Princelings and Paupers? - 麻省理工学院人工智能研究专业

Princelings and Paupers?
State Employment and the Distribution
of Human Capital Investments Among
Households in Viet Nam
∗
IAN COXHEAD AND DIEP PHAN

Inequality in access to education is known to be a key driver of income inequality
in developing countries. Viet Nam, a transitional economy, exhibits signiﬁcant
segmentation in the market for skilled labor based on more remunerative em-
ployment in government and state ﬁrms. We ask whether this segmentation is
also reﬂected in human capital investments at the household level. 我们发现
households whose heads hold state jobs keep their children in school longer,
spend more on education, and are more likely to enroll their children in ter-
tiary institutions relative to households whose heads hold nonstate jobs. 这
estimates are robust to a wide range of household and individual controls. 超过
时间, disparities in educational investments based on differential access to jobs
that reward skills and/or credentials help widen existing income and earnings
gaps between well-connected “princelings” and the rest of the labor market.
Capital market policies that create segmentation in the market for skills also
crowd out investment in private sector ﬁrms, further reducing incentives for
human capital deepening.

关键词: 人力资本, state-owned, 教育, 连接, 不等式, Viet
Nam
JEL codes: J24, J45, O15, P23

我. Policy Distortions, “Connections,” and Inequality in Transition Economies

Inequality in Viet Nam is low by the standards of Asian economies but has
risen during that country’s transition to “market-led socialism.” Part of the rise
can be explained by reference to the weakening of many socialist-era policies that
repressed returns to skills, 能力, and entrepreneurial activity, in which case greater
income disparities might be regarded as necessary and even beneﬁcial consequences
of liberalization. But despite huge strides toward a market economy, the state retains
signiﬁcant power over some product markets, notably those in which there is potential

∗Ian Coxhead is Professor, Department of Agricultural and Applied Economics at the University of Wisconsin-
麦迪逊. Diep Phan is Assistant Professor of Economics at Beloit College. We thank Bernard Thiam Hee Ng,
seminar participants at the Asian Development Bank and the University of Wisconsin-Madison, and two anonymous
referees for helpful comments on earlier drafts. Remaining errors are ours alone.

Asian Development Review, 卷. 30, 不. 2, PP. 26–48

C(西德:3) 2013 Asian Development Bank
and Asian Development Bank Institute

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PRINCELINGS AND PAUPERS? 27

for monopolistic behavior, and factor markets, especially those for capital and land. 它
follows that part of the observed rise in inequality may be due to less positive trends,
including rent capture by those with access to high-level government positions or to
employment in ﬁrms that are in some way protected by policy or market structure.
As in the People’s Republic of China (PRC), another economy undergoing a
broadly similar transition, there is widespread concern in Viet Nam over the alleged
capture of state-owned or partially privatized ﬁrms and inﬂuential public service
positions by “princelings”—that is, members of the former nomenklatura and their
close relatives and associates.1 The same concerns extend to many other developing
economies in which privileges extended to well-connected owners of capital and
land have led to diminished earnings and opportunities for owners of labor (伯格
and Ostry 2011). Paradoxically, in some economies, the structure of product and
劳动力市场 (and especially that for skilled labor) is such that the rewards to
skills are signiﬁcantly higher in public sector employment than in the private sector,
leading to queuing and competition for such jobs.2

In Viet Nam, income inequality across the state/nonstate divide is clearly
visible in household survey data. The data also reveal that this inequality is caused
by just a few households at the very top of the political hierarchy. 数字 1, 这是
based on representative national household data, shows that the per capita incomes of
“state” households (those containing at least one member working for a state ﬁrm or
in public administration) are appreciably higher than those for nonstate households,
whether in urban or rural areas.3 The gap widened between 2004 和 2008, a period
of very rapid growth in Viet Nam during which average real income per capita rose
by almost 50%.

Why should the labor market connections of households be important, 和
why should returns to skills be higher for state employees than those in the pri-
vate sector? A default model would predict equal returns to labor of equal skills in
equilibrium. 而且, the experience of the transition from socialism in Eastern
Europe and the former Soviet Union was overwhelmingly one in which movement
of white-collar workers to the private sector was strongly positively selected, 关于-
ﬂecting more productive employment opportunities with higher earnings to match
(Adamchik and Bedi 2000, 慕尼黑, Svejnar, and Terrell 2005). Viet Nam, 像
PRC, shows the opposite trend (Phan and Coxhead 2013).

Our answer, while speculative, ﬁts with the stylized facts of an economy in an
as yet incomplete transition from command to market economy. The skill intensity
of civil service employment is high, but the demand for workers is limited by budget

1“ ‘Princelings’ in [the People’s Republic of] China Use Family Ties to Gain Riches,“ 纽约时报,
17 可能 2012. 也可以看看, “In Viet Nam, Message of Equality is Challenged by Widening Wealth Gap,” New York
时代, 1 九月 2012.

2“Young Feel Hungrier for ‘Golden Rice Bowl’ Jobs: Record Numbers Eye Public Sector,“ 金融时报,

25 十月 2012.

3Simple t-tests also show statistically signiﬁcant difference in the mean per capita income between the two

groups of households, for both rural and urban areas (at signiﬁcance levels 7% or lower).

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28 ASIAN DEVELOPMENT REVIEW

数字 1. Distribution of Per Capita Income for State and Nonstate Households
(D million, 一月 1998 价格)

Kernel Density Estimate

.00006

y
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.00004

.00002

.0001

.00008

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.00006

.00004

.00002

state urban

nonstate urban

20000

40000

60000

80000

100000

kernel = epanechnikov, bandwidth = 2089.57

pcinc

Kernel Density Estimate

state rural

nonstate rural

20000

40000

60000

80000

100000

kernel = epanechnikov, bandwidth = 1501.76

pcinc

笔记: State households are those with at least one member working for the state (in either a state ﬁrm or for the

government in public administration).

