metadata: authors: 0: author: Kokas,Deeksha
1: author: Lopez-Acevedo,Gladys C.
2: author: Vu,Ha Thanh Thi
count: Viet Nam
docna: 0: docna: Export and Labor Market Outcomes : A Supply
            Chain Perspective — Evidence from Viet Nam
docty: Policy Research Working Paper
abstracts: cdata!: Are changes in the labor market in
            response to changes in exports contained specifically within
            exporting industries, or do they disperse throughout the
            economy through supply chain linkages? This paper studies
            the case of Viet Nam, an example of a successful export-led
            growth economy, to examine this question. Combining UN
            COMTRADE data, input-output tables from the Global Trade
            Analysis Project, and 2010 to 2019 annual labor force survey
            data for Viet Nam, the study constructed a measure of each
            worker&#x2019;s total exposure to export shocks. The
            measure accounts for changes due to both direct export
            exposure (increase in exports in the worker&#x2019;s own
            industry) and indirect exposure (from increased exports in
            other industries that use inputs from the
            worker&#x2019;s industry). Estimates of the
            repercussions from increasing exports on labor market
            outcomes show that both direct and indirect exposure
            significantly increase workers&#x2019; wages and
            employment, while reducing inactivity and inequality. Wage
            premiums for attending college decrease, and the gender wage
            gap narrows. Wages increase more for the lowest-income
            workers and employment gains accrue more to unskilled
            workers, while employment decreases for more skilled workers.
display_title: Export and Labor Market Outcomes : A
            Supply Chain Perspective — Evidence from Viet Nam
listing_relative_url: /research/2024/08/34377283/export-labor-market-outcomes-supply-chain-perspective-—-evidence-viet-nam
topicv3: Poverty m1326687 695,Trade m1326924 698,Gender m1327621 615,Labor Incomes and Poverty m1503852 2676
publishtoextweb_dt: 2024-08-14T00:00:00Z
dois: 10.1596/1813-9450-10868
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 49
author_keys: 0: author_key: 1363894
1: author_key: 428192
2: author_key: 662040
model_extractions: Policy Research Working Paper 10868 Export and Labor Market Outcomes A Supply Chain Perspective—Evidence from Viet Nam _Deeksha Kokas Gladys Lopez-Acevedo Ha Vu_ Poverty and Equity Global Practice August 2024
Policy Research Working Paper 10868

# **Abstract**

Are changes in the labor market in response to changes in exports contained specifically within exporting industries, or do they disperse throughout the economy through supply chain linkages? This paper studies the case of Viet Nam, an example of a successful export-led growth economy, to examine this question. Combining UN COMTRADE data, input-output tables from the Global Trade Analysis Project, and 2010 to 2019 annual labor force survey data for Viet Nam, the study constructed a measure of each worker’s total exposure to export shocks. The measure accounts for changes due to both direct export exposure (increase in exports in the worker’s own industry) and indirect exposure (from increased exports in other industries that use inputs from the worker’s industry). Estimates of the repercussions from increasing exports on labor market outcomes show that both direct and indirect exposure significantly increase workers’ wages and employment, while reducing inactivity and inequality. Wage premiums for attending college decrease, and the gender wage gap narrows. Wages increase more for the lowest-income workers and employment gains accrue more to unskilled workers, while employment decreases for more skilled workers.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at gacevedo@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Export and Labor Market Outcomes:

# A Supply Chain Perspective - Evidence from Viet Nam

Deeksha Kokas<sup>a</sup> Gladys Lopez-Acevedo<sup>b</sup> Ha Vu<sup>c</sup>

> a Nanyang Technological University

> b Poverty and Equity Global Practice, World Bank *

> c Economic Frontiers, International Institute for Applied System Analysis

*STATMEMENTS AND DECLARATIONS: This paper is a product of the Poverty and Equity Practice at the World Bank Group. It was funded by the UFT Trade Facilitation Program and the Australia World Bank Group Strategic Partnership in Viet Nam Phase 2 (ABP2). We thank the following colleagues for their support during this process Raymond Robertson, Matthew Wai-Poi, Rinku Murgai, Judy Yang, Dorsati Madani, Sacha Dray and Deborah Elisabeth Winkler. The views expressed herein are those of the authors and do not necessarily reflect the views of the World Bank.
# **1 Introduction**

In the past two decades, the notable uptick in the integration of developing nations into global trade and value chains (GVCs) has sparked heightened interest among policy makers and researchers regarding the implications for labor markets. Consequently, a substantial body of literature has emerged seeking to unravel the intricate relationship between trade dynamics and localized labor market outcomes.

