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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.
2
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
Dutta, 2006, Fleck, 2001, Standing 1999, Pearson, 1999 etc.). Alternatively, other studies
report evidence of a widening gender wage gap under trade reform (Nicita and Razzar,
2003, Paul-Majumder and Begum, 2000). While empirics on the trade - gendered
earnings linkage is abundant and mixed, it has been silent on the pervasiveness of the
informal labour sector, which notably characterizes the labour market in developing
countries. As a result, the linkage between the gendered earnings effect of trade and
labour market segmentation appears to be under researched.
Vietnam was one of the countries that embarked on significant economic reforms over
the past decades. One of the key reforms is to initiate and expand trade liberalization. In
the period 1990 � 2004, Vietnam witnessed an impressive growth of more than 7% in
GDP and of approximately of 19.3% and 13% in export and import, respectively (see
table A1). This outcome was a result of a more outward looking trade policies
accompanied by various export promotion measures. Concerning tariff evolution,
customs tariffs were first introduced in 1988, and the number of tariff lines and tariff
rates increased (table A2). It is also documented that the average effective rate of
protection (ERP) for the �tradable� sectors experienced a considerable decline while there
has been a marginal reduction of the nominal rate of protection (NRP) in the 1992 � 2003
period (Pham, 2007). Although the tariff reductions were not significant by international
standards, the substantial removal of non-tariff barriers marked a remarkable step in the
process of trade liberalization in Vietnam.
3
Vietnam�s labour market also underwent impressive changes in the period 1993-2004 As
in other developing countries, the informal labour sector captures a dominant share of
employment. This share has declined from 90% to 82.81% between the years 1009 and
2004. The active role of women in the overall labour market is widely acknowledged,
given a rising participation rate of women in economic activities (see section 4 below).
Women constituted 45.07% of total labour force in Vietnam in the year 1993 and this
figure increased to 50.35% in the year 2004. This trend was accompanied by a rise in
women�s earnings relative to men over the period 1993 � 2002 (Pham and Reilly, 2007).
Within the formal wage employment, earnings disparity seems to persist over the period
and is largely attributable to the within-sector differences rather than between-sector
differences (Liu, 2004a). Another remarkable observation is ascribed to the over
presentation of women in the informal labour sector. In the period 1993-2004, in spite of
a declining share of the informal sector, the participation rate of women in this sector
remains as high as around 86% over the period. Despite certain benefits of the informal
sector, it is evident for developing countries that the informal sector is often associated
with �lower quality� jobs and thus lower earnings as compared to its formal counterpart
(Goldberg and Pavnick, 2003). In Vietnam informal female workers are reported to earn
less than their male counterpart, and this disparity seems to grow (see table 2). As a
result, the incidence of the large informal labour sector is expected to provide certain
gender implications to an analysis of gender wage inequality under trade reform. This
issue has not, however, been empirically examined for the context of Vietnam, and thus
clearly merits further empirical considerations.
There are a number of theoretical arguments as to why trade reform has a different
impact on gendered earnings and hence on gender wage gap. Trade reform may lead to a
contraction in the gender wage gap as labour market discriminations are eventuated as a
response to increasing competitive forces induced by trade liberalization (Becker, 1971).
This taste-based approach suggests an improvement in earnings of women of comparable
skills to men, narrowing the gender wage gap. In addition, a conventional trade theory,
based on the Heckscher-Ohlin model, points to the factor-price equalization effect of
trade, which results in a relative increase in wages of unskilled labour as compared to
wages of skilled labour. This effect may advantage women and accordingly lower the
4
gender wage gap since women are often over presented in the lower-wage, lower-skilled
jobs than men.
