Analyzing Vietnam’s Economic Transformation from 2007 to 2023: Insights from Structural Decomposition of Input–Output Tables

Abstract

The present study investigates Vietnam’s economic structural transformation from 2007 to 2023, identifying key sectors contributing to output growth and poverty reduction. The study is situated within the broader context of industrialization and sustainable development in emerging economies. It employs structural decomposition analysis using Vietnam’s national input–output tables for the years 2007, 2011, 2015, 2019, and 2023. The analysis decomposes changes in total output into technical effects and final demand effects, allowing for an evaluation of the relative contributions of sectoral productivity and demand side factors. The findings of the study indicate that the manufacturing and services sectors have been the primary drivers of economic growth, with the electrical and optical equipment, food, beverages and tobacco, and basic metals sectors demonstrating particularly strong performance. The factor of final demand, which is derived from consumption, investment, and exports, has played a dominant role in driving output. Notably, export-led manufacturing has experienced significant benefits due to Vietnam’s engagement in free trade agreements. It is noteworthy that the agriculture sector demonstrated a period of recovery between 2019 and 2023, driven by an increase in final demand. This study underscores the pivotal function of sectoral adaptability, trade openness, and strategic policy in maintaining inclusive economic development. It is evident that the phenomenon under scrutiny is not only indicative of vulnerabilities and opportunities but also shaped by global shocks, for example, the coronavirus pandemic.

1. Introduction

Structural transformation has long been acknowledged as a fundamental driver of economic development, particularly in the context of developing and emerging economies. This process typically involves a significant reallocation of labor and capital from low-productivity sectors, such as agriculture, to higher-productivity sectors, such as manufacturing and services (Kuznet, 1966). The theoretical and empirical literature emphasizes that successful structural transformation is closely associated with higher economic growth, improved living standards, and greater economic diversification (Freire, 2019; Almeida & Balanco, 2020; Dore & Teixeira, 2023).

In recent decades, Vietnam has emerged as a compelling case study of structural transformation in practice. Since the implementation of Doi Moi economic reforms in 1986, the country has transitioned from a centrally planned economy to a dynamic, export-oriented market economy. Vietnam’s economic growth trajectory has been widely documented, with the country achieving middle-income status and significantly reducing poverty (Barker & Ungor, 2019).

According to the General Statistics Office (GSO) (2025), Vietnam’s economy has experienced significant change, specifically in terms of its structure. In particular, the country has reduced its dependence on sectors related to agriculture and expanded the contribution of the industrial and service sector. In 2024, Vietnam’s economy demonstrated remarkable growth, with GDP increasing by 7.09%. The nation’s economy has an estimated value of USD 476.3 billion (General Statistics Office (GSO), 2025). The export sector grew significantly, with USD 405.53 billion in total export turnover (up 14.3% year on year), while imports reached USD 380.76 billion, resulting in a trade surplus of USD 24.77 billion. The industrial production index increased by 8.4%, and the average consumer price index rose by 3.63%, indicating controlled inflation amid high growth. These figures reflect the ongoing structural shifts in Vietnam’s economy, especially the increasing contribution of industry- and export-led growth, which are central to understanding the structural transformation in the post-2007 period.

One of the most significant drivers behind this transformation has been the country’s integration into global trade networks. As of 2025, Vietnam has signed and implemented 17 free trade agreements (FTAs) with over 60 partners, including major bilateral and multilateral agreements such as the Vietnam–Japan Economic Partnership Agreement (VJEPA), the Vietnam–South Korea Free Trade Agreement (VKFTA), and the UK–Vietnam Free trade Agreement (UKVFTA). Specifically, the multilateral agreements include the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CTTPP), the EU–Vietnam Free Trade Agreement (EVFTA), and the Regional Comprehensive Economic Partnership (RCEP). These FTAs have facilitated greater access to international markets, encouraged foreign direct investment, and stimulated the development of high-value-added manufacturing and services sectors (Sahel & El Abbassi, 2025; Li et al., 2025).

Despite these achievements, the economic transformation in Vietnam remains an ongoing and complex process, marked by both progress and challenges. While there has been a visible shift in the composition of output and employment away from agriculture towards industry and services, questions remain regarding the depth, quality, and sustainability of this structural change. Previous studies (e.g., Vu, 2017; Ngoc & Pierre, 2004) have primarily adopted aggregate macroeconomic indicators to examine growth and transformation, often overlooking the inter-sectoral linkages and underlying mechanisms that drive these changes. Furthermore, recent global disruptions, such as the COVID-19 pandemic and supply chain realignments, have underscored the need for a more detailed understanding of how sectoral dynamics contribute to economic resilience and structural upgrading.

This study addresses these gaps by focusing on Vietnam’s structural transformation between 2007 and 2023, with a specific emphasis on sectoral dynamics and policy-relevant insights. The central research question guiding this study is as follows: how have changes in technology and final demand influenced the structure of Vietnam’s economy over time, and which sectors have played key roles in this process?

To answer this question, the study employs an input–output (I-O) analysis, drawing upon national I-O tables for the years 2007, 2011, 2015, 2019, and 2023, obtained from the Asian Development Bank (ADB). The most recent version of the Vietnam I-O tables, published by the ADB, encompasses a broader scope, consisting of 35 sectors. This updated dataset provides a more comprehensive and detailed representation of the country’s economic activities. The research data was sourced from the ADB database, a reputable source. This approach ensured the reliability and authenticity of the dataset.

