Phan Coxhead Vietnam Wage Paper April 14 2011 - Agricultural ...

1 

For presentation at the 8 th Midwest International Economic Development Conference, University of 

Wisconsin-‐Madison, April 15-‐16 2011. 

Draft only: comments welcome 

What happened to wages and wage premia in Vietnam during doi 

moi, and why? 

Diep Phan 1 and Ian Coxhead 2 

This version: April 14, 2011 

Abstract 

We ask what has happened to wages, intersectoral wage premia, and skill premia during Vietnam’s 

transition from command to mixed economy. During the 1990s and 2000s, wages rose in real terms and 

the skill premium also increased. We find, however, that neither trend has been linear, or even 

monotonic, over the entire transition period. In particular, while average real wages increased between 

1993 and 2008, most of this increase happened during the 1990s. Skill premia likewise rose during the 

1990s but leveled off in the 2000s. 

In a small transition economy like Vietnam, wage changes have been subject to significant policy 

influences from trade liberalization and the momentum of domestic policy reforms—notably those 

targeting labor market regulations. We designate trade policy and domestic market reforms as 

‘treatments’ imposed on an economy where, for historical and institutional reasons, state sector and 

private sector labor markets are substantively segmented. With this approach we are able, using a 

triple-‐difference estimator, to identify the contributions of each type of policy change to changes in 

wages, and to changes in intersectoral wage premia, in different phases of the economic reform 

process. 

1 Department of Economics, Beloit College, Beloit, WI, USA. 

2 Department of Agricultural & Applied Economics, University of Wisconsin-Madison, Madison, WI, USA.

1. Introduction 

2 

In the newly industrializing Asian economies in the 1960s and 1970s, poor and low-‐skilled workers were 

the disproportionate beneficiaries of opening international trade. This is an outcome predicted by the 

Stolper-‐Samuelson theorem, based as it is on the Heckscher-‐Ohlin model of endowment-‐based 

comparative advantage. Yet the experience of more recent liberalizers has frequently contradicted this 

hypothesis. In Latin America, skill premia and wage inequality have increased along with integration into 

the global market (Wood 1997; Arbache et al. 2004). Transition economies such as Poland, Hungary 

have also had seen similar rises in wage inequality, as has China (Knight and Song 2003). These trends 

may still be consistent with Heckscher-‐Ohlin, in that the entry of China and India to the global economy 

over the past two decades has seen a sharp rise in the global unskilled labor endowment. Other 

analyses have identified Ricardian technology-‐based comparative advantage as playing a leading role, 

especially in economies where industrial policy has been actively deployed to assist industries in their 

progress up the quality ladder (Feenstra and Hanson 1997; Zhu and Trefler 2005; Hausman, Huang and 

Rodrik 2007). 

In this paper we ask what has happened to wages, intersectoral wage premia, and skill premia during 

Vietnam’s period of economic reform and globalization. The Vietnamese economy grew rapidly during 

the 1990s and 2000s. Wages rose in real terms, and the skill premium also increased. Positive as these 

trends are, however, we find that neither has been especially linear – or even monotonic – over the 

entire transition period. In particular, while average real wages increased between 1993 and 2008, most 

of this increase happened during the 1990s; in the 2000s there was a clear slowdown in wage growth. 

Also, overall wage inequality and skill premia rose during the 1990s but leveled off in the 2000s. 

We explore these issues in this paper, beginning with a characterization of the data, and then moving 

into a more analytical examination of possible reasons for observed trends and puzzles. During the past 

two decades, the process of opening to global trade and investment coincided with a far-‐reaching set of 

domestic reforms to economic policy and institutions. Both set of reforms are expected to have strong 

general equilibrium effects on employment and wages in Vietnam. We explore the effects of these 

reforms in wage data from national household living standards surveys, and consider their implications 

for longer-‐term growth and development. 

The rest of the paper is organized as follows. In the next section, we examine and summarize the data, 

and conduct some preliminary statistical analysis. The results raise additional questions, notably about 

differences in returns to labor between public and private sectors, and the influence of international 

integration (i.e., trade and FDI). In section 3 we distill these findings in the form of a simple model of 

wage and skill premium determination. In section 4 we characterize these reforms as “treatments” and 

measure their effects on wages in state and private sector employment, and in industries more and less 

exposed to trade. We test some hypotheses suggested by the model and our earlier survey of data: that 

domestic institutions, labor market reform, and globalization are major contributors to changes in 

Vietnam’s wage inequality and skill premium in the 1990s and 2000s. Section 5 draws some 

conclusions, compares and contrasts findings from other studies, and identifies issues to be pursued in 

more depth in the future.

2. Vietnam’s wage growth and wage inequality 1993-‐2008 

3 

2.1. Prior studies 

The literature on wage growth, wage inequality, and returns to education in Vietnam is increasingly rich 

(Oostendorp and Doan 2010, Doan and Gibson 2010, Imbert 2010, Sakellariou and Fang 2010, Pham and 

Barry 2007a and 2007b, Liu 2005 and 2006, Nguyen et al 2006, Gallup 2002, and Moock et al 1998). 

Most of these papers estimate variations of the Mincerian earnings equation: Gallup (2002) and Liu 

(2005) employ simple OLS, Doan and Gibson (2010) the Heckman method, Liu (2006) Hay’s two-‐stage 

method (a generalization of Heckman’s approach), Pham and Barry 2007a and 2007b mean and quantile 

regression approaches, and Nguyen et al (2006) and Oostendorp and Doan (2010) difference in 

differences estimators. Some papers also apply various decomposition methods to explore 

characteristics that explain wage gaps, and study factors contributing to changes in wage gaps. For 

example, Sakellariou and Fang (2010) carry out an Oaxaca-‐Blinder decomposition based on 

unconditional quantile regression rather than on mean regression. 

Perhaps because of differences in methodology, point estimates of the rate of returns to education tend 

to vary considerably in these papers. However, they do agree on the following trends on wage growth 

and changes in returns to education. First, wage levels increased rapidly in Vietnam since doi moi. 

Sakellariou and Fang (2010) document that real earnings doubled for men and more than doubled for 

women from 1998 to 2008. Second, returns to education are low in Vietnam, but have increased over 

time. Doan and Gibson (2010), using OLS and Heckman estimators, find that the rate of return to one 

additional year of schooling rose from about 3% in 1993 to about 10% in 2008. 

Third, there is strong evidence of wage differential and labor market segmentation in various 

dimensions: gender, ethnicity, regional, and institution (public/state vs. private sector). For example, 

men in Vietnam on average earn more than women, even after controlling for differences in education, 

experience, and other characteristics. But this gap has been reducing over time. Pham and Barry 

(2007b), using a quantile regression approach, find that this earning gap was 31% in 1993 but 

diminished significantly to 19% by 1998 and exhibited stability until 2002. Liu (2006) documented that 

from 1993-‐1998, the mean real wage increased by 68% for males but 84% for women. Nguyen et al 

(2006) find that females get paid 15% less than men on average, controlling for differences in human 

capital (they use VLSS 1998 and VHLSS 2002). The gender wage gap was found to narrow down with 

primary and secondary education but not higher levels of education. This is because female workers 

with lower educational levels benefited dis-‐proportionately from labor-‐intensive export growth, a result 

found in many other studies of trade liberalization impacts on Vietnam (e.g., Jenkins 2002). 

2.2. Data and descriptive statistics 

The primary data source for this paper is the Vietnamese Living Standard Surveys: VLSS 1993 and 1998, 

and VHLSS 2002, 2004, 2006, and 2008. 3 The first lines in Tables 1 and 2 show that wages have been 

consistently rising over the years and for all groups. The trend for overall wage inequality, measured by 

3 Please refer to Appendix A for data notes.

4 

the Gini coefficient of average hourly wages, has been uneven. The coefficient rose from 0.38 in 1993 to 

0.42 in 2002, but declined to 0.36 in 2004 and 0.35 in 2006, then finally increased again to 0.39. 