来源: Viet Nam Household Living Standards Survey 2004, 2006, 和 2008.

constraints on government agencies. State-owned enterprises (SOEs), 在另一
手, beneﬁt from capital market interventions that lower their borrowing costs;
they therefore adopt relatively capital-intensive techniques. Because capital and
skills are complementary inputs, more highly educated workers are drawn to these
ﬁrms and compete to be hired by them. But since SOEs primarily supply goods and

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PRINCELINGS AND PAUPERS? 29

services to (often highly-regulated) domestic markets, their expansion—and thus
their demand for labor—is bounded in ways that do not apply to privately-owned
and trade-oriented ﬁrms. What both SOEs and civil administration have in common,
然而, is access to rents, which when distributed among their workers, 产生
potential for incomes that are higher than the earnings of equivalent workers in
competitive industries.4

Nonstate ﬁrms, 同时, suffer from crowding out in capital markets and so
adopt less capital-intensive techniques. In these ﬁrms, capital-skills complementarity
means they will hire fewer skilled workers, and will offer to compensate them at a
lower rate, commensurate with their lower value marginal product.5

在这个系统中, segmentation in the skilled labor market arises indirectly, 从
capital market distortions, market structure, and budget constraints limiting hiring
by state entities. This segmentation is visible as queuing by applicants and demands
for up-front payments from prospective employers. The difference in earnings for
equivalent workers at each type of ﬁrm will persist so long as the favored ﬁrms
face market or regulatory conditions that generate rents and so encourage them to
restrict hiring. Thus capital market policies will lead to job rationing and incentives
for corrupt behavior across a broad spectrum of the white-collar labor market, 不是
merely among the few that have direct access to the highest levels of political power.
In earlier work (Phan and Coxhead 2013), we uncovered evidence in support
of an important part of the above narrative. Viet Nam displays a high degree of
industrial policy distortion, with a clear bias in favor of state-owned enterprises in
the markets for banking sector credit, equity capital, and land (World Bank 2005,
Sj¨oholm 2008, Hakkala and Kokko 2008, Leung 2009, Nixson and Walters 2010,
IMF 2012) and in trade and pricing policies (Athukorala 2006). We discovered a
highly signiﬁcant state sector premium in earnings and in returns to education—as
的 2008, this premium had persisted despite two decades of economic reforms. 我们
also found that family connections to state sector employers increase an individual’s
own probability of having a state sector job. 一起, these results indicate that
connections to the state sector increase individual earnings and returns on human
capital investments, and that these effects operate at least in part through household-
level connections.

The concerns raised by these ﬁndings are not limited to inequality. A country’s
long-term economic growth depends on its ability to accumulate and efﬁciently
deploy human capital, and the acquisition of human capital is a key determinant of
improvements in individual earning power. The preceding narrative suggests that

4For an equivalent account using Chinese labor market data, see Xin Meng (2000).
5A recent study using labor force data covering ﬁve broad industrial sectors conﬁrms this prediction, ﬁnding
that in manufacturing, post-secondary qualiﬁcations earn a premium of only 40%–50% over primary education,
and concluding that “there is currently not a strong demand for workers with either professional training or tertiary
education in either low-value or medium-value industries. . . workers with post-secondary qualiﬁcations are therefore
likely to gravitate towards better-remunerated jobs in government and administration and the services” (Baulch, Dat,
and Thang 2012, p. 22–23).

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30 ASIAN DEVELOPMENT REVIEW

in the presence of certain policies and capital market distortions, household-level
incentives for educational investments will depend, 部分地, on the likelihood that
their children will be able to secure jobs in which skills or credentials are rewarded.
If this probability is viewed as small, then returns to additional years of education
are perceived as low, and capital-constrained parents will spend less on education
and/or withdraw children from school earlier; those children will enter the labor
force at a younger age and with less formal training.

That perceived returns matter for educational investments is well established
in empirical studies. In a study from the Dominican Republic, 例如, 詹森
(2010) ﬁnds that when children are given information on higher measured returns
to education, they complete on average 0.20–0.35 more years of schooling over the
下一个 4 年. 相似地, 詹森 (2012) ﬁnds that young rural women in India are
signiﬁcantly more likely to enter the labor market or obtain more schooling instead
of getting married and having children if they have access to recruiting services,
which increase their awareness of job opportunities.

Lower perceived returns to schooling reduce educational investments and
the schooling achievements of children. As a result their lifetime earnings proﬁles
will be ﬂatter and their capacity to invest in the education of their own children
will be diminished. 这样, initial household-level disparities in opportunity
may become persistent over more than one generation. 而且, the potential
productivity of less-educated workers will also be lower, so the economy as a whole
will face a diminished growth rate and lower steady-state income per capita relative
to the counterfactual of one in which perceived returns are higher.

在本文中, we test the hypothesis that households with close connections
to Viet Nam’s state sector invest more in their children’s human capital. Speciﬁcally,
we ask whether children from households headed by state employees are more
likely to attend high school or university, and whether those households spend more
on their children’s education. The ﬁrst of these questions explores the extensive
margin of educational attainment in an economy where only a small minority of
school-leavers continue on to higher education. The second question investigates
the intensive margin of educational investments in a system in which household
spending on discretionary educational items, such as tutors and private schools, 是
an important component of total educational expenditures.

After controlling for characteristics of the potential student, the household
头, and the household, we ﬁnd robust evidence that children from households
whose heads work for the state are more likely to attend university, and that these
households also spend signiﬁcantly more on their children’s education.

