Economic Spillover Effects of Environmental Industries in ASEAN: An Input-Output and Panel Analysis

Abstract

This study examines the economic role of environmental industries in the major Association of Southeast Asian Nations (ASEAN) economies using the environmental input-output (EIO) framework and multiregional input-output (MRIO) tables provided by the Asian Development Bank (ADB). It evaluates the production-inducement effects, value-added inducement effects, and inter-industry linkage structures of environmental industries in the five ASEAN countries: Indonesia, Malaysia, the Philippines, Thailand, and Vietnam. The results reveal three main findings. First, infrastructure-related environmental sectors, particularly the electricity, gas, and water supply sectors, exhibit strong inter-industry linkages and generate substantial production spillover effects across the ASEAN economies. Second, significant cross-country heterogeneity exists in value-added inducement effects, reflecting differences in industrial maturity, domestic value-chain depth, and institutional capacity. Third, the economic effectiveness of environmental industries depends not only on their scale, but also on their structural integration within national and global production networks. These findings suggest that environmental industries in ASEAN function not only as environmental management tools, but also as strategic drivers of economic growth.

1. Introduction

The natural environment of the Association of Southeast Asian Nations (ASEAN) serves as both the cornerstone of regional economic development and a strategic pillar of global environmental governance. Asia accounts for approximately 67% of global agricultural production (Mendelsohn, 2014), and ASEAN member states exhibit a high degree of dependence on agriculture and livestock for both gross domestic product (GDP) and employment. Despite occupying only 3% of the world’s land area, ASEAN is a critical biodiversity hotspot, hosting approximately 18% of all known species (ASEAN Centre for Biodiversity, 2010). The World Bank (2005) estimated the annual economic value of watershed protection services provided by ASEAN forests at US$17.2 billion, while the direct economic impact of ecosystem-based tourism and primary industries is reported to be approximately US$3 trillion annually (Academy of Sciences Malaysia, 2020).

Despite this significant ecological and economic potential, the region faces structural damage to its ecosystems driven by deforestation, indiscriminate logging, rapid urbanization, and industrialization. Projections suggest that climate change could reduce grain yields by more than 5% by 2050 (Woetzel et al., 2020), further exacerbating the socio-economic vulnerabilities of ASEAN countries. Given the high proportion of smallholder farms, climate risks are likely to trigger income instability, weaken food security, and intensify regional imbalances. While growth strategies centered on natural resource extraction may yield short-term gains, they create a structural dilemma characterized by environmental degradation and long-term growth constraints (Touch et al., 2024).

These challenges necessitate a re-evaluation of traditional growth paradigms. This study integrates three theoretical frameworks to underpin the analysis. First, Sustainable Development Theory (World Commission on Environment and Development, 1987) emphasizes the equilibrium between economic growth, environmental conservation, and social equity; this provides a foundation for interpreting environmental industries as potential growth drivers rather than mere regulatory costs. Second, the Environmental Kuznets Curve (EKC) (Grossman & Krueger, 1994) suggests that environmental degradation diminishes once a certain income threshold is reached. However, given the industrial structures and resource dependence of ASEAN countries, this transition may not materialize automatically; thus, policy intervention and structural transformation are critical factors. Third, Green Growth and Environmental Industry Theory (Hallegatte et al., 2012) proposes that environmental regulations and technological innovation can enhance productivity and foster new industries. This perspective aligns with the Porter Hypothesis, suggesting that the development of environmental industries can generate macroeconomic spillover effects through employment, value addition, and industry linkages.

Based on this framework, this study analyzes the “ASEAN-5” economies: Indonesia, Malaysia, the Philippines, Thailand, and Vietnam. These countries represent the middle- to high-income bracket within ASEAN, and their population sizes and industrial structures significantly influence regional economic and environmental policies. Specifically, this study quantitatively examines the economic ripple effects of environmental industries through linkage analysis from a macroeconomic perspective. The objectives are to: (1) assess whether environmental industries function as growth drivers rather than cost centers, and (2) evaluate their potential to facilitate structural transformation while achieving sustainable growth and climate change mitigation. Ultimately, this study provides empirical evidence to support green transition strategies in ASEAN and contributes to the theoretical understanding of environmental industries in developing economies.

2. Literature Review

Numerous studies (Ali et al., 2022; Sriyana, 2019; Wang et al., 2019; Xu et al., 2024; Zhao et al., 2023) have examined the nexus between environmental regulation, environmental industries, and economic growth, reflecting a paradigm shift from traditional trade-off perspectives toward dynamic, integrative analytical frameworks. Early scholarship (Crifo et al., 2017; Eliwa et al., 2019; Fonseka et al., 2019; Ge & Liu, 2015) emphasized the compliance cost burden, suggesting that stringent environmental policies impose additional costs on firms, thereby undermining industrial competitiveness. This conventional view has been challenged by the Porter Hypothesis, which posits that well-designed environmental regulations can catalyze innovation, enhance resource efficiency, and ultimately bolster both firm-level and macroeconomic performance (Porter & van der Linde, 1995).