While there was wage growth for all groups, its pace has been unequal across groups, and the trend has 

not been linear. From 1993 through 2008, the change in log average real hourly wages was 0.66 for 

women and only 0.57 for men (see Table 2). As a result, there has been a decline in the gender wage 

gap. Most of this decline happened from 1993 through 2002. Since 2002, the gender wage gap has 

stayed relatively stable. 

The rural-‐urban wage gap rose significantly in the 1990s, peaked in 2002, dropped in 2004 and 2006, but 

climbed up again in 2008. This trend might be due to rising urban living costs and the speed with which 

nominal wages kept up with this rise. In the period 2006-‐2008, inflation rates were high in Vietnam, 

largely due to higher energy and food prices. 4 These, coupled with rising real estate prices must have 

pushed up urban living costs relative to rural living costs. Indeed, the urban price deflators for the years 

2006 and 2008 were 1.23 and 1.18, respectively. These are very high compared to years 2002 and 2004, 

when the urban price deflators were only about 1.07 and 1.06, respectively. Nominal wages might not 

have increased fast enough to keep up with the unexpected and sharp increase in urban living costs in 

2006, so real wage growth in 2006 for urban workers might have been lowered. 

In 1993, ratio of the average wage of the Kinh ethnic majority to the average wage of ethnic minorities 

was quite low at 1.08. But there was a sharp increase in this ratio from 1993-‐2002 (1.84 at its peak in 

2002). After that, it decreased to 1.34 in 2004 and became stable at this level until 2008. 

Another interesting revelation from Table 1 is the wage differential between public and private sectors. 

In 1993, public sector workers’ average wage was lower than that of private sector workers. But by 

2002, public sector workers’ average wage was 170% that of private sector workers, as wage grew much 

faster in the public sector (wage growth rates were 27.6% in 1993-‐1998 and 23.02% in 1998-‐2002 for 

public sector, while the rates were 15.91% and 6.15% for private sector; see Table 2). In the period 

2002-‐2008 however, wage growth rate in the private sector started to catch up with that of public 

sector. Consequently, public to private wage ratio declined from 1.7 in 2002 to 1.57 in 2004, then 

remained stable until 2008. 

Finally, wage growth has been higher for those with higher levels of education (see Table 2), leading to a 

rise in skill premia. As can be seen in Figure 1, in 1993 there was hardly any skill premium, measured by 

the ratio of the average wage of those with a particular educational degree to those without any degree. 

This must have been a result of central planning, in which wages were institutionally set rather than 

determined by market forces. From 1993 through 2002, as the economy went through a series of 

domestic reforms, there was a dramatic increase in skill premium, especially for college-‐educated 

workers. It’s quite interesting however that from 2002-‐2008, this rise in skill premium has leveled off. 

4 Large capital inflows also made a significant contribution to rising inflation.

5 

Our descriptive analysis so far suggests that the labor market in Vietnam behaved very differently in the 

1990s and in the 2000s. There might exist one or more structural breaks in the trend of wage growth 

and wage inequality in different dimensions between the two periods. 

2.3. Determinants of wages 

While the descriptive analysis yielded many interesting results, it has not controlled for covariates when 

examining factors associated with wage differentials. We thus ran basic Mincerian wage regressions 

using OLS. 5 The findings mostly confirm those in the descriptive analysis (see Tables 3a and 3b). Over 

the years, there were consistent increases in returns to education, especially to college education. Table 

3a shows that, in 1993, there was no return to education, as the coefficient on years of schooling was 

about zero, after controlling for experience, gender, and other characteristics. In 1998, this coefficient 

jumped to 0.032, meaning that one additional year of schooling increases the log wage by 3.2%. 

Thereafter, the coefficient gradually increased and by 2008, it reached 0.051. Even after these increases, 

by 2008, returns to education in Vietnam are still very low by international standards (e.g. Cai, Park and 

Zhou 2008). This raises concerns regarding the incentive to invest in human capital. 

Table 3b replaced years of schooling with dummies for different educational levels. In 1993, there were 

hardly any differences in wages among those with varying educational levels. Only college graduates had 

some positive returns to their education. Even then, the return was very small: a college degree would 

increase the log wage by only 17% relative to those without any education. Returns to different levels of 

education increased steadily over the years from 1993 through 2008. Returns to college degree 

increased the most, as already discussed in Table 3a and in the descriptive analysis. 

Results for other dimensions of wage differentials also mirror those in the descriptive analysis. It seems 

clear that there is a structural change in Vietnam’s labor market from the 1990s to the 2000s, and the 

year 2002 seems to be the turning point. In particular, there is a leveling off or slowdown of wage 

growth and wage differentials after 2002. Public sector premium increased in the 1990s but decreased 

in the 2000s. Returns to experienced increased up to year 2002 then stabilized. Gender wage gap 

decreased in the 1990s then stabilized (but it increased again in 2008). Rural-‐urban wage gap increased 

from 1993-‐2002 then decreased afterwards. 

2.4. Wage changes: decomposition analysis 

To further understand the sources of rapid wage growth from 1993 through 2008, we carried out an 

Oaxaca-‐Blinder decomposition for the three periods 1993-‐1998, 1998-‐2002, and 2002-‐2008. 

ln !"#$ !! − ln !"#$ !! = ! !,!! 

! 

= ! !,!! 

! 

∗ ! !,!! + ! !,!! 

! 

∗ ! !,!! 

∗ ! !,!! − ! !,!! + ! !,!! − ! !,!! 

! 

5 We also ran Heckman regressions to control for sample selection bias. Identification variables include dependency 

ratio, dummy for being household head, and non-wage income (non-wage income variables are not available for 

survey years 1993 and 1998). The results (see Table 9) suggest that there are no major differences between OLS and 

Heckman estimates, even though in all regressions, the null hypothesis that rho=0 can be rejected. Hence, we decide 

to present only OLS results in the main paper. 

! !,!!

6 

The first term on the right hand side is the increase in log wage due to changes in characteristics 

between year t1 and year t2 (such as an increase in years of schooling or reallocation from rural to 

urban sector). The second term is the increase in log wage due to changes in returns to characteristics 

(such as an increase in skill premium or public sector premium). The decomposition analysis (see Table 

4) makes it clear that changes in returns to labor in Vietnam since 1993 are due to either increase in the 

base wage (i.e., wage growth for everyone) or to changes in returns to existing worker characteristics 

such as skills and experience, rather than to changes in those characteristics themselves. From 1993 to 

1998, increase in returns to education explained almost half of the wage growth. During 1998-‐2002 and 

2002-‐2008, increase in returns to education continued to be one of the most important contributors to 

wage growth, although no longer as much as in 1993-‐1998 and not statistically significant. This result is 

consistent with figure 1, which shows the dramatic increase in returns to education from 1993 to 1998 

compared with the later periods. The result also motivates a deeper search for the sources of changes in 

returns to characteristics, especially changes in returns to education. 

2.5. Discussion 

We summarize the main findings so far here: 

1. Wages have been rising rapidly. 

2. Overall wage inequality increased from 1993 through 2002, but started to level off from 2002 to 

2006, then increased somewhat again in 2008. 

3. Returns to education were extremely low in 1993, increased significantly through 2002, then 

continued to increase albeit at a slower rate from 2002 to 2008. 

4. Changes in observable worker characteristics account for a very small share of the total change 

in wages. Growth in the base wage and changes in the returns to characteristics account for 

most of the wage growth. 

5. Public sector premium has been rising, suggesting a deepening of labor market segmentation 

between the state sector and the private sector. 

