1 PEP research project 11029 INTERIM REPORT This version 9 March 2008 GENDER INEQUALITY AND LABOUR MARKET SEGMENTATION UNDER TRADE REFORM: Evidence of the gender wage gap from Vietnam, 1993 2004 Pham Thi Thu Tra & Le Thai Thuong Quan Nguyen Thai Thao Vi Ngo Quang Thanh Abstract In this study, we examine the gendered wage effect of trade reform vis--vis the employment distribution of men and women in the formal and informal labour sector in Vietnam for the period 1993-2004, using a series of household data surveys up to date. We find that the gender wage gap in favour of men persists in both sectors of wage employment. Among other factors relevant for the wage determination, trade openness appears to be a significant stimulus to an increase in individual wages in the period studied, and this effect is slightly higher for women. Our decomposition result reveals that discrimination against women is more prominent in the formal sector, despite a more severe gender gap manifest in the informal sector. For both sectors, our result indicates a narrowing, albeit small, impact of trade on the gender wage gap.
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PEP research project 11029
INTERIM REPORT
This version 9 March 2008
GENDER INEQUALITY AND LABOUR MARKET
SEGMENTATION UNDER TRADE REFORM:
Evidence of the gender wage gap from Vietnam, 1993 � 2004
Pham Thi Thu Tra &
Le Thai Thuong Quan Nguyen Thai Thao Vi
Ngo Quang Thanh
Abstract
In this study, we examine the gendered wage effect of trade reform vis-à-vis the
employment distribution of men and women in the formal and informal labour sector in
Vietnam for the period 1993-2004, using a series of household data surveys up to date.
We find that the gender wage gap in favour of men persists in both sectors of wage
employment. Among other factors relevant for the wage determination, trade openness
appears to be a significant stimulus to an increase in individual wages in the period
studied, and this effect is slightly higher for women. Our decomposition result reveals
that discrimination against women is more prominent in the formal sector, despite a more
severe gender gap manifest in the informal sector. For both sectors, our result indicates a
narrowing, albeit small, impact of trade on the gender wage gap.
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1. Introduction
In the episode of trade liberalization in developing countries, men and women tend to be
influenced differently. The effect of trade liberalization on the gender wage gap and other
gender discriminations however, is unclear, both theoretically and empirically (see
Fontana (2003) for a comprehensive review). Conceptually, the gendered wage impact of
trade is mediated though a number of channels: the changing employment opportunities
in the labour market and the changing earnings position of women relative to men�s. In
this framework, empirical studies reveal evidence of an improved role of women with
respect to both employment conditions and earnings (Pham and Reilly, 2007, Reilly and
Source: authors� calculations from the VLSS 1992/1993, VLSS 1997/1998 and VHLSS 2004.
Note: a. Figures are calculated as a participation rate of the group of interest over the employed people, for men
and women separately.
b. Labour force covers people aged from 15 to 65 years old.
c. Employment is identified as having jobs over the past 12 months
d. Self-employment consists of agricultural self-employment and non-farm self-employment. Informal wage employment is confined to paid work for other households or small household enterprises. These two categories constitute the informal sector.
e. Formal wage employment refers to those employed in formal enterprises of different kinds of ownership. This category is identified as the formal sector.
f. Government sector refers to working for the government and other state organizations.
Table 2 provides detail of the employment picture in Vietnam with indicators of average
hourly wage rates and average working hours on a daily basis. This information is
differentiated into gender participation in each sector. Regarding the allocation of
working hours per day, the average woman devoted approximately 5% less of her time to
work as compared to her male counterpart. This gender difference was small and has
been stable over time across sectors. Whereas men and women seem to contribute equal
time to income-generating activities, but they have been rewarded differently given the
fluctuations in hourly wage rates between the gender groups as shown in table 2. Hourly
wage rate has grown on average at approximately 21% per annum, increasing from
2,120VND to 5,530VND, and from 1,800VND to 4,890VND between the years 1993 and
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2004, for men and women, respectively. This overall improvement in labour earnings
was accompanied by an improved wage position of female relative to male wage
position. As can be seen from table 2, the gender wage gap in favour of men persisted,
though it has been gradually narrowed. As different sectors of employment are
considered, some interesting patterns emerged. First, formal wage earners were better
paid than their informal counterparts irrespective of gender. It is important to note that in
1997 the Vietnamese government commenced the policy on minimum wage for
employees working in Vietnamese formal enterprises. This policy might have certain
implications for the levels of wage in the formal sector. Second, and more strikingly, a
contrary between informal wage employment and formal employment was observed in
the gender wage gap. While women received a better reward in the formal sector, their
position became relatively poorer in the informal sector, i.e. the gap was narrowed from
0.668 to 0.879 for the formal sector, while it was widened from 0.846 to 0.732 for the
informal wage sector.