Building upon this theoretical evolution, subsequent research (Herrador & Van, 2024; Ng et al., 2023; Phan, 2024) has increasingly conceptualized environmental industries as endogenous drivers of economic transformation rather than mere passive outcomes of regulatory pressure. Sectors such as waste management, pollution control, and renewable energy are now identified as pivotal sources of technological innovation, job creation, and cross-sectoral spillovers. Within the green growth framework, environmental industries are viewed as productive sectors that contribute to long-term economic expansion through innovation-driven productivity gains and structural upgrading (Hallegatte et al., 2012).

Methodologically, Input-Output (I–O) analysis has emerged as a cornerstone for assessing the structural economic impacts of environmental industries. The I–O framework enables the systematic identification of inter-industry linkages and the quantification of production and value-added multipliers. Miller and Blair (2009) demonstrated that linkage analysis provides a rigorous basis for evaluating sectoral dependencies and spillover effects across the entire economic system. Extending this approach, Environmental Input-Output (EIO) models incorporate environmental resource consumption and pollution emissions into conventional structures, facilitating a comprehensive assessment of the economic–environmental nexus. For instance, Feng et al. (2017) utilized EIO models to quantify the impacts of pollution control activities, emphasizing the necessity of integrating environmental externalities into macroeconomic analysis.

Recent scholarship has increasingly utilized Multi-Regional Input–Output (MRIO) models to address global sustainability challenges. Notably, Lee et al. (2025) quantified household carbon footprints using recent South Korean data, while Wiebe et al. (2026) examined the sensitivity of global input coefficients for renewable energy, linking technical shifts to Sustainable Development Goal (SDG) indicators. Complementing these perspectives, this study employs influence and sensitivity coefficients to identify key industrial drivers. The significance of this methodological choice is further supported by Bartzokas (2026), who demonstrated how financial mechanisms facilitate green transitions in emerging economies, thereby providing a practical policy context for the structural findings presented here.

Despite these advancements, the empirical literature (Antweiler & Harrison, 2003; Ayerbe & Gorriz, 2001; Baldassarre, 2025; Xu et al., 2024; Fabrizi et al., 2024) remains heavily concentrated on advanced economies in Europe and North America, where environmental industries are relatively mature. Consequently, these findings may not be directly generalizable to emerging economies where rapid industrialization coexists with intensifying environmental pressures.

The ASEAN region represents a critical yet underexplored empirical context, characterized by high environmental vulnerability and a growing policy commitment to sustainable development. Initiatives such as the ASEAN Smart Cities Network (ASCN, 2025) exemplify technology-driven efforts to address urban environmental challenges while strengthening regional competitiveness. However, systematic empirical analyses of the macroeconomic spillover effects and inter-industry linkage structures within ASEAN remain limited. Existing studies have primarily focused on governance dimensions through political ecology or critical political economy lenses, highlighting the role of non-state actors and transnational networks (Hirsch, 2006; Yasuda, 2015; Young & Ear, 2021). While these provide valuable institutional insights, they offer limited quantitative evidence regarding the structural economic role of environmental industries. Furthermore, research on regional cooperation has largely concentrated on state-led mechanisms and sovereignty-sensitive governance (Aljunied, 2025; Koh & Karim, 2020; Varkkey, 2017), resulting in a disconnect between institutional analysis and quantitative economic modeling.

To address this gap, this study adopts an integrated analytical framework that combines EIO analysis with panel regression techniques. Specifically, it aims to: (1) quantify the production and value-added inducement effects of environmental industries; (2) identify forward and backward linkage structures across sectors; and (3) empirically examine the determinants of environmental industry development across ASEAN economies. By bridging environmental governance literature with quantitative economic analysis, this study provides new insights into environmental industries as drivers of sustainable economic transformation in developing regions.

3. Methodology

3.1. Reclassification of the Environmental Industry

Prior to estimating economic spillover effects using I–O tables, this study first establishes a classification framework for the environmental industry that is consistent with the analytical objectives. Across the ASEAN countries, the scope and scale of the environmental industry are defined differently according to national industrial structures and policy priorities. This variation indicates that the environmental industry is not confined to a single industrial category; rather, it is structurally embedded across all sectors, from primary and secondary to tertiary and emerging industries.

More specifically, the pollution prevention and renewable energy sectors are closely associated with primary industries that depend on natural resource utilization. In contrast, decarbonization and eco-friendly production process transitions are structurally linked to secondary industries, particularly manufacturing. Meanwhile, waste management, environmental remediation services, and green finance belong primarily to service and future-oriented industries. Through forward and backward inter-industry linkages, these activities generate economy-wide ripple effects. This structural interconnectedness suggests that the environmental industry should be understood not as a discrete sector but as a cross-sectoral industry that permeates the entire production system.