Our work extends the existing literature on educational inequality by identify-
ing and focusing on a previously neglected dimension. The state/nonstate dichotomy
among households proves to be an important dividing line for investments in the
most growth-oriented form of individual and household capital, 教育. 政策
that restrict access to schooling or reduce incentives to remain in school create and

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PRINCELINGS AND PAUPERS? 31

exacerbate inequality, a phenomenon now widely seen as reducing growth (斯蒂格利茨
2012). By discouraging educational investments by some, they also reduce the efﬁ-
cacy of efforts to promote and sustain long-run economic growth.

The rest of this paper is organized as follows. In Section II we review basic
data and trends on educational attainment and related indicators in Viet Nam. 在
Section III we motivate a somewhat deeper analysis and conduct an econometric
exploration of our main hypotheses. In Section IV we discuss our results, 并在
Section V we draw some tentative conclusions, speculate on the generalizability of
our ﬁndings, and propose some avenues for future research.

二. A New Dimension of Inequality: State and Nonstate Households

数据

Our primary data source is the Viet Nam Household Living Standards Survey
(VHLSS), with rounds in 1993, 1998, 2002, 2004, 2006, 和 2008.6 These surveys
gather data on household income and expenditure and are designed to measure
living conditions and poverty and inequality (Grosh and Glewwe 2000). 他们是
intended to be representative at the national and provincial levels. They also include
modules on education and on employment and wages. Early rounds of VHLSS were
smaller in size (4,800 households in 1993 和 6,000 在 1998). The survey year 2002
had the largest number of households (29,533). In the most recent three rounds, 这
number of households from which both expenditure and income data are collected
has stabilized at around 9,000.7 In our regressions, we use data from the 2004, 2006,
和 2008 rounds. Consistent questionnaires and deﬁnitions of variables in all these
three survey years allow us to pool data into one estimating model.

To measure years of education, most other studies using VHLSS data have
used the survey’s original schooling year variable, which ranges from 0 通过
12 年. We adjust schooling years for highest educational level (junior college
corresponds to 14 years of education, a college degree 16 年, master’s degree 18
年, and PhD 21 年). 因此, our calculated years of schooling are higher
than other studies.

In the descriptive analysis in the next section we also use the Viet Nam
Enterprise Survey for data on ﬁrms. This is an annual survey begun in 2000.8 It covers
all enterprises with independent accounting systems that are established under and
governed by the Law on State-owned Enterprises, the Law on Cooperatives, the Law

6Data from the most recent VHLSS rounds, 在 2010 和 2012, are not yet available to us.
7These are survey subsamples that have both income and expenditure modules. There are also much larger
surveys with expenditure modules only, which we do not want to use because data are considered less reliable when
income cannot be compared against expenditures.

8This survey existed in the 1990s, but in a somewhat different form and quality.

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32 ASIAN DEVELOPMENT REVIEW

桌子 1. Structure of Employment by Type and Ownership (%)

Self employed
Wage employed

State wage employed
Nonstate wage employed

1993

73.4
26.6
4.3
22.2

1998

59.4
40.6
6.7
33.9

2002

60.9
39.1
10.2
28.9

2004

57.0
43.0
14.7
28.3

2006

55.7
44.3
15.4
28.9

来源: Authors’ calculations from Viet Nam Household Living Standards Survey, various years.

桌子 2. Average Years of Education of Workers in State and Nonstate Sectors

状态
Nonstate

1993

11.3
5.6

1998

9.9
5.8

2002

11.7
6.7

2004

11.1
6.9

2006

11.3
7.0

来源: Authors’ calculations from Viet Nam Household Living Standards Survey, various years.

桌子 3. Workers with College Degree in State and Nonstate Sectors (%)

状态
Nonstate

1993

17.31
0.38

1998

22.22
0.78

2002

27.86
1.38

2004

25.81
0.98

2006

26.07
1.12

来源: Authors’ calculations from Viet Nam Household Living Standards Survey, various years.

2008

55.2
44.8
14.7
30.1

2008

11.8
7.3

2008

29.92
1.77

on Enterprises, and the Law on Foreign Investment in Viet Nam. All formal sectors
and industries, including agriculture, are covered. 然而, because the criterion for
inclusion in the survey is establishment and governance under the law, the informal
sector is largely ignored. The survey questionnaire includes various business and
production activities: labor and employment, incomes of employees, number of
establishments, assets and liabilities, 投资, capital stock, production costs,
turnover, 产品, proﬁts, inventories, 税收, research and development investments,
IT applications, 和别的.

乙.

Employment and Wages in State and Nonstate Firms

In the course of Viet Nam’s more than 20 years of transition to a market
经济, the state sector has retained an extraordinarily prominent role. SOEs
account for between one-third and two-ﬁfths of economic activity. 根据
VHLSS data, employment in SOEs has even risen as a share of total wage labor
就业 (which itself has risen substantially since the 1990s). 桌子 1 提供
a summary of employment by ownership type.

桌子 2 conﬁrms that state sector ﬁrms are far more intensive in their use
of educated workers than are nonstate ﬁrms. Although the average education of
nonstate workers has risen steadily, 从 5.6 years in 1993 到 7.8 在 2008, this ﬁgure
still remains far below years of education in state sector ﬁrms. 而且, 作为表 3
节目, the proportion of workers in nonstate ﬁrms with a college degree remains
extremely low (1.8% 在 2008) by comparison with state ﬁrms (30%).

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PRINCELINGS AND PAUPERS? 33

桌子 4. Capital Intensity (D million per worker)

2000

194
53
391

2002

234
49
378

2004

329
65
292

2006

407
90
499

State ﬁrms
Private ﬁrms
Foreign ﬁrms

来源: Authors’ calculations from Viet Nam Enterprise Survey, various years.

桌子 5. Hourly Wage of State vs. Nonstate Workers (D thousand per hour)

状态
Nonstate
State/Nonstate ratio

1993

1.71
1.89
0.90

1998

3.23
2.73
1.18

2002

5.49
3.14
1.75

2004

5.26
3.35
1.57

2006

5.61
3.65
1.54

来源: Authors’ calculations from Viet Nam Household Living Standards Survey, various years.