I-O analysis is particularly useful for examining structural change because it captures the complex web of interdependencies among the sectors in an economy. Unlike conventional macroeconomic models, I-O tables enable a detailed decomposition of output change into technical effects, reflecting changes in input coefficients and technology, and final demand effect, driven by consumption, investment, and exports. The use of structural decomposition analysis (SDA) in this study allows for a precise quantification of the contribution of each component to overall economic growth, thus offering insights into both direct and indirect pathways of transformation (Zuhdi, 2012; Zhang & Diao, 2020). Moreover, as emphasized by Marconi et al. (2016), I-O analysis is also essential for identifying key sectors with strong productive capabilities and inter-sectoral linkages, which are critical for guiding industrial policy and long-term development strategies.

Moreover, this study calculates backward and forward linkage indices to identify which sectors serve as key drivers or enablers within the production network. Such measures provide valuable information about a sector’s potential to induce growth in upstream or downstream activities and are essential for targeting policy interventions. This approach also allows for a comparative analysis across the time periods before, during, and after major global disruptions—highlighting the resilience and adaptability of different sectors.

The contribution of this research is threefold: First, it enhances the understanding of Vietnam’s structural transformation by providing sector-specific, empirical evidence over a multi-decade period. Second, it strengthens the methodological approach in the literature by integrating SDA with I-O linkages in a longitudinal framework. Third, it informs national and regional policymakers on how to design targeted strategies that foster inclusive and sustainable growth in the face of external shocks and internal constraints. In doing so, the study aligns with broader development priorities, including industrial upgrading, trade competitiveness, and the Sustainable Development Goals (Freire, 2019; Dore & Teixeira, 2023; Sahel & El Abbassi, 2025).

The remainder of this paper is organized as follows: Section 2 outlines the methodology and data sources used in the analysis. Section 3 presents the empirical results of the structural decomposition and sectoral linkage analysis, followed by a detailed discussion of these results in Section 4. Finally, Section 5 concludes with policy implications and directions for future research.

2. Methodology and Data

For this research, we utilized the national input–output (I-O) tables from the Asian Development Bank (ABD) for the years 2007, 2011, 2015, 2019, and 2023, focusing on Vietnam’s economic landscape. Notably, we used the most recent versions of the Vietnam I-O tables published by the ADB, encompassing a broad scope of sectors (35 in total). This updated dataset offers a more comprehensive and detailed representation of the country’s economic activities, facilitating a more nuanced analysis of structural changes. The research data was sourced from the ADB database, meaning we utilized information from reputable sources such as the Asian Development Bank (ADB), ensuring the dataset’s reliability and authenticity.

Table 1. The list of sectors selected for the study.

No.	Abbreviation	Sector
1	Agri	Agriculture, hunting, forestry, and fishing
2	Min	Mining and quarrying
3	Food	Food, beverages and tobacco
4	Text	Textiles and textile products
5	Leath	Leather, leather and footwear
6	Wood	Wood and products of wood and cork
7	Paper	Pulp, paper, paper, printing, and publishing
8	Coke	Coke, refined petroleum and nuclear fuel
9	Chem	Chemicals and chemical products
10	Rub	Rubber and plastics
11	Nonmet	Other non-metallic minerals
12	Bmetal	Basic metals and fabricated metal
13	Machin	Machinery, nec
14	Elec	Electrical and optical equipment
15	Trans	Transport equipment
16	Manu	Manufacturing, nec; recycling
17	Egas	Electricity, gas and water supply
18	Cons	Construction
19	Sale	Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of fuel
20	Wholes	Wholesale trade and commission trade, except of motor vehicles and motorcycles
21	Retail	Retail trade, except for motor vehicles and motorcycles; repair of household goods
22	Hotel	Hotels and restaurants
23	Inltran	Inland transport
24	Wattr	Water transport
25	Airtran	Air transport
26	Aux	Other supporting and auxiliary transport activities; activities of travel agencies
27	Post	Post and telecommunications
28	Finan	Financial intermediation
29	Real	Real estate activities
30	RM&Q	Renting of M&Eq and other business activities
31	Pubad	Public admin and defense; compulsory social security
32	Edu	Education
33	Health	Health and social work
34	Com	Other community, social and personal services
35	PriHH	Private households with employed persons

Note: “Machinery, nec” means machinery for exclusive use in an NACE industry.

below lists the 35 sectors selected for the study.

To capture and examine the dynamics of Vietnam’s economic structure over time, we strategically selected specific time intervals for comparison, using four-year periods between 2007 and 2023. This approach facilitated a comprehensive assessment of long-term structural changes. Furthermore, the availability of updated and expanded input–output tables for Vietnam from the Asian Development Bank (ADB), provided at constant price, significantly enhances the accuracy and robustness of our analysis. These data enable us to gain a deeper understanding of the country’s economic transformation over the selected period.

Our analytical process consists of three main stages: (i) identifying inter-sectoral linkages, (ii) decomposing output changes using structural decomposition techniques, and (iii) analyzing the acceleration or deceleration of structural shifts using the difference of differences (DoD) method.

• Step 1: Identifying the linkages

We began by examining Vietnam’s economic structure through descriptive statistics or backward and forward linkages using the Leontief inverse matrix $(I-\widehat{A}{)}^{-1}$. The sectoral output vector, represented by X, is influenced by the size of the final demand vector, denoted as F, and the technical relationship matrix involving products, referred to as A, as illustrated below.

$$X=AX+F$$

(1)

This can be expressed using the Leontief inverse

$$X={(I-A)}^{-1}F$$

(2)

where X is total output; $(I-\widehat{A}{)}^{-1}$ is the Leontief inverse matrix (L); A is the input coefficient matrix; I is the 35 × 35 identity matrix; and F is the vector of domestic final demand.