Standard theory about the benefits of trade assumes perfect mobility of factors across geographical regions and industries within a country. However, recent empirical evidence has shed light on the limitations of these conventional theoretical models. Topalova (2010) [9] uses data from India to indicate that regions more exposed to trade liberalization have experienced slower poverty reduction and muted consumption growth, diverging from the predictions of traditional trade frameworks. Assuming segmented labor markets, and exploiting cross-market variation in import exposure, a key study by Autor, Dorn, and Hanson (2013) [2] confirms that the ”China Shock” led to significant decline in employment and wages in more exposed U.S. regions. This sparked more studies on the repercussions of tariff changes or import competition on local labor markets (Pierre and Schott 2016 [7]; Acemoglu et al. 2016 [1]; Dix-Carneiro and Kovak 2013 [3]).

It is crucial to note that trade affects not only tradable but also non-tradable sectors within the same local labor markets; while increased import competition or market access directly impacts specific tradable sectors, there are also indirect effects on non-tradable sectors such as retail, healthcare, or hospitality in the same region. With few exceptions, current literature largely ignores estimating these indirect effects propagated through domestic production linkages within a country [10]. While a few studies have examined the indirect effects of import shocks on local labor markets, there has been limited exploration of indirect effects of exports. A central motivation for this empirical inquiry stems from the well-documented fact that as economies undergo structural transformation—that is, as they move from less agriculture to more services and manufacturing—the 1
proportion of domestic services or inputs in total outputs tends to rise (McCaig 2013 [6]; Ghosh 2021). At first glance, this might suggest that a larger proportion of employment remains unaffected by trade, given the larger non-tradable component of the services sector. However, more trade can even indirectly influence non-tradable industries that serve as inputs to tradeable sectors.

This paper focuses on estimating the total effect on labor market outcomes in response to an export shock at the provincial level in Viet Nam from 2009 to 2019. In order to fully capture the overall impact of trade, we need to consider crucial supply chain linkages previous research has overlooked. Our analysis goes beyond solely focusing on directly exporting industries and accounts for industries indirectly affected by the rising demand for exports.

To accomplish this, we adopt a multi-stage approach. Initially, we employ an instrumental variable (IV) methodology to isolate an exogenous component of trade driven solely by foreign demand. The chosen IV is the proportion of a given trading partner country’s share in a specific commodity relative to Viet Nam’s total export value in that commodity, adjusted by the observed GDP growth of the partner country. This IV demonstrates a strong predictive capacity for Viet Nam’s export values while maintaining plausible independence from any supply-side determinants of exports.

Subsequently, leveraging the predicted export exposure obtained in the first stage, we construct a matrix delineating the direct and indirect exposure of each industry in each province. This is accomplished by utilizing input-output tables that document the flow of intermediate goods among different sectors in the economy. The predicted export exposure calculated earlier is then distributed proportionally to the labor share of each industry within each province.

Finally, we estimate the direct and indirect effects of exports by conducting a regression analysis of these computed exposures against various labor market outcomes of interest at the provincial level: wage levels, income disparities, the premium on college education wages, gender wage differentials, employment rates, rates of inactivity, informality in employment, and female employment rates. Additionally, we conduct a detailed examination of how these labor effects differ 2
across gender, income levels, educational attainment, and employment sectors to elucidate which demographic groups benefit and which are adversely affected by this process. Our analysis goes beyond solely focusing on directly exporting industries and accounts for industries indirectly affected by the rising demand for exports.