2008

324
99
478

2008

8.02
5.01
1.60

One reason for the higher skill intensity of state sector employment is that
some jobs in this sector are government administrative positions that require higher
教育. Another important reason is technological: capital and skills are comple-
ments in production (Griliches 1969). 桌子 4 reveals much higher capital per worker
in state and foreign-invested ﬁrms compared to nonstate ﬁrms. In the case of SOEs
this is undoubtedly the result of their privileged access to capital. The combination
of technological factors and policy distortions results in higher demand for skilled
workers by SOEs than by private ﬁrms.

These differentials in capital and skill intensities between state and nonstate
ﬁrms no doubt contribute to the discrepancy in average hourly wages, shown in
桌子 5. 在 1993, workers in the state sector earned less on average than workers
in the nonstate sector. But this was prior to the implementation of most market and
labor reforms. 自那以后, they have earned about 40% more per hour than nonstate
工人.

当然, these are simple averages and do not take account of differences in
the composition of the labor force in each type of ﬁrm. But as mentioned earlier, 我们的
earlier econometric investigation conﬁrms that workers in state ﬁrms indeed receive
higher returns to education, even after controlling for many differences in worker
and job characteristics and that, far from being erased by the economic transition,
this disparity has increased over time (Phan and Coxhead 2013).

Educational Attainment and Investments by State and Nonstate Households

There is a large literature on the inﬂuence of family environment on human
capital investments (for a recent and highly relevant survey, see Yi et al. 2011).9

9See especially their footnote 21, a discussion of the “true” meaning of parental education which has been
shown to have a strong inﬂuence over schooling outcomes for children. Parts of this literature explore just what
parental education stands for—whether income, or cultural norms favoring education, or other things.

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34 ASIAN DEVELOPMENT REVIEW

For Viet Nam, the VHLSS data reveal well-known sources of cross-household
variation in schooling rates and educational expenditures such as between urban and
rural subpopulations, ethnic minority and Kinh majority households, households
in different regions of the country, and of course variation based on differences in
per capita income (Vu 2012).10 These are the familiar break points in econometric
analyses of educational attainment. But even after controlling for these sources of
variation, differences in human capital investments persist.

What explains this? One clue to the remaining differences comes from our
prior work on returns to education. Our estimates of the treatment equation for
employment in the state sector revealed that workers in households where an-
other household member works for a state ﬁrm are far more likely themselves
to have state sector jobs, even after controlling for other household factors and
individual characteristics. This empirical insight points to a previously unexam-
ined fracture line in the educational attainment and investment data: variation
by state versus nonstate households. We now turn to the examination of these
数据.

In this section we use three different measures of educational attainment and
投资: average years of schooling, net and gross enrollment rates in different
levels of schooling, and household educational expenditures.11 No matter which
measure we use, state households (those with at least one member working for
a state ﬁrm or for the government) tend to invest more in the education of their
孩子们. 数字 2 shows that for all age groups, the average years of schooling
of children from state households are higher than those of children from nonstate
households. The differences in means are small at lower levels of education, 但
widen progressively through college. Figures 3a and 3b reveal a similar story. 网
and gross enrollment rates are higher for children from state households in both
rural and urban areas. 再次, the differences are greatest at the college level—the
level most relevant for the skilled labor market. 最后, 数字 4 conﬁrms that
state households tend to spend more on their children’s education than do nonstate
households, in both rural and urban areas.

总之, the available data point to a large premium for educated workers
employed in the state sector. If the presence of a parent or other elder with a state
sector job means easier access for others in the same household, then schooling
decisions appear to be driven (at least in part) by access to jobs in the favored
sector. 有, 然而, many covariates to be controlled for when analyzing
educational investments. Therefore we now turn to a more rigorous examination of
the determinants of household educational investment.

10And compare these differentials in similar countries, such as the PRC (Wang et al. 2011).
11Net enrollment rate is the ratio of enrolled children in the ofﬁcial school age group over the total number
of children in that age group. Gross enrollment rate is the ratio of enrolled children of all ages over the total number
of children in the ofﬁcial school age group.

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PRINCELINGS AND PAUPERS? 35

数字 2. Average Years of Schooling

12.0

10.0

8.0

6.0

4.0

2.0

0.0

College Age Group
(18–22)

High School Age Group
(15–17)

Primary and Middle
School Age Group (6–14)

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来源: Viet Nam Household Living Standards Survey, 2006.

State Households

Nonstate Households

三、. Determinants of Household Educational Investments

Empirical Strategy

Our goal is to understand disparities in household educational investments. 作为
is well known, education is often terminated at discrete points such as the completion
of a given level of schooling. Therefore we focus on speciﬁc schooling decisions.
These are ﬁrst, the decision to enroll a child in high school given completion of
middle school, 第二个, the decision to enroll a potential student in university
given that he or she has completed high school. Our empirical strategy is based on
well-established human capital theory (Schultz 1960 和 1963, Becker 1964). 这
maintains that household demand for education is affected by expected returns (r)
and costs (C, including direct and opportunity costs) of education:

y∗
我

= f (ri , 词 , 从 , ui ) = a + γ ri + δci + βDi + ui

(1)

where y∗
is a latent variable capturing the decision to enroll in university or high
我
school by potential student i; Di is a vector of controls including demographic
variables such as gender, 年龄, 种族, geographic variables, and other exogenous
inﬂuences; and ui is a random error term that is assumed to be independently and
identically distributed with expected value E(ui) = 0. We have assumed a linear
functional form for the explanatory variables.