Table 2. Employment indicators: average working hours/day and nominal hourly wages
The sample size of the VLSS 1992/1993 and of the VLSS 1997/98 amounts to a number
of 4,800 and 6000 households, respectively. The full sample of VHLSS 2004 covers
45,000 households, of which 9,000 households were surveyed in terms of expenditure
1 We note that Vietnam Household Living Standard Survey conducted in 2002 is also accessible. However, we decide to select the three surveys of our main interest. i.e. VLSS 1992/1993, 1997/1998 and VHLSS 2004 to carry out our empirical analysis for the 1993 � 2004 period. While the use of all the four household surveys will not change the essence of our study, it requires much more empirical work. The analysis can be extended to include VHLSS 2002 upon request.
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and income. It should be noted that the two VLSSs construct a panel of 4300 households.
It is, however, unable to link the two VLSS with VHLSS 2004.
Through the three surveys data on employment including earnings are available for all
household members aged from 15 and 65 in the preceding 12 months. Note that this is
not the case for self-employment category. Details of employment information slightly
differ between VLSSs and VHLSS in that the latter survey provides a more specific
classification of employment category.
The individual-level sample is restricted to 7,565 wage earners including 426, 513 and
6,626 for the years 1992, 1998 and 2004, respectively2. We note that information on
earnings is not available for the self-employment category and fairly missing for the
informal category, warning us to interpret the results with some caution.
In the present study, we exploit the information on the main job over the preceding 12
months, noticing that the earnings from the second job on average hold a negligibly small
fraction in total earnings of the individuals. The nominal hourly wages include payment
in cash and kind. The nominal wages are then adjusted to the year 2000 price using the
CPI supplied by GSO. The natural logarithm form of real hour wage rates are
incorporated as the dependent variable in the Mincerian earnings equations. The sample
of wage earners is classified into three categories of employment: formal wage earners,
informal wage earners and government officers. It is necessary to provide further
explanations on this classification, especially with respect to the definition and the scope
of informal wage employment. As recommended by ICLS(2003), informal employment
consists of two groups: informal self-employment and informal wage employment. Given
the insufficiency of the data used, some adaptations are needed for our study. First,
2 Note that, while individual earnings information on the preceding 12-month jobs is abundant in the VHLSS 2004, this is relatively poorer in the two VHLSSs. On the contrary, earnings information on the preceding 7-day jobs was fuller in the two VHLSSs, while it was not at all recorded in the 2004 survey. For the sake of consistency, in our analysis we decided to count on the job over the preceding 12 months, which are available across the three surveys. This leads to a relatively small sample size of the years 1993 and 1998 samples, and thus does not allow us to estimate separate regressions for these two years. We admit that this limitation certainly has an adverse impact on the rigorousness of our empirical results. However, we argue that the earnings impact of trade on will be better captured when taking into consideration the jobs engaged in the whole year rather than the jobs over the preceding 7 days. Pham and Reilly (2007) use the preceding 7-day jobs from the former two surveys and the preceding 12-month job from the VHLSS 2002. While this gives rise to the problem of inconsistency, it remains as a possibility for our consideration in the next stage of the research.
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except for VHLSS 2004, the other two surveys do not allow to differentiate informal self-
employment from self-employment as a whole. As shown from the three household
surveys, self-employment is largely assigned to agricultural activities (see table 2 below),
which are considered to be informal according to the proposed indicators on employment
by Millennium Development Goal 3 (Chen et al., UNIFEM 2005). So, we fit self-
employment in the informal sector alone. Second, informal wage employment is not well
identified from the current surveys in that we do not have detailed information on
different types of contract workers (employees of informal enterprises, casual or day
labourers, temporary or part-time workers, paid domestic workers, unregistered or
undeclared workers, called homeworkers). For this reason, we categorize �work for small
household enterprises� (in VLSS 1997/1998), and �work for other households� (in the
VHLSS) as informal wage employment. Although this categorization may be somewhat
ad hoc, it is drawn from the ICLS�s (1993) consensus which refers the informal sector as
employment and production that takes place in small and/or unregistered enterprises.
