Financing Targeted Basic Income Through Carbon Taxation: A Simulation for Türkiye

Abstract

This research evaluates the financial sustainability of a basic income (BI) model funded through carbon taxation in Türkiye. Unlike classical BI models that provide unconditional transfers to everyone, this study proposes an income support scheme targeted only at those below the poverty line. The model seeks to balance limited resources with the goal of social equity. In this scenario, sectoral carbon taxation evolves progressively. The tax starts with the energy sector, which has the highest emissions, and subsequently shifts to industry and other sectors. Emissions will be reduced by 1% each year, while a carbon tax that starts at USD 12 per ton will be dynamically converted to TL based on the increasing exchange rate year by year. The simulation looks at 2023–2050 and computes annual revenue and expenditure forecasts for the period. The findings indicate that the revenues from carbon taxation are not only sufficient to cover the prioritized expenditure in the targeted basic income (TBI) scheme but also will lead to fiscal surplus in the long run. The research proposes for the first time a framework which integrates social protection and the environmental taxation of carbon, synergizing policies aimed at alleviating income disparity and climate change within Türkiye’s context.

1. Introduction

Universal basic income (UBI) has gained increasing attention in recent years as a viable response to global challenges such as income inequality, structural unemployment, and the social disruptions of technological transformation. In the wake of the COVID-19 pandemic, deficiencies in the flexibility and inclusiveness of social protection systems have brought the UBI concept from a theoretical debate to a practical policy alternative [1]. Defined as regular and unconditional cash transfers to all individuals, UBI aims to ensure income security as a fundamental right.

In the context of Türkiye, persistent income inequality, structural poverty, and inefficiencies in means-tested social assistance have intensified discussions around alternative income support mechanisms. Given the limitations of the national budget and institutional capacity, a fully universal model remains fiscally unfeasible in the short term. This study therefore adopts a “targeted basic income” framework, one that directs unconditional cash transfers solely to individuals below the poverty line, in line with models referred to in the literature as “basic income-like schemes” [2]. The program focuses on the most vulnerable groups by limiting eligibility to approximately 30% of the population. This threshold corresponds to those earning below 70% of the national median income, based on recent income distribution data from the Turkish Statistical Institute [3].

To ensure fiscal feasibility, the model is linked to environmental tax policy. Specifically, it proposes a phased carbon taxation strategy that redistributes collected revenues as targeted BI payments. In doing so, the model contributes to both fiscal sustainability and social equity through an integrated green public finance framework [4,5].

While several studies have explored societal perceptions, theoretical discussions, fiscal implications, and implementation challenges regarding the feasibility of universal basic income (UBI) in Türkiye, as well as international pilot projects and experimental applications [6,7,8,9,10], there remains a significant gap regarding the concrete modeling of financing mechanisms. More so, while developing plans and mid-term programs, green transformation and environmental sustainability have been given more attention in Türkiye’s recent plans [11] but there is still inadequate comprehensive integration of carbon pricing into fiscal policies. Other studies emphasized the importance of carbon pricing in the rest of the world, especially through taxation, in meeting Türkiye’s 2053 net zero target [12,13].

Nevertheless, this gap is addressed by creating a simulation-based targeted basic income (TBI) model funded by a carbon tax, incorporating dynamic indexation linked to macroeconomic indicators. While the proposed model is targeted rather than universal, it aims to inform UBI discussions by offering a practically implementable TBI alternative that is tailored to Türkiye’s context.

Several empirical studies worldwide have examined the poverty and distributional impacts of carbon taxes combined with revenue recycling. For example, Sumaila et al. (2024) conduct a global simulation across 186 countries, finding that a carbon-tax-funded universal basic income could significantly reduce poverty and emissions while boosting the GDP [14]. Vogt-Schilb et al. (2019) use a micro-simulation model in 16 Latin American and Caribbean countries, showing that targeted transfers to the poorest 40% can fully offset regressive impacts, whereas universal transfers mainly reduce inequality [15]. Ohlendorf et al. (2021) assess 87 countries and conclude that targeted revenue recycling can lift millions out of poverty [16]. Similar approaches have also been applied in China [17], South Africa [18], and in multi-country policy reviews [19], all consistently emphasizing the role of targeted transfers in neutralizing regressive effects. Building on this evidence, our study applies a dynamic micro-simulation model that is tailored specifically to Türkiye’s carbon emission structure, fiscal capacity, and poverty profile, incorporating phased carbon pricing and a targeted basic income design.

To our knowledge, there is no existing example in the literature on Türkiye that examines the integration of environmental fiscal tools—such as carbon taxation—into basic income financing schemes.

This study seeks to fill that void by developing a TBI model that is empirically tested through simulation, contributing to the broader discourse on income support policies including UBI.