This study looks at the specific context of Viet Nam for a few important reasons. First, Viet Nam exemplifies the success of Asia’s export-driven growth model, making it a prime candidate for study due to the wealth of empirical evidence available. Over the past two decades, Viet Nam has witnessed substantial increases in real income, a reduction in poverty (excluding the Covid-19 pandemic in 2020), and an alignment of import-export activities with GDP, reflecting its integration into global value chains. Improvements in the labor market have accompanied this economic progress, including lower unemployment rates and increased female workforce participation. Figure 1 encapsulates Viet Nam’s Poverty Rate Reduction driven by its export focus. Figure 3 in the Appendix provides more trends in Trade, Labor, and other Socioeconomic Indicators of Viet Nam for a side-by-side visual comparison.

3
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Second, the prominence of domestic services within Viet Nam’s non-tradable sectors is notable, representing an average of 10 percent of total output. The connection between non-service and service sectors is vital for amplifying the impact of exports on labor markets. In Viet Nam, domestic non-service industries heavily rely on domestic services as inputs. Figure 2 illustrates that around 50 percent of Vietnamese non-service sectors use local services, making up more than 15 percent of their end output. Neglecting these indirect export effects on domestic services and input supply sectors overlooks a crucial link tying local labor markets to foreign demand changes. Recognizing and understanding these connections is crucial for grasping the wider effects of export-oriented economic activities in Viet Nam. A significant proportion of non-service sector-country clusters exhibit a substantial reliance on local services, with approximately 50 percent showcasing a local services usage share exceeding 8 percent, and a minority displaying shares as high as 20 percent. Against this background, this study aims to examine the direct and indirect effects of exports, which are supported by supply chain connections, on the labor market.

Third, Viet Nam heavily relies on the advantageous demographic structure of its labor force to propel economic advancement, characterized by a great proportion of the popula- tion being of working age as well as a significant spatial variation across sectoral specialization. Therefore, this investigation aims to leverage these variances to scrutinize how the potential effects vary across diverse demographic strata within the labor force: urban, rural, youthful, highly-skilled, and female cohorts, among others.

We find that both direct and indirect exposure to exports has a significant impact on labor market outcomes, especially for those with no to little education and in the lowest income bracket. The wage premium for attending college decreases, and the gender wage gap narrows. With respect to employment variables, direct exposure to exports increases employment and reduces inactivity, with findings remaining consistent when accounting for supply chain linkages. The gains in employment concentrate among workers with no schooling, while the employment rate falls for more skilled workers.

5
In this paper, we estimate the total impact of changes in exports driven by foreign demand shocks, rather than tariff changes or import competition, on labor market outcomes including income and employment variables. This direct and indirect export-induced demand has been studied in Goutam et al. (2017) [5]; however, as only employment variables are in focus, many other questions regarding wages and heterogeneity have been left unanswered.

The paper proceeds as follows. Section 2 presents a conceptual framework that allows us to examine the local labor market repercussions of exports, incorporating a supply chain perspective. Section 3 discusses the data used and how we constructed the export exposure analysis using InputOutput linkages. Section 4 describes the empirical strategy and Section 5 presents the empirical results. Section 6 concludes.

# **2 Conceptual Framework**

We apply a standard shift-share approach that assesses the effects of trade shocks on labor markets. Relevant works in the literature include Autor, Dorn and Hanson (2013) and Dix-Carneiro and Kovak (2015) [3][2]. More directly related to exploring the effects of exports on local labor markets are studies by Robertson et. al. (2021) and G ́oes, Lopez-Acevedo, and Robertson (2023) [8] [4].

Unlike the papers above, however, our index in this paper is not one of export exposure, but one of total export receipts exposure. By exploiting the input-output structure of production, we account for both direct and indirect payments to factors of production, and use trade data to move closer to regional production, which is what we would ideally like to observe.

Let _s,d_ be industry index ( _s_ stands for source sector and _d_ stands for destination sector), and let γ _s,d_ denote the intermediate use shares of a good of industry _s_ in the production process of a good of industry _d_ . Under the assumptions of perfect competitive or monopolistic competitive product markets, a constant fraction of total sales will be paid to the factors of production. If domestic factor markets are competitive, there are no mark-ups or mark-downs on factor prices.

