endowments improving more rapidly than those of the minorities.Broadly similar findings are detected using quantile regression analysis. These findings raise importantquestions concerning the drivers of the disadvantage faced by Vietnam’s ethnic minorities.

JEL Classification: I32, J15

1. Introduction

The rapid economic growth experienced in Vietnam during the 1990s and the early 2000s

resulted in unprecedented poverty reduction. However, the ethnic groups within

Vietnam’s diverse society have not shared equally in the benefits of this growth. Poverty is

high, while life expectancy, nutritional status and other living standard measures remain

low among the ethnic minority groups despite numerous policies introduced to assist them

(Swinkels & Turk, 2006). Indeed, some recent studies (World Bank, 2009; Baulch et al.,

2010) suggest that horizontal (group-wise) inequalities within Vietnam are on the rise.1

A set of recent studies for Vietnam (Van de Walle & Gunewardena, 2001; Baulch et al.,

2004; Hoang et al., 2007), using per capita household expenditure as a welfare measure,

have investigated the average gap in living standards between the majority Kinh and Hoa

(ethnic Chinese) and the other 52 minority groups, assigning the differences to treatment and

endowment components using standard Blinder (1973) and Oaxaca (1973) decomposition

methods. Both components were found statistically to favour the Kinh and Hoa majority.

ISSN 1360-0818 print/ISSN 1469-9966 online/12/010087-31

q 2012 Oxford Department of International Development

http://dx.doi.org/10.1080/13600818.2011.646441

This research was funded by the UK Economic and Social Research Council and Department for International

Development under their Joint Research Scheme (Award Number RES-167-25-0157).

Bob Baulch, School of Business and Economics, Tan Tao University, Long An, Vietnam, and Social

Development Research Initiative, 4 Victoria Place, Bath BA2 5EY, UK. Email: bobbaulch@gmail.com. Hung T.

Pham, National Economics University, Hanoi Indochina Research and Consulting, Hanoi, Vietnam. Barry Reilly,

Department of Economics, University of Sussex, Brighton BN1 9RF, UK.

Oxford Development Studies,Vol. 40, No. 1, 87–117, March 2012

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The poor endowment levels of the ethnic minority groups are sometimes linked to the fact

that most minorities reside in remote and mountainous areas, although this is only a partial

explanation. Baulch et al. (2004, p. 274) noted that “ . . . [e]ven if ethnic minority households

had the same endowments as the Kinh and Hoa (Kinh majority and the Chinese), this would

close no more than a third of the gap in their living standards”. This suggests that the ethnic

minorities secure considerably lower returns to their endowments than the majority.

The existing evidence, while reporting a sizeable ethnic minority disadvantage within

Vietnam, provides no insights on either the magnitude of the gap at different points of the

household expenditure distribution or the evolution of horizontal inequalities over time. The

primary motivation for the current paper is therefore to address these issues by investigating

the factors that drive the level and temporal evolution of the ethnic household welfare gap

using both mean and quantile regression analysis. The decomposition analyses undertaken

attempt to identify the relative contributions of household demographics, education,

landholdings and community characteristics in explaining total treatment and endowment

effects and their change over time.

The structure of the paper is as follows. The next section provides the context for our

empirical analysis through a review of recent economic events in Vietnam. It also details

the nature of Vietnam’s ethnic diversity. This is followed by sections outlining the data

sources and the econometric methodology used, and a section discussing the empirical

results. A final section outlines policy implications and offers some concluding remarks.

2. Background

The Doi Moi (economic renovation) reforms of the late 1980s have stimulated rapid

economic growth in Vietnam over the last two decades, and this has affected greatly poverty

and welfare at the household level. Between 1993 and 2004, Vietnam’s national poverty

headcount fell from 58.1 to 19.5%, while educational enrolments, life expectancy and other

measures of human development increased dramatically (Vietnam Academy of Social

Sciences (VASS), 2007). Though the different groups within Vietnam’s ethnically diverse

society have reaped rewards from such growth, horizontal inequalities have risen because

the benefits have generally not been shared equally. For instance, despite numerous policies

and programmes designed to assist minority groups, the poverty headcount rate among

Vietnam’s broadly defined ethnic minorities fell only from 86.4 to 60.7% between 1993 and

2004 (VASS, 2007). Despite comprising just over one-tenth of the national population, the

minorities accounted for about 40% of the poor in 2004 (VASS, 2007). School enrolments,

nutritional indicators and life expectancy also remain low among the minorities.

Vietnam has 54 officially recognized ethnic groups, of which the Kinh (the Vie_t or

mainstream Vietnamese) accounted for 86.7% in 1999 (Dang et al., 2000). Traditionally,

the Kinh have inhabited lowland and coastal areas in and around Vietnam’s two densely

populated deltas (the Red River Delta and the Mekong River Delta). With the exception of

the Hoa (who tend to live in urban areas and account for 1.1% of the population), the Khmer

(who are concentrated in the Mekong Delta with a 1.2% population share) and the Cham

(representing 0.1% of the population, located along the southern coast), most other ethnic

groups are scattered across Vietnam’s upland and highland areas. Within the upland and

highland areas, some ethnic groups (in particular, the Tay, Thai, , Nung—each of

which has a population of close to one million) specialize in wet-rice cultivation and usually

live in the flatter, lower areas along the valley bottoms (the “midlands”). Other less populous

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groups (such as the Hmong, Dao and Kho-mu in the Northern Uplands and the Ede, Bana

and Hre in the Central Highlands) tend to live in higher, more mountainous areas where

often rice cannot be grown. There are also 17 ethnic groups with populations of less than

10 000, some of which are likely to disappear in the absence of dedicated measures to protect

them (Committee for Ethnic Minorities (CEM), 2009). All ethnic groups have their

individual identities that embody diverse and unique cultures, with groups in the Central

Highlands being more likely to follow matrilineal (uxorial) inheritance practices and, as

with the Hmong, the Christian religion.

Poverty among the different ethnic groups varies considerably, with the poverty

headcount and poverty gaps for the Kinh in 2004 being 13.8 and 2.7%, respectively,

compared with a headcount of 72.3% and a poverty gap above 25% for the Central

Highlands and other northern minorities.2 While poverty has fallen more quickly among

the majority than the minority groups (VASS, 2007), inequality is relatively stable within

the majority group but rising among the minorities.3 Since 1998, a plethora of government

policies and programmes, most focused on improving infrastructure and endowments in

mountainous areas, have been implemented in an attempt to reverse these disparities

(Nguyen & Baulch, 2007). However, as the last independent evaluation of the two main

programmes concluded, while their scale and breadth is clear, their impact on poverty

reduction is less obvious (MOLISA & UNDP, 2004).

Previous studies investigating ethnic minority issues in Vietnam (Van de Walle &

Gunewardena, 2001; Baulch et al., 2004; Hoang et al., 2007) have used the household

surveys conducted in 1993, 1998 and 2004, and have relied on a simple dichotomy

between the Kinh-Hoa and all other ethnic minority groups. The findings reported for these

studies suggest that between one-half and two-thirds of the ethnic gap in household

expenditures is due to differences in returns, with differences in household endowments

and community characteristics accounting for the remainder.

Qualitative studies emphasize the fact that the minorities vary considerably in terms of

their levels of economic and social assimilation, and that the targeting of assistance to the

poorer communes and households reaches only some of the minority groups (World Bank,

2009). Furthermore, despite the many educational benefits that ethnic minority pupils and

students enjoy, their lower educational attainments can be traced back to kindergarten (pre-

school), while the preferential treatment they receive at the post-secondary level may

provide employers with a rationale to prefer Kinh graduates (Vasavakul, 2003; Nguyen &

Baulch, 2007).4 Similarly, many land tenure and agricultural extension policies seem more

appropriate to the needs of Kinh-dominated lowland agriculture than to the diverse and

fragile ecologies of the uplands, where about 70% of Vietnam’s ethnic minorities reside

(Jamieson et al., 1998; Hoang et al., 2004; Vuong, 2007). Finally, policymakers rarely

understand ethnic minority customs and culture, and negative stereotyping and informal

discrimination characterize much government discourse (World Bank, 2009). As a

consequence of these overlapping disadvantages, many ethnic minority groups are poorly

positioned to benefit from the rapid economic growth experienced by the urban and coastal

areas of Vietnam, and constitute a growing share of the country’s poor.

3. Data

This paper uses data drawn from household-level surveys conducted for Vietnam in

1993, 1998 and 2004. The Vietnam Living Standards Surveys (VLSSs) of 1993 and 1998

Decomposing the Ethnic Gap in Rural Vietnam 89

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are multi-topic surveys patterned after the World Bank’s Living Standard Measurement

Surveys with nationally representative samples of 4800 and 6000 households,

respectively (see Annex to Glewwe et al., 2004). A biennial household survey

programme known as the Vietnam Household Living Standards Survey (VHLSS) was

introduced in 2002, which adopted a rotating core-and-module designed with an

expanded sample size intended to provide more representative statistics at the provincial

level (Phung & Nguyen, 2006). However, given the potential presence of large non-

sampling errors in the VHLSS 2002, the VHLSS 2004, which surveyed a total of 9189

households, is the one used in this study. Though the content of the survey

questionnaires has evolved over time, the main modules contained within these three

surveys are comparable and provide a rich set of variables that can be used to model

household welfare. Following the approach adopted in the existing literature, we use per

capita expenditure as the metric to examine ethnic differences in household welfare in rural

Vietnam.5 Although per capita expenditures are an incomplete measure of welfare, there is

considerable evidence to suggest that many of the more commonly used non-monetary

measures of well-being are highly correlated with expenditures in Vietnam (see Glewwe et al.,

2004). We restrict our sample to rural areas both because this is where the vast majority of

Vietnam’s ethnic minorities reside and because of well-documented problems with the urban

sampling frame for the 1998 and 2004 surveys (Poverty Working Group, 1999; Pincus &

Sender, 2006; VASS, 2007).

As our primary purpose is to investigate empirically the household welfare gap between

the majority and the minority ethnic groups, the ethnic group definitions used in previous

studies on Vietnam (Van de Walle & Gunewardena, 2001; Baulch et al., 2004; Swinkels &

Turk, 2006) are adhered to in the current paper. Thus, we treat households headed by either

Kinh or Hoa (ethnic Chinese) as comprising the majority group, and households headed by

those of all other ethnic origins as affiliated to a broadly defined minority group. The

motivation for merging the Chinese with the Kinh to form the majority group relates to the

fact that Chinese-headed households are widely recognized as being relatively well-off

and economically integrated in Vietnam. Approximately 14% of Vietnamese households

were headed by ethnic minorities in 1993, with that figure rising to 17% by 2004.