In an attempt to contribute to the current conversation regarding the strategic relationship between carbon taxes and social protection mechanisms, the study expands on this model by addressing the following research questions (RQs):

RQ1: Can a carbon-tax-funded targeted basic income (TBI) scheme achieve long-term fiscal sustainability under Türkiye’s current macroeconomic projections?

RQ2: How effectively does a composite indexation mechanism preserve the real value of TBI transfers amid inflation, wage fluctuations, and exchange rate volatility?

RQ3: How feasible is the integration of TBI delivery through Türkiye’s existing welfare infrastructure (e.g., EYHBS), and what institutional considerations arise?

These questions now constitute the agenda for analysis in the subsequent sections of the article.

The paper’s structure is set up as follows: the theoretical framework and global context are presented in Section 2; the model assumptions, methodology, and simulation parameters are described in Section 3; the results and financial implications are presented in Section 4; the policy implications and future research directions are covered in Section 5.

2. Theoretical Framework

The philosophical roots of UBI can be traced back to 18th-century Enlightenment thinkers such as Rousseau and Condorcet. In The Social Contract (1762), Rousseau specifically underlined liberty, equality, and popular sovereignty as fundamental ideas of social justice and economic stability. In his posthumously published work, Esquisse d’un tableau historique des progrès de l’esprit humain (1795), Condorcet also underlined the need for universal education and the state’s obligation for guaranteeing basic subsistence. The concept seemed to be more formally expressed with Thomas Paine’s Agrarian Justice (1797), where he recommended direct cash payments to every citizen. Scholars such as Amartya Sen (1999), Guy Standing (2017), and Philippe Van Parijs (2017), who expanded its theoretical basis and policy relevance in contemporary debates, have resurrected UBI in the modern literature [20,21,22,23,24].

Supporters of UBI such as Banerjee, Niehaus, and Suri (2019) argue in favor of social justice and individual liberty—an impact that is multi-dimensional [25]. They emphasize that while there is substantial evidence concerning the social and economic effects of varying UBI schemes, the context has a significant impact on the effectiveness of the programs, with some being aptly effective and others not at all [25].

Apart the social results of a UBI, its long-term sustainability is dependent on how it is funded. In this regard, tax reasons beyond economic growth—such as those aimed at protecting the environment—become promising. Carbon taxes are cost-effective environmental regulations that impose financial penalties on activities that cause pollution. Based on the theory of “the polluter pays,” these taxes aim to curb greenhouse gas emissions and fossil fuel use. According to the OECD (2021), more than 60 countries currently implement some form of carbon tax [26]. Social transfer mechanisms are used in countries such as Canada, Sweden, and Switzerland to share a portion of tax revenues. These examples show that environmental and social goals can be achieved together.

This dual purpose is embodied in the concept of green public finance, which refers to the integration of fiscal policy with environmental sustainability goals. This policy seeks to raise revenue to reduce negative environmental impacts and ensure that public funds are spent on ecological change. Carbon taxes, which involve some form of redistribution, are a good example of such a policy. However, such taxes are often regressive—they have disproportionate impacts on low-income households. Therefore, some form of subsidy or cash transfer is necessary [4,27]. Goulder (1995) makes a pivotal distinction between “revenue-raising” and “behavior-changing” goals of environmental taxation, arguing that their design can be optimized to serve both simultaneously if integrated with redistributive mechanisms. This conceptual foundation strongly supports the present model, which channels carbon tax revenues into targeted social transfers—thereby enhancing both environmental and distributional outcomes. The balance between allocative efficiency and equity, as highlighted by Goulder, underpins the rationale for using carbon taxation not only as a regulatory tool but also as a funding source for inclusive income support policies [28].

In this context, the intersection of social policy with environmental taxation is emphasized as a critical tool for achieving social and ecological goals. In this system, both carbon taxes and targeted basic income work as common components. Universal approaches are simple and cover everyone, but they create unsustainable spending problems, especially in poorer countries. For this reason, many countries have opted for targeted approaches that focus on low-income households. These are often described as “basic income-like schemes” because they can provide both fiscal sustainability and unconditional transfers [2]. Although unconditional income lies at the heart of the universal basic income (UBI) idea, the version put forward here adapts this principle to Türkiye’s circumstances by granting unconditional cash payments to everyone living below the poverty threshold. Given the country’s limited fiscal capacity and modest administrative resources, moving directly to a fully universal scheme is not realistic at present. The targeted basic income model proposed here is therefore a workable alternative that protects the moral foundation of UBI while fitting within existing institutional arrangements and safeguarding fiscal discipline. Examples from Brazil (Bolsa Família), Spain (Ingreso Mínimo Vital), and Iran (energy subsidy reform) show that targeted income transfers can effectively reduce poverty and inequality without compromising budgetary constraints.