An alternative argument by Greenaway and Nelson (2000) emphasizes that trade may
result in a premium on skills due to the increasing demand for high-skilled labour in the
era of constant technology changes and globalization. The bargaining power of high-
skilled labour will then rise while that of low-skilled labour may not. Given that in
developing countries the average man has a higher level of labour market skills and does
the average woman, this skill-favourable scheme may widen the gender pay gap. Linked
to the incidence of the informal sector under trade reform, it is commonly acknowledged
that an influx of unskilled labours, which is largely comprised of women, into the formal
wage employment, especially the export-oriented industries, could intensify the gender
wage gap towards women disadvantage. With respect to the impact of trade featured in
the informal sector of employment, Goodfriend and McDermott (1995) claim that the
informal sector is likely to absorb the negative effects of trade expansion. Trade
liberalization results in market expansion, leading to a larger scope for specialization and
inducing gains from specialization. Accordingly, production from households � the
informal sector, will be shifted towards specialized firms � the formal sector. Wages in
the formal sector will be increased more than the value of household�s labour marginal
product. Given the overrepresentation of women in the informal sector, the gender wage
gap tends to be more severe under trade reform.
In this paper, we examine the gendered earnings effect of trade liberalization vis-à-vis the
segmentation 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 for Vietnam, we
particularly investigate to what extent trade reform will exert an earnings effect on both
gender groups given their participation in the formal and informal labour sector. The first
aim of this study is to discover characteristics that are relevant for explaining the earnings
position of women relative to that of men under the era of trade liberalization. The second
aim is to distinguish the gender earnings differentials between the sectors of employment
and accordingly detect the impact of trade in each sector, using decomposition
techniques. Our empirical examination will therefore provide further insights into gender
implications of trade reform in Vietnam.
5
The paper proceeds as follows. In the next section, we review some related empirical
literature on the gender wage gap. In section 3, we highlight some stylized facts on
gender issues in relation to the labour market in Vietnam. The discussion on data and
methodology will be presented in section 4, which is followed by section 5 with a
discussion on empirical results. We conclude the paper with some remarks in section 6.
2. Literature review
There is a growing empirical literature that explores the relationship between trade and
gendered earnings in developing countries. Evidence on the topic, however, remains
inconclusive with respect to both trade measures used and the employment context
investigated.
Using a sample of both developed and developing countries, Oostendorp (2002) found a
negative association between trade openness , which is measured as the share of export
plus import over GDP or the share of foreign direct investment net inflows of GDP), and
the size of gender wage gap within occupational groups in the years 1983 � 1999. This
empirical finding, however, does not explicitly attribute the narrowing effect as
pertaining to an effect in male or female earnings. Santos and Arbache (2005) examined
the gender wage gap for Brazil in the period 1982 � 1999, using an alternative measure of
trade openness � a transformation of sectoral tariff rates. Their empirical analysis points
to a conclusion that increasing openness is associated with narrowing wage gap, which is
largely mediated through a relative decline in men�s wages.
A few other studies discern the gender wage effect of trade with a particular interest in
possible variations of such effects across different industries. For the case of Mexico,
Artecona and Cunningham (2002) found that the residual gender wage gap over the
period 1987-1993 declined more intensively in concentrated industries than in non-
concentrated industries. Alternatively, based on the same dataset, Ghiara (1999) proved
that the wage differential increased substantially in the manufacturing sector, mainly due
to changes in endowments of human capital between women and men. The study reports
that these changes were not observed in the non-tradable sectors, however. Evidence
found by Fleck (2001) further confirms that trade impact varies greatly between
industries.
6
The adverse effect of trade on labour earnings has also been broadly documented in
studies of the gender pay gap. Nicita and Razzar (2003) analyzed the extent to which the
poor benefit from trade liberalization, which is notably reflected in the growth of the
export-led sector in Madagascar. While the key empirical finding of their study suggests
a rise in the income of poor household as a result of export-driven growth, it also
indicates that the benefits are adversely distributed towards female workers, who appear
to gain less from trade expansion. In Bangladesh, Paul-Majumder and Begum (2000)
showed a similar picture of trade expansion manifest in the export-led industry. An
increase in the gender gap in favour of men is mainly because males are increasingly
employed in the skilled jobs while female workers are driven out from that job and
concentrated more and more in low-skilled jobs.