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36 ASIAN DEVELOPMENT REVIEW

1.00

0.90

0.80

0.70

0.60

0.50

0.40

0.30

0.20

0.10

0.00

Figure 3a. Net Enrollment Rate

0.90 0.90

0.86 0.88

0.88

0.79 0.80

0.79

0.74

0.61 0.61

0.45

Primary School

Middle School

中学

0.28

0.18

0.15

0.09

College and
Junior College

Urban State Households
Rural State Households

Urban Nonstate Households
Rural Nonstate Households

来源: Viet Nam Household Living Standards Survey, 2006.

Figure 3b. Gross Enrollment Rate

1.40

1.20

1.00

0.80

0.60

0.40

0.20

0.00

1.05

1.01

1.06

0.99

1.00

1.02

0.95

0.94

1.25

1.06

0.91

0.69

Primary School

Middle School

中学

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0.35

0.20 0.21

0.10

College and
Junior College

Urban State Households
Rural State Households

Urban Nonstate Households
Rural Nonstate Households

来源: Viet Nam Household Living Standards Survey, 2006.

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数字 4. Mean Household Educational Expenditure (D thousand)

PRINCELINGS AND PAUPERS? 37

2,941

1,871

1,839

915

3,500

3,000

2,500

2,000

1,500

1,000

500

Urban

Rural

State Households

Nonstate Households

来源: Viet Nam Household Living Standards Survey, 2006.

The observed variable is yi, which is a dummy indicating whether the potential

student i enrolls in university (or high school). Speciﬁcally,

yi = 1 if y∗

> 0,
= 0 否则.

我

和

因此, the frequency of the observed outcome, or the probability of enrolling

in university or high school is equal to

Pi = Pr ob(yi = 1) = Pr ob(y∗

我

> 0)

= Pr ob(A + γ ri + δci + βDi + ui > 0)
= Pr ob(ui > −α − γ ri − δci − βDi )
= 1 − G(−α − γ ri − δci − βDi )

where G(.) is the cumulative distribution of the error term (Maddala 1983).

If we use the logistic cumulative distribution function and take the log of the

odds ratios, then we have a logit model:

logit(圆周率 ) = log[圆周率 /(1 − Pi )]) = α + γ ri + δci + βDi .

(2)

Our primary focus is on explaining differential incentives to invest in educa-
的, given differences in expected returns to education in private and state sector

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38 ASIAN DEVELOPMENT REVIEW

工作. 那是, the decision to progress from middle to high school, or to enroll in
tertiary education, takes into account the trajectory of returns to education in state
and nonstate employment adjusted by the probabilities of employment in either
sector. From Phan and Coxhead (2013) we know that the average rate of return to
education in the state sector (rS) is higher than in the nonstate sector (rN). If ρi is
the probability of state sector employment for potential student i, then his expected
returns to education is ri = rSρi + rN(1 – ρi). Under the assumption of uniformity
within each employment sector, we can normalize rN = 1 and rewrite ri = 1 +
[rS – 1]ρi. Substituting this into the previous equation, our logit model becomes:

logit(圆周率 ) = (A + C ) + C (r S − 1)ρi + δci + βDi .

(3)

方程 (3) is our estimating equation.12 The variable of interest is ρi, 这
probability of getting a state sector job. Lacking direct observations on this, 我们
use two proxies: an “SOE” dummy which equals 1 if household head works for
a state ﬁrm, and a “civil” dummy equal to 1 if the head of household works in
public administration. These dummies aim to capture a household’s connection to
the state sector, whether state-owned enterprises or government. The null hypothesis
is that these dummies are not statistically different from zero; 那是, the sector of
employment of a potential student’s household head has no effect on probability
of high school or university enrollment. Rejection of the null is evidence of state
employment as a source of household differences in educational incentives. 我们
discuss the implications of such a ﬁnding in Section IV.

We include three other sets of explanatory variables:

(我) household characteristics, speciﬁcally log of household income,13 家庭
composition by age, urban or regional dummies, ethnic minority dummy (1 如果
household is not of Kinh or Chinese ethnicities);

(二) household head characteristics, namely age, 性别 (1 if male), years of school-

英, and skill dummy (1 if household head holds a skilled job); 和

(三、) child characteristics, comprising gender (1 if male) 和年龄.

Among the control variables, those of greatest economic interest are the
household’s ability to ﬁnance education, as measured by household income, 和
household head’s years of schooling. 明显地, wealthier households are more able
to pay for education and to keep children out of the labor force until a later age. A

12The model is estimated using maximum likelihood method using Stata.
13We also ran a series of regressions using household expenditure, which yield similar results. Details are

available from the authors.

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PRINCELINGS AND PAUPERS? 39

large empirical literature conﬁrms that more educated parents tend to invest more
in the education of their own children.14 Controlling for parents’ education also
helps reduce (although not completely eliminate) omitted variable biases, 因为
this variable serves as proxy for many monetary and nonmonetary factors that affect
schooling decisions. 例如, we have no information on children’s intelligence
or ability: smarter children do better in school and are more likely to attend high
school and college, 其他条件相同. Another omitted variable is preferences: 一些
children may love schooling for the sake of knowledge, not for the monetary returns.
If these omitted variables are correlated with employment sector of household head,
their omission causes upward biases in estimates of the SOE and civil dummies. 但
it is reasonable to assume that parents who are smarter and who love education tend
to transfer their intelligence and love of schooling to their children. Such parents
also tend to attain more education. So parents’ education partly proxies and controls
for the two omitted variables, children’s ability and love of schooling.

In estimating determinants of school enrollment probability, we look only at
the children and grandchildren of household heads. We do this intentionally to avoid
potential endogeneity due to reverse causality. Since we examine the impact of the
older generation’s employment on educational investments for the younger gener-
ation and it is not plausible that the younger generation’s educational achievement
increases the likelihood of state employment by the older generation, there is no
reverse causality problem.

In addition to estimating the probability of university or high school enroll-
蒙特, we also estimate household educational expenditures, another measure of
household educational investment. Since many households have zero educational
expenditure, our sample suffers from censoring. 因此, we use a Tobit model
for this estimation.