Structurally, the process of growth, reform and globalization that Vietnam has undergone could have 

conflicting effects on wages and skill premia. Growth raises labor demand and should, other things 

equal, increase the demand for skills more rapidly than that for ‘raw’ labor as the expanding economy 

demands more specialized services in banking, finance, insurance, management and related tasks. 

Reforms have had a large impact on the relative position of public and private sector activity, and on the 

degree of engagement of foreign capital and joint-‐venture operations in production. As discussed in 

more detail below, these changes could have an influence on the growth of relative demand for skills. 

Finally, globalization requires a reorientation of large parts of the economy to the norms of the 

international market. Price convergence (in activities with comparative advantage, from below; in those 

with comparative disadvantage, from above) helps determine changes in returns to all factors, including 

labor. In the case of a labor-‐abundant, low-‐skill economy such as Vietnam, the Stolper-‐Samuelson 

theorem predicts a rise in returns to unskilled wages relative to those for skills. 

In addition to globalization, the influence of economic and institutional reforms is also of particular 

importance. Vietnam’s experience, as a transitional economy, is unusual in the East Asian setting; only

China has undergone such a sweeping change in economic organization, from quasi-‐closed and almost 

entirely state-‐controlled to mainly open, with public and private institutions coexisting. One 

characteristic of the old system was a clear distinction between wages, returns to skills, and other 

conditions of public and private sector labor markets. Table 5 highlights contrasts between these 

institutions in the returns to labor overall, and in the spread of wages by education. 6 

7 

Moreover, differences in returns to skills persist throughout the period covered by our data, as seen in 

Table 6. Returns to schooling in Vietnam’s public sector were initially low (1993) but rose very sharply. 

Those in the private sector have remained low throughout, with the consequence that the ratio of 

public/private returns to schooling rose from 1.6 in 1993 to a peak of 5.2 in 2004, before settling back to 

3.4 by 2008. 

Finally, the contribution to employment growth by institution has been dramatically different. Table 6 

shows changes in the structure of employment. The share of wage employment has been increasing 

while that of self-‐employment has been decreasing, an expected trend for a developing economy. 

Within wage employment, public sector’s contribution to employment is much smaller compared to that 

of the private sector. This should be judged against the high GDP share of the state sector, which has 

been declining since the 1990s albeit at a slow rate (from 40.18% in 1995 to 35.5% in 2008 7 ). The state 

sector has not generated many jobs despite its large share in the economy’s GDP, although it has slowly 

become more labor-‐intensive over the years. Therefore, it seems that public and private sector 

employers are responding to different signals, or applying different rules in deciding on how much labor 

to employ, and what wages to pay. 

In short, both the average wage and the returns to skills show strong initial differences between public 

and private sector workers, especially in first decade of Vietnam’s modern economic growth experience. 

Differences in wages and skill premia are reinforced by differential growth rates of employment. 

3. Theory 

In the foregoing section we saw that changes in observable worker characteristics account for a 

relatively small share of the total change in wages in Vietnam. We also found considerable, if 

circumstantial, evidence for a form of labor market segmentation between the state sector and the 

private sector. This was revealed in persistently different wages by skill, skill premia, and employment 

trends relative to output growth rates. These findings raise two interesting questions. To what extent 

do domestic institutions and reforms govern the evolution of wages and skill premia? What is the 

contribution of globalization—the very rapid opening to world markets that Vietnam underwent at the 

same time? In this section we construct a simple model with which to form hypotheses about wage and 

skill premium trends in the globalizing Vietnamese economy. This sets the stage for empirical 

hypothesis tests in section 4. 

6 Interestingly, these data have a strong similarity to those from a comparable period in China, where the ratio of 

average state to non-state sector wages rose from 0.4 in 1988 to approximate parity (0.9) in 2001, while the 

coefficient of variation of wages across institutions fell from 0.46 to 0.16 (Cai, Park and Zhao 2008, Table 6.4). 

7 Data from GSO website.

8 

The workhorse of the returns-‐to-‐labor literature is the Mincer’s “human capital earnings function,” in 

which the rate of return to an individual’s schooling is estimated by reference to years of education and 

a polynomial in experience (Mincer 1974). Subsequent generalizations have brought in other worker 

characteristics such as gender and ethnicity, as well as conditioning variables such as family background, 

cognitive ability and school quality, generating a class of models known as “returns to schooling 

functions” (for a survey, see Card 2008). An ex post interpretation of this function also includes post-‐ 

schooling information such as industry and location (e.g., rural v. urban). Here, we adopt a general 

equilibrium interpretation of the returns to schooling function; in this, each worker earns a wage equal 

to the average rate plus or minus premia due to individual characteristics such as gender and ethnicity. 

The average wage itself is a function of general equilibrium variables: prices, policies, and aggregate 

factor endowments. 

Our analysis of the Vietnam case is special due to the qualitatively different treatment of private and 

public sector workers. On one hand, the public sector in Vietnam has always been very tightly 

regulated, and remains so to this day. On the other, in the first decade of economic reforms (roughly 

1986-‐1998) the Vietnamese government introduced a number of changes directly and indirectly 

affecting wages and conditions for public sector workers. Direct influences included a wholesale reform 

of the public sector, resulting in the loss of an estimated 1.5 million public sector jobs, and the 1994 

introduction of a new Labor Law, which relaxed somewhat the regulations governing public sector 

workers’ compensation and benefits (Moock et al., 2003). These labor law reforms were thought by 

contemporary observers to have had little direct impact on private sector workers, as “in general the 

private sector was not hampered by the more rigid labor remuneration regulations” to which 

government workers and those in state-‐owned enterprises were subject (World Bank 1995: 63). 

Indirect influences included early initiatives to “equitize” (partially privatize) some state-‐owned 

enterprises, and the relaxation of statutory limitations on joint venture partnerships with foreign capital. 

These liberalizing reforms were adopted in the 1990s while retaining very high rates of protection and 

other forms of preferential treatment for state-‐owned enterprises (Athukorala 2006). As the World 

Bank (1995) concluded, “These privileges -‐ in particular preferential access to land and foreign trade 

quotas and licenses -‐ have played a very important role in the concentration of foreign direct investment 

in joint ventures with state enterprises, which is transferring to them new financial, managerial and 

technological resources.” Undoubtedly, the differential access of SOEs to foreign capital and joint 

venture partnerships in the 1990s helped raise their productivity, and along with it the returns to their 

labor force—subject, of course, to the restrictions on compensation imposed by the Labor Law. 

These empirical conclusions from contemporary observers of the Vietnamese economy motivate a 

model in which the labor market – and especially that for skilled workers – is not well integrated 

between public and private institutions. Hiring and wages in the latter depend on conventional 

profitability calculations, while in the former, we find persuasive evidence of non-‐market wage-‐setting. 

This is consistent both with tighter regulation of state wages, and—and in the case of state-‐owned 

enterprises, with the partial monetization in wages of rents attributable to quasi-‐monopoly status and 

other statutory privileges.

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In stylized form, we can think of the private sector returns to schooling function as depending on a 

combination of the workers’ own characteristics and the mean wage as determined by macroeconomic 

supply and demand factors. Demand factors are dominated of course by the prices earned industries, 

whereas supply factors are dominated by long-‐run labor force growth and participation rates, as well as 

any transfer of workers from public to private sector employment-‐-‐ itself the indirect impact of policies 

in government and state-‐owned industries. 

Formally, we can derive the aggregate private sector wage function from an aggregate revenue (or GDP) 

function (Dixit and Norman 1980). Let w be the average wage, p be a vector of output prices, and V be 

the total factor endowment vector, and let s(π) be the demand for each factor from State employers. 

Then aggregate private sector output (G) is produced from the net factor endowment vector: G =G(p, v), 

where v = V-‐s(κ). The factor price function is obtained by differentiation of G(p, v) with respect to the 

labor element of the net endowment vector, v. In general vector notation, 

w = ∂G(p, V-‐s(κ))/∂v. 