6
Under those assumptions, then, up to a first-order approximation, the value of export sales can be distributed through the production network in the following fashion: Therefore, we can account for total payments to each source sector _s_ by summing over payments to sector _s_ from every sector _d_ in addition to the value added of sector _s_ : or in words, Total Export Exposure ∝ Indirect Export Exposure + Direct Export Exposure So far, we have defined these relationships in terms of input-output linkages. To turn to the empirical effects on labor markets, we now define local labor markets exposure to total export receipts. Let _r_ denote different regions in the country, exposure to total export receipts growth at regional level is defined as: where _Xr,s,t_ denotes total export exposure of industry _s_ to region _r_ at period _t_ , as defined above; _Lr,s,t_ denotes total employment of industry _s_ in region _r_ at time _t_ . The term<sup>_L_</sup> _L_<sup>_r_</sup> _s_<sup>_<u>,s</u>_</sup> _,t_<sup>_<u>,t</u>_measures the share</sup> of region _r_ in the national employment of industry _s_ .

7
# **3 Data**

The goal of the paper is to assess the direct and indirect effects of export expansion on local labor market outcomes in Viet Nam while accounting for supply chain linkages. To do this, we exploit variation in export expansion across provinces and industries between 2010 and 2019 and combine export data from the United Nations Commodity Trade Statistics (UNCOMTRADE) data, inputoutput coefficient matrix from Global Trade Analysis Project (GTAP) data, and information on local labor market outcomes from Viet Nam’s Labor Force Survey (LFS) data. Details on each dataset and cleaning techniques are described below.

## **3.1 Labor Force Data**

Our main source of labor market data is the LFS provided by General Statistics office of Viet Nam (GSO) between 2010 and 2019, a period during which it was implemented every year. The LFS observations collect information in a host of areas including key labor market, household, and individual demographic characteristics.

Our analysis looks at two main sets of outcome variables: wage outcomes and employment outcomes. The wage outcome data sets include real annual wages, real annual income, college degree wage premium and gender wage premium. The employment outcome sets include employment rate, inactive rate, informality status, and female labor force participation. All of the outcomes are constructed from survey questionnaires, of which the wage outcomes are calculated at the province x sector level, while the employment outcomes are aggregated at the province level because we do not have sector information for those who are not employed. Over the period 2010 to 2019, several changes were introduced in the Viet Namese LFS, together with updates in concepts and definitions. These have been standardized to make key labor market outcomes, administrative geographies, as well as industry classifications, comparable over time.

8
# **3.2 Construction of Export Exposure Using Input-Output Linkages**

Any changes in the foreign export demand for products of a particular sector will have dual effects. First, it will lead to a direct increase in demand for output in that sector. Secondly, it indirectly affects the upstream sectors that supply inputs to the directly impacted sector. Not accounting for these linkages will underestimate the export exposure at the province level, as some provinces may not have a concentration of industries directly exporting but still be supplying to exporting sectors. To account for these value chain linkages, the literature represents uses Leontief inverse of an input-output production matrix for an economy. The method clearly tracks the use of intermediate inputs by each sector (Goutam et al. 2017; Acemoglu et al. 2016; Acemoglu et al. 2012).

To explore potential effects of exports through domestic inputs, we employ the 2011 Viet Nam Input-Output table to calculate the input shares of each industry. These shares are determined by dividing the input usage by the gross output (which includes the value added in the own sector with own-sector inputs). We then multiply the resulting shares by the exports of the final sector aggregated over the input industry to obtain the total value of exports for each input sector (representing the cumulative effect of servicing multiple exporting sectors). In this sense, non-traded sectors that are assigned a value “zero” for exports will also have an implied value and will be used to estimate the total export exposure index at the province level using the following index.

The total export exposure (accounting for supply chain linkages) is measured as the growth in exports in industry _i_ between time periods, _t_ and _t_ + 1, captured by the term ∆ _Wi,t_ + _h_ = _Wi,t_ − _Wi,t_ + _h_ . This change is allocated to each province _r_ in Viet Nam using the share of provinces in total national employment in each industry _i_ .