乙.

结果

Estimation results are presented in Tables 6 通过 9 (a table of summary
statistics of key variables is in the Appendix). In Tables 6 和 7, we use logistic
regressions to estimate school enrollment probabilities (参见方程 3). We report
both estimated coefﬁcients and odds ratios. Standard errors are robust and adjusted
for clustering at the commune level. In both Tables 6 和 7, most variables have
coefﬁcients of expected signs and statistical signiﬁcance. For brevity, we restrict our
discussion to the main variables of interest, the civil and SOE dummies. 表中 6,
these dummies are not statistically signiﬁcant. The household head’s employment
does not seem to affect children’s probability of enrolling in high school. 但在
桌子 7, both dummies are positive and statistically signiﬁcant. The estimated odds
ratios imply that the university enrollment probability of a potential student whose

14A recent study of rural households in southern Viet Nam conﬁrms that as agricultural incomes increase,

the schooling years of children (especially daughters) 增加. See Edmonds (2005).

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40 ASIAN DEVELOPMENT REVIEW

桌子 6. Determinants of High School Enrollment Probability

Odds Ratio

Coeff.

S.E.

p-value

Household Head Characteristics

Head works for SOE (SOE dummy)
Head works for gov’t (civil dummy)
Head has a skilled job (skill dummy)
Head years of schooling
Gender of household head (male = 1)
Age of household head
Household Characteristics
Log of household income
Ethnic minority dummy = 1

Controls

Family demographic structure
Child’s age and sex
Region
年
持续的
氮
Pseudo R-squared

1.264
0.998
1.392
1.080
0.918
1.011

1.224
1.481

0.161
0.117
0.113
0.009
0.065
0.003

0.036
0.099

0.146
0.984
0.003
0.000
0.185
0.000

0.000
0.000

0.448

0.000

0.234
–0.002
0.331∗∗
0.077∗∗
–0.086
0.011∗∗

0.202∗∗
0.393∗∗

是的
是的
是的
是的
3.348∗∗
12,333
0.299

∗∗= statistically signiﬁcant at 5% level or less, ∗= statistically signiﬁcant at 5%–10% level.
Notes:
1. Estimates are from logit regressions with robust standard errors adjusted for clustering at commune level.
2. Dependent variable: dummy equals 1 if potential student was currently enrolling in high school during survey
年; sample includes children and grandchildren (who already obtained middle school diploma) of household
头.

3. Controls: family demographic structure (number of children ≤ 5 years old, children 6–10 years old, 孩子们
11–14 years old, children 18–22 years old, family members 23–65 years old); 地区 (8 administrative regions);
年 (dummies for 2006 和 2008).

来源: Author’s computations using data from Viet Nam Household Living Standards Survey 2004, 2006, 和 2008.

household head works in an SOE is 1.3 times greater than that of someone whose
household head works elsewhere. For someone whose household head works in
public administration, the probability is 1.4 times greater.

That connection to the state sector is not a source of inﬂuence in schooling
decisions at lower levels of education is consistent with a theoretical model in
Phan and Coxhead (2013). In that paper, we argue that the rising wage premium
of state sector jobs is a result of government intervention in both capital markets
and the market for skilled labor. As the government allocates capital to the state
sector, this raises the demand for skilled labor in that sector (because of skill–capital
complementarity). But since access to state sector jobs is restricted, the increase
in demand for skilled labor translates to higher earnings for skilled workers in this
sector. These distortions do not apply to unskilled labor markets, which require lower
教育. Therefore we do not expect a relationship between state connection and
investment in lower levels of schooling.

In Tables 8 和 9, we estimate the determinants of households’ educational ex-
penditures and the share of education in total household expenditures. 再次,
employment of the household head is inﬂuential. 表中 8, the SOE and civil
dummies have positive and statistically signiﬁcant impacts on (log of) 家庭

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PRINCELINGS AND PAUPERS? 41

桌子 7. Determinants of University or College Enrollment Probability

Odds Ratio

Coeff.

S.E.

p-value

Household Head Characteristics

Controls

Family demographic structure
Child’s age and sex
Region
年
持续的
氮
Pseudo R-squared

1.332
1.438
1.210
1.115
0.922
1.018

1.325
0.546

0.287∗
0.363∗∗
0.191
0.109∗∗
–0.081
0.018∗∗

0.281∗∗
–0.604∗∗

是的
是的
是的
是的
–4.585∗∗
8,531
0.106

0.148
0.145
0.117
0.012
0.087
0.005

0.044
0.177

0.053
0.012
0.102
0.000
0.352
0.000

0.000
0.001

0.558

0.000

来源: Author’s computations using data from Viet Nam Household Living Standards Survey 2004, 2006, 和 2008.

education expenditure, after controlling for household income and other character-
主义. 表中 9, the civil dummy has a positive and statistically signiﬁcant impact
on the share of household education expenditure in total expenditure.

To summarize these results, even after controlling for the usual determinants
of educational investments we decisively reject the null hypothesis of no effect of
state employment of parents on investments in the education of children. The impli-
cation is that due to underlying distortions that give rise to state sector wage premia
and labor market segmentation, factors other than ability are helping determine
who among children receives more and better educational opportunities. This has
consequences for both equity and growth in the long run.

IV. 讨论

不等式

When there is rationing in the market for skills, discrepancies in the household
distribution of assets, including claims on state sector jobs, can be transmitted across

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42 ASIAN DEVELOPMENT REVIEW

桌子 8: Determinants of Household Educational Expenditure: Total Spending

Dep. var: h’hold educational expenditure (D)

Coeff.