Directing carbon tax revenues to targeted BI schemes allows environmental and social policy agendas to advance simultaneously. Jakob et al. [29] state that such integration increases both fiscal sustainability and public acceptance. For developing countries such as Türkiye, aligning carbon tax revenues with targeted BI programs offers an innovative policy option to simultaneously promote climate resilience and social justice.

In recent years, universal basic income (UBI) has evolved from a marginal policy idea to a widely discussed global proposal [24]. Many pilot programs and partial implementations have been conducted to test the feasibility, economic impact, and public reception of UBI, including large-scale experiments in Finland [21] and unconditional cash transfer programs in Kenya [30]. The following section examines some examples of significant UBI experiments and initiatives from various regions, discussing their designs and outcomes, and drawing implications for the Turkish context.

In order to contextualize the discussion for Türkiye, we adopt the eco-welfare state approach articulated by Gough [30], which suggests a convergence between welfare and environmental states, especially in response to structural pressures such as inequality and climate risk. This model positions carbon taxation not just as a budgetary tool but also as part of a dismantling socio-environmental strategy. Universal entitlements are something that can be maintained by high-income countries but middle-income contexts like Türkiye require adaptive models that take into consideration institutional and budget limitations. Comparative experiences show that even within OECD nations, the configuration of environmental tax revenue use differs based on political economy and welfare traditions. Integrating such insights helps localize the model without losing relevance for global debates [30].

2.1. Finland: A UBI Pilot Within a Welfare State

A two-year pilot study including 2000 randomly chosen jobless individuals between 2017 and 2018 was carried out in Finland. Participants received EUR 560 a month, unqualified. Notwithstanding modest employment effects, the results of the experiment showed notable increases in mental well-being, life satisfaction, and trust in institutions. Though its scale and scope were limited, the Finnish example demonstrates how universal basic income (UBI) can have positive psychological and social effects even in well-developed welfare systems [31].

2.2. Canada (Ontario): A Promising Initiative Interrupted by Politics

Ontario launched a basic income pilot in 2017, involving over 4000 participants across three cities. Monthly payments ranged between CAD 1400–2000, depending on marital status. Although preliminary findings indicated improved food security, reduced stress, and better financial stability, the program was terminated in 2018 due to a change in provincial government. Despite promising early results, the Ontario case underscores the susceptibility of UBI programs to political shifts [32].

2.3. Spain: From Local Pilots to National Implementation

Spanish policy toward basic income has developed as a result of both national reform and municipal experimentation. The 2017–2019, the B-MINCOME pilot in Barcelona tested conditional and unconditional transfer models among low-income households. While employment outcomes were limited, improvements were observed in well-being, social engagement, and perceptions of autonomy [33].

In response to the COVID-19 crisis, Spain introduced Ingreso Mínimo Vital (IMV) in 2020—a means-tested national minimum income scheme. While IMV is not a complete universal basic income (UBI), it offers monthly payments to low-income households, affecting more than 2.3 million individuals. Together, these initiatives serve as an illustration of Spain’s progressive efforts to achieve income security by employing diverse delivery models [34].

2.4. Kenya: The Longest Running Unconditional Basic Income Pilot

Under the leadership of the non-profit organization GiveDirectly, Kenya is home to the most extensive and sustained pilot of unconditional basic income in the world. Since 2018, over 20,000 individuals from more than 200 rural villages have been enrolled in a 12-year randomized controlled trial with three distinct groups: long-term monthly recipients (12 years), short-term recipients (2 years), and one-time lump-sum recipients. Early results suggest that long-term and lump-sum transfers lead to more durable improvements than short-term assistance [35].

Additionally, Haushofer and Shapiro [36] conducted experimental research on Kenya’s previous cash transfer programs, which verifies the multifaceted advantages of unconditional transfers. They discovered substantial enhancements in the psychological well-being, asset acquisition, food security, and consumption levels of recipients in their randomized study [36]. Transfer recipients consistently had better measures of life satisfaction, happiness, and less stress. Particularly among women, cortisol tests revealed lowered biological stress markers [35].

These results together show that UBI-style interventions can efficiently lower poverty, improve household resilience, and support mental health without creating social conflict, offering important new perspectives for future application in low-income environments.

2.5. Brazil: Bolsa Família and the Global CCT Model

One of the biggest and most successful conditional cash transfer (CCT) systems worldwide is the Bolsa Família Program (BFP), which came out of the merger of four already running social programs starting in 2003. Through direct cash transfers, the program is meant to lower short-term poverty; it also aims to change the intergenerational transmission of poverty by pushing school attendance and health checks and increasing complementary social services [37].

Targeting is based on household income thresholds and is administered through the Cadastro Único system. Conditionalities include school enrollment and attendance, child vaccinations, and prenatal care adherence [37]. By 2006, BFP had reached over 11 million families—nearly a quarter of Brazil’s population—with 73% of benefits going to the poorest income quintile and 94% to the bottom two quintiles [37].