Accordingly, supplementary reclassification is necessary to quantitatively assess the economic impact of the environmental industry within the conventional I–O framework. To this end, this study reconstructs the environmental industry classification based on the definition provided by the Environmental Business International (EBI) and the international standards developed by the Organization for Economic Cooperation and Development (OECD).

The proposed classification system distinguishes between core and related activities. Core activities include industrial operations aimed at enhancing environmental protection and resource efficiency. Related activities encompass industries that indirectly support environmental performance or generate derivative environmental benefits. Furthermore, each category was systematically organized into three functional sectors—equipment, services, and resources—in accordance with international classification standards. This structure enables one-to-one concordance between environmental industry components and the corresponding sectors in the I–O matrix.

The resulting reclassification framework (Table 1) provides a rigorous analytical foundation for identifying upstream and downstream industrial linkages in the environmental industry and for precisely estimating inducement and value-added inducement effects within the ASEAN economies.

Table 1. Environmental Industry Classification Framework.

Category	Functional Type	Sub-Sector
Core Activities	Equipment	Water treatment equipment
		Air pollution control equipment
		Waste treatment equipment
	Services	Solid waste treatment
		Hazardous waste treatment
		Soil remediation and industrial environmental services
		Water treatment services
Related Activities	Equipment	Environmental equipment and information systems
		Process optimization and pollution prevention technologies
	Services	Environmental consulting and engineering
		Environmental analytical and testing services
Resources		Water resources
		Resource recovery and recycling
		Environmental and renewable energy resources

Note: The classification was reconstructed by the author based on the environmental goods and services sector (EGSS) framework of the Organisation for Economic Co-operation and Development (OECD) and industry definitions provided by Environmental Business International (EBI).

3.2. Integration with I–O Tables

For quantitative estimation, these domains were further categorized into equipment, services, and resources. This tri-sectoral approach allows for precise one-to-one mapping with detailed sectors in the national I–O tables. This systematic reclassification provides a robust analytical foundation for identifying backward and forward linkage effects and estimating production-inducement and value-added-inducement effects across the macroeconomy.

This study applies the EIO methodology developed by Feng et al. (2017) to evaluate the economic viability of environmental industries in the major ASEAN-5 countries. The EIO framework integrates environmental resources into the conventional I–O system by treating environmental resource use as economic inputs, capturing the output effects of economic activities on environmental resources, and accounting for pollutant emissions and environmental governance throughout the production process (Sun, 2005).

The empirical analysis employs multiregional I–O tables provided by the Asian Development Bank (ADB). The key structural coefficients are derived, including the input coefficients and value-added coefficients. Following the standard I–O framework (Miller & Blair, 2009), this approach enables the estimation of final demand-induced output, value-added inducement effects, and inter-industry spillover effects. The ADB International Input-Output Tables provide I–O tables for 64 countries. Table 2 illustrates the basic structure of an I–O table for a single industry. The vertical series consists of the sum of intermediate inputs and value added, while the horizontal segment is divided into two parts: intermediate demand for intermediate goods, final demand for consumer goods, and capital goods. The sum of these constitutes total demand, which is calculated by subtracting income from total output. Furthermore, the total output of each industrial sector and corresponding total inputs are always equal. In the industry-related table in Table 2, various multipliers can be derived from the identity Total Output = Intermediate Demand + Final Demand − Imports, which can be used to calculate production and value-added effects.

Table 2. The structure of Multiregional I–O.

	Outputs		Intermediate Transactions			Final Demand				Total Output
Inputs			1	…	n	1	…	n	Exports
Intermediated inputs		1	Z11	…	Z1n	Y	…	Y	Y	X1
		:	:		:	:		:	:	:
		n	Zn1	…	Znn	Y	…	Y	Y	Xn
Imports			Z	…	Z	Y	…	Y	0	Y = ZI + YI
Value added			V1	…	Vn
Total inputs			X1	…	Xn

Source: drawn by author based on MRIO (2024).

The analytical procedure was as follows. First, environmental industries are classified based on sectoral concordance within the ADB I–O tables. Second, the inter-industry ripple effects of these classified sectors were estimated using the Leontief demand-driven model. The I–O framework is particularly appropriate because it quantifies inter-industry dependencies through input coefficients, thereby capturing structural linkages across sectors.

The input coefficient is defined as:

$$\mathit{a}\mathit{i}\mathit{j}={\displaystyle \frac{\mathit{x}\mathit{i}\mathit{j}}{\mathit{X}\mathit{j}}}$$

(1)

where a_ij denotes the input coefficient representing the intermediate input from sector i to sector j, x_ij is the transaction value from sector i to sector j, and Xj is the total output of sector j. This coefficient captures the direct production relationship between sectors.