Third, in the VLSS 1992/1993, working for other households is merged in the same
group with working for private enterprises. As a matter of fact, the number of private
enterprises was reckoned to be very small in the period 1992/1993. Therefore, we claim
�working in private company/household� in the VLSS 1992/1993 as pertaining to
informal employment. Fourth, while employment in the government sector captures a
considerable share in the labour market in Vietnam, its connection to trade reform may be
limited. Moreover, significant gender wage disparities were not found within the
government sector in the previous studies using the data from VLSSs (Liu, 2004a).
Finally, the government sector was treated as a special type of employment according to
the VHLSS 2004 survey and thus precluded from the formal labour work. To make it
compatible among the three surveys, we therefore exclude individuals employed in the
government sector in the two earlier surveys.
Model specifications.
In an attempt to identify the effect of trade on individual earnings, we adopt an extended
Mincerian earnings equation, which controls for various determinants of earnings
including individual endowments, geographical and regional attributes and industry
affiliations. By convention, individual endowments such as age, marital status, education,
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working experience, household headship and migrant status are included in the earnings
model. Following Pham and Reilly (2007), Reilly and Dupta (2006), we use a set of
educational dummies rather than years in schooling to capture human capital effects.
Indicators of completion of primary school, secondary, high school and higher education
are constructed with the reference group of individuals who are illiterate or without any
schooling. To proxy for labour market experience, we use both age and its squared term,
and also working experience and its squared term. As in Pisani and Pagan (2004), we
argue that indicators of regional residence may also influence earnings and therefore
include a set of seven regional dummies in the earnings models. Further, indicators for
industry affiliation of individuals are introduced to control for industry-fixed effects.
Finally, year dummies are incorporated to capture the impact of other economic policies
than trade on individual earnings.
The standard Mincerian wage equations are then augmented with the inclusion of trade
variable L to capture the impact of trade on sectoral wages. Though some argue that in
developing countries employment responses to trade policy are greater than wage
responses (Goldberg and Pavnick, 2004), this remains as a strong assumption. Thus, it is
reasonable to consider the effect of trade in wage equations, making it possible to detect a
link between trade and the gender wage gap in the next empirical application.
A critical concern in the estimation of earnings is attributed to the choice of individual
between different sectors of employment. Econometric techniques can be used to correct
for self-selection, and appear to be most effective if identification of the selection
equation is achieved by the inclusion of one or several variables that affect the choice of a
certain sector, but not the sectoral earnings. In this framework, the probability of working
in a certain sector will be first estimated, assuming that an individual chooses the sector
which maximizes their utility. The resultant coefficients from this selection equation are
then used to compute the inverse of the mills ratio term for inclusion in the earnings
equations. While a few studies on gender pay gap for Vietnam apply this two-step
procedure and find a significant selection effect in regard to female earnings estimates
(Liu, 2004ab), others argue that the use of self-selection correction techniques is highly
sensitive to distributional assumptions and to the choice of appropriate instruments
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(Rama, 2001, Pham and Reilly, 2007). Following the latter argument, we resign from a
selection correction procedure in this paper3.
Measures of trade openness
In pursuit of identifying the impact of trade on individual earnings, we introduce a set of
trade variables L in both the Mincerian equations to proxy for trade openness. As a
phenomenal problem in the trade literature is pertaining to the lack of a clear definition of
what is meant by �trade openness�, there is little consensus on the measures of trade in
existing empirical studies (Yanikkaya, 2003). Broadly, trade openness measures can be
divided into two categories: measures of trade volume and measures of trade restrictions.