In pursuit of the trade-gender linkage inducted in the Vietnam�s context, the empirical
literature to date has remained modest, although studies on gender inequality have been
growing. Liu (2004a, 2004b) examined gender inequality vis-à-vis gender earnings gap in
Vietnam. In the former study, she considered the heterogeneity across the state and
private sector in relation to gender wage gap and concluded that within-sector differences
contribute more than between-sector differences in explaining the gender earnings gap.
The latter study analyzes the decomposition of earning differentials across time: between
1993 and 1998. This study reveals some evidence of a wage disparity between male and
female workers in Vietnam and attributes this disparity to an adverse change in
discrimination. The findings of both Liu�s studies are interesting but indifferent toward
the presence of trade liberalization in Vietnam. In a field study on female workers in the
garment sector, Kabeer and Tran (2006) characterized working conditions of and
problems faced by women employed in this sector in 2001. They concluded that women
were crowded into the garment industry as a path out of rural poverty as other sectors are
not open to them. While this finding helps clarify the employment status of women and
necessitate policies for a sustainable employment solution for women, it does not
exclusively address the impact of trade on gendered employment and earnings. Using
individual and household data obtained from VLSS 1992/1993 and 1997/1998, Rama
(2001) pinpointed a sharp decline in the gender pay gap, and attributed this decline to the
effects mediated through the economic reforms under Doi Moi. Pham and Reilly (2007)
7
offered further insights into a sizable contraction in the gender pay gap by examining the
degree to which the gender pay gap varies across the conditional wage distribution. The
key results point to stability in the gender pay gap in most wage distributions over the
period 1993-2002, and assign this stability to much of the effects exerted by the
economic reforms in Vietnam. Like Rama (2001), Pham and Reilly (2007) were not able
to distinguish components of Doi Moi, which may be accountable for an improved wage
position of women. A very recent study by Nguyen et al. (2007) examined the impact of
trade liberalization, which is measured by sectoral trade intensity, on gendered earnings
and on returns to education in particular. Consistently with previous studies on Vietnam,
Nguyen et al. (2007) reported a contraction in the gender wage gap and associated this
contraction with export-driven changes in female labour demand rather than with import-
driven changes in competition. In addition, the study reveals that the returns to education
have increased, but the increase in the returns to education cannot be explained by
increases in trade openness.
Admittedly, these studies do not provide conclusive evidence of the relationship between
trade and the gender pay gap. Moreover, has none of the existing studies examined the
trade-gendered earnings linkage intersected with distinctive features of the labour market
in developing countries, notably the incidence of the informal sector, under the presence
of trade liberalization. Further empirical investigations on this field for Vietnam as a
developing country case are therefore clearly warranted to grasp a better understanding
on the nature of the relationship between trade and gender pay gap.
3. The Vietnam�s labour market: gender and sectoral distribution of employment
In this section, we highlight some issues relating to Vietnam�s labour force participation
and segmentation in the period 1993 � 2004. We also compare some key employment
indicators between different categories formed by gender and sector.
Vietnam�s labour market is characterized by a high participation rate among both men
and women as shown in table 1. Different patterns in the changes of gender-specific
participation rates emerged in the period, with an increase in the participation rate of
women from 79.34% to 80.28% between the years 1003 and 2004. Table 1 also depicts
the dynamics of the labour market, differentiated into sector of employment and gender.