The value-added coefficient is calculated as:

$$\mathit{v}\mathit{j}={\displaystyle \frac{\mathit{V}\mathit{j}}{\mathit{X}\mathit{j}}}$$

(2)

where V_j denotes the value added in sector j. By construction, the column-wise sum of the input and value-added coefficients satisfies

$$\sum _{\mathit{i}}\mathit{a}\mathit{i}\mathit{j}+\mathit{v}\mathit{j}=\mathbf{1}$$

(3)

The production-inducement effect is derived from the standard Leontief system:

AX + Y − M = X

(4)

where A is the matrix of input coefficients, X is the gross output vector, Y is final demand, and M represents imports. Rearranging yields the Leontief inverse form, which enables the estimation of the total production inducement resulting from changes in final demand.

The value-added inducement effect is obtained by multiplying the total induced output by the value-added coefficient.

V = v_jX

(5)

This allows us to assess the contribution of environmental industries to national income in major ASEAN economies.

In addition, this study evaluates the structural position of environmental industries within national production networks by computing normalized backward and forward linkage indices derived from the Leontief inverse matrix, L = (I − A)⁻¹. Following standard I–O linkage analysis, the backward linkage (influence coefficient) of sector j is defined as the column average of the Leontief inverse, normalized by the overall mean of L:

$$\mathit{B}\mathit{L}\mathit{j}\mathbf{=}{\displaystyle \frac{\frac{\mathbf{1}}{\mathit{n}}{\sum }_{\mathit{i}\mathbf{=}\mathbf{1}}^{\mathit{n}}\mathit{L}\mathit{i}\mathit{j}}{\frac{\mathbf{1}}{\frac{\mathbf{1}}{\mathit{n}\mathbf{2}}{\sum }_{\mathit{i}\mathbf{=}\mathbf{1}}^{\mathit{n}}{\sum }_{\mathit{j}\mathbf{=}\mathbf{1}}^{\mathit{n}}\mathit{L}\mathit{i}\mathit{j}}}}$$

(6)

Similarly, the forward linkage (sensitivity coefficient) of sector i is defined as the row average of the Leontief inverse, normalized by the same overall mean:

$$\mathit{F}\mathit{L}\mathit{i}\mathbf{=}{\displaystyle \frac{\frac{\mathbf{1}}{\mathit{n}}{\sum }_{\mathit{i}\mathbf{=}\mathbf{1}}^{\mathit{n}}\mathit{L}\mathit{i}\mathit{j}}{\frac{\mathbf{1}}{\mathit{n}\mathbf{2}{\sum }_{\mathit{i}\mathbf{=}\mathbf{1}}^{\mathit{n}}{\sum }_{\mathit{j}\mathbf{=}\mathbf{1}}^{\mathit{n}}\mathit{L}\mathit{i}\mathit{j}}}}$$

(7)

where n denotes the number of sectors in the I–O system. By construction, the economy-wide mean of both indices equals 1, so values greater (less) than 1 indicate above-average (below-average) linkage effects. Through these estimations, the study quantitatively evaluates the production-inducement, value-added, and network spillover effects of environmental industries in the ASEAN-5 countries. The results provide empirical evidence that climate change mitigation and environmental pollution response policies do not necessarily constrain economic growth; rather, environmental industries can function as strategic growth drivers within regional production systems.

4. Results

This study utilizes the ADB multiregional I–O (MRIO) database (2024) to analyze the economic impacts of the environmental industries in the ASEAN-5 economies. Specifically, it estimates production inducement effects, value-added inducement effects, and forward and backward linkage effects within a Leontief demand-driven framework. This approach allows for the identification of both direct and indirect economic spillovers while simultaneously capturing the structural interdependencies across sectors. By combining the inducement and linkage indicators, this analysis provides a comprehensive assessment of the scale, depth, and systemic integration of environmental industries within regional production networks.

4.1. Production-Inducement Effect

Input coefficients were derived to understand the production inducement effects of the ASEAN-5’s environmental industries, as shown in Table 3. The input coefficients in the I–O table represent the ratio of intermediate inputs, such as raw materials and parts, required for a specific industrial sector to produce one unit of output. These coefficients are useful for understanding the production technology structure of each industry and the interdependencies among industries (Chenery & Watanabe, 1958).

Table 3. Input Coefficients of Environmental Industry Sectors in the ASEAN-5 Countries.