Table A1 of the Appendix provides a description of the variables used and selected

summary statistics. Using the estimates reported in that table, the average annual growth

rate in real per capita household expenditure for the majority group in rural Vietnam

between 1993 and 2004 is estimated at 4.4%, compared with 3.2% for the minority group.

Over this period, the national poverty headcount fell sharply from 54 to 14% for the

majority group, while declining from 86 to 61% for the minority group.

Further insights on the changes in poverty and welfare over time are obtained by

plotting the kernel densities for per capita household expenditure for majority and

minority groups (Figure 1). The poverty line, using the GSO and World Bank criterion, is

also superimposed on these densities.6 The unbroken plot represents the Kinh and Chinese

and the broken plot that of the other ethnic minority groups. In general, the densities for the

majority group are strongly right-skewed compared with the minority group. The contrasts

between the reduction in headcount poverty between 1993 and 2004 for the two groups can

be largely explained by the mode of the majority group’s distribution having crossed the

poverty line, while the mode for the minorities remains below it.

Finally, Figure 2 depicts the evolution of the mean per capita expenditure gap

between the majority and the minority groups by percentile and survey year. It is

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Den

sity

0 2500

0.0008

0.0006

0.0004

0.0002

0

Den

sity

0.0005

0.0004

0.0002

0.0003

0.0001

0

Den

sity

0.0006

0.0004

0.0002

0

5000 7500 10000 12500 15000Real expenditure per capita (VND thousand) in 1993

0 2500 5000 7500 10000 12500 15000Real expenditure per capita (VND thousand) in 1998

0 2500 5000 7500 10000 12500 15000Real expenditure per capita (VND thousand) in 2004

Figure 1. Kernel density plots of the majority/minority per capita expenditures, 1993–2004.Note: Expenditures per capita are given in January 2004 prices; the solid line represents the kerneldensity of the per capita household expenditures for the Kinh and Chinese; the dashed line representsthat of the other ethnic minority groups. Source:Drawn from VLSS 1993 and 1998, and VHLSS 2004.

Decomposing the Ethnic Gap in Rural Vietnam 91

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evident that the gaps in household living standards have widened considerably over

time at almost all the non-extreme percentiles of the distribution and that the largest

part of the increase occurred between 1998 and 2004. The mean per capita expenditure

among the majority group was 47% higher than that of the minority in 1993, and

increased to 69% by 2004. Our calculations also suggest that the average minority

group’s household expenditure has steadily fallen down the rankings within the

majority household’s actual expenditure distribution (from the 21st percentile in 1993

to the 13th by 2004).

4. Methodology

Separate equations describing the determination of log per capita household expenditure

are specified for the majority (Kinh-Hoa) and minority groups as follows:

ym ¼ xm0bm þ um ð1Þ

ye ¼ xe0be þ ue; ð2Þ

where yj denotes the per capita household expenditure measure expressed in natural

logarithms for the jth ethnic group (where j ¼ m or e, denoting the majority and minority

groups, respectively); x j is a (k £ n) matrix of household characteristics (e.g. household

structure, education of members, household landholding) and community characteristics

(e.g. infrastructure conditions); b is a (k £ 1) vector of unknown parameters capturing the

effects of the relevant covariates on log per capita expenditure; uj is an (n £ 1) vector of

random error terms for which the standard assumptions apply for estimation by ordinary

least squares (OLS). 7

40

60

80

100

120

% d

iffer

ence

in p

c ex

pend

iture

s

0 20 40 60 80 100

Percentiles of expenditure distribution

1993 1998 2004

Figure 2. The majority–minority gap in per capita expenditures in rural areas, 1993–2004.Source: Drawn from VLSS 1993 and 1998, and VHLSS 2004.

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Using the standard decomposition approach (Blinder, 1973; Oaxaca, 1973), the

estimated mean ethnic difference in log per capita household expenditure can be

expressed as:

ym 2 ye ¼ ðxm 2 xeÞ0bm þ xe

0ðbm 2 beÞ; ð3Þ

where the overbar represents mean values, the hat denotes OLS coefficient estimates,

and the subscripts “m” and “e” represent the majority and ethnic minority groups. This

allows the overall average differential in per capita household expenditure between

the two ethnic groups to be decomposed into a part attributable to differences in

characteristics (the endowment component) and a part attributable to differences in the

estimated returns to characteristics between majority and minority households

(the treatment component). The final part of expression (3) is sometimes taken to

reflect the degree of unequal treatment experienced by ethnic minorities. This approach

assumes that in the absence of unequal treatment, the majority group’s coefficient

structure would prevail.8 The overall treatment and endowment components can be

decomposed further into sets of characteristics and coefficient differences to identify

the key factors driving the overall components. In this study, the variables are classified

according to household structure (e.g. household size and the age structure composition

of the household), household education levels, landholding characteristics (e.g.

household’s access to different types of land) and commune characteristics (such as

access to electricity, markets, post offices, roads and schools plus the geographic region

within which the communes are located).9

The decomposition described in equation (3) is cast entirely within the mean regression

framework. An exclusive focus on the mean, however, provides an incomplete account of

the nature of ethnic welfare disadvantage in rural Vietnam. The estimation of a set of

conditional quantile functions allows for a more detailed portrait of the relationship

between the household welfare measure and selected covariates than that provided by

mean regression analysis (Koenker & Bassett, 1978; Deaton, 1997; Koenker, 2005). The

quantile functions are then estimated conditional on a given specification for various

percentiles of the residuals (e.g. 10th, 25th, 50th, 75th or 90th) by minimizing the sum of

absolute deviations of the residuals from the conditional specification (see Chamberlain,

1994). The sampling variances for the quantile regression estimates are obtained using

bootstrapping with 200 replications.10

In the current application, the quantile regression for the majority (m) and minority (e)

subsamples can be defined as:

ym ¼ xm0bum þ uum ð4Þ

ye ¼ xe0bu e þ uu e: ð5Þ

If Qu(·) is taken to denote the conditional uth quantile operator, then Qu ðwjjxjÞ ¼ xj0bu j,

where bujis the unknown parameter vector for the uth quantile, with u representing the

selected quantile of interest (i.e. 0.1, 0.25, 0.5, 0.75 and 0.9 in the current context); uu jdenotes the error term, the distribution of which is left unspecified but for which

QuðmujjxjÞ ¼ 0 is assumed; and subscript j denotes either the majority or the minority

group.

Decomposing the Ethnic Gap in Rural Vietnam 93

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Using equations (4) and (5), the conditional uth quantile functions for the two groups are

expressed as:

QuðymÞ ¼ Eðxmjym ¼ QuðymÞÞ0bum þ Eðmumjym ¼ QuðymÞÞ ð6Þ

QuðyeÞ ¼ Eðxejye ¼ QuðyeÞÞ0bue þ Eðmuejye ¼ QuðyeÞÞ; ð7Þ

where the hats now denote quantile regression estimates and E(·) denotes the expectations

operator. In expressions (6) and (7), the characteristics are evaluated conditionally at the

quantile values for the log household per capita expenditure and not unconditionally as in

the mean regression case. The terms Eðmujjwj ¼ QuðwjÞÞ are thus non-zero. However,

these terms tend to be small and can be conveniently ignored if we decompose the ethnic

household welfare gap in terms of the predicted rather than actual log household

expenditures at selected quantiles. Thus,

D^

u ¼ DVu0bum þVue

0Dbu; ð8Þ

where D^

u denotes the differences in predicted expenditures at the uth quantile; Dbu ¼

ðbum 2 bueÞ; and DVu ¼ Vum 2Vue with Vum ¼ Eðxmjwm ¼ QuðwmÞÞ and Vue ¼

Eðxejwe ¼ QuðweÞÞ. The first and second expressions on the right-hand side of equation

(8) are the quantile regression analogues, respectively, to the differences in characteristics

and differences in returns components reported for the conventional mean-based

decomposition described in equation (3) earlier.

In the computation of expression (8) it is necessary to use realizations of characteristics

that accurately reflect the relevant points on the conditional per capita household

expenditure distribution. In order to address this issue, we use an approach originally

suggested by Machado & Mata (2005) to derive the realizations for the relevant

characteristics at different quantiles of the conditional household expenditure distribution.

The procedure involves drawing 100 observations at random and with replacement from

each of the majority and minority subsamples. Each observation once ranked comprises a

percentile point on the log per capita household expenditure distribution. The full set of

household-level and other characteristics for the observation at the uth expenditure quantile

is then retrieved. This process is then replicated 500 times to obtain 500 observations at the

selected uth quantile. The mean characteristics of these observations at each quantile are

then used to construct the realizations for VumandVueused in expression (8).

We also investigate the temporal evolution of the mean ethnic welfare gap using a

framework developed by Juhn et al. (1991). This framework allows the decomposition of

the change in the average gap across two points in time. Following Reilly (1999), the

procedure used here requires only the OLS estimation of the majority group’s household

expenditure equation for each year of interest. If we denote the mean difference in the

ethnic household welfare gap in year t as dt, the differential in the average ethnic welfare

gap between any two years (labelled with subscripts 1 and 0) can then be decomposed as:

d1 2 d0 ¼ ½Dx1 2 Dx0�0bm1 þ Dx0

0½bm1 2 bm0� þ sm1½Dmm1 2 Dmm0�

þ Dmm0½sm1 2 sm0�; ð9Þ

where smt is the residual (or regression) standard error from the majority group’s

household expenditure equations at time t (t ¼ 0, 1 where 1 is the most recent year), and

94 B. Baulch et al.

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mmt is the standardized residual, which has a mean of zero and a standard deviation of unity

for the majority group; Dmmt is computed as Dmmt ¼ 2½yet 2 xet0bmt�=smt, while Dxt ¼

ðxmt 2 xetÞ:The first term on the right-hand side of equation (4) captures the effect of changes in

differences in (observable) characteristics between the majority and minority groups over

time on the ethnic gap in household welfare. The second term captures the effect of

changes in returns to characteristics for the majority group. The third term captures the

“gap effect”, which measures the impact of changes in the relative position of the average

ethnic minority households within the majority group’s residual household expenditure

distribution. The fourth term reflects changes in residual dispersion of living standards of

the majority group. This term can be taken to reflect the role of temporal changes in the

unobservable coefficient structure. Note that the first and third terms measure ethnic-

specific factors, while the second and fourth capture the effects, respectively, of changing

coefficient structures.