8
In terms of sector, self-employment represented a largest component of Vietnam�s labour
market. The share of self-employment, however, exhibited a contraction over this period,
i.e. from 79.95% in 1993 to 68.98% in 2004. By contrast, the shares of formal wage
employment and of informal wage employment were both increased. A rise of formal
wage employment from 2.44% of the labour force in 1993 to 16.69% in 2004 was
indicative of a remarkable growth of the formal labour sector in Vietnam during this
period. This outcome seems to accords with the introduction of the new Enterprise Law
enacted in 1999. On the other hand, the development of the informal wage sector was
inclined with the prosperity of household enterprises in the period studied (Vijverberg
and Haughton, 2002). The shares of men and women in the labour force also describe
some interesting patterns across sectors. Self-employment category was constantly
marked by the active role of women, except for the year 1998. In contrast, women were
less active than men in the category of informal wage employment, evident from a lower
share of women relative to that of men. Moreover, this category also exhibited a falling
share of female labours, in contrast to a steady extension of male labours. A similar trend
was observed with respect to formal wage employment, though the lowest proportion of
women was exhibited in the year 1998 and increased in the year 2004. Not surprisingly,
women appeared to be less attached to and/or less chosen to join the formal sector as
compared to men. So, although women have been actively involved in the Vietnam�s
labour market under the era of economic reforms, the majority of working women was
absorbed in self-employed jobs. This outcome gives an indication of gender employment
disadvantage, as also pointed out by other studies (Kabeer et al. 2005).
9
Table 1. Labour force participation and labour force segmentation 1993 - 2004
1993 1998 2004
Aggregate Male Female Aggregate Male Female Aggregate Male Female
Labour force participation (%)
81.24 83.38 79.34 79.62 80.83 78.52 81.78 83.31 80.28
Labor force segmentation by gender (%)
Overall - 48.21 51.76 53.48 46.52 50.23 49.77
Self-employment 47.16 52.84 51.91 48.09 44.99 55.01
Informal wage employment 59.43 40.57 62.24 37.76 68.43 31.57
Formal wage employment 51.92 48.08 63.35 36.65 56.27 43.73
Labour force segmentation by sector (%)
Self-employment 79.95 78.16 81.63 72.12 70.00 74.56 68.98 61.78 76.25 Informal wage employment 13.16 16.21 10.32 10.59 12.32 8.59 14.34 19.53 9.09
Formal wage employment 2.44 2.62 2.26 8.70 10.30 6.85 16.69 18.69 14.66
Public sector & others 4.45 3.01 5.79 8.59 7.37 9.99 - - -
100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
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
10
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
Working hours/day
Nominal hourly wage rate (1000VND)
1993 1998 2004 1993 1998 2004
Male 7.042 7.966 7.16 2.115 5.292 5.525
Female 6.611 7.546 6.809 1.796 4.673 4.887 F/M Ratio 0.939 0.947 0.951 0.849 0.883 0.885
Self-employment Male 6.801 8 6.616 - - -
Female 6.467 7.22 6.485 - - - F/M ratio 0.951 0.903 0.980 - - -
Informal wage employment Male 8.317 8.115 8.135 2.266 5.553 4.265
Female 7.781 8.027 7.725 1.917 4.253 3.122 F/M ratio 0.936 0.989 0.950 0.846 0.766 0.732
Formal wage employment Male 6.707 8.275 7.941 1.956 6.149 6.837 Female 6.573 8.254 7.901 1.306 5.34 6.009 F/M ratio 0.980 0.997 0.995 0.668 0.868 0.879
Source: authors� calculations from the VLSS 1992/1993, VLSS 1997/1998 and VHLSS 2004. Note:
a. Hourly wage rate includes all payments in cash and kinds.
b. F/M ratio is an indication of the relative position, measured as the ratio of average female wage (working hour) to that of male counterpart.
11
In sum, the foregoing descriptive analysis points to a contraction of the informal sector,
and on the contrary a growth of the formal sector in Vietnam�s labour market in the
period 1993 � 2004. In both sectors of wage employment, men were reported to earn
more than did women during this period. While the differential was narrowed in the
formal sector, it was substantially widened in the informal sector, implying a relatively
poorer position of women in informal employment along the Doi Moi also noticed by
Kabeer (2005). A question remains as to what extent the divergence in the gender pay
gap across sectors can be explained using empirical models, which account for the
presence of trade interlinked with gender and sector of employment.