S.E.

p-value

Household Head Characteristics

Controls

Family demographic structure
Child’s age and sex
Region
年
持续的
氮
Pseudo R-squared

0.495∗∗
0.503∗∗
0.313∗∗
0.190∗∗
–0.414∗∗
–0.045∗∗

0.812∗∗
–0.937∗∗

是的
是的
是的
是的
–6.726∗∗
27,563
0.115

0.128
0.101
0.099
0.009
0.068
0.003

0.036
0.107

0.000
0.000
0.000
0.000
0.000
0.000

0.000
0.000

0.401

0.000

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∗∗= statistically signiﬁcant at 5% level or less, ∗= statistically signiﬁcant at 5%–10% level.
Notes:
1. Estimates are from Tobit regressions with robust standard errors adjusted for clustering at commune level.
2. Dependent variable: log of educational expenditure.
3. Controls: family demographic structure (number of children ≤ 5 years old, children 6–10 years old, children 11–14
years old, children 18–22 years old, family members 23–65 years old); 地区 (8 administrative regions); 年
(dummies for 2006 和 2008).

来源: Author’s computations using data from Viet Nam Household Living Standards Survey 2004, 2006, 和 2008.

几代人. It follows (although we do not address this directly) that unequal access
to education and an unequal distribution of incentives to enroll in tertiary education
could both exacerbate initial inequality and increase the rate at which the fortunes of
favored and less favored households diverge during the course of economic growth
and transition to a market economy.

Our main result elaborates a point that has been made before in other settings.
Becker and Tomes (1993), 例如, explore the potential of capital market
imperfections to lower parents’ investments in their children’s acquisition of human
首都. The data from Viet Nam suggest two potentially interesting twists on this
帐户. 第一的, it is not only widely-studied constraints such as access to credit
that distinguish the fortunes of one family from those of another. Labor market
segmentation may also give rise to a structural disparity that is hard for households
to bridge. 第二, and related to this, in our data it appears that a key asset that parents
can bequeath to their children is access to state jobs, and this in turn inﬂuences the
expected rate of return to the latters’ education. But access, like human capital
本身, does not function well as collateral. Two implications follow. 第一的, 即使
a household could self-ﬁnance a higher level of education for its children, 那
investment might still not pay off in the labor market. 第二, public policies aimed

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桌子 9. Determinants of Household Educational Expenditure: Expenditure Share

Dep. var: share of education in total h’hold expenditure

Coeff.

S.E.

p-value

PRINCELINGS AND PAUPERS? 43

Household head characteristics

Controls

Family demographic structure
Child’s age and sex
Region
年
持续的
氮
Pseudo R-squared

0.003
0.003
0.003
0.000
0.002
0.000

0.001
0.002

0.228
0.009
0.000
0.000
0.000
0.000

0.000
0.000

0.009

0.000

0.004
0.007∗∗
0.010∗∗
0.004∗∗
–0.011∗∗
–0.001∗∗

0.008∗∗
–0.023∗∗

是的
是的
是的
是的
–0.091
27,563
–0.396

∗∗= statistically signiﬁcant at 5% level or less, ∗= statistically signiﬁcant at 5%–10% level.
Notes:
1. Estimates are from Tobit regressions with robust standard errors adjusted for clustering at commune level.
2. Dependent variable: share of education in total household expenditure.
3. Controls: family demographic structure (number of children ≤ 5 years old, children 6–10 years old, 孩子们
11–14 years old, children 18–22 years old, family members 23–65 years old); 地区 (8 administrative regions);
年 (dummies for 2006 和 2008).

来源: Author’s computations using data from Viet Nam Household Living Standards Survey 2004, 2006, 和 2008.

at broadening access to education might not raise enrollments if incentives are
reduced by distortions that lower the probability of getting a suitably rewarding job.

乙.

生长

In low-income countries, and especially in those undergoing transition, ag-
gregate growth can be sustained for a time through mobilization of underutilized
resources and efﬁciency gains due to economic policy reforms. But in the longer
跑步, continued growth relies on increases in total factor productivity and invest-
ments in reproducible factors of production, most notably human capital. Develop-
ing economies that underinvest in human capital risk landing in a middle-income
trap in which their continued progress up the product quality ladder or participa-
tion in global production networks is constrained by human capital shortages. 这
leaves them reliant on other sources of income, typically natural resource extraction
or low-skill manufactures, for which global competition among suppliers is intense.
Our results suggest that at present, a large majority of workers in Viet Nam
have a low probability of ﬁnding employment in an industry or occupation where
returns to higher-quality education or tertiary credentials will justify the cost of

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44 ASIAN DEVELOPMENT REVIEW

their acquisition. Even if other constraints (such as access to credit) do not bind,
some fraction of high school and college age children are rationally opting out of
education to join the unskilled or semi-skilled labor force.

It may be possible for these individuals to acquire additional skills later in
生活, for example through vocational training or on-the-job training, but at present,
neither of these channels appears promising in Viet Nam. Vocational training is not
widespread nor is it respected by employers in Viet Nam (Chirot and Wilkinson
2010). Due to the crowding out of banking sector capital for small and medium en-
terprises, capital intensity outside of the state sectors and a few other well-connected
industries is very low. 因此, returns to education and skills are also low in
these industries (Baulch, Dat, and Thang 2012). Viet Nam therefore confronts a
medium-run future in which a large part of its adult labor force is inadequately pre-
pared to support a move up the product quality ladder, from assembly to innovation.
最后, as discussed at the start of this paper, inequality and long-run eco-
nomic growth are increasingly widely regarded as positively linked, with access
to education and incentives to acquire human capital as key conduits. 这是
succinctly stated in a recent report on rising inequality around the world:

If income gaps get wide enough, they can lead to less equality of oppor-
统一性, especially in education. Social mobility in America, contrary to
conventional wisdom, is lower than in most European countries. 这
gap in test scores between rich and poor American children is roughly
30%–40% wider than it was 25 几年前. And by some measures class
mobility is even stickier in [the People’s Republic of] China than in
America.15

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The report’s primary proposed remedy is to dismantle monopolies and vested
兴趣, be they state-owned enterprises in the PRC, India’s “unequal oligarchy or
更差,” or big banks on Wall Street.16 Although by the usual measures inequality
in Viet Nam is much lower than in most economies, so too is its per capita income.
所以, the prospect of a lower growth rate due to inequality in human capital
investments must be treated very seriously.