To construct the total exposure index at the province level in Viet Nam, we utilize several databases. Initially, we gather data on export value from the UNCOMTRADE database. To account for de9
mand generated in other sectors as a result of exports, and thus calculate the overall exposure index, we incorporate the 2011 input-output (I-O) GTAP tables. We chose 2011 I-O table instead of a more recent year available (2016) because it reflects the economy at the beginning of the studied period, which guarantees that all the shocks computed are ex-ante. An important underlying assumption with this decision is that there isn’t any significant changes in the sectoral structure. Admittedly, this is a major limit of the paper that we have to accept due to data constraint.<sup>1</sup> We begin by computing the input-output coefficients from the GTAP I-O tables, which capture the interdependencies between sectors in an economy. We match these coefficients with trade data the UNCOMTRADE data to compute the total export value for each sector, accounting for indirect changes in export demand through input-output linkages.

The next step is to link these total export data with the LFSs. We utilize concordance tables available from UNSD that translate International Standard classification (ISIC) rev 3.1. codes into HS codes. By leveraging this concordance, we merge the micro-data on labor force variables at the industry and area level in Viet Nam with total export data. Once the integrated labor and trade data is prepared, we are able to calculate the total trade exposure index based on provinces, as previously explained. The starting point for the analysis is the idea that the impact of a trade shock differs across regions, depending on each province-industry composition.

A fundamental principle for this approach is the existence of segmented labor markets. Existing labor mobility barriers or rigidities (such as commuting costs or lack of transport infrastructure) allow us to observe variations in local labor market outcomes and, as a result, to estimate the effects of differentiated exposure to trade. One heuristic method for assessing labor-market integration involves examining the standard deviation of wages across regions and over time. This heuristic measure is used because various factors can prevent wage equalization across regions. To investigate the level of labor-market integration in Viet Nam, we calculate province and industryprovince premiums, the existence of which can indicate segmented labor markets. Tables 1 and 2

> 1In future exercises, we will attempt to test this assumption using a later I-O table

10
in the Appendix clearly show that wages are not equal across provinces and industry-provinces in Viet Nam, providing strong support for the existence of segmented labor markets during our study period.

# **4 Identification**

The goal of our empirical strategy is to understand how rising export expansion affects real wages, informality, and female labor force participation, exploiting data on cross-regional exposure to total exports in Viet Nam between 2010 and 2019. To this effect, we consider the following simple linear regression model: where ∆ _Yr,t_ + _h_ is the change in outcomes of interest, may it be employment rate, informality rate, female participation rate, average annual income average annual wage, college premium or gender wage gap, among others, identified at province _r_ over the period from time _t_ to _t_ + _h_ . ∆ _Xr,t_ + _h_ is our main independent variable, which stands for the change at regional level of total export exposure, as defined in the previous section. The key coefficient of interest is β1, which measures the effects of total trade exposure on the outcome after accounting for the I-O structure, _Kr,t_ is the vector of ex-ante control variables including individual demographic background taken from the LFS such as urban dummy, gender, marital status, age group, education level, social security ownership, among others.

A relevant issue that needs to be addressed is potential endogeneity in the export exposure covariate. Since we observe changes in labor outcomes and exports simultaneously, we cannot identify which one is driving the other. To ensure truly exogeneity of our export exposure, we need a variable that predicts exports from Viet Nam based solely on its trading partners internal 11
demand growth, rather than supply-side determinants. Hence, we construct our instrument using time-series regressions of Viet Nam exports to its trading partners on the trading partner’s GDP by industry at the four-digit level as follows: where,<sup>_<u>Qj,i,t</u>_</sup> _<u>Q j,i,t</u>_<sup>_j_’s share of industry</sup><sup>_i_’ export;∆</sup><sup>_Yj,t_+</sup><sup>_h_is the change in real</sup> _Qi,t_<sup>=</sup> ∑ _j Q j,i,t_<sup>denotes country</sup> GDP in destination country _j_ .