4. Data and Model specification
Data descriptions
The paper makes use of several sources of available data. The major source of data refers
to the three household surveys, two Vietnam Living Standard Surveys (VLSS,
henceforth) conducted in 1992/1993 and 1997/1998 and the Vietnam Household Living
Standard Survey (VHLSS, henceforth) conducted 20041. Another source of data from
General Statistics Office of Vietnam offers information on export, import values and
GDP at the provincial level, from which commune adjusted trade ratios will be derived to
proxy for trade liberalization.
Although the household surveys were slightly modified over time, the basic content
between the two early surveys VLSSs and the later VHLSS are similar. At the household
and individual level, the surveys provide a wide range of information on household
characteristics including basic demography, employment and labour force participation,
education, health, income, expenditure, housing, fixed assets and durable goods etcetera.
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.
12
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.
13
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,
14
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
15
(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
16
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.
17
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).
18
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.
19
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
-0.0006 -0.0006 0.0001 0.0007 -0.0006 -0.0003 0.0001 0.0008
(0.0002)*** (0.0002)*** (0.0002) (0.0005) (0.0003)** (0.0003) (0.0002) (0.0005) Education dummies Completion of primary school
-0.0654 -0.1114 0.0297 0.2505 -0.0307 -0.0178 0.0353 0.2098
(0.0993) (0.0937) (0.0781) (0.0975)** (0.1108) (0.0985) (0.0787) (0.0983)** Completion of secondary school
-0.0014 -0.0454 0.0985 0.2576 0.0067 0.0293 0.1123 0.2291
(0.0907) (0.0923) (0.0806) (0.1090)** (0.1010) (0.0978) (0.0801) (0.1108)*** Completion of high school 0.1881 0.1425 0.2165 0.4975 0.2187 0.2194 0.2219 0.4294 (0.0925)** (0.0898) (0.0851)** (0.1283)*** (0.1046)** (0.0965)** (0.0892)** (0.1355)*** Higher education 0.5207 0.4587 0.0520 1.1957 0.5865 0.5477 -0.2621 0.8903 (0.0941)*** (0.0929)*** (0.3547) (0.2469)*** (0.1068)*** (0.1014)*** (0.5309) (0.1547)***
20
Formal Informal Formal Informal Male (1)
Female (2)
Male (3)
Female (4)
Male (5)
Female (6)
Male (7)
Female (8)
Region dummies Red River Delta -0.0091 -0.1911 0.0442 -0.2487 0.0202 -0.1842 0.0401 -0.1682 (0.0471) (0.0476)*** (0.0457) (0.0776)*** (0.0523) (0.0540)*** (0.0468) (0.0715)** North Central Coast -0.0934 -0.1753 0.0558 -0.3113 -0.1125 -0.1161 0.0493 -0.2668 (0.0538)* (0.0565)*** (0.0541) (0.1033)*** (0.0628) (0.0684)* (0.0574) (0.1017)*** South Central Coast 0.0903 0.0054 0.1834 -0.0407 0.1055 -0.0009 0.2002 0.0040 (0.0501)* (0.0506) (0.0521)*** (0.0827) (0.0600) (0.0620)* (0.0558)*** (0.0794) Central