In the context of the quantile regression approach, the most appropriate method to

decompose gaps over time is not entirely transparent. There are a number of different ways

that the temporal change in the predicted gap at selected quantiles can be decomposed. The

approach adopted here requires separate estimation of both majority and minority

regression models at the selected quantiles. This decomposition approach is relatively easy

to estimate, and yields four components that are amenable to straightforward

interpretation. Using this approach, the predicted ethnic welfare gap at selected quantiles

between year 1 and year 0 can be expressed as follows:

D^

u;1 2 D^

u;0 ¼ ðDVu;1 2 DVu;0Þ0bum;1 þ ðVue;1 2Vue;0Þ

0Dbu;1 þ DVu;00ðbum;1

2 bum;0Þ þVue;00ðDbu;1 2 Dbu;0Þ: ð10Þ

Thus, the overall change in the ethnic gap in living standards between two years at the uth

quantile can be decomposed into four parts. The first part is attributable to the change over

time in the (observable) characteristics between the majority and minority groups at the

uth quantile of the conditional expenditure distribution, evaluated using the majority

group’s coefficients. The second part is attributable to the change over time in the

(observable) characteristics of the minority group at the uth quantile of the conditional

distribution. The third part is attributable to the temporal change in the majority group’s

returns to characteristics at the uth quantile. The fourth term is attributable to the change

over time in differences in returns between the majority and minority groups at the uth

quantile of the conditional distribution. The final term offers the potential for insight into

the role of temporally changing ethnically motivated unequal treatment.11

5. Empirical Results

The raw mean ethnic gap in per capita household expenditures rose by 14.6% (0.137 log

points) between 1993 and 2004. As can be seen from Figure 2, most of this increase occurred

over the shorter time period between 1998 and 2004, during which time the ethnic gap

increased by 12% (0.113 log points). The decomposition estimates reported in Table 1 use

the standard Blinder–Oaxaca decomposition of expression (3), and assume the majority

coefficient structure prevails in the absence of unequal treatment.12 The estimated effects

Decomposing the Ethnic Gap in Rural Vietnam 95

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Table

1.

Dec

om

po

siti

on

of

the

eth

nic

dif

fere

nti

alin

ho

use

ho

ldex

pen

dit

ure

sat

the

mea

n,

19

93

–2

00

4

(1)

Wit

hco

mm

un

eco

ntr

ols

(2)

Wit

hd

istr

ict

effe

cts

19

93

19

98

20

04

19

93

19

98

20

04

Totaldifferential

0.3876

**

*0.4112

**

*0.5241

**

*0.3876

**

*0.4112

**

*0.5241

**

*(0.025)

(0.029)

(0.016)

(0.025)

(0.001)

(0.016)

Dueto

differencesin

characteristics

0.1651

**

*0.1585

**

*0.187

**

*0.1909

**

*0.2126

**

*0.2705

**

*ofwhich:

(0.026)

(0.035)

(0.023)

(0.03)

(0.008)

(0.064)

Ho

use

ho

ldst

ruct

ure

0.0

67

5*

**

0.0

67

1*

**

0.1

02

9*

**

0.0

74

4*

**

0.0

69

5*

**

0.1

17

9*

**

(0.0

14

)(0

.00

5)

(0.0

07

)(0

.01

6)

(0.0

03

)(0

.00

6)

Ed

uca

tio

n0

.06

54

**

*0

.07

2*

**

0.0

76

2*

**

0.0

79

6*

**

0.0

82

7*

**

0.0

92

5*

**

(0.0

10

)(0

.00

6)

(0.0

04

)(0

.01

1)

(0.0

05

)(0

.00

4)

Lan

dh

old

ing

20

.02

63

**

20

.03

98

**

*2

0.0

34

**

*2

0.0

10

62

0.0

27

**

*2

0.0

31

1*

**

(0.0

12

)(0

.01

1)

(0.0

08

)(0

.01

)(0

.00

7)

(0.0

08

)C

om

mu

ne

or

dis

tric

tef

fect

s0

.05

85

**

*0

.05

92

*0

.04

19

*0

.04

75

*0

.08

73

**

*0

.09

11

(0.0

20

)(0

.03

2)

(0.0

24

)(0

.02

7)

(0.0

06

)(0

.06

3)

Dueto

differencesin

returns

0.2224

**

*0.2527

**

*0.3371

**

*0.1967

**

*0.1986

**

*0.2555

**

*ofwhich:

(0.033)

(0.045)

(0.028)

(0.034)

(0.008)

(0.064)

Ho

use

ho

ldst

ruct

ure

0.1

11

20

.22

96

0.3

92

3*

*2

0.0

37

90

.04

65

0.1

93

9(0

.26

6)

(0.2

26

)(0

.20

2)

(0.2

49

)(0

.22

8)

(0.1

8)

Ed

uca

tio

n0

.04

40

0.0

01

92

0.0

21

70

.07

28

**

0.0

60

8*

**

0.0

10

8(0

.03

0)

(0.0

31

)(0

.02

0)

(0.0

29

)(0

.02

4)

(0.0

16

)L

and

ho

ldin

g2

0.0

18

02

0.0

36

52

0.0

13

02

0.0

66

9*

20

.07

29

**

20

.05

97

**

*(0

.04

2)

(0.0

31

)(0

.02

0)

(0.0

37

)(0

.03

)(0

.01

7)

Co

mm

un

eo

rd

istr

ict

effe

cts

0.1

96

0*

*0

.30

90

**

0.1

22

00

.18

38

**

0.1

26

3*

**

0.0

40

8(0

.07

9)

(0.1

38

)(0

.12

1)

(0.0

88

)(0

.02

3)

(0.0

99

)C

on

stan

tte

rmef

fect

20

.11

08

20

.25

13

20

.14

26

0.0

44

90

.03

80

.06

96

(0.2

81

)(0

.26

8)

(0.2

4)

(0.2

66

)(0

.23

2)

(0.2

35

)

Notes:

Th

ed

eco

mp

osi

tio

nin

this

tab

leu

ses

the

seto

fm

ajo

rity

coef

fici

ents

asth

ere

fere

nce

gro

up

for

un

equ

altr

eatm

ent;

see

equ

atio

n(3

).F

or

(1),

the

log

of

per

cap

ita

ho

use

ho

ldex

pen

dit

ure

isre

gre

ssed

on

ase

to

fh

ou

seh

old

char

acte

rist

ics

and

ase

to

fco

mm

un

ech

arac

teri

stic

s(i

ncl

ud

ing

geo

gra

ph

ical

typ

eo

fco

mm

un

e,ac

cess

toro

ad,p

ub

lic

tran

spo

rt,p

ost

offi

ce,d

aily

mar

ket

,el

ectr

icit

yan

dh

avin

gfa

cto

ries

loca

ted

wit

hin

10

km

).F

or

(2),

the

set

of

com

mu

ne

char

acte

rist

ics

in(1

)is

rep

lace

db

ya

seto

fd

istr

ictd

um

mie

s.T

he

nu

mb

ero

fd

istr

ictef

fect

sin

clu

ded

was

12

0,1

50

and

57

4in

19

93

,19

98

and

20

04

,res

pec

tiv

ely

.Sta

nd

ard

erro

rsar

ere

po

rted

inp

aren

thes

es.

Th

esu

rvey

des

ign

effe

cts

of

clu

ster

ing

and

stra

tifi

cati

on

are

tak

enin

toac

cou

nt

inth

eco

mp

uta

tio

no

fth

ese

stan

dar

der

rors

.*

**

,*

*,

*S

tati

stic

ally

sig

nifi

can

tat

the

0.0

1,

0.0

5an

d0

.1le

vel

s,re

spec

tiv

ely

.

96 B. Baulch et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f B

ath]

at 0

3:07

16

Febr

uary

201

2

for the regressions for the majority and minority groups are generally signed in accordance

with priors and have plausible magnitudes, and are reported in Table A2 of the Appendix.

Using the specification containing commune characteristics (see note “For (1)” under

Table 1), approximately two-fifths of the gap in all three years is attributable to endowment

differentials. This is consistent with the findings reported in the existing literature. There is

no statistical evidence that the differences in endowments have widened over time, with the

absolute t-ratio for a test of the difference between the initial and terminal years computed at

a statistically insignificant 0.63.

Unlike previous studies, Table 1 attempts to isolate the relative contributions of

demographic factors, education, landholding patterns and community characteristics to the

ethnic expenditure gap. The contributions of differentials in household demographic

structure and education levels to the overall endowment effect are broadly similar, while

differences in community characteristics account for a smaller portion of the ethnic gap

and decline over time. However, different landholding patterns between the majority and

minority groups are found to narrow the endowment differential. The negative signs on the

landholding variables for the mean decompositions possibly reflect the greater experience

and knowledge that ethnic minority peoples have in farming upland areas.

The part of the gap due to differences in returns reported in Table 1 widened by a

statistically significant amount over time. The overall gap due to differences in returns rose

by 0.11 log points between the initial and terminal years, with the estimated absolute

t-ratio computed at 2.6. Thus, almost two-thirds of the household welfare gap was

attributable to differential treatment effects by 2004. The key drivers responsible for the

treatment differentials are less transparent than was the case with regard to the endowment

differentials. However, in both 1993 and 1998 commune characteristics accounted for a

sizeable proportion of the treatment differential in total per capita expenditures.13 By

2004, a sizeable role for the differential treatment effects associated with the set of

demographic structure variables was detected.

If we use the richer set of district-level controls rather than the commune controls, the

interpretational narrative detailed above is not materially altered. The overall endowment

effects are magnified slightly and the treatment differentials attenuated. Indeed, the

estimated difference in these effects between 1993 and 2004 is now statistically

indistinguishable from zero at a conventional level (jtj ¼ 0.81). However, even allowing

for the introduction of a large array of district controls, a sizeable treatment effect,

comprising about one-half of the raw difference, remains for each year. This suggests that

the disadvantaged position of Vietnam’s rural ethnic minority groups cannot be attributed

exclusively to the role of geography and the concentration of ethnic minorities within the

more remote parts of the country.

We now turn to a discussion of the decompositions computed at selected points of the

conditional expenditure distribution using equation (8).14 The estimates for this exercise

are reported for the three years in Tables 2–4. In all cases, the point estimates for the raw

ethnic gap in household welfare exhibit an increase between the 10th and 90th percentiles,

though the evolution of the increase is not monotonic for any of the three years. The

portion of the mean gap accounted for by endowment differences is fairly stable across the

selected percentiles and comprises between one-fifth and two-fifths of the relevant total

raw gap in each of the three years. The roles played by household demographic structure,

education and commune characteristics in determining the overall endowment effects are

similar to the findings obtained using the mean regression analysis for all years. In a direct

Decomposing the Ethnic Gap in Rural Vietnam 97

Dow

nloa

ded

by [

Uni

vers

ity o

f B

ath]

at 0

3:07

16

Febr

uary

201

2

Table

2.