The assumption here is that s(κ) is determined by state policies, not by market forces, and that this gives 

rise to a segmented factor market. 

This model captures the general equilibrium influences on w from all sources. It is helpful to think of it 

in the form of a total differential: 

dw = (∂w/∂p)dp + (∂w/∂v)[dV -‐ (∂s/∂π)dκ]. 

In a small open economy, the first product on the right hand side captures Stolper-‐Samuelson effects 

associated with trade and trade policy reform. The second product captures influences on factor 

returns associated with changes in total factor endowments. The third product captures the effects of 

state policies—in Vietnam for example, the elimination of about 1.5m jobs in government and SOEs in 

the mid-‐1990s, as previously discussed. 

Finally, the wage wi earned by any individual with a vector of characteristics xi ≠ x will deviate from the 

average: 

wi = βxi + w(p, V-‐s(κ)), 

where β is a vector of returns to characteristics. 

With this theoretical and empirical context, it is not obvious what increased trade openness will do to 

wages and overall inequality in a poor developing country such as Vietnam. On the one hand, Vietnam 

has been pursuing labor-‐intensive export-‐oriented growth, as evidenced by the rapid production and 

export growth of labor-‐intensive industries. The Stolper-‐Samuelson theorem would predict a decline in 

both the skill premium and wage inequality. On the other hand, growth due to greater openness – 

especially if that openness is tempered by some degree of industrial policy, as Hausmann, Huang and 

Rodrik (2007) assert it has been in China – could stimulate a rapid rise in the skill premium. Conversely,

changes in government policies that affect state sector employment have the potential to shift the 

supply of skills, which also influences the private sector returns to schooling function. 

10 

This model is preliminary in nature and has many shortcomings (it is, for example, static, and imposes a 

number of assumptions, among them competitive wage-‐setting in private sector employment). Its 

virtue is its simplicity; it draws attention to what are arguably the dominant sources of wage 

determination for private sector workers: their own characteristics (e.g., education); their marginal 

value product in employment which is affected by reforms such as trade liberalization, and changes in 

aggregate supply, including those resulting from policies affecting state-‐controlled employment. 

4. Sources of differential wage growth 

The Vietnam data show that between 1993 and 2008, wages and the skill premium rose substantially. 

But it is easy also to see that virtually all of the growth took place in the first decade of the reform era, 

and that with the sole exception of the college degree/no education ratio in year 2008, every measure 

of the premium declined after 2002. What is behind these contrasting trends? This is not an easy 

question to answer in an economy where rapid growth is causing many things to change at once. 

Moreover, Vietnamese statistical sources on some variables (such as workers’ wages and employment 

by skills) are very difficult to reconcile with those providing other kinds of information, such as 

employment, output and profits at firm or industry level. Our approach in this study relies primarily on 

VHLSS sources. 8 This allows us to retain the richness of the individual data in VHLSS, at the cost of 

constraining somewhat our ability to characterize the determinants of the general equilibrium wage. 

Our solution is to consider the two types of policy innovations– those addressing labor and other 

conditions in government and state-‐owned enterprises, and reforms affecting the profitability of 

production of tradables versus goods for the home market– as exogenous treatments, the effects of 

which we measure against trends reflecting underlying economic growth and development and 

captured in the evolution of wages for a control group. This section describes the methodology and 

reports econometric results of hypothesis tests. 

4.1. Empirical methodology: triple difference estimator 

Our goal is to measure the effects of two policy “treatments” on wage growth and wage inequality. 

Because we have two independent treatments, we employ a triple difference (DDD) estimator. To 

measure the “treatment” effects of trade liberalization and domestic reform, we divide the sample by 

public and nonpublic sector, and also by tradable and non-‐tradable industries (see appendix B for a list 

of industries in each category). While labor market reforms could have affected workers in both the 

public and private sectors, the evidence presented in section 2 suggests that they had first-‐order 

impacts only on the public sector. Thus, in a single-‐treatment difference in difference (DD) analysis, we 

can think of public sector workers as the treatment group and private sector workers as the control: 

!"# !"#! ! = ! ! + ! ! ∗ !"#$2 ! + ! !!"#$%& ! + ! !!"#$2 ! ∗ !"#$%& ! + ! !! + ! ! 

8 In related research currently in progress, we approach the same question via other sources such as Enterprise 

Surveys.

11 

where Year2 is a dummy for the later year, Public is a dummy for public sector worker, Z is a vector of 

workers’ characteristics including education, experience, trade dummy, and other covariates. ! ! 

represents the time trend in the control group, i.e., the increase in wage from year 1 to year 2 for 

private sector workers. ! ! represents the wage differential between private and public sector workers in 

year 1. ! ! represents the difference in changes over time between groups, i.e., the average treatment 

effect. If ! ! > 0, this is evidence that labor market reform between year 1 and year 2 raised wages in 

the public sector more than it did in the private sector. 

In this analysis, there is an unavoidable spillover from the treatment group to the control group. In 

general equilibrium, wages offered by government and state firms would certainly affect wages offered 

by private employers. To the extent that this is so, estimates of the treatment effect (! ! above) suffer 

from a bias. If we find that ! ! = 0 , we cannot conclude that there isn’t any significant treatment effect 

(labor market reform did not impact the labor market, whether public or private sector workers) 

because the actual ! ! might be larger in the absence of the spillover. But if we find that the treatment 

effect is positive (labor market reform impacted public sector workers more than private sector 

workers), then we can conclude that there is a treatment effect, and that our estimate of the treatment 

effect is an underestimate of the actual effect, due to downward bias caused by the spillover. 

Similarly, the trade liberalization should have first-‐order effects on tradable industries only. In this case, 

therefore, we can consider workers in tradable industries as the treatment group, and workers in non-‐ 

tradable industries as the control. Once again considering only the single-‐treatment (DD) version: 

!"# !"#$ ! = ! ! + ! ! ∗ !"#$2 ! + ! !!"#$% ! + ! !!"#$2 ! ∗ !"#$% ! + ! !! + ! ! 

! ! captures the time trend in the control group, i.e., the wage increase from year 1 to year 2 for workers 

in tradable industries. ! ! captures the wage premium for workers in tradable industries in year 1. 

Finally, ! ! captures the difference in changes over time between groups, or the treatment effect of 

trade liberalization. If ! ! > 0, this is evidence that wages increased more for workers in tradable 

industries. On the other hand, ! ! < 0 means that wages increased less for workers in tradable 

industries. In this DD, there is again a spillover effect similar to that in the DD analysis for public vs. 

private sector. So again, while a positive ! ! allows us to conclude that there is a statistically significant 

effect of trade liberalization, we only have an underestimate of the effect. 

In principle, we can estimate the above two DD models above and examine the impact of domestic 

reform and trade liberalization separately. But since these two reforms occurred simultaneously there 

is potential for wage variations in three dimensions: between time periods, between public and private 

sectors, and between tradable and non-‐tradable industries. Because of initial differences among 

institutions, for example, the wage offered to a public sector worker in a tradable industry might vary 

over time in ways that differ from that offered to a private sector worker. To allow for this, we use a 

triple difference estimator: 

!"# !"#$ ! = ! ! + ! ! ∗ !"#$2 + ! ! ∗ !"#$% + ! ! ∗ !"#$%& 

+ ! ! ∗ !"#$2 ∗ !"#$% + ! ! ∗ !"#$% ∗ !"#$%& + ! ! ∗ !"#$%& ∗ !"#$2 

+ ! ∗ !"#$2 ∗ !"#$% ∗ !"#$%& + ! ∗ ! + ! !

In this expression, the triple difference effect is: 

12 

!!! = !" !" ! !" !" !" 

! ! − !! − !! − !! 

!" !" 

− !!" 

! !" !" 

− !!" − !!" 

!" 