Category	Sub-Sector	Indonesia	Malaysia	Philippine	Thailand	Vietnam
Resources	Agriculture, forestry, and fishing	0.0001	0.0024	0.0025	0.0086	0.0000
Equipment	Transportation	0.0036	0.1465	0.0020	0.0007	0.0126
	Waste	0.0079	0.0224	0.0073	0.0274	0.1327
Service	Electricity, gas, and water supply	0.1035	0.2083	0.1159	0.2526	0.0159
	Education	0.0011	0.0068	0.6463	0.0000	0.0209
	Health and social	0.0047	0.0013	0.2697	0.0000	0.0201
	Others	0.0014	0.1979	0.8654	0.0437	0.0101

Note: Only significant coefficients are derived. Source: Author’s calculations based on MRIO (2024).

Overall, this result shows that Malaysia and Thailand demonstrate a strong intermediate dependence on utilities and selected service sectors, which is consistent with their semi-industrialized economic structures. The Philippines also shows unusually high service-sector coefficients, particularly in education and other services, suggesting that environmental activities are embedded in human-capital-intensive and service-driven production systems.

These differences which service dependence but also structural differences imply that the production inducement effects of environmental industries will likely vary substantially across the ASEAN-5 countries owing to structural heterogeneity in intermediate input dependence.

Table 4 presents the production inducement values of the environmental industry sectors across the five ASEAN-5 countries along with cross-country descriptive statistics. The results reveal substantial heterogeneity in both absolute magnitude and relative dispersion across sectors.

Table 4. Production Inducement Value of Environmental Industry Sectors in the ASEAN-5 Countries (US$ million).

Category	Sub-Sector	Indonesia	Malaysia	Philippine	Thailand	Vietnam	Mean (μ)	Std. Dev. (σ)	CV (σ/μ)
Resources	Agriculture, forestry, and fishing	9796.2	22,948.7	30,352.9	41,433.7	1284.0	21,163.1	15,939.4	0.75
Equipment	Transportation	9727.2	16,795.6	30,380.9	42,090.7	1251.9	20,849.2	15,792.5	0.76
	Waste	9644.5	22,037.9	30,058.5	39,871.7	965.9	20,515.7	15,274.8	0.74
Service	Electricity, gas, and water supply	7875.4	14,451.3	23,839.9	23,543.7	1243.6	14,190.7	9297.2	0.65
	Education	9776.6	22,743.3	3816.1	42,148.4	1230.8	15,943.0	17,550.6	1.1
	Health and social	9706.2	22,996.5	16,270.3	42,148.9	1232.9	18,470.9	14,854.7	0.8
	Others	9770.9	14,834.0	552.3	38,552.1	1258.1	12,993.4	14,915.3	1.15

Source: Authors’ calculations based on ADB MRIO and national statistical office data from the ASEAN-5 countries.

First, in terms of mean production inducement effects, resource- and equipment-related sectors—namely agriculture, forestry, and fishing (μ = 21,163.10) and transportation equipment (μ = 20,849.26)—exhibit the highest average spillover effects. These findings suggest that capital- and resource-intensive environmental sectors generate stronger backward linkages within the national production systems. In contrast, electricity, gas, and water supply shows a comparatively lower mean value (μ = 14,190.78), indicating more moderate but stable inter-industry linkages.

Second, the coefficient of variation (CV) highlights the significant structural dispersion across countries. Education (CV = 1.10) and other services (CV = 1.15) display the highest relative variability, exceeding unity, indicating pronounced cross-country asymmetry in service-based environmental activities. This pattern reflects uneven institutional development and differentiated public-sector integration across the ASEAN-5 economies. In contrast, electricity, gas, and water supply (CV = 0.65) demonstrate the lowest dispersion, suggesting relatively homogeneous production linkages across the region.

Third, the analysis highlights the pivotal role of resource-intensive and equipment-related sectors in driving ecological and economic interconnections within the ASEAN-5 countries. Policymakers are encouraged to leverage these strengths while addressing disparities in the education and other service sectors. Targeted policies aimed at enhancing integration in these high variability sectors are crucial for holistic economic advancement.

4.2. Value-Added Inducement Effect

The value-added coefficient in the input-output table measures the amount of gross value-added directly or indirectly generated in the national economy by a one-unit change in final demand for a specific industry. This coefficient allows us to understand the extent to which the ASEAN environmental industry production adds value to each country’s GDP.

Table 5 shows that resource-based environmental industries tend to generate the highest value-added multipliers, particularly in resource-abundant economies. Manufacturing-based environmental equipment sectors also show stronger inducement effects in more industrialized economies (e.g., Thailand), whereas service-oriented environmental industries display relatively stable but institutionally dependent multiplier structures. These results suggest that the depth of domestic value creation in the ASEAN-5 environmental industries depends on both natural resource endowments and industrial maturity. Countries with stronger manufacturing bases or institutionalized public service systems tend to retain a larger share of value-added within their domestic production networks.