Dec

om

po

siti

on

of

the

eth

nic

dif

fere

nti

alin

ho

use

ho

ldex

pen

dit

ure

atse

lect

edq

uan

tile

s,1

99

3

10

th2

5th

50

th7

5th

90

th

Totaldifferential

0.3767***

0.3085***

0.2949***

0.4113***

0.4716***

(0.035)

(0.036)

(0.029)

(0.028)

(0.042)

Dueto

differencesin

characteristics

0.1336***

0.0834**

0.1484***

0.1576***

0.1975***

ofwhich:

(0.047)

(0.036)

(0.025)

(0.027)

(0.051)

Ho

use

ho

ldst

ruct

ure

0.0

48

5*

**

0.0

38

8*

**

0.0

56

2*

**

0.0

85

9*

**

0.0

66

5*

**

(0.0

1)

(0.0

06

)(0

.00

8)

(0.0

06

)(0

.00

9)

Ed

uca

tio

n0

.05

09

**

*0

.03

70

**

*0

.06

69

**

*0

.05

38

**

*0

.11

90

**

*(0

.01

1)

(0.0

07

)(0

.00

9)

(0.0

08

)(0

.02

7)

Lan

dh

old

ing

20

.01

82

0.0

48

42

0.0

26

8*

**

20

.04

59

**

*2

0.0

38

9*

**

(0.0

25

)(0

.03

2)

(0.0

11

)(0

.00

9)

(0.0

14

)C

om

mu

ne

char

acte

rist

ics

0.0

52

30

.05

60

**

0.0

52

1*

**

0.0

63

7*

*0

.05

09

(0.0

42

)(0

.02

4)

(0.0

19

)(0

.02

8)

(0.0

44

)

Dueto

differencesin

returns

0.2431***

0.2251***

0.1465***

0.2538***

0.2742***

ofwhich:

(0.061)

(0.051)

(0.039)

(0.038)

(0.061)

Ho

use

ho

ldst

ruct

ure

20

.23

49

0.3

28

20

.66

67

*0

.48

58

20

.05

16

(0.4

38

)(0

.41

1)

(0.3

67

)(0

.36

5)

(0.3

76

)E

du

cati

on

0.0

09

10

.03

71

0.0

45

30

.01

41

0.0

29

9(0

.06

2)

(0.0

43

)(0

.03

5)

(0.0

38

)(0

.07

1)

Lan

dh

old

ing

20

.00

35

20

.00

01

20

.06

6*

0.0

11

62

0.0

35

8(0

.05

8)

(0.0

57

)(0

.03

7)

(0.0

45

)(0

.05

6)

Co

mm

un

ech

arac

teri

stic

s0

.16

23

0.2

95

30

.17

91

*0

.11

18

0.0

42

5(0

.18

7)

(0.1

46

)(0

.11

5)

(0.1

02

)(0

.12

4)

Co

nst

ant

term

effe

ct0

.31

02

20

.43

54

20

.67

85

*2

0.3

69

50

.28

91

(0.4

69

)(0

.44

9)

(0.3

93

)(0

.36

4)

(0.4

13

)

Notes:

Th

ed

eco

mp

osi

tio

nin

this

tab

leu

ses

the

set

of

maj

ori

tyco

effi

cien

tsas

the

refe

ren

ceg

rou

pfo

ru

neq

ual

trea

tmen

t;se

eeq

uat

ion

(8)

inth

ete

xt.

Th

elo

gp

erca

pit

ah

ou

seh

old

exp

end

itu

reis

reg

ress

edo

na

set

of

ho

use

ho

ldch

arac

teri

stic

san

da

set

of

com

mu

ne

char

acte

rist

ics

(in

clu

din

gg

eog

rap

hic

alty

pes

of

com

mu

nes

,ac

cess

toro

ad,

pu

bli

ctr

ansp

ort

,p

ost

offi

ce,

dai

lym

ark

et,

elec

tric

ity

and

hav

ing

fact

ori

eslo

cate

dw

ith

in1

0k

m).

Sta

nd

ard

erro

rsar

ere

po

rted

inp

aren

thes

esan

dar

eb

ased

on

bo

ots

trap

pin

gw

ith

20

0re

pli

cati

on

s.*

**

,*

*,

*S

tati

stic

ally

sig

nifi

can

tat

the

0.0

1,

0.0

5an

d0

.1le

vel

s,re

spec

tiv

ely

.

98 B. Baulch et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f B

ath]

at 0

3:07

16

Febr

uary

201

2

Table

3.

Dec

om

po

siti

on

of

the

eth

nic

dif

fere

nti

alin

ho

use

ho

ldex

pen

dit

ure

atse

lect

edq

uan

tile

s,1

99

8

10

th2

5th

50

th7

5th

90

th

Totaldifferential

0.4049

**

*0.4773

**

*0.4084*

**

0.5367

**

*0.6151

**

*(0.031)

(0.024)

(0.024)

(0.026)

(0.043)

Dueto

differencesin

characteristics

0.1713

**

*0.1991

**

*0.1807*

**

0.1909

**

*0.2152

**

*ofwhich:

(0.025)

(0.028)

(0.029)

(0.029)

(0.063)

Ho

use

ho

ldst

ruct

ure

s0

.11

46

**

*0

.06

62

**

*0

.08

79*

**

0.0

62

**

*0

.11

34

**

*(0

.01

)(0

.00

5)

(0.0

05

)(0

.00

6)

(0.0

13

)E

du

cati

on

0.0

53

6*

**

0.0

74

9*

**

0.0

57

7*

**

0.1

03

8*

**

0.0

73

4*

**

(0.0

08

)(0

.01

6)

(0.0

04

)(0

.01

)(0

.01

2)

Lan

dh

old

ing

20

.02

78

**

20

.02

31

**

20

.08

84*

**

20

.02

71

20

.05

5(0

.01

2)

(0.0

11

)(0

.02

3)

(0.0

18

)(0

.04

8)

Co

mm

un

ech

arac

teri

stic

s0

.03

1*

*0

.08

11

**

*0

.12

35*

**

0.0

52

20

.08

34

**

(0.0

16

)(0

.02

)(0

.02

5)

(0.0

21

)(0

.04

)

Dueto

differencesin

returns

0.2336

**

*0.2782

**

*0.2277*

**

0.3458

**

*0.3998

**

*ofwhich:

(0.037)

(0.035)

(0.041)

(0.037)

(0.08)

Ho

use

ho

ldst

ruct

ure

s0

.00

05

0.2

26

50

.46

96*

0.6

98

7*

*0

.12

85

(0.3

56

)(0

.29

4)

(0.2

63

)(0

.32

8)

(0.4

)E

du

cati

on

20

.03

08

20

.02

43

20

.01

91

20

.00

69

20

.01

96

(0.0

45

)(0

.03

7)

(0.0

35

)(0

.03

5)

(0.0

44

)L

and

ho

ldin

g2

0.0

86

4*

*2

0.0

53

1*

20

.01

08

20

.01

97

20

.05

12

(0.0

44

)(0

.03

4)

(0.0

5)

(0.0

43

)(0

.06

9)

Co

mm

un

ech

arac

teri

stic

s0

.12

05

0.2

86

4*

*0

.29

68*

*0

.40

97

**

*0

.45

88

**

*(0

.14

3)

(0.1

19

)(0

.10

8)

(0.1

17

)(0

.14

4)

Co

nst

ant

term

effe

ct0

.22

98

20

.15

72

20

.50

88*

20

.73

61

**

20

.11

68

(0.3

53

)(0

.31

4)

(0.2

83

)(0

.33

6)

(0.4

01

)

Notes:

See

no

tes

toT

able

2.

Decomposing the Ethnic Gap in Rural Vietnam 99

Dow

nloa

ded

by [

Uni

vers

ity o

f B

ath]

at 0

3:07

16

Febr

uary

201

2

Table

4.

Dec

om

po

siti

on

of

the

eth

nic

dif

fere

nti

alin

ho

use

ho

ldex

pen

dit

ure

atse

lect

edq

uan

tile

s,2

00

4

10

th2

5th

50

th7

5th

90

th

Totaldifferential

0.482

**

*0.5865

**

*0.5941*

**

0.5524

**

*0.5485

**

*(0.024)

(0.019)

(0.022)

(0.026)

(0.024)

Dueto

differencesin

characteristics

0.207

**

*0.2438

**

*0.2471*

**

0.1973

**

*0.200

**

*ofwhich:

(0.026)

(0.027)

(0.024)

(0.027)

(0.039)

Ho

use

ho

ldst

ruct

ure

s0

.07

06

**

*0

.13

09

**

*0

.11

66*

**

0.1

08

3*

**

0.1

41

7*

**

(0.0

08

)(0

.01

)(0

.00

7)

(0.0

09

)(0

.01

2)

Ed

uca

tio

n0

.07

66

**

*0

.08

17

**

*0

.11

36*

**

0.0

87

9*

**

0.0

48

6*

**

(0.0

06

)(0

.00

6)

(0.0

06

)(0

.00

6)

(0.0

04

)L

and

ho

ldin

g2

0.0

30

8*

**

20

.04

12

**

*2

0.0

59

7*

**

20

.03*

**

20

.02

36

(0.0

11

)(0

.01

)(0

.00

8)

(0.0

1)

(0.0

22

)C

om

mu

ne

char

acte

rist

ics

0.0

90

7*

**

0.0

72

4*

**

0.0

76

6*

**

0.0

31

20

.03

34

(0.0

23

)(0

.02

4)

(0.0

23

)(0

.02

4)

(0.0

32

)

Dueto

differencesin

returns

0.275

**

*0.3427

**

*0.347*

**

0.3551

**

*0.3485

**

*ofwhich:

(0.038)

(0.033)

(0.032)

(0.033)

(0.047)

Ho

use

ho

ldst

ruct

ure

s0

.41

79

0.4

02

40

.30

05

0.3

26

40

.02

19

(0.3

01

)(0

.27

2)

(0.2

2)

(0.2

5)

(0.4

29

)E

du

cati

on

20

.01

09

20

.00

75

20

.01

06

20

.01

57

20

.09

88

**

*(0

.02

7)

(0.0

23

)(0

.02

8)

(0.0

3)

(0.0

34

)L

and

ho

ldin

g0

.01

03

0.0

03

32

0.0

06

82

0.0

32

32

0.0

24

8(0

.03

1)

(0.0

26

)(0

.02

3)

(0.0

24

)(0

.03

2)

Co

mm

un

ech

arac

teri

stic

s0

.13

58

0.2

56

9*

**

0.1

88

7*

0.0

44

32

0.0

22

6(0

.17

7)

(0.1

44

)(0

.11

5)

(0.1

22

)(0

.17

5)

Co

nst

ant

term

effe

ct2

0.2

78

12

0.3

12

52

0.1

24

90

.03

24

0.4

72

8(0

.35

9)

(0.2

99

)(0

.24

8)

(0.2

81

)(0

.47

5)

Notes:

See

no

tes

toT

able

2.