− ! !" 

The first term in brackets is the difference in wage change between tradable and non-‐tradable industries 

for public sector workers. The second bracketed term is the difference in wage change between trade 

and non-‐traded industries for non-‐public sector workers. The DDD method allows us to examine 

whether changes in wage from year 1 to year 2 vary by both institution (public vs. private sector) and by 

trade status. 

By differentiation, we see that the marginal impact on log wage of being in the public sector is: 

∂log (!"#$ !) 

!!"#$%& = ! ! + ! ! ∗ !"#$! + ! ! ∗ !"#$2 + ! ∗ !"#$2 ∗ !"#$% 

A positive ! ! means that there is a public sector premium in year 1 (the average wage in public sector is 

higher than that in private sector in year 1). A positive ! ! implies that public sector premium is higher 

for workers in tradable industries in year 1. A positive ! ! says that public sector wage has increased 

from year 1 to year 2. If ! > 0 and ! ! > 0, then the increase in public sector wage is larger for tradable 

industry workers. If ! > 0 and ! ! < 0, then the decrease in public sector wage is less for tradable 

industry workers. If ! < 0 and ! ! > 0, the increase in public sector wage is smaller for tradable industry 

workers. If ! < 0 and ! ! < 0, the decrease in public sector wage is larger for tradable industry workers. 

The marginal impact on log wage of being in a tradable industry is: 

∂log (!"#$ !) 

!!"#$% = ! ! + ! ! ∗ !"#$2 + ! ! ∗ !"#$%& + ! ∗ !"#$2 ∗ !"#$%& 

If ! ! > 0, it means that there is a trade sector premium in year 1. If ! ! > 0, average wage in tradable 

industries has increased from year 1 to year 2. If ! ! > 0, the tradable sector premium is higher for 

public sector workers in year 1. If ! > 0 and ! ! > 0, then the increase in the tradable sector wage is 

larger for public sector workers. If ! > 0 and ! ! < 0, then the decrease in the tradable sector wage is 

less for public sector workers. If ! < 0 and ! ! > 0, the increase in the tradable sector wage is smaller for 

public sector workers. If ! < 0 and ! ! < 0, the decrease in the tradable sector wage is larger for public 

sector workers. 

4.2. Estimation results 

Table 8 presents the DDD estimation results. Many coefficients have signs as expected. For example, 

year 2 dummy is always positive (! ! > 0), implying that there was wage growth in all groups for all 

periods. There was a negative public sector premium in 1993 and 1998 (! ! < 0 in the first two periods’ 

regressions), a remnant of central planning. By 2002, the public sector had a positive wage premium 

(! ! > 0 in the last period’s regression). However, ! ! is positive in all periods, which indicates that the 

public sector premium increased in all periods. ! ! < 0 in the first two periods, so the tradable sector

premium actually decreased during 1993 through 2002. But during 2002-‐2008, it increased (! ! < 0). 

These results have already been found in the basic wage regressions in Tables 3a and 3b. 

13 

! ! is positive in all periods but statistically significant only in the last period’s regression. This result has 

two simultaneous implications for the year 2002: public sector premium is higher for workers in tradable 

industries, and the tradable sector premium is higher for workers in the public sector. 

Finally, the coefficient of the most interest is the triple interaction term, !. It is positive in the first 

period 1993-‐1998, not significant (positive and small) in 1998-‐2002, and negative in 2002-‐2008. In the 

first period 1993-‐1998, since ! > 0 and ! ! > 0, the increase in public sector wage is larger for tradable 

industry workers. Also, since ! > 0 and ! ! < 0, the decrease in the tradable sector wage is less for 

public sector workers. The two results both imply that there is an interaction between institutions and 

trade: in the early years of doi moi there was an advantage in being a public sector worker in a tradable 

industry. 

During this early period of reform, even though public sector workers had lower average wage, they saw 

faster wage growth due to the labor market reform. This wage growth differential was even more 

pronounced if public sector workers also happened to be in a tradable industry. This interaction effect 

might be a result of incomplete liberalization. In the 1990s, although Vietnam liberalized markets and 

international trade and implemented policies to attract foreign direct investments, there remained a 

heavy bias toward joint ventures with state firms in tradable industries, mainly at the higher end of the 

capital-‐intensity range (World Bank 1995). 9 Thus, workers in state firms in tradable industries must have 

enjoyed rapid wage growth not only thanks to labor market reform, but also thanks to the ability of 

these firms to attract large quantities of new investment both from the domestic economy and from 

abroad. For tradable industry workers not in the public sector, wages relative to workers in non-‐tradable 

industries decreased from 1993 to 2002. So the net impact of trade liberalization on the overall labor 

market, being an aggregation of conflicting trends in public and private sectors, was limited during this 

period. 

In 2002-‐2008, the trend reversed. Since ! < 0 and ! ! > 0, the increase in the public sector wage is 

smaller for tradable industry workers. Also, since ! < 0 and ! ! > 0, the increase in the tradable sector 

wage is smaller for public sector workers. That is, even though both public sector workers and tradable 

industry workers saw their premium rise during 2002-‐2008, this rise would be less if a worker was in 

both the public sector and a tradable industry. So again, there is an interaction between institution and 

trade: in the second decade of doi moi, there was a disadvantage in being a public sector worker in a 

tradable industry. 

By the 2000s, the country deepened external sector reforms, signing a bilateral trade agreement with 

the USA (2001) and preparing for WTO accession (1997). Domestic reforms began to level the playing 

9 In its report, the World Bank noted that “the vast majority of FDI has financed joint ventures with [State-‐owned 

enterprises], whose capital contribution to the joint venture has usually consisted of land use rights. Several 

reasons have contributed to this trend: the relatively small size of most private enterprises, their concentration on 

few industrial subsectors, their more limited connections with decision makers, and -‐most important -‐ their limited 

access to land” (p.35).

14 

field between state and private industries. Passage of the Enterprise Laws in 2000 and 2005 stimulated 

FDI not only in the state sector but also in the private sector, and not only in capital-‐intensive industries 

but also, increasingly, in labor-‐intensive industries. All these reforms had the impact of expanding labor-‐ 

intensive tradable industries, which have become the engines of export and employment growth in 

Vietnam. This in turn raised the wages that workers in tradable industries received relative to those in 

non-‐tradable industries (! ! > 0 in 2002-‐2008). But this rise was smaller for public sector workers in 

tradable industries. By the 2000s, even though public sector workers continued to experience a rise in 

their wage premium, the rise was no longer as large (! ! = 0.135 in 1993-‐1998 and ! ! = 0.336 in 1998-‐ 

2002, but it was only 0.052 in 2002-‐2008). This deceleration in the rise of public sector premium might 

be because the impact of labor market reform had already run its course. Another reason is that in the 

2000s, state firms started to face more competition from private firms, or from joint ventures between 

domestic and foreign firms. 

In short, through the DDD analysis, we have been able to trace the impacts on wages of increased 

economic openness and labor market reforms, and unpack interactions between the two. There is 

evidence that labor market reforms had a stronger impact on the Vietnamese labor market in the early 

period of doi moi, while in the later period, it was continued opening to the global economy that had a 

stronger impact. 

These findings extend and to some extent unify those of prior contributions to this literature. Imbert 

(2010) documented the considerable increase in average earnings of public sector workers from 1993 to 

2006, following labor market reform. Taking into account the effect of unobserved worker 

characteristics, the author found that the rise in public sector premium cannot be explained by a change 

in worker selection into the sector. Rather, it’s explained by differences in returns to characteristics, or 

sectoral differences in wage setting, indicating dualism in the labor market. Nguyen et al (2006) 

analyzed the impact of trade liberalization on wage structure in Vietnam, in particular the rate of returns 

to education and gender wage gap, but found only limited evidence of an impact. Oostendorp and Doan 

(2010) on the other hand, found that trade liberalization reduces the return to education by 1.2-‐3.6%. 