While the former mostly refers to the ratios of exports plus imports to GDP, the import
penetration ratios, and export shares in GDP, the latter contains tariff rates, export taxes,
total taxes on international trade and indices of non-tariff barriers. Not only does each
trade measure encounter its own problem, it also provides different implications to the
issues studied. Trade volume is a standard measure and often suffers from criticism,
which argues that a highly open economy may well be accompanied by export subsidies
and/or by trade barriers to protect its import sector. From a policy point of view, a
comprehensive form of trade barriers appears to be ideal in ascertaining the impact of
trade policy (Yanikkaya, 2003, Harrison and Hanson, 1999 among others).
Unfortunately, such as a measure is hardly available for developing countries. Moreover,
for the context of Vietnam the heavy use of non-tariff barriers as a substantial trade
restriction during the early nineties may weaken the effectiveness of tariff rates as a
proxy of trade liberalization (Pham, 2007). At the current stage of this study, we are
therefore confined to the use of trade intensity ratios as an indicator for trade openness in
our empirical applications. Two proxies for trade openness will be in place. The first
proxy refers a standard measure of the degree of openness - the share of exports and
imports as a percentage of GDP at the provincial level. Although this ratio is warned as a
�loose� measure of trade liberalization, it does reflect trade intensity, which is believed to
have an impact on labour earnings as reported in other studies on the gender pay gap
(Oostendorp, 2002). We adopt this measure while allowing for some caution with result
3 As a matter of fact, we re-estimated the Mincerian earnings equations using the Heckman selectivity correction and found no evidence of significant selection-bias
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interpretations. Regarding the level of trade exposure captured by this trade index,
another limitation of this proxy arises because earnings are estimated at the individual
level while trade intensity is measured at an aggregate level � the provincial level.
The second proxy of trade openness is accordingly derived from the first proxy, aiming to
translate the impact of trade, which occurs at macro level, into the effect of trade on
wages and employment decision at the individual level. In this way, we construct trade
indices at the commune level � the lowest administrative level, using the information on
exports, imports and GDP at the provincial level. We argue that the level of trade
exposure for individuals/households should be adjusted according to the relative
contribution of each commune to the provincial trade performance4 .
The provincial aggregated export (import) over GDP data are, therefore, adjusted to the
commune level, generating two trade openness indices: rural trade openness index rcT
for rural communes and urban trade openness index ucT for urban communes.
(1)
1
p pr cc C
pc
i
EX IMQT
GDPQ
(2)
1
p pu cc C
pc
i
EX IMET
GDPE
where cQ is the output value of all farming activities at commune c; C is the
number of communes in province p; pEX , pIM , GDPp are aggregate values of export
import, and GDP of province p. rcT is the trade exposure adjusted by the agricultural
output weight at each rural commune. cE is the number of people working in tradable
sectors in each urban commune; and ucT is the trade exposure adjusted by the employment
weight of each urban commune.
The use of this proxy rests on the assumption that individuals are tied to their commune
to make contribution to their provincial trade performance. As such, labour mobility is
4 Pham (2006) suggests to combine the tariff data and the household surveys to construct a proxy of trade exposure the commune level. The nationally aggregate sectoral tariff data are, therefore, adjusted to the commune level, generating two trade openness indices: agricultural openness index and nonfarm openness index. In our application, trade intensity is used rather than trade restrictions, and similar weights as used by Pham are applied here.
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assumed to be minimal across communes. Despite this strong assumption, the trade
indices as applied appear to be a practical choice for the surveys 1997/1998 and 2004
given the coverage of a reasonably large number of communes in the three surveys, 150
communes in VLSS 1992/91, 156 communes in VLSS 1997/98, and 3081 communes in
VHLSS 2004.
5. Empirical Results
Wage equations
Given the two employment outcomes of our interest, i.e. formal vs. informal
employment, we carry out the estimation for each sector separately. Note that the
estimation of the pooled sample of both gender groups (not reported here) for both
sectors indicates that the sectoral dummy is significant. Informal wage earners in general
earn 10% less than their peers employed in the formal sector. The results for the pooled
sample of each gender group with respect to both proxies of trade are presented in table
3.
We first examine the effects which are reported as the most relevant in determining
individual earnings. We notice a significant wage differential between men and women
across both sectors of employment. Indeed this wage differential appears to be more
pronounced in the informal sector where men earn approximately 30% higher then
women while this figure is 10% in the formal sector. This finding is consistent under both
trade measures used.
