The stakes are enormous. Vietnam’s revised Power Development Plan 8, approved in 2023 and updated in April 2025, aims for renewables other than hydropower to supply 28 to 36 percent of electricity generation by 2030, on a path to net-zero emissions by 2050. Meeting the plan’s generation and transmission goals during 2026 to 2030 is estimated to require 136.3 billion US dollars, with 118.2 billion for generation and 18.1 billion for transmission. Drawing that sum from the budget would collide with an annual public-debt ceiling of 60 percent of gross domestic product set for the same period. Meanwhile, the median weighted average cost of capital for utility-scale solar in Vietnam stands at roughly 9 percent, compared with 5 to 6.5 percent in advanced economies, meaning financing terms, not equipment prices, often determine whether projects get built at all.

To test how these constraints shape outcomes, the study employed a recursive-dynamic computable general equilibrium model, the standard tool for tracing how policy-induced price changes propagate through interlinked goods, factor and foreign exchange markets. The model distinguishes 24 production activities, 20 commodities, five electricity generation technologies, coal, gas, hydro, solar and wind, three primary factors, capital, skilled labour and unskilled labour, and four institutional accounts. It was calibrated to a social accounting matrix for Vietnam in 2022, built from the national input-output table and balanced to within four parts in one hundred million, and solved annually from 2022 to 2030. Crucially, the researchers fixed the policy outcome: every scenario is constrained to a common renewable path reaching a 32.0 percent solar-and-wind share of generation in 2030, the midpoint of the plan’s target range, while the intensity of each instrument is solved endogenously.

The five scenarios span the instruments Vietnam is actually implementing or preparing. The first extends a feed-in tariff-type output subsidy on solar and wind, financed by a non-distortionary lump-sum tax on households, a first-best benchmark. The second combines a carbon tax on fossil fuels, reaching 25.0 percent on coal by 2030, with a modest 2.41 percent renewable subsidy funded from recycled revenue. The third applies a stand-alone carbon tax, which must climb to 30.3 percent on coal to do all the work alone. The fourth simulates an emissions trading scheme with free allocation covering coal-fired and gas-fired generation, iron and steel, and non-metallic minerals, with the cap set 29.49 percent below baseline covered emissions. The fifth models concessional green credit that cuts the user cost of capital for solar and wind by 22.6 percent, capped at 30 percent, with the resource cost entering the balance of payments as an external inflow, mirroring the structure of Vietnam’s Just Energy Transition Partnership.

The macroeconomic verdict is stark. Against the business-as-usual baseline, which leaves the renewable share at 20.04 percent in 2030, the lump-sum-financed subsidy raises real GDP by 1.36 percent and aggregate employment by 1.81 percent. The carbon-pricing designs move in the opposite direction: the revenue-recycled carbon tax trims GDP by 0.58 percent and employment by 0.81 percent, the stand-alone carbon tax by 0.75 and 1.07 percent respectively, and the emissions trading scheme, whose narrower coverage leaves most energy users unpriced, by only 0.06 and 0.03 percent. The green credit scenario towers over the rest, lifting GDP 4.17 percent above baseline, employment 5.73 percent, and real household income 2.01 percent, all while delivering the identical renewable share. Lowering the price of capital, the simulations suggest, generates crowd-in effects on investment that raising the price of energy cannot match.

Beneath the aggregates lies a consistent map of structural winners and losers. Coal mining, oil refining, transport, chemicals, paper, iron and steel and non-metallic minerals contract in every scenario, while electronics, textiles, machinery, construction and market services expand. The carbon taxes produce the deepest adjustment, cutting coal mining output by 15.0 to 16.3 percent and oil refining by 12.9 to 15.0 percent relative to baseline. Green credit softens the pain dramatically: coal mining falls just 5.2 percent, oil refining actually rises 1.6 percent, and the expanding side surges, with electronics output up 13.9 percent, textiles 7.3 percent, market services 5.9 percent, machinery 4.8 percent and construction 3.8 percent. Iron and steel and cement remain exceptions even under green credit, because their energy intensity means higher input costs dominate the demand impulse from renewable investment.

The labour-market decomposition reveals distributional stakes that GDP figures conceal. The model imposes capital-skill complementarity, so capital deepening raises the relative demand for skilled workers, and it supplies unskilled labour along an upward-sloping schedule with an elasticity of 3.0, reflecting Vietnam’s large informal and underemployed workforce. Under green credit, skilled labour demand in electronics reaches 20.2 percent above baseline and market services 11.9 percent, while unskilled demand rises 13.0 percent in electronics and 8.9 percent in textiles, with contractions in mining and chemicals limited to 1.8 percent. Under the revenue-recycled carbon tax, by contrast, unskilled employment in mining falls 14.7 percent and in chemicals 9.9 percent. The question is urgent because only 26.4 percent of Vietnam’s employed workers held a formal qualification at the end of 2022, and displaced fossil-fuel workers often share skill profiles with general construction and manufacturing more than with clean-energy operations themselves.

Because every elasticity in such a model is calibrated rather than estimated, the team subjected the results to a systematic Monte Carlo sensitivity analysis, drawing 100 parameter vectors by Latin hypercube sampling over ten parameters, each support centred on the calibrated value at plus or minus 20 percent. Every draw re-solved the full 2022 to 2030 path with the renewable-share constraint re-imposed, and all draws converged. The qualitative ranking survived intact. Green credit was positive in every draw, with a mean GDP effect of 4.18 percent and a 5th-to-95th percentile range of 3.19 to 5.21 percent, and it ranked first in all 100 draws. The subsidy scenario ranked second in all 100. The three carbon-pricing designs were negative in every draw, the emissions trading scheme outperformed both carbon taxes in all draws, and the full five-way ordering held in 76 of them, with every exception an exchange between the two carbon taxes, whose central estimates differ by only 0.19 percentage points.

The authors are careful about what the headline result does and does not establish. Green credit’s advantage depends on the concessional resource cost being borne externally, as the Just Energy Transition Partnership’s initial package is provided by international partners and mobilised private capital rather than the Vietnamese budget; if disbursement falls short, terms deteriorate or part of the cost shifts to the domestic budget, the measured gain would shrink. Credit additionality, exchange-rate risk and financial-intermediary constraints sit outside the model, which also features a single representative household and therefore speaks to sectoral and factor demand rather than inequality. Carbon pricing and emissions trading remain central to Vietnam’s long-term decarbonisation signalling, and recycling their revenues toward investment, household compensation or retraining could reduce their costs. The broader message is one of integrated packages: Vietnam’s transition can raise output and labour demand if policy tilts toward concessional finance and broadly funded renewable support, but coal-dependent regions will need vocational retraining, portable social protection and targeted adjustment support to ensure the shift is genuinely just.

Subject of Research: Renewable energy policy, financing mechanisms, and structural change in Vietnam: A CGE analysis of SDG 7 and SDG 13 pathways

Article Title: Renewable energy policy, financing mechanisms, and structural change in Vietnam: A CGE analysis of SDG 7 and SDG 13 pathways

Article References: Bui, T. D., Bui, H. T. M., & Dinh, K. S. (2026). Renewable energy policy, financing mechanisms, and structural change in Vietnam: A CGE analysis of SDG 7 and SDG 13 pathways. Heliyon, 12(16), Article e45543. https://doi.org/10.1016/j.heliyon.2026.e45543

Image Credits: AI Generated

DOI: 10.1016/j.heliyon.2026.e45543

Keywords: Renewable, energy, policy, financing, mechanisms, structural, change, Vietnam, analysis, pathways, scientific research