Assessing the Impact of EU State
Aid on the Sustainable
Transformation of the Iron and
Steel Industries in Montenegro
and Albania
PROGRAMME NAME: BU7530-202425 MSC FINANCE DISSERTATION
March 2025
(I) Aims and Objectives
1. Research Aim
The aim of this study is to critically assess the impact of EU state aid policies (including subsidies, tax incentives and regulatory frameworks) on the sustainable transformation of the iron and steel industries in Montenegro and Albania. These aid policies have played a positive and important role in reducing carbon emissions, adopting green technologies and improving industrial competitiveness. As such, these policies benefit not only the economic but also the environmental aspects, supporting the EU's broader decarbonisation and eco-transition objectives. As Montenegro and Albania are EU candidate countries, their alignment with EU industrial and environmental policies makes them ideal cases for examining how external financial and regulatory support can influence sustainable transformation.
These two countries were selected because of their increasing integration with the EU, their strategic importance in the steel industry and the urgent need for economic reforms aimed at sustainable development. In addition, the need for these two countries to rely on state aid and foreign investment to modernise their industrial infrastructure provides an opportunity to assess the effectiveness of EU interventions in promoting low-carbon industrial transformation.
The steel industry in Montenegro accounts for about 8 per cent of GDP and 12 per cent of industrial employment (World Bank, 2023). For Albania, the steel industry is the main driver of exports, a large part of which goes to the EU (European Commission, 2024). However, EU interventions have not been very effective for these economies due to systemic problems such as outdated domestic infrastructure (World Bank, 2023), lax regulatory enforcement (European Court of Auditors, 2023) and market fragmentation (European Commission, 2023).
By integrating financial, environmental and governance indicators, this study will explore whether EU-funded interventions have been effective in achieving the objectives of the EU Green Deal (i.e. to reduce carbon emissions, promote innovation and improve industrial competitiveness).
2. Research Objectives
To achieve this goal, the study will endeavour to achieve the following objectives:
In order to unpack the causal mechanisms through which EU state aid may shape sustainable industrial transformation, the study adopts a multi-dimensional approach. This involves examining both financial and technological channels through which such interventions operate at the firm level.
2.1 Quantify the financial impact of EU state aid policies on steel firms in Montenegro and Albania by using targeted firm-level financial indicators. The analysis will focus on three main metrics:
Return on Assets (ROA) to assess how efficiently firms use their assets to generate profits.
Return on Equity (ROE) to evaluate profitability from shareholders’ perspective.
and EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) to capture firms’ operational cash flow and debt sustainability.
These indicators are selected because they reflect different dimensions of firm performance: efficiency, profitability, and financial resilience. The objective is to compare these outcomes between firms receiving EU state aid and those that do not, to test whether subsidised firms demonstrate higher investment returns and/or greater financial volatility. One analytical strand will focus on positive financial outcomes (e.g., improved ROE), while the other will assess financial risk exposure (e.g., higher variance in EBITDA for larger firms subject to corporate tax differentials).
2.2 Assess the influence of EU-funded green R&D subsidies and technology-specific state aid schemes—such as those supporting hydrogen-based steelmaking, carbon capture and storage (CCS), and energy-efficient retrofitting—on innovation outcomes in steel firms. The focus will be on identifying whether such interventions stimulate firm-level adoption of low-carbon technologies and increased patenting activity in environmental technologies. Emphasis will also be placed on how targeted aid differs in impact from broader industrial subsidies.
2.3 Examine the environmental outcomes of EU state aid by measuring changes in CO₂ emissions intensity (per ton of steel produced) and alignment with EU sustainability benchmarks, such as those set under the Green Deal and the Fit-for-55 package. In addition, firm-level ESG scores—drawn from recognized rating agencies (e.g., Sustainalytics, MSCI ESG Ratings)—will be used to assess longer-term environmental and governance impacts. While carbon intensity remains the primary environmental indicator, ESG performance will be further explored in a dedicated robustness check.
2.4 Compare the financial, operational, and environmental performance of EU- subsidised and non-subsidised steel firms to assess the effectiveness of state aid in promoting sustainable industrial transformation. Financial metrics will include ROA, ROE, and EBITDA; operational performance will be measured through output growth and productivity levels; and environmental performance will focus on CO₂ intensity and energy efficiency. This comparison will help isolate the net effect of state aid on firm-level transformation.