The effect of age is evident and significant in most estimation. Apparently, age and its
squared term describe the expected inverted-U shaped relationship between wage rates
and the human capital attribute. An exception is accredited to female earnings equation in
the formal sector, where the impact of age follows the same pattern but appears to be
insignificant. Unlike the effect of age, reward to working experience is only significant in
the formal sector, indicating experience as an important criterion in wage determination
in this sector. The returns to experience, however, appear to be relatively low for both
males and females. For instance, an increase of one year in working experience only
offers a rise of approximately 4% in the wage rate. This finding is also found by other
studies on Vietnam gender pay gap (Liu, 2004ab and Rama, 2001).
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An interesting finding emerges as regards to returns to education. For both men and
women employed in the formal sector, returns to education appear to be significantly
higher at more advanced levels of education, i.e. completion of high school and
completion of higher education. For the informal sector, low levels of education are also
found to be significant, especially for women. While the evidence of an increased returns
to education is not surprising as it is also documented by other studies for Vietnam (Pham
and Reilly, 2007, Nguyen et al, 2006, Liu 2004ab), this finding highlights an interesting
divergence in returns to education between the two sectors of employment across gender
groups. Although education attainment is higher for both men and women in the formal
sector than in the informal sector, discrimination against women is manifest only in the
formal sector, where reward to education is in favor of men. Men are reported to earn
approximately 10% ceteris paribus higher than women of a comparable level of
education. By contrast, educated women are more appreciated in the informal sector
given a pay premium of 24% over men.
Table 3 also reports evidence of the role of regional attributes on labour earnings. Across
estimations, variations in earnings describe a geographical pattern in which workers in
the south on average earn more than in the centre and the north of Vietnam, irrespective
of sector of employment. As a matter of fact, this finding is consistent with a popular
stylized fact in Vietnam, and also well confirmed by previous studies (Pham & Reilly,
2007, Liu, 2004ab). Similar to the regional effect, the impact of industry affiliation
appears to be exciting. It should be noted that non-tradable sectors including construction
and services are taken as the reference group in our estimation. For men, manufacturing
and food processing sectors are among the most well paid in the formal sector, while at
the same time these sectors absorb the highest share of male workers. Agriculture and
textile sectors, as commonly observed, offer a relatively lower wage to male workers. A
different story applies for women, as only is the negative effect of industry affiliation
evident. This finding implies that women less from trade when employed in the tradable
sectors, as also suggested by Nicita and Razzra (2003) for Madagascar, and by Paul-
Majumder and Begun (2000) for Bangladesh. In particular, textile and food processing
industries are found to be attached with a lower pay in both sectors of employment.
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Table 3. Regression results of earnings for gender and sector of employment Dependent variable: the natural log of real hourly wage. The estimates based on the first proxy of trade are presented in the first four columns, and the last four columns refer to the estimates with the second proxy of trade
Formal Informal Formal Informal Male (1)
Female (2)
Male (3)
Female (4)
Male (5)
Female (6)
Male (7)
Female (8)
Individual endowments Marital status -0.0273 -0.1015 -0.0666 0.0326 -0.0218 -0.1158 -0.0518 0.0437 (0.0478) (0.0372)*** (0.0358)* (0.0498) (0.0542) (0.0404)*** (0.0357) (0.0508) Age 0.0249 0.0002 0.0388 0.0540 0.0261 0.0110 0.0404 0.0661 (0.0116)** (0.0124) (0.0081)*** (0.0140)** (0.0132)** (0.0138) (0.0085)*** (0.0154)*** The squared term of age -0.0003 0.0000 -0.0005 -0.0007 -0.0004 -0.0002 -0.0005 -0.0009 (0.0001)** (0.0002) (0.0001)*** (0.0002)*** (0.0002)** (0.0002) (0.0001)*** (0.0002)*** Migrant status -0.0259 -0.0158 0.0184 0.0467 -0.0182 -0.0364 0.0519 0.1051 (0.0571) (0.0513) (0.0707) (0.1051) (0.0754) (0.0580) (0.0783) (0.1114) Household headship -0.0107 -0.0805 -0.0497 -0.0001 -0.0027 -0.0728 -0.0468 -0.0217 (0.0322) (0.0401)** (0.0325) (0.0779) (0.0401) (0.0560) (0.0345) (0.0870) Working experience 0.0387 0.0374 0.0031 -0.0153 0.0399 0.0324 0.0034 -0.0190 (0.0065)*** (0.0069)*** (0.0062) (0.0120) (0.0078)*** (0.0080)*** (0.0061) (0.0124) The squared term of working experience
The results also indicate that marital status profoundly reduces female earnings in the
formal sector, while this does not apply in the informal sector. It is interesting to note that
although this factor is reasonably assumed not to be related to labour productivity (Liu,
2004a), it turns out to be a determinant in wage determination of the formal sector. This
may give rise to an additional warning on discrimination in the formal sector. Consistent
with other studies on Vietnam, we do not find evidence for the effect of migrant status
and household headship on earnings.