As outlined by Miller and Blair (2009), based on the foundational work of Hirschman (1958), the backward linkage (BL) indicator reflects the degree to which a given sector depends on inputs from other sectors, highlighting its role as a consumer of intermediate goods. In contrast, the forward linkage (FL) indicator captures the extent to which a sector supplies its output to other sectors, emphasizing its contribution to downstream production activities. These inter-sectoral linkages are quantified using Equations (3) and (4):

$$BackwardLinkage={\displaystyle \frac{{\sum }_{i}Lij}{\frac{1}{n}{\sum }_{ij}Lij}}$$

(3)

$$ForwardLinkage={\displaystyle \frac{{\sum }_{j}Lij}{\frac{1}{n}{\sum }_{ij}Lij}}$$

(4)

In the above equations, $L={\left[(I-\widehat{A})\right]}^{-1}$ represents the Leontief inverse matrix, where A is the technical coefficient matrix and n is the total number of sectors (in this study, n = 35). The term ${\sum }_{i}Lij$ denotes the column sum of the Leontief inverse, representing the backward linkage of sector “j”, while ${\sum }_{j}Lij$ denotes the row sum, reflecting the forward linkage of sector “i”.

• Step 2: Output decomposition using structural decomposition analysis

To examine Vietnam’s economic structural change, we applied a comprehensive methodology developed by Dietzenbacher and Los (1998). We begin by calculating the change in output across sectors over two time periods, denoted as $∆X_t$. By analyzing these output changes over time, we are able to identify the sectors that have driven economic growth and transformation.

According to Dietzenbacher and Los (1998), changes in sectoral output over time can be decomposed into two primary components—technical change (TC) and final demand change (FD)—as shown in Equation (5):

$$∆X_t=X_t-X_{t-1}=\underset{\mathrm{Technical}\mathrm{change}}{\underbrace{{\displaystyle \frac{1}{2}}∆L_t\left(F_t+F_{t-1}\right)}}+\underset{\mathrm{Final}\mathrm{demand}\mathrm{change}}{\underbrace{{\displaystyle \frac{1}{2}}∆F_t\left(L_t+L_{t-1}\right)}}$$

(5)

Here, $L_t={\left[(I-\widehat{A})\right]}^{-1}$ is the Leontief inverse matrix for year t; $F_t$ is the vector of final demand in year t. The first term represents the effect of changes in technology (i.e., input coefficients), while the second term captures the effect of changes in final demand across sectors.

Equation (6) then disaggregates the final demand effect into three components: consumption, investment, and exports. This breakdown enables a more precise identification of the individual contributions of each demand component to output growth across sectors. The decomposition can be represented by the following equation:

$${L_t∆}^{2}F=L_t{∆}^2{C}_t+L_t{∆}^2{I}_t+L_t{∆}^2{E}_t$$

(6)

Here, ${∆}^2{C}_t$, ${∆}^2{I}_t$, and ${∆}^2{E}_t$ denote the second differences in consumption, investment, and exports, respectively.

• Step 3: Analyzing Acceleration or Deceleration: the DoD method

The standard decomposition method fails to capture the dynamic acceleration or deceleration in output changes observed across different time intervals, as highlighted by (Huq & Ichihashi, 2023). To address this limitation, we adopted the difference of differences (DoD) decomposition method proposed by Huq and Ichihashi (2023), which enables the analysis of variations in the rate of output change between two consecutive periods. The DoD decomposition is formulated as follows:

$${∆}^2{X}_t={∆}_{X_t}-{∆}_{X_{t-1}}$$

(7)

Substituting Equation (5) into Equation (7), we obtain the following:

$${∆}^2{X}_t={\displaystyle \frac{1}{2}}\left\{\begin{array}{c}∆L_t\left(F_t+F_{t-1}\right)+\left(L_t+L_{t-1}\right)∆F_t-∆L_{t-1}\left(F_{t-1}+F_{t-2}\right)\\ -(L_{t-1}+L_{t-2})∆F_{t-1}\end{array}\right\}$$

(8)

Then, Equation (8) can be further decomposed into three components, each signifying specific increments or decrements in output change. As outlined by Huq and Ichihashi (2023), these components are

$${∆}^2{X}_t={\displaystyle \frac{1}{2}}\left\{(∆L_t{F}_t+L_t∆F_t)+\left({∆}^2{L}_t{F}_{t-1}+L_{t-1}{∆}^2{F}_t\right)-(∆L_{t-1}{F}_{t-2}+L_{t-2}∆F_{t-1})\right\}$$

(9)

Definitions of the components in the above equation are provided below:

-

The direct increment reflects output growth, primarily driven by recent changes in technology and final demand: ${\displaystyle \frac{1}{2}}\{(∆L_t{F}_t+L_t∆F_t)\}$.

-

The acceleration component captures the compounded effect of second-order changes in technology and final demand, indicating sectors with increasing momentum: $\left({∆}^2{L}_t{F}_{t-1}+L_{t-1}{∆}^2{F}_t\right)$.

-

The previous increment represents the lingering influence of earlier structural and demand changes: $(∆L_{t-1}{F}_{t-2}+L_{t-2}∆F_{t-1})$.

-

$∆L_t$ reflects technological change in production structure.

-

$∆F_t$ represents demand side change, such as increased exports or consumption.