100 B. Baulch et al.

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uary

201

2

comparison between 1993 and 2004, the estimated differences in the magnitudes of the

endowment and treatment effects were found to be statistically significant only in a couple

of cases for each of the two component parts. The estimated endowment effect rose by a

statistically significant 0.16 log points at the 25th percentile (jtj ¼ 3.57) and by 0.097 log

points at the median (jtj ¼ 2.86). The treatment component rose by 0.20 log points at the

median (jtj ¼ 3.98) and by 0.10 log points at the 75th percentile (jtj ¼ 2.01).15

The Juhn, Murphy and Pierce (1991) decomposition is now exploited to investigate the

evolution of the mean gap in per capita expenditures between the majority and minority

groups over time. The analysis is undertaken separately for 1993 and 2004 and for 1998

and 2004.16 The results are reported in Tables 5 and 6, which decompose the changes in

the ethnic gap into the four component parts described in equation (9).

Approximately 70% of the 0.137 log point increase in the ethnic gap between 1993 and

2004 is attributable to changes in unobservable characteristics and around one-fifth to

changes in observable characteristics (Table 6). Changes in the observed coefficient

structure account for most of the remaining differential.

Table 5. Temporal decomposition of the ethnic differential in household expenditures at the mean

1993–2004 1998–2004

Change in the differential 0.1371*** 0.1129***(0.024) (0.033)

Due to changes in observed characteristics 0.0249 0.0277**of which: (0.017) (0.011)

Household structure 0.0329*** 0.0369***(0.002) (0.003)

Education 0.0142*** 0.0027**(0.001) (0.001)

Landholding 20.0176*** 20.0211***(0.004) (0.006)

Commune characteristics 20.0046 0.0092(0.017) (0.01)

Due to changes in observed coefficient structure 0.0093 0.0010of which: (0.034) (0.041)

Household structure 0.0012 20.0012(0.008) (0.007)

Education 20.0029 0.0016(0.009) (0.007)

Landholding 0.0252*** 0.0288**(0.009) (0.013)

Commune characteristics 20.0141 20.0281(0.034) (0.039)

Due to changes in unobserved characteristics 0.0963* 0.0689*(0.053) (0.045)

Due to changes in unobserved coefficient structure 0.0066*** 0.0153***(0.0005) (0.0008)

Notes: See equation (9) for a description of the decomposition. Standard errors are reported inparentheses. Standard errors for the final two entries are calculated using bootstrapping (using theminority subsample of households) with 1000 replications.

***, **, *Statistically significant at the 0.01, 0.05 and 0.1 levels, respectively.

Decomposing the Ethnic Gap in Rural Vietnam 101

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2

Table

6.

Tem

po

ral

dec

om

po

siti

on

of

the

eth

nic

gap

inh

ou

seh

old

exp

end

itu

res

atse

lect

edq

uan

tile

s,1

99

3–

20

04

10

th2

5th

Med

ian

75

th9

0th

Changein

totaldifferential

0.1053

**

0.2779

**

*0.2992

**

*0.1411

**

*0.0769

*(0.049)

(0.038)

(0.039)

(0.036)

(0.047)

Changein

observable

characteristics

0.0249

20.0472

0.05

0.0362

0.0017

(betweenmajority

andminority

groups)

(0.089)

(0.064)

(0.072)

(0.066)

(0.116)

ofwhich:

Ho

use

ho

ldst

ruct

ure

20

.00

53

0.0

19

20

.01

93

20

.00

03

20

.01

9(0

.01

8)

(0.0

15

)(0

.01

8)

(0.0

19

)(0

.03

3)

Ed

uca

tio

n0

.01

73

0.0

26

1*

*0

.01

54

0.0

13

0.0

01

(0.0

14

)(0

.01

1)

(0.0

1)

(0.0

11

)(0

.01

1)

Lan

dh

old

ing

20

.01

62

0.0

24

3*

20

.00

05

20

.00

86

0.0

00

9(0

.02

2)

(0.0

15

)(0

.01

4)

(0.0

16

)(0

.01

8)

Co

mm

un

ech

arac

teri

stic

s0

.02

89

20

.06

80

.05

44

0.0

32

10

.01

88

(0.0

84

)(0

.05

7)

(0.0

65

)(0

.06

1)

(0.1

09

)

Changein

observable

ethnic

differences

0.0285

0.1969

**

*0.1011

**

*2

0.0254

20.0071

oftheminority

group

(0.036)

(0.026)

(0.02)

(0.024)

(0.046)

ofwhich:

Ho

use

ho

ldst

ruct

ure

0.0

21

4*

**

0.1

11

3*

**

0.0

74

3*

**

0.0

08

60

.06

99

**

*(0

.00

7)

(0.0

08

)(0

.00

5)

(0.0

06

)(0

.01

2)

Ed

uca

tio

n0

.02

89

**

*0

.05

97

**

*0

.05

36

**

*0

.03

79

**

*2

0.0

37

7*

**

(0.0

03

)(0

.00

4)

(0.0

05

)(0

.00

4)

(0.0

1)

Lan

dh

old

ing

20

.00

78

0.0

07

72

0.0

43

8*

**

20

.01

81

**

*2

0.0

07

4(0

.01

1)

(0.0

1)

(0.0

07

)(0

.00

7)

(0.0

14

)C

om

mu

ne

char

acte

rist

ics

20

.01

40

.01

82

0.0

16

92

0.0

53

7*

*2

0.0

31

9(0

.03

4)

(0.0

2)

(0.0

2)

(0.0

22

)(0

.04

)

Changein

themajority

group’s

returnsto

characteristics

0.0449

20.0366

20.0023

0.0652

0.0096

ofwhich:

(0.067)

(0.046)

(0.038)

(0.044)

(0.079)

Ho

use

ho

ldst

ruct

ure

0.0

00

72

0.0

19

3*

*2

0.0

13

90

.01

38

*0

.00

53

(0.0

13

)(0

.01

)(0

.01

)(0

.00

9)

(0.0

12

)E

du

cati

on

20

.00

32

20

.01

51

**

20

.00

72

0.0

03

82

0.0

32

7(0

.01

3)

(0.0

08

)(0

.00

9)

(0.0

1)

(0.0

34

)

102 B. Baulch et al.

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Febr

uary

201

2

Lan

dh

old

ing

20

.00

52

0.0

00

50

.01

09

0.0

34

**

*0

.02

26

(0.0

25

)(0

.03

)(0

.01

1)

(0.0

1)

(0.0

15

)C

om

mu

ne

char

acte

rist

ics

0.0

52

32

0.0

01

70

.00

76

0.0

21

20

.01

44

(0.0

63

)(0

.03

7)

(0.0

37

)(0

.04

4)

(0.0

73

)

Changein

differencesin

returns

0.007

0.1647

**

0.1505

*0.0651

0.0727

(betweenmajority

andminority

groups)

(0.118)

(0.084)

(0.086)

(0.085)

(0.137)

ofwhich:

Ho

use

ho

ldst

ruct

ure

0.6

58

0.0

55

22

0.3

46

82

0.1

59

10

.09

26

(0.5

82

)(0

.49

2)

(0.4

)(0

.4)

(0.5

25

)E

du

cati

on

20

.03

71

20

.07

06

20

.07

13

*2

0.0

42

72

0.1

29

8*

(0.0

73

)(0

.05

2)

(0.0

45

)(0

.04

3)

(0.0

82

)L

and

ho

ldin

g0

.02

98

0.0

27

80

.05

97

20

.03

53

0.0

10

1(0

.06

3)

(0.0

63

)(0

.04

2)

(0.0

41

)(0

.05

9)

Co

mm

un

ech

arac

teri

stic

s2

0.0

55

50

.02

95

20

.04

48

20

.09

96

20

.08

39

(0.2

75

)(0

.21

6)

(0.1

49

)(0

.14

8)

(0.1

82

)C

on

stan

tte

rmef

fect

20

.58

82

0.1

22

90

.55

37

0.4

01

90

.18

36

(0.6

16

)(0

.51

3)

(0.4

44

)(0

.41

9)

(0.5

98

)

Notes:

See

equ

atio

n(1

0).

Sta

nd

ard

erro

rsar

ere

po

rted

inp

aren

thes

es.

**

*,

**

,*

Sta

tist

ical

lysi

gn

ifica

nt

atth

e0

.01

,0

.05

and

0.1

lev

els,

resp

ecti

vel

y.

Decomposing the Ethnic Gap in Rural Vietnam 103

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uary

201

2

The first component of the Juhn, Murphy and Pierce decomposition captures the

contribution of changes in observed characteristics in explaining the changes in the

ethnic gap. This component accounts for one-fifth of the overall change in the ethnic gap

between 1983 and 2004, and one-quarter for the shorter period between 1998 and 2004.

As shown in Table 5, the most important subset of characteristics relates to ethnic

differentials in household demographic structure variables followed by changes in ethnic

differences in education. By contrast, changes in ethnic differences with respect to

landholdings serve to narrow the temporal change in the household welfare gap. The

second component of the decomposition, which shows temporal changes in the majority

group’s coefficient structure, accounts for a modest part of the rise in the ethnic gap.

Moreover, the estimated effect is not found to be significant at a conventional level.17

The third component is the most important: about 70% of the overall temporal change is

accounted for by changes in unobservable household and community characteristics.

This component reflects the sharp decline in the percentile rankings of the average

minority household within the majority group’s residual welfare distribution. Just over

60% of this change occurred between 1998 and 2004. The final component of the

decomposition reveals that changes in the residual dispersion of the welfare measure

account for little of the rising ethnic welfare gap.

Overall, the ethnic-specific factors relating to observable and unobservable

characteristics account for over 80% of the increase in the ethnic expenditure gap.

There appears to be a negligible role for changes in coefficient structure, whether observed

(i.e. changes in the estimated coefficients over time) or unobserved (i.e. changes in the

residual expenditure dispersion over time). That around two-thirds of the increase in the

ethnic gap between these two years is attributable to unobserved factors is noteworthy and

could be linked to either greater unobserved heterogeneity and/or an increasingly unequal

treatment of the ethnic minorities within Vietnam in recent times (see Section 6).

Finally, an analysis of the temporal changes in the ethnic gaps at selected quantiles is

implemented using expression (10). The results of this exercise are reported in Tables 6

and 7, and are again based on comparisons conducted between 1993 and 2004, and 1998

and 2004, respectively. For the period 1993–2004 (Table 6), the differentials in the

temporal change in the overall predicted raw gaps were found to be statistically significant

at all the selected quantiles, with the lowest gaps at the two extreme percentile points used

in our analysis. At the median, the predicted gap rose by approximately 0.30 log points

between 1993 and 2004. About one-third of this change is attributable to changes over

time in the characteristics of the minority group, with changes in household structure and

educational levels being the most important subset of variables. Approximately one-half

of the increase in the ethnic disadvantage at the median is attributable to a widening of the

gap between majority and minority returns to included characteristics.18

The results reported in Table 7 for 1998–2004 are broadly congruent with the findings

of Table 6. However, the share of the change in the ethnic gap accounted for by changes in

the difference in returns at the median rose to almost three-fifths, while that accounted for

by changes in observable ethnic differentials declined to one-twentieth; but none of the

subsets of variables was found to be statistically significantly from zero in this case,

underlining the need for further interrogation of the two unobserved components of the

decomposition within the most recent 6-year period. By contrast, the subsets of variables

for household structure, education and landholdings explain most of the changes in

observable ethnic differences that occurred over the same period.