We turn now to examine the impact of trade openness on individual earnings in both
sectors of employment. Measured by the percentage of export plus import over GDP at
the provincial level, trade openness is shown to have a gendered effect in the period
studied. Irrespective of sector, the results indicate that greater openness is associated with
higher wages, evident from significant coefficients in estimations for both gender groups.
For example, in the formal sector, 1% markup in the trade index corresponds to a rise of
7.1% and of 7.6% in male and female earnings, respectively. Regarding the informal
sector, the positive effect is, however, rather marginal and moderately significant, i.e. an
increase of 2.7% and of 4.4% in the wage rates for males and females, respectively. As
the second trade proxy, i.e., the commune adjusted trade index, is applied, the trade effect
on informal earnings is no longer significant, though has the same sign. The reported
coefficients also reveal a difference in gendered response to trade openness. Slightly
higher coefficients attached with openness in female earnings equations give a rough
indication of a narrowing effect of trade on gender wage disparity. This finding seems to
support the hypothesis on trade premium skills (Greenaway and Nelson, 2000), and needs
to be further examined by a decomposition analysis.
Decomposition analysis
Given the estimated wage distributions, we decompose the wage gap to investigate
whether the wage differentials are caused by wage discrimination, or from a disparity in
skill endowments between men and women in each sector of employment. To do so, we
follow the conventional decomposition Blinder-Oaxaca (1973) approach, which has been
commonly used in wage gap studies. This approach isolates the wage gap not explained
by endowments but by a difference in endowments� rewards � the so-called �treatment effect�. Let wm and wf be the means of the natural logs of male (m) and female ( f ) wages.
The wage gap can be written as:
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m f m m f m f fw w x x x (3) for male structure wage
f m f f m f m mw w x x x (4) for female structure wage
where mx and fx
are vectors containing the means of independent variables
(��endowments��) for males and females, respectively, and m and
f are the
estimated coefficients from the regressions shown in table 3. The first term on the right-
hand side in both equations is the part of the wage gap that is attributable to differences in
endowments; the second term is the part attributable to differences in returns to those
endowments. It is essential to note that this approach provides both the aggregate
decomposition and the detail decomposition for each group of variables, including trade
variables5. In this way, this allows us to detect the impact of trade on gender wage gap.
Table 4 presents decomposition results separately for the formal and informal sector of
employment. Since both proxies of trade provide similar results, our analysis is focused
on the decomposition attached with the first trade measure. As earlier noted, the gender
wage gap is more severe in the informal sector than the formal sector. Viewed in the
framework of Becker�s hypothesis (1971), this outcome in part reflects a relatively high
taste-biased tendency due to the surplus of working females in this sector. It is also
evident that the gender gap is largely explained by treatment effects rather than
endowment effects across sector. Further, endowment differences are more noticeable in
the informal sector than in formal sector, suggesting that more standardized employment
qualifications are applied in the formal sector while low-skilled labors are dominant in
the informal sector. Strikingly, discrimination appears to be more pronounced in the
formal sector, capturing 93.5% the gender gap in the formal sector, while it contributes to
84.5% to the gap in the informal sector. Liu(2004a) arrived at similar evidence of
discrimination against women in both private and state formal sectors for the year 1998�s
data; and argues that the wage distributions of the state formal sector should be
interpreted with caution due to the lack of factors unrelated to human productivity, i.e.
5 We acknowledge a typical drawback of this decomposition method � the index problem as the use of both the male and female wage structures may produce different results
24
institutional attachments, but apparently relevant in wage determination of this sector.