Analyzing these components allows us to determine whether total output ${∆}^2{X}_t$ is positive or negative and to attribute the causes of this change to either technological advancements or shifts in final demand.

The accelerating component, in particular, highlights sectors undergoing sustained structural transformation. As noted by Huq and Ichihashi (2023), these sectors may warrant targeted policy support to harness their long-term growth potential.

3. Results

We begin our empirical investigation by estimating the linkages between production and trade using Equations (3) and (4) based on five Vietnam Input–Output (I-O) tables for the years 2007, 2011, 2015, 2019, and 2023. As noted by Khan (2020), a defining feature of I-O tables is their ability to reveal both direct and indirect inter-sectoral linkages, particularly between production activities and trade flows. This makes them a valuable analytical tool for assessing structural dynamics within an economy. The results identifying the top ten sectors with the strongest backward (BL) and forward linkages (FL) are presented in

Table 2. Top 10 sectors in Vietnam by backward linkage and forward linkage (2007–2023).

	2007		2011		2015		2019		2023
Rank	BL	FL	BL	FL	BL	FL	BL	FL	BL	FL
1	Food 1.50	Agri 2.38	Wood 0.72	Agri 2.03	Wood 1.40	Agri 2.00	Food 1.41	Agri 2.41	Pulp 1.23	Agri 2.03
2	Wood 1.41	Bmetal 1.86	Food 0.69	Coke 1.83	Food 1.37	Mining 1.99	Wood 1.31	Bmetal 1.85	Food 1.34	Bmetal 1.94
3	Manu 1.24	Elec 1.67	Pulp 0.64	Bmetal 1.61	Manu 1.24	Coke 1.88	Pulp 1.26	Mining 1.58	Wood 1.30	Mining 1.59
4	Machi 1.23	Whole 1.47	Manu 0.63	Mining 1.52	Pulp 1.24	Wholes 1.51	Manu 1.23	Food 1.42	Manu 1.28	Finan 1.45
5	Pulp 1.23	Chem 1.38	Trans 0.59	Wholes 1.43	Hotel 1.18	Bmetal 1.47	Bmetal 1.20	Elec 1.41	Rub 1.16	Egas 1.36
6	Trans 1.21	Elec gas 1.26	Agri 0.58	Chem 1.43	Trans 1.15	Chem 1.38	Rub 1.19	Finan 1.35	Cons 1.12	Food 1.33
7	Bmetal 1.17	Finan 1.15	Hotel 0.55	Finan 1.34	Coke 1.09	Food 1.34	Leath 1.14	Aux 1.18	Leath 1.12	Chem 1.27
8	Nonmet 1.14	Pulp 1.14	Watertran 0.55	Pulp 1.24	Cons 1.06	Finan 1.32	Nonmet 1.14	Chem 1.16	Coke 1.11	Pulp 1.23
9	Rub 1.03	Food 1.08	Coke 0.54	Food 1.18	Rub 1.05	Pulp 1.22	Elec 1.13	Pulp 1.15	Text 1.11	Aux 1.19
10	Agri 1.11	Nonmet 1.04	Rub 0.54	RM&Q 1.16	Nonmet 1.05	RM&Q 1.18	Cons 1.11	RM&Q 1.13	Machin 1.09	Wholes 1.15

.

Table 2 presents the sectors with the highest backward and forward linkages across five selected years (2007, 2011, 2015, 2019, and 2023) based on Vietnam’s input–output tables. These rankings provide insights into the structural interdependencies within the Vietnamese economy. As emphasized by Khan (2020), I-O analysis serves as a powerful tool to reveal both direct and indirect linkages between sectors, particularly in terms of production and trade integration.

Among the sectors examined, several demonstrate consistently strong backward linkages, indicating a high degree of dependence on inputs from other sectors. In particular, the food; beverages and tobacco; wood and wood products; and pulp, paper, printing, and publishing sectors frequently appear at the top of the ranking across multiple years. This highlights their extensive reliance on intermediate goods from other sectors, reflecting deeply embedded supply-chain relationships within the economy. Conversely, sectors with high forward linkages play a critical role as input suppliers to other industries, thus acting as key drivers of downstream production. Throughout the 2007–2023 period, the agriculture, hunting, forestry, and fishing sector consistently demonstrates strong forward linkages, indicating that its outputs are extensively utilized across other sectors.

Following agriculture, other sectors exhibiting high forward linkage effects include basic metals and fabricated metal products, coke, refined petroleum, and nuclear fuels and mining and quarrying. These sectors contribute significantly to the input requirements of downstream industries, providing essential raw materials and intermediate goods that underpin broader production systems. This result reflects the foundational nature of these sectors in supporting both upstream and downstream production, in line with Hirschman’s (1958) classical theory on unbalanced growth and more recent empirical studies (Skolka, 1989; Dietzenbacher & Los, 1998).

To understand structural transformation over time, we then applied Equation (5) to calculate changes in total output ($∆X_t$) and further decomposed these changes into the technical effect (TE) and final demand effect (FDE) using Vietnam’s national I-O tables as the analytical framework. The results are systematically presented in

Table 3. Top 10 sectors with highest total output change (in 2010 constant USD millions).