Most of this decline was due to changes in the industry distribution of employment, not due to the 

decline in Mincerian return. Our analysis has shown the net impact of trade liberalization might be 

masked because of the interaction between institution and trade. 

5. Conclusion 

In Vietnam, the transition from command to mixed economy and the concomitant opening to 

international trade and investment has seen real wages and returns to schooling both rise as expected. 

These trends have been well documented. The contribution of this paper is first to identify distinct 

phases of change in wages and intersectoral wage premia, and second, to begin the task of explaining 

them. Mincerian regressions and wage growth decompositions of the kind that we have reported and 

discussed in the first part of this paper can document changes that have occurred over time, but do not 

tell us much about the reasons for them. Indeed, the large “change in coefficients” component of the 

decomposition analysis for wage growth (Table 4) simply reveals the extent of our ignorance of 

underlying causal factors.

15 

Each individual’s wage is determined by his or her own characteristics as well as by broader forces 

operating on labor markets. In a small transition economy like Vietnam, these broader forces are 

increasingly dominated by global influences through trade, and the momentum of domestic policy 

reforms—notably, though not exclusively, those specifically targeting the operation of labor markets. 

Our approach has been to designate trade policy and domestic market reforms as ‘treatments’ imposed 

on an economy where, for historical and institutional reasons, state sector and private sector labor 

markets are substantively segmented, general equilibrium labor market constraints notwithstanding. 

With this approach we are able, using a triple-‐difference estimator, to identify the contributions of each 

type of policy change to changes in wages, and to changes in intersectoral wage premia, in different 

phases of the economic reform process. 

The results, though preliminary, are intriguing. In the early reform years, the public sector (mainly state-‐ 

owned enterprises) was substantially shielded from the process of economic liberalization. State-‐owned 

firms and industries remained the beneficiaries of many privileges that made them attractive partners 

for early foreign capital inflows and joint-‐venture production arrangements. So trade liberalization in 

the 1990s raised the premium to state sector workers in tradable industries; these gains were 

augmented by domestic reforms that liberalized the state sector labor market, allowing wages in this 

sector to rise. Also, because state firms tend to be very skill-‐intensive, 10 this might have contributed to 

the rise in returns to skill of state sector workers. At the same time, the laying off of a large number of 

state workers during the 1990s might have increased the supply of skilled labor to the private sector, 

causing returns to skill in the private sector to not increase by as much. In short, the rapid increase in 

returns to skill in the 1990s was mostly driven by the increase in skill premia in the state sector rather 

than in the private sector. 

In later years, the momentum of trade and investment began to shift (albeit gradually) toward private 

sector firms. This slowed the increase in public sector premium relative to private sector premium. But 

investments in the expansion of private sector activity were motivated much more by the desire to 

exploit Vietnam’s comparative abundance of unskilled workers; hence, returns to skill in the private 

sector remained rather low, an outcome of the Heckscher-‐Ohlin effect. This result, coupled with the 

increased importance of private sector employment, yielded the net effect that the skill premium in the 

overall labor market flattened out in the 2000s (the effect of the private sector skill premium now 

dominates that of the public sector skill premium). Our triple-‐difference analysis has quantified wage 

changes and changes in intersectoral wage premia within a unified econometric framework. Knowing 

that state sectors are more skill-‐intensive by virtue of their special policy treatment, our results then 

contribute to a deeper understanding of the skill premium trends shown in Figure 1. 

The flattening of the skill premium, if maintained, has potentially important development implications. 

On one hand, decreased skill premia associated with the increased specialization in labor-‐intensive 

industries should reduce wage inequality. On the other hand, a lower skill premium reduces incentives 

10 In another paper which we use Enterprise Survey 2007, we have been able to show that state firms tend to be 

much more skill-intensive than private firms. Higher degree of capital-intensity contributes to higher skilledunskilled 

relative labor demand for state firms, but it contributes to less skilled-unskilled relative labor demand for 

private firms.

16 

to accumulate human capital, which will hinder long-‐term economic growth to the extent that this 

depends on steady progress up the quality (and thus skill-‐intensity) ladder. To offset the effects of 

globalization-‐driven changes from the demand side of the market for skills requires policy reforms and 

investments that address supply, mainly through improvements in the quality, quantity and affordability 

of education. At the same time, there is a large growth dividend associated with the further relaxation 

of special treatment for SOEs. As a group, these industries absorb a large share of Vietnam’s investment 

capital and skilled labor, yet they are highly inefficient and their activities contribute relatively little to 

overall income growth. 11 

11 To illustrate, CIEM estimates a state-sector ICOR of 17.5 as opposed to a private sector ICOR of 4.6 (cited in 

Asia Times: “Vietnam changes course”, April 12 2011, 

http://www.atimes.com/atimes/Southeast_Asia/MD12Ae01.html).

17 

Table 1: Mean hourly wages (thousand VND) 

1993 1998 2002 2004 2006 2008 

all 1.83 2.90 3.83 4.54 4.56 7.34 

Gini 0.38 0.35 0.42 0.36 0.35 0.39 

men 2.07 3.10 3.99 4.74 4.77 7.62 

women 1.49 2.59 3.57 4.22 4.23 6.91 

men/women ratio 1.39 1.20 1.12 1.12 1.13 1.10 

T-‐stat for diff. in mean b/t men & women 6.95 5.16 5.40 5.62 5.50 3.78 

rural 1.80 2.46 2.96 3.69 4.02 5.99 

urban 1.87 3.53 5.46 5.82 5.38 9.38 

urban/rural ratio 1.04 1.43 1.84 1.57 1.34 1.56 

T-‐stat for diff. in mean b/t rural & urban 0.86 12.65 24.62 18.80 13.25 16.40 

Kinh 1.84 2.95 3.98 4.61 4.63 7.44 

minority 1.70 2.27 2.22 3.43 3.53 5.73 

Kinh/minority ratio 1.08 1.30 1.79 1.34 1.31 1.30 

T-‐stat for diff. in mean b/t Kinh & minority 0.80 3.47 9.20 4.45 4.40 3.51 

Public 1.71 3.23 5.49 5.64 5.61 9.34 

Non-‐public 1.89 2.73 3.14 3.60 3.65 5.84 

Public/nonpublic ratio 0.90 1.18 1.75 1.57 1.54 1.60 

T-‐stat for diff. in mean b/t public & private 2.08 5.95 25.24 21.70 21.75 20.28 

no degree 1.76 2.53 2.54 3.07 3.13 4.80 

primary school degree 1.99 2.68 3.03 3.50 3.53 5.39 

middle school degree 1.74 2.68 3.72 3.92 3.89 5.60 

high school degree 1.75 3.20 4.70 5.42 4.99 7.82 

college degree and higher 2.03 5.36 7.37 8.08 8.42 14.74 

T-‐stat for diff. in mean b/t primary degree & others 2.32 4.57 10.59 12.37 12.16 10.64 

T-‐stat for diff. in mean b/t middle school degree & others 1.34 3.48 3.24 7.24 8.02 9.89 

T-‐stat for diff. in mean b/t high school degree & others 0.88 2.54 8.82 9.32 5.97 3.74 

T-‐stat for diff. in mean b/t college degree & others 1.25 17.73 28.00 27.74 32.60 32.18 