Predicted values or exports from these regressions serve as a proxy for Viet Nam’s exports to its trading partners explained exclusively by the export market’s domestic aggregate demand. These predicted exports combine with I-O coefficients to generate total exports accounting for supply chain linkages. Subsequently, we use these total exports to generate provincial export exposure in Viet Nam.

Then, estimation will take the form of two-stage least squares, with the first stage being: and the second stage: where ∆ _X_<sup>ˆ</sup> _r,t_ + _h_ is the predicted value obtained from the first stage regression: 12
# **5 Results**

## **5.1 Impact of Exports on Wages**

Table 6 presents the outcomes of the two-stage least squares regression, detailing the relationship between changes in income-related variables—wages, income, gender wage differentials, and the college wage premium—and shifts in exposure to exports, instrumented by alterations in exposure to foreign demand. All models incorporate standard errors clustered at the province level and control for various socio-demographic factors such as age, gender, education level, urban-rural status, economic sector, and hours of work. It is important to note that although Wages are measured annually, we have included Hours of Labor (Weekly average) in the regression to control for the amount of time the workers spend at work. Thus, the results can also reflect an effect that is similar to the effect on hourly wage. Another detail that is worth noting is that the Income variable often reflects a more positive improvement compared to the Wage variable for individuals, as it encompasses additional sources of non-wage income such as bonuses, dividends, and personal gifts.

Overall, all measures of exposure—Total Exposure, Direct Exposure, and Indirect Exposure—exhibit statistically significant effects on income-related variables. Direct Exposure demonstrates the most substantial improvement, with a US$32.5 increase in annual wages and a US$36.31 increase in annual income for every US$1,000 rise in annual Direct Exposure per worker. While Indirect Exposure yields a similar effect on wages (an increase of US$31.14 per unit of exposure), its influence on income is relatively lower (an increase of US$23.22 per unit of exposure) compared to Direct Exposure.

Additionally, variables reflecting labor market inequality—namely, the college wage premium and gender wage gap—decrease in response to export exposure, with the college premium exhibiting a higher degree of significance. Specifically, a US$1,000 increase in annual direct exposure per worker results in about a US$28 reduction in return on attending college. The effect of indirect 13
exposure on this premium is a reduction of about US$30.87. To give a benchmark, the national mean annual wage throughout the 2010-2019 period is US $1,654, meaning that an effect of US $30 is equivalent to approximately 1.81 percent. Compared to the average wage of US $1,867.5 in the urban area and US $1,433.8, this effect translates to 1.6 percent and 1.8 percent respectively.

A noteworthy observation across various outcomes in the analysis is that Total Exposure, which represents the sum of Direct and Indirect Exposure, consistently yields smaller absolute effects compared to either Direct or Indirect Exposure. This could look puzzling at first glance, however, there are a few econometric reason why this is the case. First, one reason could be that the controls could absorb differently the effects on labor outcomes that are not caused by direct and indirect exposure. It’s likely that direct exposure is more correlated with some of the controls than indirect exposure or vice versa. For example, it could be that workers in tradable sectors tend to be younger and less educated. Furthermore, there could also be larger error terms in the indirect exposure regression, and indeed this may be why we see much less significance for indirect exposure.

# **5.2 Impact of Exports on Employment**

Regarding employment outcomes, Table 7 illustrates that both Total Exposure and Indirect Exposure exert statistically significant effects on the employment rate at the provincial level. Specifically, for every US$1000 increase in Total Exposure per worker, the likelihood of employment rises by 0.2 percent point, while Indirect Exposure increases the employment rate by 0.52 percent point. Interestingly, Direct Exposure exhibits either non- or minimally significant effects on the employment rate and other employment metrics such as the rate of informal employment and female employment rate. Conversely, both Total Exposure and Indirect Exposure significantly reduce informality rates and augment female participation in the labor force. All of these trends imply that exports have caused healthy benefits to the labor market and created a more efficient and balanced working environment for workers.