Table 5. Value-Added Inducement Factors for the Environmental Industries in the 5 ASEAN Countries.

Category	Sub-Sector	Indonesia	Malaysia	Philippine	Thailand	Vietnam
Resources	Agriculture, forestry, and fishing	0.1451	0.0902	0.09	0.0823	0.1834
Equipment	Transportation	0.0159	0.0116	0.0019	0.0439	0.0142
	Waste	0.0062	0.0035	0.0032	0.0081	0.0214
Service	Electricity, gas, and water supply	0.0088	0.0276	0.034	0.0399	0.0254
	Education	0.0243	0.0405	0.0396	0.0373	0.0337
	Health and social	0.0062	0.0217	0.0183	0.03	0.0149
	Others	0.0179	0.0135	0.0173	0.0272	0.0248

Note: Higher values indicate stronger domestic value-added creation and deeper inter-industry linkages within the national production system. Source: Author’s calculations based on MRIO (2024).

The value-added impact of each ASEAN country’s environmental sector reflects the overall economic impact of increased production in subsectors within the environmental industry category. The goal is to understand the economic spillover effects across each country’s economy when production activities in agriculture, environmental facilities, waste management, public energy services, education services, and health and social services are used as intermediate goods. Table 6 shows the value-added by environmental industries in the ASEAN-5 countries. This is used to estimate the value-added impact.

Table 6. Value-Added Inducement of Environmental Industry Sectors in the ASEAN-5 Countries (US$ million).

Category	Sub-Sector	Indonesia	Malaysia	Philippine	Thailand	Vietnam
Resources	Agriculture, forestry, and fishing	1.5288	36.9807	31.8057	24.0428	-
Equipment	Transportation	1.4202	58.8831	0.015	0.7183	0.5667
	Waste	0.4492	603.25	0.1936	2.4316	4.0744
Service	Electricity, gas, and water supply	12.4674	194.4498	58.1831	135.3166	1.5226
	Education	1.094	15.4014	26.3221	0.0209	7.7406
	Health and social	0.4046	1.085	3.2303	0.0285	1.6361
	Others	0.8758	123.4674	20.9242	36.5908	2.2332

Source: Author’s calculations based on MRIO (2024).

Table 6 reports the value-added generated by environmental industry sectors across the ASEAN-5 economies. These results capture the total direct and indirect value-added generated per unit of final demand, thereby reflecting the depth of domestic value chains and the degree of sectoral integration.

First, Malaysia exhibits exceptionally high value-added in waste management (603.25) and electricity, gas, and water supply (194.45), indicating a highly concentrated environmental production structure. These magnitudes substantially exceed those of the other ASEAN countries, suggesting either strong domestic vertical integration or sectoral classification differences in the national I–O structure. Malaysia may have highly developed domestic supply chains in environmental sectors, enabling strong backward linkages and high value retention. Alternatively, the magnitude may reflect a classification bias within the MRIO framework, in which environmental sectors (particularly waste) are aggregated with broader industrial activities. Such an aggregation inflates the value-added estimates and obscures sectoral specificity. Malaysia’s proactive environmental and infrastructure policies may have created policy-induced concentration effects, in which public investment and regulatory incentives disproportionately stimulate specific sectors.

Second, Thailand demonstrates a relatively balanced yet robust value-added structure, particularly for utilities (135.32) and other services (36.59). Unlike Malaysia, Thailand’s distribution suggests a more diversified environmental production system in which both infrastructure- and service-based sectors contribute to value creation.

Similarly, the Philippines shows a moderate-to-high value-added generation in utilities (58.18) and education (26.32), indicating the growing importance of human-capital-intensive environmental services. This reflects a transition toward knowledge-based environmental governance, which is consistent with the service-led development pathways identified in the emerging ASEAN economies.

By contrast, Vietnam records comparatively across most sectors, implying a shallower domestic production structure. This suggests that environmental industry activities may be more reliant on imported intermediate inputs, leading to lower domestic value retention, a phenomenon commonly associated with an early-stage global value chain (GVC) participation. Third, Indonesia records relatively low value-added across equipment and service sectors, except for utilities (12.47), implying more limited domestic value-chain depth in environmental industries.

Indonesia exhibits consistently low value-added inducements across most sectors, except utilities (12.47). Despite its large economy, this pattern indicates a relatively limited domestic value chain depth in environmental industries, particularly in the equipment and service sectors.

From a GVC perspective, this suggests that Indonesia’s environmental industry is positioned in lower value-added segments with weaker forward and backward linkages. This finding is consistent with earlier production inducement results, in which high-output effects do not necessarily translate into high value-added generation, indicating structural inefficiencies and leakage effects in the domestic economy.