NOTE: all wages have been deflated to January 1998 prices

Table 2: Average annual growth in wages 

1993-‐ 

1998 

1998-‐ 

2002 

2002-‐ 

2008 

18 

1993-‐ 

2008 

All 12% 8% 15% 20% 

Men 10% 7% 15% 18% 

Women 15% 10% 16% 24% 

rural 7% 5% 17% 16% 

urban 18% 14% 12% 27% 

Kinh 12% 9% 14% 20% 

minority 7% -‐1% 26% 16% 

Public 18% 17% 12% 30% 

Private 9% 4% 14% 14% 

no degree 9% 0% 15% 12% 

primary 7% 3% 13% 11% 

lower 11% 10% 8% 15% 

upper 17% 12% 11% 23% 

college 33% 9% 17% 42% 

3.50 

3.00 

2.50 

2.00 

1.50 

1.00 

0.50 

0.00 

Figure 1: Vietnam's skill premium 1993-‐2008 

(relaPve wage to workers with no degree) 

1993 1998 2002 2004 2006 2008 

primary school degree middle school degree 

high school degree college degree and higher

Table 3a: Determinants of Wage – OLS Estimation Results Specification 1 

Dependent variable: log(hourly wage) 1993 1998 2002 2004 2006 2008 

Years of education 0.004 0.032 0.036 0.040 0.048 0.051 

Years of experience 0.017 0.023 0.022 0.038 0.035 0.036 

Years of experience squared 0.000 0.000 0.000 -‐0.001 0.000 -‐0.001 

Male dummy 0.295 0.167 0.179 0.170 0.178 0.192 

Ethnic minority dummy -‐0.029 -‐0.003 -‐0.351 -‐0.108 -‐0.065 -‐0.063 

Urban dummy 0.072 0.182 0.251 0.153 0.037 0.147 

Public sector dummy -‐0.120 -‐0.105 0.245 0.137 0.151 0.142 

Tradable industry dummy 0.026 -‐0.010 -‐0.106 -‐0.009 0.002 -‐0.031 

Constant 0.051 0.326 0.467 0.596 0.807 1.133 

N 2608 3590 21451 6639 6901 7019 

Adjusted R-‐squared 0.06 0.13 0.25 0.27 0.29 0.29 

Notes: Bold means statistically significant at 5% or less 

Italic means statistically significant at 10% 

Standard errors are robust and adjusted for clustering 

Table 3b: Determinants of Wage – OLS Estimation Results Specification 2 

Dependent variable: log(hourly wage) 1993 1998 2002 2004 2006 2008 

Primary school degree 0.011 0.037 0.064 0.080 0.101 0.078 

Middle school degree -‐0.097 0.023 0.081 0.089 0.157 0.098 

High school degree -‐0.036 0.182 0.257 0.292 0.320 0.306 

College degree and above 0.175 0.546 0.610 0.630 0.736 0.813 


Years of experience squared 0.000 0.000 -‐0.001 -‐0.001 0.000 -‐0.001 

Male dummy 0.294 0.176 0.190 0.191 0.196 0.214 


Urban dummy 0.073 0.180 0.244 0.140 0.026 0.119 

Public sector dummy -‐0.113 -‐0.103 0.210 0.120 0.137 0.122 


Constant 0.097 0.505 0.613 0.784 1.026 1.402 


Adjusted R-‐squared 0.07 0.14 0.26 0.29 0.31 0.32 



Standard errors are robust and adjusted for clustering 

19

20 

Table 4: Oaxaca-‐Blinder Decomposition of Sources of Wage Growth 

Δlog(wage) 

1993-‐1998 1998-‐2002 2002-‐2008 

% 

contribution Δlog(wage) 

% 

contribution Δlog(wage) 

% 

contribution 

Observed total increase in log(wage) 0.543 0.217 0.933 

Due to increase in base wage 0.275 50.7% 0.141 64.9% 0.666 71.4% 

Due to changes in characteristics 0.028 5.2% 0.024 11.2% 0.023 2.5% 

Years of education 0.014 2.6% -‐0.004 -‐1.8% 0.046 5.0% 

Years of experience 0.003 0.6% 0.136 62.4% -‐0.191 -‐20.5% 

Years of experience squared -‐0.001 -‐0.2% -‐0.091 -‐41.7% 0.124 13.3% 

Male dummy 0.002 0.5% 0.002 0.9% -‐0.001 -‐0.1% 

Ethnic minority dummy 0.000 0.0% -‐0.011 -‐5.1% 0.006 0.6% 

Urban dummy 0.015 2.7% -‐0.035 -‐15.9% 0.007 0.8% 

Public sector dummy -‐0.004 -‐0.7% -‐0.012 -‐5.6% 0.024 2.6% 

Tradable industry dummy -‐0.001 -‐0.2% 0.000 0.2% 0.008 0.9% 

Due to changes in returns to 

characteristics 0.240 44.1% 0.091 41.8% 0.244 26.1% 

Years of education 0.229 42.2% 0.028 13.1% 0.142 15.2% 

Years of experience 0.046 8.5% -‐0.008 -‐3.7% 0.139 14.9% 

Years of experience squared 0.008 1.4% -‐0.028 -‐13.1% -‐0.021 -‐2.3% 

Male dummy -‐0.076 -‐14.0% 0.007 3.1% 0.008 0.8% 

Kinh ethnicity dummy 0.002 0.3% -‐0.021 -‐9.7% 0.022 2.4% 

Urban dummy 0.046 8.5% 0.033 15.1% -‐0.039 -‐4.2% 

Public sector dummy 0.006 1.0% 0.131 60.4% -‐0.042 -‐4.5% 

Tradable industry dummy -‐0.021 -‐3.8% -‐0.051 -‐23.5% 0.035 3.7% 



Table 5: average hourly wage by educational level and institution, 1993 

Public Nonpublic Public/Ratio 

no degree 1.89 1.75 1.08 

primary school 1.85 2.02 0.92 

lower secondary 1.54 1.88 0.82 

upper secondary 1.63 2.01 0.81 

college & above 2.04 1.90 1.07 

Wage ratio (base = no degree) 

no degree 1 1 

primary school 0.98 1.16 

middle school 0.82 1.07 

high school 0.86 1.15 

college & above 1.08 1.09 

Wages are in thousand VND, January 1993 price, deflated regionally and monthly

21 

Table 6: returns to education in public vs. private sectors 

1993 1998 2002 2008 

public private public private public private public private 

primary -‐0.084 0.116 -‐0.002 0.051 0.038 0.068 0.015 0.065 

middle -‐0.165 0.118 0.020 0.066 0.134 0.078 0.076 0.126 

high -‐0.031 0.109 0.145 0.171 0.252 0.216 0.398 0.211 

college 0.251 0.272 0.505 0.875 0.557 0.600 0.764 0.581 

educ_yrs 0.029 0.018 0.053 0.023 0.053 0.019 0.081 0.024 



OLS regressions with robust and clustering adjusted standard errors 

Other covariates (experience, gender, ethnicity, urban, trade) were included but not reported 

Table 7: structure of employment 

1993 1998 2002 2004 2006 2008 

Self employed 73.9% 59.1% 63.9% 60.7% 58.7% 58.3% 

Wage employed 26.1% 40.9% 36.1% 39.3% 41.3% 41.7% 

Public 5.8% 7.1% 9.3% 13.3% 14.2% 13.6% 

Private 20.3% 33.7% 26.8% 26.0% 27.1% 28.1% 

Table 8: Difference in Differences in Differences Estimation 

Dependent variable: log(hourly wage) 

1993 & 

1998 

1998 & 

2002 

2002 & 

2008 

Later year dummy (a1) 0.527 0.171 0.857 

trade (a2) 0.057 -‐0.009 -‐0.143 

public (a3) -‐0.228 -‐0.142 0.168 

Later year * trade (b1) -‐0.131 -‐0.140 0.111 

trade * public (b2) 0.004 0.066 0.137 

Later year * public (b3) 0.135 0.336 0.052 

Later year * trade * public (c ) 0.107 0.061 -‐0.171 

Years of education 0.022 0.036 0.041 

Years of experience 0.021 0.023 0.026 

Years of experience squared 0.000 -‐0.001 -‐0.001 

Male dummy 0.218 0.171 0.176 

Kinh ethnicity dummy -‐0.007 -‐0.307 -‐0.278 

Urban dummy 0.139 0.230 0.217 

Constant -‐0.090 0.317 0.420 



OLS regressions with robust and clustering adjusted standard errors

22 

Table 9: Determinants of Wage -‐ Heckman Estimation Results 

Wage equation (dependent variable = log wage) 