2.5 Analyse regional implementation differences in EU state aid policy between Montenegro and Albania, with particular attention to governance challenges such as inconsistent criteria in subsidy allocation, limited monitoring capacity, bureaucratic delays, and institutional enforcement gaps. The analysis will also assess how variations in tax incentive structures and administrative procedures influence policy outcomes at the firm level.
2.6 Evaluate the role of firm-level ESG performance as a moderating or secondary explanatory variable in understanding variation in state aid outcomes. ESG scores— drawn from established rating providers such as MSCI or Sustainalytics—will be used to examine how firms with stronger environmental, social, and governance profiles respond differently to EU state aid, particularly in emissions reduction and access to green financing. ESG performance will also be considered in an additional robustness check section to test the stability of main financial and environmental results.
3. Research Questions
Q1: Has the EU state aid policy improved the financial performance of subsidised steel companies?
Q2: Does state subsidies encourage increased investment in R&D?
Q3: Does the state aid policy reduce carbon emissions in the steel sector?
Hypothesese
H1: EU-subsidised firms exhibit higher returns on investment compared to non- subsidised firms, due to relaxed capital constraints and improved competitiveness associated with state aid.
H2: Firms receiving EU state aid allocate a greater proportion of their budgets to R&D activities—particularly in low-carbon technologies—than firms that do not receive such support.
H3: Firms benefiting from targeted EU state aid experience a reduction in carbon intensity over time, relative to firms without such policy support.
H4: Firms with stronger ESG performance are more likely to qualify for favourable EU state aid conditions and demonstrate faster emissions reductions.
(II) Rationale and Contribution
1. Description of Topic
The steel industry is a crucial component of the European Union's industrial strategy, employing over 300,000 individuals and contributing approximately €140 billion annually to the EU economy (World Steel Association, 2024). However, the steel sector, which accounts for 11 per cent of total CO₂ emissions in the EU, remains one of the largest industrial sources of carbon emissions (European Commission, 2023). The European Green Deal requires the steel industry to reduce its emissions by 55% by 2030 and to achieve climate neutrality by 2050, under a legally binding decarbonisation framework (European Commission, 2023; UNEP, 2023). Since 2020, the EU has allocated over €50 billion in state aid to energy-intensive industries—including steel— in support of these environmental objectives (European Commission, 2023; European Court of Auditors, 2023).
Yet the effectiveness of such interventions remains contested, especially in smaller Balkan economies like Albania and Montenegro, where outdated coal-based blast furnaces remain in operation and structural barriers persist (World Bank, 2023; OECD, 2023). These include inadequate infrastructure, fragmented markets, and limited institutional implementation capacity, all of which may constrain the transformative potential of EU-funded aid (European Commission, 2024; OECD, 2023).
This study therefore addresses a critical knowledge gap by assessing how EU financial support influences sustainable transformation in steel firms operating in transitional economies.
2. Rationale for the Choice of Topic
Montenegro and Albania, as EU accession candidates, are required to progressively align their industrial and environmental policies with the EU’s sustainability frameworks. This study seeks to generate empirically grounded insights to inform the design of EU state aid programs that effectively support low-carbon industrial transformation in candidate countries with transitional economies.
Although the literature on EU state aid has expanded in recent years, it remains disproportionately focused on Western European economies, such as Germany and France. In contrast, the specific institutional and structural challenges faced by the Western Balkans—namely, weak regulatory enforcement, systemic corruption, and reliance on external financial assistance—have received limited scholarly attention. This research aims to address this gap by focusing on two underexamined but strategically important cases.
The economic relevance of the steel industry in these countries further underscores the importance of this inquiry. In Montenegro, the steel sector accounts for 8 per cent of GDP, 12 per cent of industrial employment and 22 per cent of total steel exports. In Albania, the iron and steel sector is the main source of industrial emissions, emitting about 1.8 million metric tonnes of carbon dioxide per year, or 15 per cent of the national total. The situation is even more pressing in the Montenegrin steel industry, which alone accounts for 22 per cent of the country's total carbon dioxide emissions.