14
# **5.3 Heterogeneity by Education**

Tables 10 and 11 provide insights into how wage and employment outcomes vary across different segments of the population based on their level of education. Our findings suggest that workers across all educational strata benefit from trade. Notably, individuals with a college education premium derive the greatest absolute benefit, with a US$42.38 increase in wages for every US$1,000 rise in Total Exposure, compared to a US$14.84 gain for workers with no formal education. However, as shown in Table 3, mean annual wages increase considerably as education levels increase. Thus, in a relative terms, these effect among workers with a college degree translates to 1.23 percent, lower than that of 1.55 percent among workers with no education.

This disparity becomes more pronounced when examining the impact of Direct Exposure and Indirect Exposure on workers with a college degree, yielding increases of US$67.11 and US$72.13, respectively, for each type of exposure. Interestingly, the indirect effect is only significant for less educated labor while the direct effect is most significant for more educated labor. This suggests a higher concentration of skilled workers in exporting sectors and unskilled workers in non-exporting sectors. Yet generally, the absolute discrepancy between changes in wages resulting from Direct and Indirect exposure is minimal across all educational levels.

On the contrary, changes in employment outcomes exhibit divergent patterns across different educational groups. While the employment rate among workers with little to no formal education (primary school level) tends to increase, that of college graduates decreases in response to higher export exposure, whether direct or indirect. For instance, a US$1000 increase in annual Total Expo- sure per worker can elevate the employment rate of workers with no formal education by 0.15 percent point while concurrently reducing the likelihood of employment for college graduates by 0.19 percent point. This outcome, coupled with the discussed variance of education on wages, suggests a nuanced interpretation. Specifically, it implies a more competitive environment for highly-skilled workers, juxtaposed with an expansion in economic opportunities for low-skilled 15
workers following an export-driven boost.

# **5.4 Heterogeneity by Economic Sector**

Tables 12 and 13 provide a detailed examination of wage and employment outcomes across various economic sectors, namely Household Farm, Household Business, Private Sector, State Agency, and Foreign Sector. While employment demonstrates significant improvement across all sectors, Household Farm experiences the most substantial gains, with approximately a 4.87 percent point increase for every US$1000 rise in total exposure, followed by Household Business, Private sector and State Agency with 4.12, 4.05 and 3.78 percentage points, respectively. In terms of wages, the findings also reveal notable wage increases in most sectors except Foreign sector, regardless of the type of exposure. Particularly, Household Business witnesses a sharper rise in wages, amounting to approximately US$53.26 per worker for every unit increase in Total Exposure, compared to a US$32.8 increase in wage observed in the Household Farm sector, US$29.6 in Private sector and US$37.6 in State Agency. The reason why no significant increase in wages was observed in Foreign Sector in spite of an increase in employment in the same sector probably roots in corporate culture where multinational employers tend to anchor their pay rates around homeland culture and regulations.

# **5.5 Heterogeneity by Income Level**

To gain a comprehensive understanding of how trade influences income inequality within the labor market, we extend our analysis to examine various income quantiles among workers. Tables 14 and 15 present the outcomes of these regressions. Our findings indicate that the most significant wage improvements occur among workers in the lowest income quantile, which aligns with the observation that the sectors most affected by trade tend to predominantly employ labor from this demographic segment.

16
Conversely, we observe enhanced employment opportunities across all income quantiles, albeit with diminishing effects as income levels rise. Specifically, the likelihood of employment increases the most among workers in the lowest income quantile, with an about 1.77 percent point rise for every US$1,000 increase in Total Exposure. This effect gradually diminishes across the second and third lowest quantiles, reaching as low as a 0.14 percent point increase in employment probability in the highest worker income bracket.

# **5.6 Heterogeneity by Tradability**

In our final analysis, we speculate about the spillover of direct trade exposure into indirect exposure, a phenomenon closely intertwined with the tradability nature of sectors. In this section, we explore the divergent effects of direct and indirect exposure on labor outcomes between tradable and non-tradable sectors. We classify industries into “non-tradable” sectors if their export exposure is “zero”, as indicated by the summary statistics in Table 4. These sectors include Mining Extraction, Chemicals, Pharmaceuticals & Medical Products, Rubber and Plastics, Electrical Equipment, Electricity, Gas Manufacturing and Distribution, Water Supply, Construction, Wholesale and Retail Trade, Accommodation and Food Service, Land Pipelines and Transportation, Water Transportation, Air Transportation, Warehousing, Other Financial Inter-mediation, Insurance, Real Estate Activities, Other Government Services, Education, and Human Health & Social Work. Broadly, these sectors are characterized by their focus on supplementary goods and domestic services. Conversely, we designate sectors with “non-zero” export exposure as “tradable”.