Generalizability

Our data are drawn from just one developing economy, but there are strong
indications that the analysis is relevant to a larger group. In many countries with
less restrictive regimes than Viet Nam, SOEs enjoy qualitatively similar positions
in terms of their access to domestic capital, dominance in domestic markets, 和

15“Crony Tigers, Divided Dragons,” The Economist, 13 十月 2012.
16“True Progressivism,” The Economist, 13 十月 2012. The quote is attributed to Raghuram Rajan.

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PRINCELINGS AND PAUPERS? 45

connections to political decision makers. State involvement in developing economies
is not disappearing as quickly as was perhaps expected in the post-Cold-War, Wash-
ington Consensus era. In fact there are some recent signs of a resurgence of state
engagement.17 Thus the role of personal connections, so highly signiﬁcant in the
case of one rather heavily distorted developing economy, may well be present, 甚至
less starkly so, in many others.

Our results are necessarily conditional on a set of parameters that is sub-
ject to change along with the economic policies of Viet Nam. 尤其, 这
state–nonstate gap in labor productivity (and thus in returns to skills and earn-
英格斯) could be reduced or eliminated by structural reforms that reduce or eradicate
the special economic status of state sector enterprises. 或者, greater ac-
cess by ﬁrms, and especially by small and medium enterprises, to foreign capital
would be inﬂuential since it would offset the productivity-reducing effects of capital
crowding-out by SOEs. Whether either of these changes is sufﬁcient to reverse the
trend toward greater disparity that we have documented remains an open question.
Further analysis with the most recent rounds of VHLSS (2010 和 2012), once they
become available, will help answer this question.

V. 结论

In this paper we have explored a hitherto neglected dimension of
inequality—that arising in a transitional economy between households with ac-
cess to rationed, rent-yielding state sector jobs and those without. Data from several
rounds of Viet Nam’s household living standards surveys conﬁrm a substantial dif-
ference in per capita incomes across this divide. Our research then reveals that the
state–nonstate dichotomy also marks a signiﬁcant discrepancy in households’ educa-
tional investments in their children. When state employers are the largest demanders
of skills, and when they compensate those skills far more generously on average
than do nonstate employers, there is competition among workers to win state jobs.
These jobs are effectively rationed by public sector budget constraints and limited
domestic markets for the goods and services produced by state-owned corporations.
因此, connections based on family ties become important factors raising
the probability of winning a state sector job. Households for which these connections
are strong tend to invest more heavily than others in education and credentials for
their offspring. In other households, the data suggest that opportunity cost drives

17“The Great Slowdown, The Economist, 21 七月 2012. The article comments on this as follows: “Sadly,
many emerging-world governments have interpreted the crisis in rich-world ﬁnance as a reason to preserve a more
muscular role for the state. [The People’s Republic of] China has reserved some sectors for state-owned enterprises. 在
Brazil the big state-controlled oil company, 巴西国家石油公司, and the state-controlled banks have become virtual appendages
of government policy. Having so much leverage over the economy is indeed helpful during a crisis, but in the long
run it will stiﬂe competition, starve the private sector of capital, deter foreign investment and know-how, and breed
corruption.”

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46 ASIAN DEVELOPMENT REVIEW

children whose parents cannot help them win lucrative state sector jobs out of
education earlier and at lower levels, and that those households invest less overall
in education of their children. These divisions depend on policy, not on secular
development trends, and so could well persist across generations, creating a two-
track labor market of “princelings” and “paupers.”

International evidence suggests further that unequal incentives to invest in
human capital will in the long run lead to slower rates of aggregate economic
生长. 如果是这样, then Viet Nam could face an earlier onset of the middle income trap
than would be the case under the counterfactual of a more level playing ﬁeld for
labor and education. Prior experience of other regional economies like Indonesia,
Malaysia, and Thailand pinpoints underinvestment in human capital formation as a
key contributing factor to growth slowdowns and vulnerability to economic crises
(展位 2003, Warr 2005, Coxhead and Li 2008). These are important lessons for
policymakers in Viet Nam. The insight from our study is that skills shortages will
not necessarily be resolved simply by increasing the supply of schools and teachers.
There is a potentially binding demand-side constraint on human capital deepening,
and this can be eliminated only by deeper structural reforms.

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附录: Summary Statistics of Main Variables

不. households
HH head works for civil admin (%)
HH head works for SOE (%)
HH Head education (年)
(s.d.)
Ethnic minority HH (%)
HH per capita income (million VND)
(s.d.)
HH per capita expenditure (million VND)
(s.d.)
HH expenditure on education (million VND)
(s.d.)
HH with zero educ. expenditure (%)
不. 个人
Completed middle school (%)
– Of which, attended high school (%)
Completed high school (%)
– Of which, attended tertiary inst’n (%)

Notes: Data are from VHLSS 2004, 2006, 和 2008.

2004

9,188
6.92
3.17
7.01
(3.99)
14.30
11,887
(24,726)
4,927
(4,410)
1,121
(2,167)
28.50
40,439
22.21
19.60
11.14
13.78

2006

9,192
6.17
3.23
7.13
(3.99)
15.06
15,710
(40,801)
6,130
(5,019)
1,397
(2,521)
32.04
39,071
18.69
26.03
10.63
19.25

2008

9,189
6.26
2.83
7.35
(4.16)
15.00
24,596
(67,443)
8,233
(6,451)
1,987
(4,028)
34.01
38,253
19.60
21.49
12.02
20.13

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