Structural Decomposition Analysis
2007–2011
Rank	Sector	Technical Effect	Final Demand Effect	Total Change
1	Food, beverages, and tobacco	3587.69	20,265,50	23,853.19
2	Agriculture, hunting, forestry, and fishing	−5256.47	20,039.84	14,783.36
3	Coke, refined petroleum, and nuclear fuel	7145.92	2258.75	9404.67
4	Construction	368.75	7176.46	7545.22
5	Textiles and textile products	481.41	6342.61	6824.03
6	Mining and quarrying	3791.18	2687.71	6478.89
7	Manufacturing nec; recycling	1375.87	3322.17	4698.04
8	Wholesale trade and commission trade, except for motor vehicles and motorcycles	1135.65	3155.89	4291.55
9	Financial intermediation	2519.19	1603.71	4122.91
10	Hotels and restaurants	113.63	3292.86	3406.50
2011–2015
1	Food, beverages, and tobacco	4788.49	11,677.67	16,466.17
2	Electrical and optical equipment	−4423.14	11,234.69	6811.54
3	Construction	872.82	5840.05	6712.87
4	Textiles and textile products	−1455.11	7703.08	6247.96
5	Wholesale trade and commission trade, except for motor vehicles and motorcycles	2619.35	3156.11	5775.47
6	Leather, leather products, and footwear	−780.98	5851.71	5070.73
7	Basic metals and fabricated metal	−522.26	5263.16	4740.90
8	Agriculture, hunting, forestry, and fishing	135.33	3874.07	4009.41
9	Coke, refined petroleum, and nuclear fuel	1836.27	1471.71	3307.98
10	Manufacturing nec; recycling	268.93	3017.60	3286.53
2015–2019
1	Electrical and optical equipment	1485.59	65,248.19	66,733.79
2	Construction	−383.66	29,175.96	28,792.29
3	Basic metals and fabricated metal	4978.36	14,400.51	19,378.87
4	Renting of M&Eq and other business activities	−1072.11	12,860.55	11,788.44
5	Textiles and textile products	−3839.45	14,851.66	11,012.20
6	Agriculture, hunting, forestry, and fishing	7853.64	2493.98	10,347.62
7	Other supporting and auxiliary transport activities; activities of travel agencies	−414.07	10,712.01	10,297.94
8	Post and telecommunications	−790.41	9115.55	8325.13
9	Inland transport	722.93	7149.17	7872.11
10	Retail trade, except for motor vehicles and motorcycles; repair of household goods	1386.95	5761.68	7148.64
2019–2023
1	Electrical and optical equipment	−4001.59	37,472.18	33,470.58
2	Food, beverages, and tobacco	−1651.67	20,989.68	19,338.01
3	Construction	−3282.04	20,031.89	16,749.85
4	Basic metals and fabricated metal	−1940.27	15,854.55	13,914.27
5	Agriculture, hunting, forestry, and fishing	−8794.38	17,971.11	9176.72
6	Transport equipment	−613.09	8042.67	7429.58
7	Wholesale trade and commission trade, except for motor vehicles and motorcycles	967.82	6284.29	7252.12
8	Manufacturing nec; recycling	3335.36	3647.89	6983.26
9	Post and telecommunications	1123.57	5461.62	6585.20
10	Chemicals and chemical products	2331.51	3529.82	5861.33

, which highlights the top ten sectors with the largest total output changes (in 2010 constant million USD) across four periods: 2007–2011, 2011–2015, 2015–2019, and 2019–2023. This enables a detailed assessment of the relative contributions of technical change and final demand to economic restructuring over time. As shown in Table 3, Vietnam’s economic transformation has been predominantly demand-driven across all periods, consistent with earlier work by Ngoc and Pierre (2004), who emphasized demand shocks in Vietnam’s post-reform industrialization.

The findings reveal a consistent pattern in which the leading sectors contributing to output growth are predominantly manufacturing- and service-related sectors. These results mirror the findings of Franke and Kalmbach (2005) and Erumban et al. (2019), who emphasized the catalytic role of key manufacturing sectors in shaping modern inter-industry dynamics. Notably, final demand effects overwhelmingly drive these changes, underscoring the importance of consumption, investment, and export dynamics in shaping sectoral performance.

Specifically, during the 2007–2011 period, the food, beverages, and tobacco sector led with a total output increase of USD 23,853.19 million, primarily driven by FDE (USD 20,265.50 million). The agriculture, hunting, forestry, and fishing sector followed, registering a total change of USD 14, 783.36 million, despite the negative TE (−USD 5256.47 million). Meanwhile, the coke, refined petroleum, and nuclear fuel sector posted strong growth (USD 9404.67 million), largely attributed to TE (USD 7145.92 million). Other notable sectors included construction (USD 7545.22 million) and textiles and textile products (USD 6824.03 million), both propelled by robust demand.

In the subsequent period, 2011–2015, the food, beverages, and tobacco sector remained the top contributor, though its total change declined to USD 16,466.17 million. The electrical and optical equipment sector experienced significant growth (USD 6811.54 million), driven entirely by FDE, despite a negative contribution of TE (−USD 4423.14 million). The construction sector continued to expand, recording a total output change of USD 6712.87 million. Other key contributors included textiles and textile products (USD 6247.96 million) and wholesale trade and commission trade (except motor vehicles and motorcycles) (USD 5775.47 million), further confirming the sustained impact of final demand across various sectors.

A major shift occurred in the 2015–2019 period. The electrical and optical equipment sector surged to the top, with a remarkable total output change of USD 66,733.79 million, nearly all of which stemmed from FDE (USD 65,248.20 million), marking the sector’s technological ascent. The construction sector followed with USD 28,792.29 million, with this growth also being demand-driven. The basic metals and fabricated metal sector ranked third, with a total change of USD 19,378.87 million, reflecting a balance of TE and FDE influences. Other emerging sectors such as renting of machinery and equipment and other business activities (USD 11,788.44 million) and supporting transport and travel services (USD 10,296.94 million) also entered the top ranks, indicating diversification of growth engines.