Having established this differentiation based on tradability, we conduct regression analysis on samples restricted to these two categories. This approach enables us to derive insightful interpretations regarding how direct and indirect exposure to exports affect labor outcomes. As anticipated, Table 16 indicates that direct exposure exerts a notably pronounced and robust impact on both wage and employment outcomes within tradable sectors, whereas indirect exposure demonstrates 17
a more modest effect on wages while still fostering employment growth and reducing informality. This observation aligns logically with the understanding that tradable sectors, in addition to producing goods for direct export, may also provide inputs for other traded sectors, thereby benefiting from indirect exposure.

Table 17 initially presents a perplexing observation, revealing an unexpected trend wherein both direct and indirect exposure reduces employment and wages within non-tradable sectors, with indirect exposure exhibiting a stronger negative effect. However, upon closer examination, this finding unveils contrasting patterns regarding how trade influences these two distinct sectors. On one hand, trade has the potential to expand the overall economic “pie”, thereby reshaping wage and employment dynamics in both tradable and non-tradable sectors. Conversely, an intriguing offsetting effect, wherein trade acts as a driving force, can pull labor directly from non-tradable to tradable sectors within the confines of fixed labor supply. This second nuance might have a greater significance given the ample evidence of relatively full employment in Viet Nam and the limited benefits or unemployment insurance available, rendering staying in non-tradable sectors a far less attractive option compared to seeking opportunities in rapidly expanding tradable sectors.

# **6 Conclusion**

The intrinsic connection between direct exporting sectors and the indirect supplying sectors (that furnish production inputs to exporters), is crucial for transmitting the benefits of foreign demanddriven exports not only to tradable sectors, such as agriculture and manufacturing, but also to non-tradable sectors, such as services, where such effects are less anticipated. Leveraging this relationship within the supply chain, we have devised a theoretical framework and an empirical approach to re-examine the ramifications of trade on the labor market, incorporating considerations of both direct and indirect export exposure.

Our analysis provides comprehensive insights into the impact of trade on various aspects of 18
the labor market, shedding light on nuanced patterns across different demographic and economic segments. The results indicate significant labor benefits from exposure to exports on incomerelated variables such as wages, income, and labor market inequality, with directly exposed sectors and provinces enjoying the greatest benefit. Moreover, both exposure types contribute to a decrease in labor market inequality measures such as the college wage premium and the gender wage gap. Employment out- comes also vary, with both total and indirect exposure positively affecting employment, informality, and female employment rates, while direct and total exposure reduce informality rates and increase female labor force participation.

Across education levels, workers benefit from an increase in trade, with college-educated individuals deriving the greatest wage benefits. Changes in employment outcomes vary, with employment increasing for workers with lower education but decreasing for college graduates in response to higher export exposure. Employment improves across all economic sectors, with the Household Farm sector experiencing the most substantial gains, while notable wage increases are observed only in the Household Farm and Household Business sectors, suggesting differential impacts across economic sectors. Wage improvements are most significant among workers in the lowest income quantile, while enhanced employment opportunities are observed across all income levels, albeit with diminishing effects as income rises. Direct exposure causes a pronounced increase on both wage and employment outcomes within tradable sectors, while indirect exposure exhibits a more modest increase in wages but still fosters employment growth. In contrast, both direct and indirect exposure reduce employment and wages within non-tradable sectors, highlighting the intricate interplay between trade dynamics and labor markets.

Considering both direct and indirect export exposure leads to a more nuanced understanding of how trade shapes employment, wage dynamics, and labor market inequality across various sectors and demographic groups. These insights are crucial for policymakers and stakeholders seeking to navigate the complexities of globalization and ensure inclusive economic growth.

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