104 B. Baulch et al.

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Table

7.

Tem

po

ral

dec

om

po

siti

on

of

the

eth

nic

gap

inh

ou

seh

old

exp

end

itu

res

atse

lect

edq

uan

tile

s,1

99

8–

20

04

10

th2

5th

Med

ian

75

th9

0th

Changein

totaldifferential

0.0771

**

0.1092*

**

0.1853

**

*0.0157

20.0666

(0.038)

(0.031)

(0.033)

(0.033)

(0.051)

Changein

observable

characteristics

0.0103

20.0269

0.0099

0.0101

20.0805

(betweenmajority

andminority

groups)

(0.045)

(0.05)

(0.041)

(0.03)

(0.061)

ofwhich:

Ho

use

ho

ldst

ruct

ure

20

.01

45

0.0

12

42

0.0

22

72

0.0

25

3*

*2

0.0

25

2(0

.01

9)

(0.0

13

)(0

.01

5)

(0.0

11

)(0

.02

)E

du

cati

on

0.0

14

90

.01

42

0.0

29

5*

*0

.01

85

*0

.00

32

(0.0

11

)(0

.01

1)

(0.0

12

)(0

.01

)(0

.01

2)

Lan

dh

old

ing

20

.01

81

20

.03

8*

*2

0.0

18

82

0.0

28*

*2

0.0

41

6*

(0.0

17

)(0

.01

7)

(0.0

13

)(0

.01

3)

(0.0

26

)C

om

mu

ne

char

acte

rist

ics

0.0

27

92

0.0

15

50

.02

19

0.0

45*

**

20

.01

7(0

.03

5)

(0.0

4)

(0.0

31

)(0

.01

7)

(0.0

43

)

Changein

observable

ethnic

differences

20.0123

0.0608*

**

0.044

**

0.0044

0.0121

oftheminority

group

(0.028)

(0.02)

(0.019)

(0.011)

(0.04)

ofwhich:

Ho

use

ho

ldst

ruct

ure

20

.03

76

**

*0

.07

12*

**

0.0

26

8*

**

0.0

43

5*

**

20

.00

52

(0.0

08

)(0

.00

7)

(0.0

07

)(0

.00

6)

(0.0

09

)E

du

cati

on

0.0

09

6*

**

20

.00

19

0.0

56

1*

**

20

.00

36

20

.00

34

(0.0

02

)(0

.00

5)

(0.0

05

)(0

.00

3)

(0.0

06

)L

and

ho

ldin

g0

.01

51

20

.00

72

0.0

20

7*

**

20

.02

5*

**

0.0

19

2(0

.01

2)

(0.0

1)

(0.0

07

)(0

.00

6)

(0.0

2)

Co

mm

un

ech

arac

teri

stic

s0

.00

07

20

.00

16

20

.01

82

20

.01

05

*0

.00

15

(0.0

25

)(0

.01

4)

(0.0

17

)(0

.00

6)

(0.0

3)

Changein

themajority

group’s

returnsto

characteristics

0.0479

20.0161

0.0219

0.0021

20.0273

ofwhich:

(0.044)

(0.042)

(0.04)

(0.037)

(0.072)

Ho

use

ho

ldst

ruct

ure

20

.00

64

20

.00

66

0.0

01

60

.00

28

0.0

33

4*

*(0

.01

4)

(0.0

06

)(0

.00

8)

(0.0

1)

(0.0

17

)E

du

cati

on

0.0

13

40

.00

87

20

.00

04

20

.01

23

20

.02

14

(Continued

)

Decomposing the Ethnic Gap in Rural Vietnam 105

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uary

201

2

Table

7.Continued

10

th2

5th

Med

ian

75

th9

0th

(0.0

1)

(0.0

15

)(0

.00

5)

(0.0

12

)(0

.01

6)

Lan

dh

old

ing

20

.01

81

20

.01

10

.04

94

**

0.0

22

20

.01

22

(0.0

16

)(0

.01

2)

(0.0

23

)(0

.01

7)

(0.0

42

)C

om

mu

ne

char

acte

rist

ics

0.0

59

20

.00

71

20

.02

87

20

.01

06

20

.05

16

(0.0

41

)(0

.03

5)

(0.0

36

)(0

.03

)(0

.05

8)

Changein

differencesin

returns

0.0312

0.0914

0.1095

**

20.0009

0.0292

(betweenmajority

andminority

groups)

(0.067)

(0.07)

(0.057)

(0.053)

(0.1)

ofwhich:

Ho

use

ho

ldst

ruct

ure

0.4

31

80

.16

35

20

.14

21

20

.34

72

0.0

81

4(0

.47

4)

(0.3

99

)(0

.35

5)

(0.4

13

)(0

.51

5)

Ed

uca

tio

n0

.00

50

.00

26

20

.02

06

20

.02

73

20

.08

25

*(0

.06

)(0

.04

5)

(0.0

41

)(0

.04

5)

(0.0

52

)L

and

ho

ldin

g0

.11

48

**

0.0

94

4*

*0

.02

28

0.0

15

30

.06

8(0

.05

)(0

.04

3)

(0.0

5)

(0.0

46

)(0

.06

6)

Co

mm

un

ech

arac

teri

stic

s2

0.0

12

62

0.0

14

20

.13

20

.41

04

**

*2

0.4

64

5*

*(0

.20

2)

(0.1

79

)(0

.13

9)

(0.1

62

)(0

.22

3)

Co

nst

ant

term

effe

ct2

0.5

07

82

0.1

55

30

.37

93

0.7

68

4*

0.5

89

6(0

.49

8)

(0.4

48

)(0

.38

)(0

.43

7)

(0.5

56

)

Notes:

See

no

tes

toT

able

6.

106 B. Baulch et al.

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uary

201

2

6. Summary and Conclusions

In 1946, Ho Chi Minh famously asserted that:

As people born from the same womb, whether Kinh or Tho, Muong or Man, Gia Rai or

Ede, Xedang or Bana, or any other ethnic minority, all of us are the children of Vietnam,

all of us are brothers and sisters. We live and die together, share happiness and sorrow

together, [and] whether hungry or full, we help each other. (Dao et al., 2000, p. 545)

It is now over 30 years since the reunification of Vietnam and around 20 since the Doi Moi

economic reforms were first initiated. The rapid economic growth experienced since the

early 1990s has certainly been of central importance in poverty reduction and improving

the well-being of the Vietnamese people across a broad range of dimensions. However, on

the basis of the empirical analysis reported in this paper, it is clear that the ethnic

minorities have not benefited from this process to the same extent as the Kinh-Hoa

majority. Indeed, economic horizontal inequalities are substantial and rising, with the

ethnic gap in per capita expenditures in rural Vietnam widening considerably since 1998.

The increase in the ethnic expenditure gap in rural areas has, however, been relatively

constant across the conditional expenditure distribution, with little evidence that it has

widened more among either the richer or the poorer households.

In line with the existing literature, this study found that the larger portion of the ethnic

gap in household welfare levels is attributable to differences in returns to endowments

(treatment effects) rather than the differences in the endowments themselves. Previous

studies using mean regression analysis have found this to be a persistent feature over time

in the mean expenditure gap, but we have shown it is also the case at selected quantiles of

the conditional household expenditure distribution. The factors underlying the overall

treatment differentials are difficult to unpick, although the estimated differences in returns

due to household demographic structure were found to be important in both mean and

median regression analysis. The characteristics driving the endowment differentials were

more clear-cut and comprised, in order of importance, ethnic differences in household

demographic structure, education levels and commune characteristics.

As ethnic minorities in Vietnam tend to live in higher, more mountainous and more

remote areas than the majority, a failure to control for spatial heterogeneity may bias, among

other things, the estimated treatment effects. We therefore introduced controls for a large

number of districts. An important finding of the current study is that, even allowing for the

introduction of such a large array of district effects, a sizeable treatment effect remains in all

years. This finding supports the view that the horizontal inequalities between ethnic

minority groups in rural Vietnam cannot be ascribed entirely to the role of geography and the

concentration of ethnic minorities within the more remote parts of the country.

1The widening of the mean ethnic expenditure gap over the 11-year interval we analysed

was dramatic and mostly concentrated in the second half of this period. The rise was not

restricted to the mean but occurred at most points of the conditional household expenditure

distribution. Our temporal decomposition analysis shows that at least half of the increase in

the ethnic expenditure gap is attributable to changes in unobservable characteristics, with

less than a quarter due to changes in the observable ethnic differences in characteristics.

Changes over time in coefficient structure, whether observed or unobserved, accounted for a

negligible part of the increase. This finding appears to be invariant to the use of mean or

quantile regression analysis.

Decomposing the Ethnic Gap in Rural Vietnam 107

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In an additional piece of research undertaken in this study, following an approach

suggested in Pham & Reilly (2009), we used auxiliary regression analysis in an attempt to

uncover the role of cultural, geographic and language variables in explaining the variation in

the estimated treatment effects across the minority groups. The point estimates obtained

suggest that membership of the Central Highlands minorities, lack of ability in the

Vietnamese language, and distance to the commune and district centres amplified the

treatment effects, while membership of the Khmer and Cham ethnic groups or being a

Christian diminished them. However, these estimated effects were generally not found to be

well-determined across all three survey years, and any inferences must be treated with a

great deal of interpretational caution. We are thus left to conjecture that the source of these

unexplained differences may be partially rooted in: negative stereotyping and poor

understanding of ethnic minority customs and cultures; and unobserved variations in

household-level endowments (e.g. education, distance from the commune centre and land

quality). Unfortunately, the data available to us do not permit us to distinguish empirically

between these two probably reinforcing and complementary explanations.

This paper’s empirical results do suggest that the geographically targeted and infrastructure-

focused interventions that have been implemented in Vietnam’s ethnic minority areas since

1998 have not been able to counteract the widening gap in majority–minority living standards.

Policies and programmes are also required to enhance the lower returns that the ethnic

minorities obtain from their endowments.19 These and other measures that reduce and

dismantle the multiple barriers that restrict most ethnic minorities fromparticipating fully in the

growth process are urgently required. By doing this, Ho Chi Minh’s vision of equality and

mutual interdependence among all Vietnam’s ethnic groups can be furthered.