The latest period (2019–2023) reflects evolving sectoral dynamics. The electrical and optical equipment sector remained dominant, recording USD 33,470.58 million in total output change, despite a negative TE (−USD 4001.59 million), with FDE accounting for the entire net gain (USD 37,472.18 million). The food, beverages, and tobacco sector followed with USD 19,338.01 million, again driven by FDE. Construction (USD 16,749.85 million) and basic metals and fabricated metal (USD 13,914.27 million) remained key contributors. The agriculture, hunting, forestry, and fishing sector displayed a total change of USD 9176.72 million, with FDE (USD 17,971.11 million) exceeding the negative TE (−USD 8794.38 million), reflecting persistent structural challenges despite rising demand. Other notable sectors included transport equipment, wholesale trade, and telecommunications.

Across all periods, the final demand effect (FDE) consistently emerges as the dominant driver of output growth, reflecting the strong influence of domestic consumption, investment activity, and export performance. The electrical and optical equipment sector stands out for its exponential rise, driven almost entirely by FDE, signifying Vietnam’s deepening engagement with technology-intensive industries. In contrast, the agriculture hunting, forestry, and fishing sector displays volatile dynamics, with large variations in both TE and FDE over time. The frequent presence of negative TE suggests persistent inefficiencies or technological stagnation, despite growing downstream demand.

In the next step, the final demand effect was disaggregated into its three components—consumption effect, investment effect, and export effect—based on Equation (7). The results are presented in Figure 1, Figure 2, Figure 3 and Figure 4, revealing that export-led growth has been a dominant force, especially in electrical and optical equipment and textiles. This result is consistent with Vietnam’s proactive trade strategy, as shown in Abbott et al. (2009), who pointed out the significant export gains following Vietnam’s entry into key bilateral and multilateral trade agreements. Similarly, Uy (2013) and Vu (2017) argue that trade openness accelerates structural change, particularly by relocating resources toward high-productivity, export-oriented sectors.

Figure 1, Figure 2, Figure 3 and Figure 4 illustrate the decomposition of the final demand effect (FDE) into three components—consumption, investment and exports—for the top 10 sectors contributing to output growth in Vietnam between 2007 and 2023.

During the period 2007–2011, the food, beverages and tobacco sector recorded the highest total FDE, with exports being the dominant driver, followed by consumption and investment. The construction sector was primarily driven by investment, reflecting Vietnam’s growing infrastructure development during this period. The textile sector and electrical and optical equipment sector also showed significant export-driven growth; however, the electrical sector showed a negative investment effect, which slightly offset its total FDE. Sectors such as the hotel, manufacturing, and leather and footwear sectors experienced modest contributions from both consumption and export effects, while public administration, communications, and postal services were primarily driven by the consumption effect.

For the 2011–2015 period, the electrical and optical equipment sector led with the highest total FDE, overwhelmingly driven by exports, while showing a negative investment effect. This reflects the sector’s strong integration into global value chains and dependence on foreign market demand. The food, beverages, and tobacco sector ranked second, with growth largely supported by consumption, followed by exports, reflecting strong domestic demand and stable international market access. The leather and footwear sector showed a similar trend, led by export effects with a minor contribution from other components. Sectors such as textiles, healthcare, and education displayed a more balanced contribution, with the consumption effect being prominent, highlighting rising domestic demand for essential services.

Investment effects were particularly influential in sectors such as construction and telecommunications, especially during the 2015–2019 period. This trend corresponds with rising infrastructure investment and foreign direct investment (FDI), which supported domestic capacity building and economic modernization. In parallel, consumption played a leading role in sectors such as retail trade, food, beverages and tobacco, and financial intermediation during the 2011–2015 period, reflecting rising household incomes and the emergence of a growing middle class.

The post-COVID-19 period (2020–2023) also marked a subtle rebalancing of growth drivers. While export-led sectors remained prominent, domestic investment and consumption played a comparatively greater role in supporting growth in sectors such as construction, telecommunications, and retail trade, aligning with Dempster (2014) and Dhahri and Omri (2020), who advocate for internal demand stimulation as a response to external shocks. These examples of domestic rebalancing reflect Vietnam’s shift toward strengthening internal economic resilience amid global uncertainty.

A persistent trend across all periods is the dominant role of export-driven growth in key manufacturing sectors, particularly electrical and optical equipment, basic metals, and textiles and textile products. These sectors benefitted from Vietnam’s deepening integration into global value chains, supported by its participation in bilateral and multilateral free trade agreements (FTAs). Their performance reflects strong external demand and Vietnam’s strategic positioning as a manufacturing hub for export markets.

Based on the results of our analysis of inter-sectoral linkages and structural decomposition, several sectors clearly stand out as key drivers of Vietnam’s economic transformation from 2007 to 2023. These include food, beverages and tobacco, electrical and optical equipment, basic metals and fabricated metal products, textiles and textile products, agriculture, and construction. Their repeated presence among the top contributors to output growth and their strong forward or backward linkages underscore their central role in shaping production networks, stimulating final demand, and facilitating export expansion. These sectors not only reflect Vietnam’s evolving industrial structure but also highlight strategic areas for contributing investment, productivity enhancement, and policy support to sustain long-term development.