In this context, there are both environmental and economic reasons for accelerating industrial decarbonisation. Failure to achieve a low-carbon transition as soon as possible will not only jeopardise the requirements for EU accession, but also destabilise the domestic economy through increased unemployment, reduced competitiveness and widening trade deficit. This study is therefore conducted at the intersection of economic policy, environmental governance and regional integration.
3. Literature Review
The literature on EU state aid and industrial transformation can be broadly categorised into three areas: (1) financial outcomes for the firm level, (2) innovation and environmental performance, and (3) governance and distributional challenges. This section reviews the main contributions in each of these areas.
3.1 State Aid and Financial Performance:
Zhang and Wang (2020) show that state subsidies can improve firms' competitiveness and profitability, especially for capital-intensive industries. However, at the same time, unregulated subsidies may lead to misallocation of resources.The trade-off between short-term fiscal gains and long-term sustainability is also mentioned in Midttun (2021), which argues that financial assistance without incentives to innovate may lead to delays in structural transformation.
An empirical study of strategic industries (Zhang & Wang, 2020) similarly mentions significant improvements in financial indicators such as return on investment (ROI) and earnings before interest, taxes, depreciation, and amortisation (EBITDA) among firms receiving targeted subsidies. However, long-term investment returns can also be volatile if financial assistance is not strictly regulated.
Conclusion: While state aid can improve business profitability in the short term, it must be strictly regulated to avoid inefficiencies and support sustainable competitiveness.
3.2 Innovation and Environmental Outcomes:
Innovation plays an important role in achieving long-term environmental goals, especially in carbon-intensive industries such as steel. However, the development of innovation often depends on the availability of well-designed State aid instruments. When subsidies are linked to specific innovation and decarbonisation targets, they can accelerate technological progress and contribute to measurable environmental outcomes. The OECD (2023) criticises the use of subsidy packages that lack environmental conditionality and calls for financial support to be linked to tangible green outcomes, such as carbon emission reductions or investments in low-carbon technologies.Hartley (2021) supports this position, emphasising the role of conditional public-private finance in accelerating innovation, particularly in heavy industries such as steel.
Midttun (2021) notes that green R&D is often relegated to the back burner in favour of immediate job retention and industrial stabilisation, especially in emerging economies. zhang and Wang (2020) add that untargeted aid may cause firms to delay long-term environmental investments due to weaker regulatory pressures.
Innovation-oriented conditional subsidies are more effective than general financial support in advancing environmental transformation goals. Hartley (2021) also notes that long-term investments in decarbonisation are more successful when firms co-finance aid with private capital, such as green bonds or debt swaps.
3.3 Governance and Distributional Imbalance:
Governance capacity and the fair distribution of EU state aid have emerged as key concerns in the literature on regional development policy. The European Court of Auditors (2023) reports that only 40% of EU member states apply a comprehensive monitoring framework for state aid, resulting in large regulatory inconsistencies across countries. These problems are particularly acute in candidate countries such as Montenegro and Albania, where institutional capacity to manage, monitor, and evaluate aid remains underdeveloped (European Commission, 2023).
Recent research highlights the unequal spatial allocation of green transition funds. According to Pelikaan (2022) and the EU Industrial Policy White Paper (2023), Western European countries continue to receive the majority of EU funding, while newer and candidate member states in the Western Balkans receive significantly less per capita, despite facing more severe structural barriers. This disparity contributes to the emergence of a so-called ‘two-speed Europe’, whereby well-integrated economies accelerate their green industrial transformation, while peripheral regions fall further behind in meeting EU climate and competitiveness targets.
Moreover, transparency and enforcement mechanisms in aid disbursement remain weak in some newer member states. The State Aid Scoreboard (European Commission, 2023) warns that in the absence of stronger oversight, risks such as regulatory capture and selective implementation of conditionalities may undermine policy effectiveness in transitional economies.
In sum, the literature suggests that unless issues of institutional governance and distributional equity are systematically addressed, EU state aid may reinforce existing disparities rather than mitigate them. This study contributes to this debate by empirically examining whether aid recipients in Albania and Montenegro are disadvantaged not only in terms of financial outcomes, but also in the consistency of policy implementation.