Highland 0.2771 0.0671 0.1562 0.0020 0.2790 0.1415 0.1875 0.1618 (0.0751)*** (0.0816) (0.0747)** (0.1080) (0.0935)*** (0.1083) (0.0792)** (0.1109) South East 0.2607 0.2640 0.3555 0.1422 0.3643 0.3842 0.3851 0.2408 (0.0535)*** (0.0525)*** (0.0540)*** (0.0921) (0.0574)*** (0.0557)*** (0.0539)*** (0.0881)*** Mekong River Delta 0.1960 0.2147 0.2691 -0.0315 0.2428 0.2512 0.2739 0.0523 (0.0496)*** (0.0471)*** (0.0488)*** (0.0839) (0.0578)*** (0.0552)*** (0.0513)*** (0.0812) Urban 0.2239 0.1046 0.0630 0.0599 0.1533 0.0997 0.0453 0.0980 (0.0288)*** (0.0279)*** (0.0312)** (0.0507) (0.0351)*** (0.0329)*** (0.0354) (0.0585)* Industry affiliations Agriculture -0.0714 -0.0338 -0.1517 0.0006 -0.0163 -0.0469 -0.1495 -0.0157 (0.0718) (0.0874) (0.0323)*** (0.0642) (0.0733) (0.0896) (0.0327)*** (0.0669) Manufacturing 0.2091 0.0547 -0.0305 0.0274 0.2650 0.0929 -0.0189 0.0434 (0.0362)*** (0.0465) (0.0324) (0.0640) (0.0401)*** (0.0512) (0.0326) (0.0644) Food processing 0.0783 -0.1271 -0.0776 -0.1366 0.1170 -0.1284 -0.0608 -0.1516 (0.0512) (0.0605)** (0.1082) (0.1057) (0.0545)** (0.0651)** (0.1080) (0.1014) Textile and garment -0.1014 -0.1148 -0.3178 -0.1294 -0.0387 -0.0870 -0.3074 -0.1383 (0.0712) (0.0422)*** (0.1031)*** (0.0644)** (0.0756) (0.0492)* (0.1038)*** (0.0663)** Paper and other light goods
-0.0438 -0.1342 -0.2094 -0.1682 0.0178 -0.0944 -0.1819 -0.1311
(0.0773) (0.0959) (0.0842)** (0.1019)* (0.0794) (0.0977) (0.0810)** (0.1024) Year 2004 0.9828 0.8756 0.4439 0.3755 1.0916 0.8800 0.4478 0.3506 (0.1470)*** (0.0927)*** (0.0647)*** (0.0910)*** (0.1626)*** (0.0963)*** (0.0683)*** (0.1019)***
21
Formal Informal Formal Informal Male (1)
Female (2)
Male (3)
Female (4)
Male (5)
Female (6)
Male (7)
Female (8)
Year 1998 1.1139 1.0552 0.5263 0.6126 1.1302 1.0035 0.4780 0.5618 (0.1444)*** (0.1258)*** (0.1018)*** (0.1217)*** (0.1601)*** (0.1255)*** (0.0953)*** (0.1248)*** Trade openness [(Ex + Im)/GDP]
Trade index at the provincial level
0.0711 0.0759 0.0266 0.0442
(0.0139)*** (0.0141)*** (0.0156)* (0.0232)* Trade index at the commune level
0.2528 0.2455 -0.1083 -0.4522
(0.1832) (0.1329)* (0.0865) (0.3169) Constant -0.5402 0.0764 -0.1280 -0.6029 -0.6789 -0.1270 -0.1577 -0.7337 (0.2825) (0.2307) (0.1714) (0.2479)** (0.3150)** (0.2453) (0.1810) (0.2521)*** Observations 2068 1615 1903 780 1579 1207 1722 707 R-squared 0.36 0.44 0.19 0.23 0.34 0.41 0.19 0.22 Robust standard errors in parentheses *significant at 10% level; ** significant at 5% level; *** significant at 1% level
22
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:
23
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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APPENDIX
Table A1: Vietnam: Real GDP and trade 1990 - 2005 1990-1995 1996-2000 2001-2005 Real GDP growth (%) 8.2 6.9 7.5 Export growth (%) 16.4 19.3 17.9 Import growth (%) 21.7 12.5 19.1
Sources: Mekong Economics (2002) and GSO (2001, 2003) Table A2. Nominal tariffs in Viet Nam, 1992-2003