In the next step, we estimated the structural decomposition of output change using the second-order difference method, as formulated in Equations (8) and (9). Following the approach of Huq and Ichihashi (2023), the total change in sectoral output is disaggregated into three distinct components.

As shown in

Table 4. The results of the top 10 sectors with highest difference of difference output changes for Vietnam (2015, 2019, and 2023) (in million USD constant price).

Rank	Sector	Dir. Inc	Acc Part	Pre Inc	∆2Xt
1	Food	9392.66	20,869.38	−11,884.39	42,146.45
2	Coke	811.67	7671.26	−2384.71	10,867.65
3	Mining	1686.99	6458.22	−2138.35	10,283.58
4	Wholes	3668.56	5521.69	1331.61	7858.65
5	Trans	3578.73	4002.10	−161.12	7741.96
6	Chem	3101.11	3814.09	871.21	6043.98
7	Manu	3883.08	2886.60	792.61	5977.07
8	Leather	1335.37	2268.91	−797.28	4401.57
9	Machinery	1005.40	1722.59	−72.92	2800.91
10	Rubber	2834.46	1272.28	1364.65	2742.09

, the food sector recorded the highest total output change (∆²X_t = 42,146.45 million USD), driven predominantly by a significant acceleration component (USD 20,869.39 million), followed by direct increment (USD 9392.67 million). Although this sector showed a negative contribution from the previous increment (−USD 11,884.40 million), the strong recent and accelerating effects suggest sustained growth momentum and increased demand in recent periods. The coke and refined petroleum sector ranked second, with a total output change of 10,867.66. The bulk of this change stemmed from the acceleration component (USD 7671.27 million), indicating a trend of long-term growth. Similarly, the mining and wholesale trade sectors followed closely, with ∆²X_t values of 10,283.58 and 7858.65, respectively, each showing a strong influence from recent demand shifts and positive accelerative effects. Sectors such as the transport, chemicals, manufacturing, and leather sectors also displayed substantial output increases, largely attributed to consistent or accelerating trends, despite some fluctuations from previous increments.

The acceleration component plays a critical role in identifying sectors undergoing long-term structural change. Sectors like food, coke, and mining show large positive values in this component, indicating that they are currently experiencing rapid, sustained expansion. According to Huq and Ichihashi (2023), such trends warrant targeted policy attention, including investment incentives, infrastructure development, and workforce training to support continued growth.

By contrast, sectors with negative or marginal acceleration (e.g., leather and machinery) may require closer examination to determine whether structural stagnation, volatility in final demand, or technological constraints are limiting their development.

4. Discussion

In developing countries, the manufacturing sector plays a critical role in driving economic transformation, not only through its direct contributions to output and employment but also by generating significant spillover effects across other sectors. Structural change, defined as the reallocation of economic activity from agriculture and low-productivity services to manufacturing and modern services, has long been recognized as a central pathway to sustainable economic growth (Franke & Kalmbach, 2005). This transition is often accompanied by technological progress and innovation, enhancing productivity and stimulating broader industrial upgrading (Erumban et al., 2019). In the case of Vietnam, our analysis confirms that the manufacturing sector has served as a principal engine of growth over the past two decades, particularly in the period between 2007 and 2023.

The empirical results from our structural decomposition analysis highlight a group of manufacturing subsectors—food, beverages, and tobacco; electrical and optical equipment; basic metals; textiles and textile products; and leather and footwear—as the dominant contributors to total output growth. These sectors consistently ranked among the top ten in terms of output changes, indicating their centrality in Vietnam’s economic structure. Their prominence can be attributed to a combination of comparative advantages, including low labor costs, a strategically advantageous geographical location, an abundant workforce, and a stable macroeconomic environment. Additionally, Vietnam’s proactive investment and industrial policies have promoted export-oriented growth and improved infrastructure, playing a key role in attracting foreign direct investment (FDI) to these sectors.

From 2007 to 2023, Vietnam’s industrial landscape was profoundly shaped by its deepening integration into the global economy. The country engaged in a series of bilateral and multilateral trade agreements that opened new export markets and enhanced its attractiveness to international investors. Key milestones include the ASEAN Free trade Area (AFTA), the Vietnam US Bilateral Trade Agreement, its accession to the World Trade Organization (WTO) in 2007, and, more recently, its participation in the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) and the EU–Vietnam Free Trade Agreement (EVFTA). These agreements collectively reduced tariff and non-tariff barriers, introduced regulatory reforms, and encouraged technology transfer and innovation.

These trade and investment frameworks facilitated a rapid expansion of export-oriented manufacturing. For example, the textile sector experienced exceptional growth from 2007 to 2019, making Vietnam one of the world’s leading suppliers to global fashion brands. Similarly, the electronics and electrical equipment sector, driven by investments from major firms such as Samsung and Intel, experienced exponential growth, eventually surpassing traditional sectors in both scale and complexity. As our findings indicate, by 2015–2019 and especially 2019–2023, electrical and optical equipment had become the top contributor to total output growth, underscoring Vietnam’s shift toward more technology-intensive and high-value-added manufacturing.

However, this growth trajectory was not without challenges. The COVID-19 pandemic, beginning in early 2020, had a significant impact on Vietnam’s economy, exposing structural weaknesses in supply chains, labor markets, and sectoral resilience. While the agriculture and food sectors remained relatively stable, supported by domestic demand, the textile sector experienced a sharp decline. Our results show that textiles and textile products, which were previously among the top-performing sectors, dropped out of the top ten in the 2019–2023 period. This downturn is likely attributable to a combination of factors—disruptions in global supply chains, decreased demand from key markets, rising competition from regional rivals such as Bangladesh and Cambodia, and a growing need for automation and digitalization in a labor-intensive industry—as mentioned by Huq and Ichihashi (2023).