Notes

1 Horizontal inequality is not a term that is in common use in Vietnam, although group-wise inequality is

clearly of concern to national policymakers. For a useful overview of the horizontal inequality

literature, see Stewart et al. (2005).2 These estimates are based on the authors’ own calculations using the VHLSS 2004.3 The estimated Gini coefficient for the Kinh and Hoa majority located in rural areas, based on the per

capita household expenditure measure, is approximately 0.27 for both 1993 and 2004. By contrast,

household expenditures within the minority groups have become more unequal, with Gini rising from

0.24 in 1993 to 0.29 in 2004. The differential in the Gini point estimates for the minority group across

these two years is statistically significant at a conventional level.4 Ethnic minority students can attend college or university without taking the normal entrance

examinations if they are nominated by their provincial authorities, or can attend one of three pre-

universities if their examination score grades do not qualify them for immediate admission to college

or university. Some colleges and universities also have special classes for ethnic minority students,

although such classes are now less common than in the past (Nguyen & Baulch, 2007).5 Our chosen measure is defined as real household per capita expenditure computed on the basis of total

household food and non-food consumption over the past 12 months. The living standard variable is

expressed in real terms at January 2004 prices.6 There are two poverty lines in common use within Vietnam: the GSO-World Bank poverty line (which is

based on a standard “cost-of-basic-needs” methodology and estimated from the V(H)LSS) and the

MOLISA poverty lines (which are used for targeting social assistance as well as monitoring the number of

poor households at the commune level). The “international” $1.25 and $2 a day poverty lines are rarely

used for poverty analysis within Vietnam owing to issues relating to Purchasing Power Parity conversion.7 In the mean regression analysis, the effects of clustering and stratification are taken into account in the

mean estimation of the per capita log expenditure equation by exploiting each of the relevant survey’s

sample design features.

108 B. Baulch et al.

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8 The minority coefficient structure could also be assumed to prevail in the absence of unequal treatment.

This will yield numerically different values for the component parts of equation (3) given the well-

known index number problem.9 Coastal, delta, midlands, low mountains and high mountains are the geographic types of commune that

are distinguished in the VLSS and VHLSS.10 It should be noted that the quantile approach used here does not incorporate survey design features in

the construction of the sampling variances as there are several communes (the primary sampling unit

for the VLSS and VHLSS) with only one ethnic minority household in the sample. This problem is

especially severe in the VHLSS 2004 in which expenditure data were collected only for three

households per commune. So while it is possible to account for the survey design in quantile

regressions for the majority group, it is not possible to do so in quantile regressions for the minority

group. We thank an anonymous referee for helping us clarify this point.11 It is acknowledged that this approach is also subject to the conventional index number problem.12 We also decomposed the ethnic per capita household expenditure gaps under the assumption that the

minority coefficients prevailed in the absence of unequal treatment. The results, which are available

from the corresponding author on request, suggest relatively modest evidence of an “index number”

problem. Furthermore, as the Kinh and Hoa majority group accounts for about 85% of the total sample,

it is reasonable to assume the majority coefficient structure is the relevant benchmark in the absence of

unequal treatment. We therefore focus on the decomposition results using equation (3) in this paper.13 The declining importance of commune characteristics in accounting for both endowment and treatment

differentials between 1998 and 2004 may reflect the impact of the geographically targeted

infrastructure investments, which focused on commune roads, clean water and irrigation systems,

markets, schools and health centres, and electricity supply under Programmes 133 and 135 in ethnic

minority areas. See Nguyen & Baulch (2007) for further details of these and other ethnic minority

policies and programmes in Vietnam.14 For brevity, the full set of quantile regression estimates is not reported here but is available from the

corresponding author on request. Note that, in contrast to the mean linear regressions reported in

Table A2, a large number of commune or district fixed effects cannot be introduced into the quantile

regressions because of a programming constraint (the group demeaning approach to estimating fixed

effects cannot be used in the quantile regression context).15 Note that the median estimate of the raw differential is materially different from the mean estimate in

only the first year of our analysis, suggesting a large role for outliers in this particular year. This has

implications for the mean estimate of the treatment effect, which is over 50% higher than the median-

based effect. The mean decompositions thus appear to understate by a magnitude of about one-half the

increase in the ethnic disadvantage for a median household between 1993 and 2004.16 In order to ensure that the temporal comparisons are comparable to the quantile regressions, only the

expenditure equations with commune controls are used in this exercise.17 Note that temporal differences in the estimated landholding effects in the majority equations are

statistically significant from zero, and exert a widening effect on the observed change on the per capita

household welfare gap.18 This finding is not detected at the extremes of the distribution where the estimated change in treatment

effects is found to be poorly determined. The imprecisely estimated effect at the 90th percentile, for

example, may be due to the low density of data points in the minority equations at this particular

quantile.19 The priority areas that are likely to achieve this include, inter alia, improving agricultural extension,

marketing services and the quality of education in mountainous areas, improved access to wage

employment, and the improvement of Vietnamese language skills among some ethnic minority groups.

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Decomposing the Ethnic Gap in Rural Vietnam 111

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Appendix

Table

A1.

Des

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112 B. Baulch et al.

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uary

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2

Mo

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Geo

gra

ph

ical

typ

eso

fco

mm

un

e:ru

ral

inla

nd

del

ta0

.64

01

0.0

94

90

.60

60

0.0

96

60

.63

56

0.0

82

0G

eog

rap

hic

alty

pes

of

com

mu

ne:

rura

lm

idla

nd

s0

.05

85

n/a

0.0

75

50

.00

06

0.0

71

10

.01

40

Geo

gra

ph

ical

typ

eso

fco

mm

un

e:ru

ral

low

mo

un

tain

0.1

49

40

.30

41

0.1

79

50

.36

08

0.1

41

10

.25

19

Geo

gra

ph

ical

typ

eso

fco

mm

un

e:ru

ral

hig

hm

ou

nta

in0

.06

29

0.5

40

70

.06

48

0.4

96

80

.06

56

0.6

39

8C

om

mu

ne

hav

ing

acce

ssto

road

that

car

can

trav

el0

.82

54

0.9

29

50

.82

22

0.9

31

00

.95

63

0.9

66

4C

om

mu

ne

hav

ing

acce

ssto

pu

bli

ctr

ansp

ort

0.5

12

10

.57

56

0.5

79

40

.48

40

0.5

22

90

.36

93

Co

mm

un

eh

avin

gac

cess

top

ost

offi

ce0

.34

19

0.3

52

20

.22

92

0.2

53

20

.30

63

0.2

46

3C

om

mu

ne

hav

ing

acce

ssto

dai

lym

ark

et0

.59

03

0.2

47

10

.52

79

0.3

36

80

.32

10

0.1

38

7C

om

mu

ne

hav

ing

acce

ssto

elec

tric

ity

0.5

01

10

.05

34

0.9

38

50

.69

70

0.9

83

60

.86

39

Co

mm

un

eh

avin

gfa

cto

ries

loca

ted

wit

hin

10

km

0.4

71

00

.31

96

0.5

75

60

.48

57

0.6

99

30

.43

08

Ch

aman

dK

hm

erN

.A.

0.1

41

3N

.A.

0.1

26

5N

.A.

0.0

79

2T

ay,

Th

ai,

Mu

on

g,

Nu

ng

N.A

.0

.54

50

N.A

.0

.47

94

N.A

.0

.57

47

Oth

erN

ort

her

nU

pla

nd

sm

ino

riti

esN

.A.

0.1

26

6N

.A.

0.1

11

8N

.A.

0.1

74

7C

entr

alH

igh

lan

ds

min

ori

ties

N.A

.0

.09

54

N.A

.0

.22

50

N.A

.0

.15

59

Oth

erm

ino

rity

gro

up

sN

.A.

0.0

91

7N

.A.

0.0

57

4N

.A.

0.0

15

5N

ot

spea

kin

gV

ietn

ames

eN

.A.

0.5

45

0N

.A.

0.2

64

7N

.A.

0.3

06

1D

ista

nce

toco

mm

un

ece

ntr

e(k

m)

N.A

.2

.96

51

N.A

.3

.07

49

N.A

.2

.18

90

N.A

.(3

.56

1)

N.A

.(2

.43

6)

N.A

.(3

.58

3)

Dis

tan

ceto

dis

tric

tce

ntr

e(k

m)

N.A

.1

1.2

95

N.A

.1

4.9

99

N.A

.1

7.0

39

(Continued

)

Decomposing the Ethnic Gap in Rural Vietnam 113

Dow

nloa

ded

by [

Uni

vers

ity o

f B

ath]

at 0

3:07

16

Febr

uary

201

2

Table

A1.Continued

19

93

19

98

20

04

Bri

efd

escr

ipti

on

of

var

iab

les

(1)

(2)

(1)

(2)

(1)

(2)

N.A

.(7

.73

5)

N.A

.(1

2.9

3)

N.A

.(1

5.8

2)

Dis

tan

ceto

maj

or

citi

es(k

m)

N.A

.n

/aN

.A.

n/a

N.A

.2

25

.91

N.A

.N

.A.

N.A

.(1

87

.0)

Mat

rili

nea

lp

ract

ice

N.A

.n

/aN

.A.

0.0

63

2N

.A.

0.0

86

5M

ino

rity

-on

lyco

mm

un

eN

.A.

0.2

93

6N

.A.

0.2

76

5N

.A.

n/a

No

reli

gio

nN

.A.

0.6

86

2N

.A.

0.7

30

9N

.A.

n/a

Nu

mb

ero

fo

bse

rvat

ion

s3

29

45

45

35

90

68

05

53

11

18

1

Notes:

(1)

and

(2)

rep

rese

nt

the

sam

ple

aver

age

val

ues

for

the

char

acte

rist

ics

of

the

maj

ori

tyan

dm

ino

rity

gro

up

s,re

spec

tiv

ely

.n

/a:

no

tav

aila

ble

;N

.A.:

no

tap

pli

cab

leas

thes

ev

aria

ble

sar

eo

nly

con

stru

cted

for

the

aux

ilia

ryre

gre

ssio

ns

for

the

min

ori

tyh

ou

seh

old

s.S

tan

dar

dd

evia

tio

ns

of

the

con

tin

uo

us

var

iab

les

are

rep

ort

edin

par

enth

eses

.Sources:

VL

SS

19

92

/93

,V

LS

S1

99

7/9

8an

dV

HL

SS

20

04

.

114 B. Baulch et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f B

ath]

at 0

3:07

16

Febr

uary

201

2

Table

A2.