4. Contribution to Financial, Management, and Public Policy
Financial Impact: The study will quantify the return on investment (ROI) of state aid to steel companies, enabling investors and policymakers to gain a more intuitive understanding of the profitability risks and opportunities of green subsidies.
Management Strategy: By analysing the distribution model, the study will provide companies with suitable recommendations that can be used to optimise state aid for technological upgrades, such as the transition from blast furnaces to electric arc furnaces (EAFs).
Public Policy: The results of the study will help the EU institutions to redesign and refine the Country Assistance Framework (CAF) to address regional disparities, enhance accountability and prioritise high-impact decarbonisation projects.
(III) Methodology
1. Research Methodology
In order to analyse the impact of EU state aid on financial and environmental outcomes, this study will use a difference-in-differences (DiD) model. The two main dependent variables are return on assets (ROA), which indicates financial performance, and carbon intensity (CO2 emissions per tonne of steel), which reflects environmental outcomes. Control variables include firm size (log of total assets) and leverage (debt-to-equity ratio), which reflect differences in economies of scale and financial structure.
In addition, the study will include R&D intensity (R&D expenditures/revenues) as a mediating variable rather than a control variable to be used to examine whether state aid indirectly affects environmental and financial outcomes by stimulating investment in innovation. This mediating relationship will be explored using interaction terms or causal mediation analyses, as appropriate.
Semi-structured interviews with industry stakeholders will supplement the quantitative analysis by providing context on implementation mechanisms and firm-level decision- making.
The DiD model is appropriate for identifying the causal impact of state aid, as it compares outcome changes over time between subsidised and non-subsidised firms, while accounting for firm-level heterogeneity in scale, capital structure, and innovation behaviour.
2. Data Collection
Financial Data: Data from Bureau van Dijk's Orbis database covering 100-200 steel companies in Montenegro and Albania (2015-2024). Key variables:
Profitability: ROA, ROE, EBITDA margins.
Liquidity: Current ratio, quick ratio.
Investment: R&D expenditure, capital expenditures (CapEx).
State Aid Data: Extracted from the European Commission's State Aid Transparency Database, inclusive:
Subsidy amounts (grants, tax breaks).
Conditionalities (e.g., emissions reduction targets, job retention quotas).
Compliance records (e.g., Montenegro’s 2020 violations).
Environmental Data:
Carbon emissions from the 2024 Sustainable Development Indicators Report (Scope 1 and 2). In addition, as part of the robustness check, the performance of the ESG will be analysed to assess its role in moderating the effectiveness of state aid policies.
ESG scores from DSTI-SC(2024)1-FINAL
3. Sample and Population
Treatment Group: Between 2015 and 2024, 50-100 enterprises in Montenegro and Albania received EU state aid.
Control Group: 50-100 non-subsidised firms, matched by size (employees, revenue), capacity (tonnes/year) and pre-treatment financial performance (average 2015-2019).
Exclusions: Companies with incomplete or questionable financial records and companies that were acquired during the study period.
4. Data Analysis Techniques
4.1 Difference-in-Differences (DiD) Model:
Yit = α + β1Treatmenti + β2Postt + β3(Treatmenti × Postt) + γXit + εit
Dependent Variables (Y): ROA, ROE, carbon intensity (CO2/ton steel), ESG scores.
Treatment Variable: Binary indicator (1 = received state aid; 0 = did not receive).
Control Variables (X): Firm size (log of total assets), leverage (debt-to-equity ratio), R&D intensity (R&D expenditure as a share of revenue), EU policy milestones (e.g., Green Deal ratification), and country fixed effects to account for institutional and structural differences between Montenegro and Albania.
4.2 Robustness Checks:
Propensity Score Matching (PSM): To address selection bias by pairing treated and control firms with similar pre-treatment characteristics.
Event Study Analysis: To assess stock market reactions to state aid announcements, proxying investor confidence in sustainability outcomes.
5. Ethical Considerations and Data Availability
Ethical Compliance: All data is anonymised and publicly accessible, complying with the GDPR and EU open data regulations. No confidential or personally identifiable information is used.
Data Limitations: Reliance on self-reported emissions data may bias measurements. Sensitivity analyses will measure the robustness of alternative emission estimates.