The pandemic also served as a catalyst for broader structural shifts. Sectors that could adapt to remote work, facilitate digital transformation, and automate production fared better during this period. The resilience of the electrical and optical equipment sector, despite a negative technical effect, suggests that its performance was sustained by continued external demand for electronics and its integration into regional and global production networks. Moreover, sectors such as post and telecommunications and transport equipment began to gain prominence, reflecting changes in consumer behavior and logistics requirements in a post-pandemic context.

Another important observation from our results is the persistent but evolving role of the agriculture, hunting, forestry, and fishing sector. While it did not consistently rank among the top sectors in total output change, it remained significant in terms of final demand effect (FDE), particularly during periods of economic uncertainty. The sector’s negative technical effects (TE) in recent years point to ongoing challenges such as low productivity, fragmented production, and limited technological adoption.

The findings of our study align with prior research conducted by Huq and Ichihashi (2023) and Ha and Trinh (2018). Huq and Ichihashi highlighted Vietnam’s successful diversification of its manufacturing base and its reliance on multiple leading sectors to sustain growth. They also emphasized the critical role of FTA in accelerating structural transformation. Ha and Trinh (2018), using earlier I-O data tables from 2012 and 2016, identified the food, oil and gas, and manufacturing sectors as central drivers of inter-sectoral linkages, reinforcing the idea that structural change in Vietnam has been both gradual and multifaceted.

In summary, the evolution of Vietnam’s economic structure over the past two decades illustrates the country’s remarkable transition from an agriculture-based economy to one increasingly defined by export-oriented, high-value-added manufacturing. While free trade agreements and FDI have been instrumental in this process, recent global shocks, particularly the COVID-19 pandemic, have underscored the importance of sectoral resilience, technological upgrading, and policy adaptability. Moving forward, sustaining growth will require deeper investment in human capital, digital infrastructure, and green technology, particularly as global trade dynamics shift and sustainability becomes a central policy priority.

5. Conclusions

In developing countries, the identification and promotion of key industries play a crucial role in fostering both poverty reduction and economic development. Successful examples of leading industries can be observed in developed nations, including the IT industry in the United States, the automobile industry in Japan, and the electric equipment industry in South Korea, all of which have contributed significantly to their respective countries’ growth. Despite being classified as a developing country, Vietnam has experienced rapid economic growth over the past two decades. This study has provided a comprehensive examination of Vietnam’s economic structural transformation over the 2007–2023 period through the application of input–output analysis and structural decomposition techniques. By analyzing changes in total output across four distinct timeframes and decomposing them into technical effects (TE) and final demand effects (FDE), the research identified the sectors that have most significantly contributed to Vietnam’s economic growth and transformation.

The findings reveal a clear shift in the nation’s economic structure, from traditional primary sectors to a more diversified manufacturing and service base. Key manufacturing sectors, including food, beverages and tobacco, electrical and optical equipment, basic metals, textiles, and leather and footwear, consistently emerged as the leading contributors to output growth. The dominant role of final demand effects across all periods suggests that Vietnam’s growth has been largely driven by rising domestic consumption, investment, and export demand rather than productivity gains alone.

Vietnam’s successful integration into global value chains, facilitated by its active engagement in a wide range of bilateral and multilateral free trade agreements (FTAs), has significantly enhanced the competitiveness of its manufacturing sector. Agreements such as the EVFTA, Vietnam’s participation in the CPTPP, and Vietnam’s accession into the WTO have provided the country with greater market access and incentivized institutional reforms. The country’s receipt of foreign direct investment (FDI), supported by a young labor force, competitive wages, and favorable policies, has further accelerated industrial expansion and export diversification.

However, the analysis also highlights emerging challenges. The COVID-19 pandemic had a disruptive impact on global and domestic production networks, exposing vulnerabilities in supply chains and revealing technological limitations in certain labor-intensive sectors such as the textiles sector. Moreover, sectors such as agriculture and textile manufacturing, though still important, exhibited declining technical efficiency, indicating the need for modernization, innovation, and resilience-building.

Importantly, this study underscores that while Vietnam has made significant progress in transitioning toward a more industrialized and globally integrated economy, sustaining this momentum will require a shift in focus. Future growth will depend not only on external demand but also on productivity-enhancing investments, digital transformation, and green industrial policies. Upgrading technology, strengthening value chain linkages, and building a skilled workforce are critical factors for maintaining competitiveness in an increasingly complex and uncertain global environment.

In conclusion, Vietnam’s structural transformation over the past two decades has been remarkable. The country’s ability to harness global trade opportunities and attract investment has laid a strong foundation for continued growth. Moving forward, aligning economic policy with sustainability, inclusiveness, and resilience will be essential to ensure that this transformation leads to broad-based, long-term development.

Looking ahead, future research could explore several promising avenues. First, more detailed form-level or regional analysis could complement the national I-O-based approach, shedding light on spatial disparities or enterprise-level innovation dynamics. Second, extending the I-O framework to incorporate environmental and social indicators such as carbon emissions and labor standards would allow researchers to assess the sustainability of structural change. Third, integrating behavioral factors and demand elasticities into hybrid I-O models could offer more nuanced predictions under varying policy or market scenarios. Lastly, comparative studies between Vietnam and other emerging economies could deepen our understanding of the unique or shared patterns in structural transformation under globalization.