Overall, the findings suggest that value-added generation in the ASEAN-5 environmental industries is not uniformly distributed, but reflects distinct national development trajectories. Advanced service economies concentrate value in knowledge-intensive environmental services, while industrializing economies rely more on infrastructure and utility-based sectors. Therefore, strengthening domestic intermediate production capacity and institutional integration may enhance value-added retention in lower-performing economies.

This indicates that while the environmental industries in ASEAN generate substantial production spillovers, their capacity to retain domestic value-added differs markedly across countries, reflecting divergent development paths between production-led and value-added-led environmental industrialization.

4.3. Forward and Backward Linkage Effect

An analysis of the production inducement effects reveals that the transportation sector generates the largest economic spillover effect among the environmental industry sectors in the major ASEAN countries. Because the transportation sector is a key component of supply chains (UNCTAD, 2013), it is necessary to examine both forward and backward linkages to estimate the degree of interindustry production linkages. Accordingly, based on the production inducement coefficients derived above, we calculate the sensitivity and influence coefficients to assess how the growth of environmental industries in the major ASEAN countries affects other industries.

The sensitivity coefficient represents the forward linkage effect, indicating the degree to which the environmental industry responds when final demand for products across all industrial sectors increases by one unit. By contrast, the influence coefficient represents the backward linkage effect, measuring the extent to which all industrial sectors are affected when the final demand for products in the environmental industry increases by one unit (Anderson-Hsieh et al., 1992).

The sensitivity coefficients derived from the I–O tables are reported in Table 7. Overall, the electricity, gas, and water supply sectors exhibit consistently high forward linkage effects across the ASEAN-5 countries, particularly in Thailand (1.338), Malaysia (1.263), and the Philippines (1.185). This indicates that environmental infrastructure functions as a key downstream-connected sector that expands in response to economy-wide demand growth.

Table 7. Sensitivity Coefficients (Forward Linkage Effects) of Environmental Industry Sectors in the ASEAN-5 Countries.

Category	Sub-Sector	Indonesia	Malaysia	Philippine	Thailand	Vietnam
Resources	Agriculture, forestry, and fishing	1	1.002	1.002	1.009	1.013
Equipment	Transportation	1.004	1.172	1.002	1.001	1.153
	Waste	1.008	1.023	1.007	1.028	1.016
Service	Electricity, gas, and water supply	1.115	1.263	1.185	1.338	1.021
	Education	1.001	1.007	2.827	1	1.021
	Health and social	1.005	1.001	1.369	1	1.01
	Others	1	1.002	1.002	1.009	1.013

Note: The sensitivity coefficient (FL) is the normalized forward linkage index computed from the Leontief inverse. Values greater than 1 indicate that the sector is more downstream-connected than the economy-wide average, meaning it tends to respond more strongly when final demand across all sectors increases. Values below 1 indicate below-average forward linkages. Source: Author’s calculations based on ADB MRIO (2024) I–O tables.

By contrast, agriculture, forestry, and fishing remains close to the economy-wide average, suggesting limited specialization in forward production linkages. The waste management sector shows moderately above-average forward linkages in most countries, reflecting stable embedding across production activities. Notably, the Philippines recorded exceptionally high forward linkage effects in education (2.827) and health and social services (1.369), indicating the strong demand responsiveness of service-oriented environmental activities in the Philippines’ production system. Overall, these results suggest that the environmental infrastructure sectors, particularly the electricity- and water-related services, function as key upstream industries within the ASEAN production system, whereas service-oriented environmental sectors display stronger forward linkage effects in specific national contexts.

The influence coefficients, which represent backward linkage effects, indicate the extent to which an increase in the final demand for environmental industry sectors stimulates production across other industries. Table 8 presents the influence coefficients of the environmental industry sectors across the major ASEAN countries.

Table 8. Influence Coefficients (Backward Linkage Effects) of Environmental Industry Sectors in the ASEAN-5 Countries.

Category	Sub-Sector	Indonesia	Malaysia	Philippine	Thailand	Vietnam
Resources	Agriculture, forestry, and fishing	1	1.002	1.002	1.009	1.013
Equipment	Transportation	1.004	1.172	1.002	1.001	1.153
	Waste	1.008	1.023	1.007	1.028	1.016
Service	Electricity, gas, and water supply	1.115	1.263	1.185	1.338	1.021
	Education	1.001	1.007	2.827	1	1.021
	Health and social	1.005	1.001	1.369	1	1.01
	Others	1	1.002	1.002	1.009	1.013

Note: The influence coefficient (BL) is the normalized backward linkage index computed from the Leontief inverse. Values greater than 1 imply that an increase in final demand for the sector induces above-average upstream production in other industries, while values below 1 indicate below-average upstream inducement effects. Source: Author’s calculations based on ADB MRIO (2024) I–O tables.