The same reasoning can also be applied here.
Table 4. Blinder-Oaxaca (1973) decomposition of the gender wage gap
Formal Informal Formal Informal
(1) (2) (3) (4)
Wm (predicted male wage in log points) 1.522 1.172 1.410 1.148
Wf (predicted male wage in log points) 1.414 0.823 1.325 0.806
Explained gap 10.8 34.9 8.5 34.2
Endowment effect 0.7 5.4 0.3 6
Of which trade -0.7 -0.2 -0.4 0.1
Treatment effect 10.1 29.5 8.2 28.2
Of which trade -0.4 -1.1 0.0 1.5
Note: a. Positive number indicates male advantage while negative number indicates female advantage b. The first two columns and the last two columns correspond to the first and the second proxy of trade,
respectively. Our foremost concern is to discern the effect of trade on the gender wage gap. The
decomposition analysis shows that trade openness has a role in narrowing the gender
wage gap in both sectors, as evident from the negative signs attached with both
endowment and treatment effects of the trade variable. Trade exposure by women is
comparatively higher than by men, captured by a difference of 0.7 points and of 0.2
points in the formal and informal sector, respectively. Perhaps this reflects a relatively
high participation rate of women in export-driven activities, which are more likely to take
place in the formal sector under the era of trade reform (Kabeer et al., 2005). At the
same time, women also seem to marginally benefit from a higher trade exposure given a
slightly higher return to trade. This outcome is more strongly observed in the informal
sector. Arguably, an increase in the returns to trade exposure of females relative to that of
males can be a reflection of a rise in low skilled premium prompted by trade as predicted
by the Heckscher- Ohlin model. It is, however, important to note that the narrowing
impact of trade as detected is rather moderate, especially for the formal sector. While the
modest role of trade may be a result of trade proxies we use in the analysis, it signals that
trade openness seems to lessen, albeit at a limited extent, the severity of discrimination,
25
which is found to be essential to explaining the gender wage gap in both formal and
informal labour sector.
6. Conclusions and Remarks
Vietnam�s labour market is overwhelmingly characterized by the existence of the
informal sector, in which women are overrepresented. There has been a contraction of the
informal labour sector in the period 1993 � 2004 in contrast to a growth of the formal
labour sector. In both sectors of wage employment, men are reported to earn more than
women during this period, and the gender wage disparity persists with a wider gap
observed in the informal sector.
In this paper, we identified relevant factors in wage determination in each sector of wage
employment for each gender group. We found that education, age and labour market
experience are strong endowments driving individual earnings in both sectors. Other non-
related labour productivity characteristics, e.g. marital status, are relevant in wage
determination for the formal sector, but not for the other. In addition, regional attributes
and industry attachments are also found to be important. The impact of these factors,
however, varies between the sectors, especially concerning the returns to the endowment.
Nepotism against women is observed in the formal sector in rewards to education and to
working experiences. With respect to trade, we found that trade openness is a significant
stimulus to an increase in individual wages in the period studied, and this effect is slightly
higher for women. Our decomposition analysis suggests that treatment effects appear to
play a larger role in contributing to the gender wage gap than endowment effects. This
holds for both sectors. However, evidence of discrimination is more prominent in the
formal sector, despite a more severe gender gap in favor of men manifest in the informal
sector. For both sectors, our results indicate a narrowing impact of trade on the gender
wage gap. We argue that, this effect, albeit small, reflected in a difference in trade
exposure faced by working men and women, rather than by a divergence in the return to
trade exposure.
In line for the next stage of our study, it is necessary to put forward a few important
remarks. First, the use of current trade measures is subject to certain suspicion as
mentioned in the paper. Therefore, in the next application we attempt to seek an
alternative trade measure, e.g. adjusted-tariff data, to apply for our empirical analysis.
26
Second, our research aims to investigate gender inequality along its broad dimensions.
Apart from employment opportunities and the wage dimension, we pursue to ascertain
another important pattern of gender inequality, i.e. unpaid care work. We are interested
in discovering changes in the allocation of unpaid care work between men and women
and in examining to what extent these changes are mediated through trade reform. We
will carry out this analysis in the next stage of our research. Finally, we will draw policy
implications to gender inequality based on the main empirical findings of our analysis.
27
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