92 93 94 95 96 97 98 99 �00 �01 �02 �03 Shares of tariff
0 - to 10% 68 66 66 62 65 64 62 59 60 60 60 57
Above 10 -20% 15 14 13 20 13 13 11 10 9 0 9 10
Above 20 -40% 15 15 16 14 17 17 18 21 21 21 21 22
Above 40% 2 5 5 4 5 6 7 11 10 19 10 11
Average Rate 10.7 11.8 12.3 12.3 12.3 13.4 13.6 16.3 16.2 15.7 15.4 16.6
Maximum rate 120 150 200 200 100 200 60 100 100 120 100 113
Total tariff lines
2813 2967 2934 3023 3180 3126 3163 6056 6341 5724 6413 5107
Source: retrieved from various sources
30
Table A3. Summary statistics of variables
Pooled sample 1993 1998 2004 Variable Obs Mean Obs Mean Obs Mean Obs Mean Natural log of real hourly wage 7,565 1.260 426 0.488 513 1.260 6,626 1.310 (0.681) (0.805) (0.724) (0.638) Formal 25,510 0.154 2,135 0.069 1,851 0.087 21,524 0.169 Informal 25,510 0.139 2,135 0.132 1,851 0.106 21,524 0.143 Self-employment 25,510 0.700 2,135 0.800 1,851 0.721 21,524 0.689 Gender (1 if male) 38,591 0.495 2,135 0.482 14,932 0.485 21,524 0.503 Marital status ( 1 if married)
38,591 0.425 2,135 0.631 14,932 0.647 21,524 0.250
Migrant (1 for migrant) 38,588 0.125 2,135 0.212 14,929 0.261 21,524 0.022 Head (1 for household head) 38,591 0.327 2,135 0.302 14,932 0.322 21,524 0.333 Age (in years) 38,591 35.266 2,135 31.750 14,932 34.611 21,524 36.070 (12.85) (12.87) (13.14) (12.55) Working experience ( in years) 25,396 11.518 2,135 11.891 1,737 11.282 21,524 11.500 (10.27) (11.40) (10.96) (10.10) No education 33,910 0.051 1,950 0.268 14,932 0.063 17,028 0.015 Completion of primary school 32,293 0.238 1,950 0.317 13,315 0.075 17,028 0.355 Completion of secondary school
32,293 0.309 1,950 0.264 13,315 0.210 17,028 0.391
Completion of high school 32,293 0.143 1,950 0.065 13,315 0.108 17,028 0.180 Higher education 32,293 0.043 1,950 0.012 13,315 0.030 17,028 0.057 Region dummies Red River Delta 38,588 0.192 2,135 0.225 14,929 0.174 21,524 0.202 North Central Coast 38,588 0.107 2,135 0.109 14,929 0.107 21,524 0.106 South Central Coast 38,588 0.104 2,135 0.115 14,929 0.128 21,524 0.086 Central Highland 38,588 0.060 2,135 0.021 14,929 0.068 21,524 0.059 South East 38,588 0.144 2,135 0.128 14,929 0.172 21,524 0.127 Mekong River Delta 38,588 0.209 2,135 0.295 14,929 0.203 21,524 0.205 Urban (1 if urban) 38,588 0.237 2,135 0.147 14,929 0.261 21,524 0.230 Industry affiliations Agriculture 38,591 0.601 2,135 0.762 14,932 0.631 21,524 0.565 Manufacturing 38,591 0.041 2,135 0.030 14,932 0.029 21,524 0.051 Textile and garment 38,591 0.032 2,135 0.019 14,932 0.035 21,524 0.031 Food processing 38,591 0.024 2,135 0.000 14,932 0.026 21,524 0.025 Paper and light goods 38,591 0.021 2,135 0.013 14,932 0.025 21,524 0.018 Trade measures Trade index (ex+im)/GDP at province level
38,588 0.399 2,135 0.243 14,929 0.231 21,524 0.531
(0.708) (0.439) (0.175) (0.904) Trade index (ex+im)/GDP at commune level
35,021 0.042 2,066 0.127 13,465 0.059 19,490 0.021
(0.109) (0.295) (0.098) (0.064)
Standard deviation of continuous variables in parentheses.