The influence coefficients (backward linkage effects) are listed in Table 8. The electricity, gas, and water supply sectors show the strongest backward linkage effects across the ASEAN-5 countries, with particularly high values in Thailand (1.790), Vietnam (1.790), Malaysia (1.596), the Philippines (1.279), and Indonesia (1.240). This implies that the final demand expansion in environmental utilities widely stimulates upstream production, and serves as a major demand-generating hub in the environmental economy.

The waste management sector exhibits modest but consistently above-average backward linkages across countries, whereas the transportation equipment sector is highly heterogeneous, with Malaysia (1.373) showing a strong upstream inducement structure relative to the other ASEAN-5 economies. Overall, the results indicate that environmental infrastructure sectors, particularly electricity, gas, and water supply, function as key demand-generating industries within the ASEAN production networks, whereas service-oriented environmental sectors exhibit stronger spillover effects in specific national contexts.

The empirical results indicate that the environmental industry sectors exhibit heterogeneous linkage structures that fundamentally determine their GVC positioning. In particular, the electricity, gas, and water supply sectors demonstrate consistently strong forward and backward linkage effects across the ASEAN economies, especially in Thailand and Malaysia. This dual linkage characteristic suggests that the environmental infrastructure functions as a central hub within the production system, simultaneously responding to economy-wide demand expansion while inducing upstream production across multiple sectors. Such a configuration reflects a high degree of structural embeddedness and positions environmental utilities as a core organizational sector within the environmental GVC.

At the country level, the analysis reveals divergent GVC trajectories among ASEAN economies. Thailand exhibits a relatively balanced and integrated structure, approaching the high production–high value-added quadrant, supported by strong linkage effects and diversified sectoral development. Malaysia demonstrates a similar upward trajectory, driven primarily by infrastructure-centered sectors with strong linkage intensity. The Philippines shows signs of transition toward service-based upgrading, particularly through high forward linkage effects in education and social services. In contrast, Indonesia remains constrained by limited value-added conversion despite moderate production effects, indicating persistent structural leakage. Vietnam, meanwhile, reflects an early-stage development pattern characterized by weak linkage structures and low value-added retention.

Taken together, these findings suggest that the economic effectiveness of environmental industries in ASEAN is not determined solely by production scale but by the interaction between linkage intensity and GVC positioning. Sectors with strong forward and backward linkages are more likely to achieve higher value-added retention, whereas those with weak or imbalanced linkage structures remain trapped in low-value segments of the production network.

5. Conclusions

This study examines the economic role of environmental industries in the ASEAN economies by applying an EIO framework. Using MRIO data from the ADB, the analysis evaluates the production-inducement effects, value-added generation, and interindustry linkage structures of environmental industry sectors in Indonesia, Malaysia, the Philippines, Thailand, and Vietnam.

Our empirical findings provide several important insights. First, environmental industries generate significant production spillover effects within the ASEAN economies. In particular, infrastructure-related sectors such as electricity, gas, and water supply exhibit strong forward and backward linkages, indicating that they play a central role in the regional production network. These sectors function as both upstream suppliers and demand-generating hubs, stimulating economic activity across multiple industries.

Second, value-added inducement analysis reveals substantial cross-country heterogeneity in the economic contributions of environmental industries. While some economies demonstrate strong domestic value creation in environmental sectors, others are characterized by relatively shallow value chains and limited domestic integration. These differences reflect variations in industrial maturity, technological capabilities, and institutional development across the ASEAN countries.

Third, the findings suggest that optimizing the economic performance of environmental industries necessitates three strategic pillars: (1) strengthening domestic supply chains to increase backward linkages; (2) expanding knowledge-intensive services to reinforce forward linkages; and (3) promoting industrial upgrading to shift production toward higher value-added segments. Specifically, environmental infrastructure should be leveraged as a strategic hub for broader industrial integration, while service-based sectors, including education and environmental consulting, should be developed as engines for long-term value creation.

From a policy perspective, the results imply that strengthening domestic environmental expenditure and upgrading industrial structures can significantly enhance the production multiplier effects of environmental industries. Furthermore, the persistence observed in the dynamic model suggests that early-stage policy interventions may generate long-term structural benefits. For example, as transportation sectors contribute to the formation of continuous production networks, improving environmentally sustainable transportation systems, such as green logistics, low-carbon transportation infrastructure, and smart mobility systems, can enhance both environmental sustainability and regional economic integration.

While this study provides a comprehensive assessment of the economic role of the environmental industries in ASEAN, future research should focus on dynamic modeling, improved measurement, and deeper integration of GVC and environmental performance analyses to enhance both analytical precision and policy relevance.

In conclusion, this study provides empirical evidence that environmental industries function as key drivers of sustainable growth in the ASEAN economies. By strengthening the structural linkages between environmental industries and broader production systems, the ASEAN countries can simultaneously achieve economic development and environmental sustainability in the era of climate change.