1993 1998 2002 2004 2006 2008 



Years of experience squared 0.000 0.000 -‐0.001 -‐0.001 0.000 -‐0.001 

Male dummy 0.390 0.314 0.219 0.210 0.220 0.244 

Ethnicity minority dummy -‐0.114 -‐0.137 -‐0.387 -‐0.159 -‐0.121 -‐0.146 

Urban dummy 0.226 0.403 0.292 0.192 0.081 0.194 

Public sector dummy -‐0.121 -‐0.100 0.243 0.136 0.148 0.138 


Constant -‐0.606 -‐0.608 0.254 0.378 0.555 0.815 

Selection equation 


Male dummy 0.327 0.345 0.384 0.396 0.360 0.372 


Urban dummy 0.539 0.578 0.457 0.420 0.415 0.369 

Dependency ratio -‐0.033 0.049 0.091 0.068 0.079 0.139 

Log (non-‐wage income) -‐ -‐ -‐0.173 -‐0.205 -‐0.203 -‐0.126 

Dummy for head of household 0.042 0.067 0.053 0.022 0.040 0.038 

Age -‐0.004 -‐0.003 -‐0.001 -‐0.001 -‐0.001 0.000 

Constant -‐1.176 -‐1.268 -‐0.974 -‐1.111 -‐1.121 -‐1.249 


Rho 0.508 0.729 0.206 0.242 0.298 0.327 

Sigma 0.747 0.744 0.679 0.552 0.529 0.597 

Lamda 0.379 0.542 0.140 0.133 0.158 0.195 

Chi2 for Wald test that rho=0 2.25 95.62 29.18 6.95 5.00 3.03 



All regressions have robust and clustering adjusted standard errors

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Appendix A: Data Notes 

25 

The primary source of data is the Vietnamese Living Standard Surveys (VLSS 1993 and 1998, and VHLSS 

2002, 2004, 2006, and 2008). These are all standard World-‐Bank-‐type income and expenditure 

household survey, designed to study living conditions and poverty and inequality issues. They have 

employment modules that produce employment and wage data used in this paper. The earlier rounds 

(VLSS 1993 and 1998) were smaller in size (4,800 and 6,000 households respectively) and were 

representative at the national, rural/urban, and regional levels. The survey year 2002 had the most 

number of households at 29533. For the last there rounds, the number of households stayed constant at 

9189. 

In our empirical work, we include all individuals in the working age (15-‐60 years of age) with reported 

wages. Hourly wage (thousand VND per hours worked) is calculated by dividing annual total wage (main 

salary plus other bonuses and cash benefits) by the estimated number of hours work during the year. 

Only the primary job is counted. Within each survey year, wages are regionally deflated to the January 

of the year using the provided deflators in the surveys (rcpi and mcpi). For year 2002, there are no data 

on experience. So we replace it with the minimum of age-‐17 and age – schooling years – 17. 

Most other papers that use the VHLSS data use the survey’s original schooling year variable, which 

ranges from 0 through 12 years only. In our paper, we adjusted education years for highest educational 

level (a junior college degree means 14 years of education, a college degree 16 years of education, 

master degree 18 years, and PhD 22 years). As a result, average years of schooling that we present are 

higher than that found in most other studies also using the VHLSS. This might also lead to lower 

estimates of returns to schooling years.

Appendix B: Tradable and Non-‐tradable Industry List 

26 

Non-‐tradable industries include industries numbered 37 through 73, 75 through 91, and 93 through 98. 

The rest are tradable industries. This definition is based on examining UN’s COMTRADE data. If an 

industry does not show up in COMTRADE data, it’s considered non-‐tradable. All agricultural, mining, and 

manufacturing (except recycling) industries are in COMTRADE. Most utility and service industries do not, 

except 40 (electricity, gas, and water), 74 (other business activities), 92 (disposable collection and public 

sanitation), and 99 (foreign organization activities). 

industry code 

Agriculture and sylviculture 

01 Agriculture and relating services (including livestock raising) 

02 Sylviculture and relating services 

Aquaculture 

05 Catching and raising seaproducts, and relating services 

mining industry 

10 Coal mining 

11 Oil and gas drilling and related services 

(except: exploring/searching activities) 

12 Uranium and Thorium mining 

13 Metal mining 

14 Mining for rocks, stone, sand, salt, fertilizer... 

Processing industry 

15 Food and beverage production 

16 Tobacco production 

17 Textile 

18 Fur processing and fur products (excluding garments) 

19 Leather tanning and leather products including wallets, seats, 

suitcases 

20 Wood, bamboo, rattan processing and production of wood, 

bamboo and rattan products 

21 Paper and paper products 

22 Printing and publishing (books, magazines, newspapers, and 

23 Coke, crude oil, uranium processing 

24 Chemicals and chemical products 

25 Plastic and Rubber production and products 

26 Other non-metal mineral products production 

27 Metal production and processing 

28 Metal products (except machines and equipment) 

29 Other equipment and machinery not specified elsewhere 

30 Office and computer equipment production 

31 Other electronic, electric equipment not specified elsewhere 

32 Radio, TV, broadcasting and other communication equipment 

33 Medical and laboratory equipment, precision instruments, and meters (clocks) 

34 Motor vehicles and spare parts 

35 Other means of transportation (boats, railroad, airplane) 

36 Furniture production and other productions not specified elsewhere 

37 Recycling, reprocessing

27 

Electricity, gas, and water production and distribution 

40 Electricity, gas, water steam, hot water production and distribution 

41 Water exploitation, purification, and distribution 

Construction 

45 Construction 

trading; repairation of motor vehicles and motorbikes 

private and household tools 

50 Vehicle sales, maintenance and repair; retail sale of gas 

51 Wholesale and agent sales (excluding motor vehicles and motorbikes) 

Retail sales (excluding motor vehicles and motorbikes);repairs of family 

52 appliances 

55 

hotel and restaurant 

Hotel and restaurant (including big and small restaurants, cafe, beverage and 

drink stands,...) 

transportation, warehouse/ storage site, communication 

60 Road, railroad and pipeline transport 

61 Water transport 

62 Airline transport 

63 Services in transport; tourist services 

64 Post and telecommunications 

Finance and credit 

65 Financial intermediary (excluding insurance and social welfare) 

66 Insurance and pensions (excluding social insurance) 

67 Assistance in finance (including social insurance) 

Science and technology activities 

70 Science and technology activities 

Activities relating asset businesses and consulting services 

71 Activities relating real-estate 

Rental of machines and equipment (excluding operators); rental of furnitures 

72 and household goods 

73 Computer-related activities 

74 Other business activities (accounting, tax and other consulting, 

architecture, advertising, protection, housecleaning, photography, packaging, 

etc. 

Government administration and national defense; promulgated social ensurance 

75 Government administration and national defense; promulgated social ensurance 

Education and training 

80 Education and training 

85 

90 

health and social relief 

Health and social relief (hospitals, health centers, veterinary care, social 

relief,...) 

Cultural and sport activities 

Cultural and sport activities (broadcasting, television, cinema, recreation 

and entertainment, press, library, 

museum, sport,...) 

Communist party, mass organizations, professional associations 

91 Communist party, mass organizations, professional associations 

Public and personal services 

92 Disposal collection, public sanitation improvement, and similar activities 

93 Other service activities (laundry, hairdressing, funerals,…) 

housework services provided at client's home

28 

95 Housework services provided at client's home 

Activities of foreign organizations 

99 Activities of foreign organizations

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