gender inequality and labour market segmentation …€¦ · that discrimination against women is...

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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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Page 1: GENDER INEQUALITY AND LABOUR MARKET SEGMENTATION …€¦ · that discrimination against women is more prominent in the formal sector, despite a more severe gender gap manifest in

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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

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.

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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

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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.

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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.

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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)

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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.

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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).

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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

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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

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.

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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.

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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

-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)***

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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)***

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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

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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

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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,

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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.

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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.

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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

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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.