OL

Ses

tim

ates

for

log

per

cap

ita

ho

use

ho

ldex

pen

dit

ure

reg

ress

ion

mo

del

so

fth

em

ajo

rity

and

min

ori

tyg

rou

ps,

19

93

–2

00

4

19

93

19

98

20

04

Maj

ori

tyM

ino

rity

Maj

ori

tyM

ino

rity

Maj

ori

tyM

ino

rity

Ho

use

ho

ldsi

ze2

0.0

48

2*

**

20

.02

01

**

20

.05

77

**

*2

0.0

69

2*

**

20

.04

83

**

*2

0.0

57

4*

**

(0.0

08

)(0

.01

)(0

.01

)(0

.01

2)

(0.0

08

)(0

.01

1)

Pro

po

rtio

no

fch

ild

ren

aged

fro

m7

to1

6y

ears

0.4

59

5*

**

0.2

59

9*

*0

.39

7*

**

0.5

73

5*

**

0.2

81

8*

**

0.4

74

**

*(0

.05

9)

(0.1

22

)(0

.06

6)

(0.1

24

)(0

.05

9)

(0.1

08

)P

rop

ort

ion

of

mal

ead

ult

s0

.56

42

**

*0

.76

23

**

*0

.59

68

**

*0

.46

42

**

*0

.79

53

**

*0

.72

65

**

*(0

.07

8)

(0.1

65

)(0

.09

)(0

.10

1)

(0.0

7)

(0.1

54

)P

rop

ort

ion

of

fem

ale

adu

lts

0.5

35

9*

**

0.7

19

7*

**

0.4

76

9*

**

0.5

09

2*

**

0.6

71

1*

**

0.5

90

4*

**

(0.0

8)

(0.1

81

)(0

.08

2)

(0.1

64

)(0

.07

3)

(0.1

56

)H

ou

seh

old

typ

e2

:p

aren

tsan

do

ne

chil

d2

0.0

12

52

0.0

34

42

0.0

44

62

0.0

80

82

0.0

37

22

0.0

49

7(0

.04

2)

(0.1

67

)(0

.04

2)

(0.1

02

)(0

.03

4)

(0.1

01

)H

ou

seh

old

typ

e3

:p

aren

tsan

dtw

och

ild

ren

20

.03

62

20

.07

19

20

.10

09

**

20

.11

64

20

.02

09

20

.16

09

*(0

.04

4)

(0.1

68

)(0

.04

3)

(0.1

05

)(0

.03

6)

(0.0

93

)H

ou

seh

old

typ

e4

:p

aren

tsþ

.th

ree

chil

dre

n2

0.0

89

8*

20

.14

62

20

.15

12

**

*2

0.2

22

8*

*2

0.0

99

6*

*2

0.2

19

6*

*(0

.04

8)

(0.1

7)

(0.0

49

)(0

.10

3)

(0.0

43

)(0

.09

9)

Ho

use

ho

ldty

pe

5:

thre

e-g

ener

atio

nh

ou

seh

old

20

.09

67

*2

0.3

03

1*

20

.10

93

*2

0.1

99

9*

*2

0.0

87

8*

*2

0.1

43

7(0

.05

7)

(0.1

78

)(0

.05

8)

(0.0

98

)(0

.04

4)

(0.1

04

)H

ou

seh

old

typ

e6

:o

ther

ho

use

ho

ldst

ruct

ure

s2

0.0

65

92

0.1

42

0.1

46

8*

**

20

.16

12

*2

0.0

46

20

.19

05

*(0

.05

)(0

.16

7)

(0.0

52

)(0

.09

6)

(0.0

45

)(0

.10

4)

Ag

eo

fh

ou

seh

old

hea

d0

.00

71

*2

0.0

03

0.0

07

0.0

01

30

.00

05

20

.00

78

(0.0

04

)(0

.01

)(0

.00

5)

(0.0

06

)(0

.00

4)

(0.0

08

)A

ge

of

hea

dsq

uar

ed(d

ivid

edb

y1

00

)2

0.0

07

9*

20

.00

02

20

.00

68

20

.00

09

20

.00

17

0.0

04

8(0

.00

4)

(0.0

1)

(0.0

04

)(0

.00

7)

(0.0

03

)(0

.00

7)

Ho

use

ho

ldh

ead

isfe

mal

e0

.00

04

20

.01

51

20

.00

52

0.0

78

2*

**

0.0

28

10

.00

98

(0.0

24

)(0

.05

5)

(0.0

24

)(0

.02

6)

(0.0

2)

(0.0

5)

Mo

sted

uca

ted

mem

ber

:p

rim

ary

edu

cati

on

20

.16

49

**

20

.42

17

**

*2

0.1

26

5*

*2

0.1

19

9*

20

.18

05

**

*2

0.1

95

2*

**

(0.0

73

)(0

.07

9)

(0.0

58

)(0

.06

8)

(0.0

29

)(0

.04

)M

ost

edu

cate

dm

ember

:lo

wer

seco

nd

ary

0.1

28

9*

**

0.1

46

**

*0

.12

6*

**

0.1

14

2*

*0

.08

44

**

*0

.13

54

**

*(0

.02

2)

(0.0

41

)(0

.02

3)

(0.0

48

)(0

.01

7)

(0.0

29

)M

ost

edu

cate

dm

ember

:u

pp

erse

con

dar

y0

.25

55

**

*0

.13

88

**

0.2

72

5*

**

0.2

9*

**

0.2

39

9*

**

0.3

37

4*

**

(Continued

)

Decomposing the Ethnic Gap in Rural Vietnam 115

Dow

nloa

ded

by [

Uni

vers

ity o

f B

ath]

at 0

3:07

16

Febr

uary

201

2

Table

A2.Continued

19

93

19

98

20

04

Maj

ori

tyM

ino

rity

Maj

ori

tyM

ino

rity

Maj

ori

tyM

ino

rity

(0.0

28

)(0

.05

8)

(0.0

27

)(0

.04

8)

(0.0

22

)(0

.05

3)

Mo

sted

uca

ted

mem

ber

:v

oca

tio

nal

/tec

hn

ical

0.2

92

5*

**

0.1

95

8*

**

0.3

05

7*

**

0.3

45

3*

**

0.3

54

3*

**

0.3

42

2*

**

(0.0

32

)(0

.05

6)

(0.0

32

)(0

.07

)(0

.02

3)

(0.0

55

)M

ost

edu

cate

dm

emb

er:

coll

ege/

un

iver

sity

0.5

01

1*

**

0.2

21

20

.56

96

**

*0

.45

27*

**

0.6

23

4*

**

0.6

05

**

*(0

.06

2)

(0.1

99

)(0

.03

8)

(0.1

48

)(0

.03

2)

(0.1

05

)Ir

rig

ated

ann

ual

cro

pla

nd

(10

00

m2)

0.0

16*

**

0.0

29

5*

0.0

06

4*

**

0.0

14

6*

**

0.0

09

3*

**

0.0

10

3*

**

(0.0

02

)(0

.01

8)

(0.0

02

)(0

.00

4)

(0.0

01

)(0

.00

3)

No

n-i

rrig

ated

ann

ual

cro

pla

nd

(10

00

m2)

0.0

14

5*

**

0.0

05

9*

0.0

02

80

.00

47

0.0

03

9*

**

0.0

08

1*

**

(0.0

03

)(0

.00

4)

(0.0

02

)(0

.00

7)

(0.0

01

)(0

.00

2)

Per

enn

ial

lan

d(1

00

0m

2)

0.0

21

8*

**

0.0

30

7*

**

0.0

12

4*

**

0.0

25

1*

**

0.0

05

30

.00

93

**

*(0

.00

5)

(0.0

07

)(0

.00

1)

(0.0

06

)(0

.00

3)

(0.0

02

)F

ore

stp

lot

(10

00

m2)

20

.00

23

0.0

15

2*

**

0.0

07

6*

**

0.0

04

4*

*0

.00

11

*0

.00

02

(0.0

04

)(0

.00

4)

(0.0

03

)(0

.00

2)

(0.0

01

)(0

)W

ater

surf

ace

(10

00

m2)

0.0

14

70

.15

22

**

0.0

00

*0

.01

01

0.0

11

**

*0

.02

5*

(0.0

1)

(0.0

76

)(0

.00

)(0

.03

0)

(0.0

02

)(0

.01

5)

Oth

ercu

ltiv

ated

lan

ds

(10

00

m2)

0.0

01

90

.01

21

**

*0

.00

65

**

*0

.00

74

0.0

23

1*

**

0.0

07

8(0

.00

4)

(0.0

05

)(0

.00

2)

(0.0

05

)(0

.00

4)

(0.0

06

)G

eog

rap

hic

alty

pes

:ru

ral

coas

tal

0.0

38

52

0.2

55

1*

*0

.00

21

20

.41

04*

**

20

.00

62

0.0

01

1(0

.03

4)

(0.1

3)

(0.0

6)

(0.1

35

)(0

.03

1)

(0.1

58

)G

eog

rap

hic

alty

pes

:ru

ral

mid

lan

ds

20

.08

85*

**

n/a

20

.04

07

20

.48

75*

**

0.0

17

50

.06

39

(0.0

32

)n

/a(0

.09

5)

(0.1

6)

(0.0

3)

(0.1

58

)G

eog

rap

hic

alty

pes

:ru

ral

low

mo

un

tain

20

.09

67*

**

20

.22

39

*2

0.1

22

4*

*2

0.2

61

7*

*2

0.0

33

82

0.1

64

4*

*(0

.02

3)

(0.1

26

)(0

.05

)(0

.12

1)

(0.0

21

)(0

.06

)G

eog

rap

hic

alty

pes

:ru

ral

hig

hm

ou

nta

in0

.01

53

20

.35

67

**

*0

.00

16

20

.29

68*

**

0.0

23

42

0.2

61

8*

**

(0.0

36

)(0

.12

6)

(0.0

7)

(0.1

01

)(0

.04

1)

(0.0

59

)C

om

mu

ne

hav

ing

acce

ssto

road

that

car

can

trav

el2

0.2

26

6*

**

20

.09

89

0.0

35

50

.01

14

0.0

03

20

.07

62

(0.0

27

)(0

.14

)(0

.05

1)

(0.0

72

)(0

.04

3)

(0.0

91

)C

om

mu

ne

hav

ing

acce

ssto

pu

bli

ctr

ansp

ort

0.1

91*

**

0.1

15

8*

*0

.05

38

20

.04

66

0.0

58

5*

**

0.0

51

4(0

.02

1)

(0.0

49

)(0

.04

5)

(0.0

73

)(0

.01

6)

(0.0

32

)C

om

mu

ne

hav

ing

acce

ssto

po

sto

ffice

20

.12

64*

**

0.0

44

60

.05

63

0.1

08

60

.04

56

**

*2

0.0

41

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Decomposing the Ethnic Gap in Rural Vietnam 117

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Febr

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2