Impact evaluations estimate that the BFP contributed to 20–25% of the decline in inequality and 16% of the reduction in extreme poverty in the early 2000s [37]. Its decentralized structure and targeting accuracy have made it a global reference for CCT program design.

2.6. India: UBI Pilots in Rural Communities

Between 2011 and 2012, the Self-Employed Women’s Association (SEWA) and UNICEF implemented two substantial universal basic income demonstration programs in Madhya Pradesh, India. In the initial experiment, over 6000 individuals received monthly unconditional cash distributions for a period of 18 months in nine villages. A control group was established in a comparable set of villages. A second pilot study focused on tribal communities.

Results from both experiments demonstrated marked improvements in nutrition, school attendance, health care usage, and sanitation. Notably, the transfers empowered women, increased savings and investment in productive assets, and reduced reliance on informal moneylenders. Community members also reported a stronger sense of economic and personal agency [38].

India’s pilots provide strong empirical support for the idea that even modest, regular, unconditional payments can produce transformative social and economic outcomes in rural and low-income settings.

2.7. Iran: A De Facto Basic Income Through Energy Subsidy Reform

Iran’s 2010 subsidy reform is one of the most comprehensive real-world examples of nearly universal basic income. The government started giving unconditional monthly cash payments of about USD 45 (Rl 455,000) to almost all of the nation’s residents as part of a comprehensive overhaul of energy subsidies [39]. These “cash subsidies” replaced highly regressive fuel and commodity subsidies that had primarily benefited wealthier urban households.

Although not framed as a basic income policy, the program meets many of its criteria: unconditionality, universality (with few exceptions), and individual-level transfers. Tabatabai [39] notes that the reform was initially well-received and reduced income inequality, but the program later faced fiscal sustainability concerns, inflationary pressures, and political contestation.

Despite its limitations, the Iranian model demonstrates how fiscal space for basic income can be created by reconfiguring inefficient subsidy systems. Examining the political and economic compromises associated with wealth redistribution on a national scale is still worthwhile.

2.8. Alaska (USA): Oil Revenues as a De Facto Basic Income

One of the oldest examples of a basic income-like system in the real world is the Alaska Permanent Fund Dividend (PFD). Established in 1982, the PFD distributes an annual, unconditional cash payment to nearly all Alaska residents. The dividend is financed through investment earnings from the Alaska Permanent Fund, which itself is sustained by oil royalties collected from resource extraction on public land [40].

While the payment size varies by year, the PFD remains universal, individual, non-conditional, and is delivered as cash—thus aligning closely with basic income principles. Although modest in size relative to poverty thresholds, it contributes significantly to household income in rural areas and has had measurable effects on poverty reduction and income equality. In the 1980s and 1990s, Alaska was the only U.S. state where income growth among the poorest 20% outpaced that of the wealthiest quintile [40]. The program is politically resilient, and its popularity has fostered a unique sense of shared ownership over natural resource revenues.

The Alaska model demonstrates how resource wealth can be transformed into a broadly shared public benefit, offering a real-world policy laboratory for future income redistribution models.

The country examples cited in this section are summarized in

Table 1. Global implementations of universal basic income (UBI).

Country	Program	Features	Source
Finland	Government-supported pilot (2017–2018)	Unconditional monthly payments of EUR 560 to 2000 unemployed individuals	Kangas et al. [31]
Canada (Ontario)	Provincial-level pilot (2017–2019)	Monthly payments between CAD 1400–2000 to 4000 low-income individuals	Hamilton & Mulvale [32]
Spain	Ingreso Mínimo Vital (2020–present)	Conditional, ongoing income support for low-income households	Ministerio de Inclusión [41]; Eurofound [34]
Kenya	GiveDirectly initiative (2016–2029)	12-year unconditional cash transfers in rural villages	Haushofer & Shapiro [36]; Kelly [35]
Brazil	Bolsa Família/Renda Básica de Cidadania	Conditional cash transfer program evolving into UBI debate	Lindert et al. [37]
India	UBI pilot in Madhya Pradesh	Rural cash transfer experiments across tribal and non-tribal villages	Davala et al. [38]
Iran		Near-universal monthly payments covering ~95% of the population	Tabatabai [39]
Alaska (USA)		Annual unconditional cash payments from oil revenues	Goldsmith [40]

below. The variety of UBI proposals around the globe shows how national differences in institutional capacity, fiscal space, political will, and socioeconomic priorities shape such programs. For simple income plans as well as a useful framework for comparison study, this variety offers operational flexibility. For nations like Türkiye who are looking to create UBI plans that strike a mix between social equity and financial sustainability, these models provide a basis.

According to the sources listed in Table 1, financing models also differ significantly across contexts. In high-income countries like Finland, Canada, and Spain, programs of the basic income type are largely financed from general taxation, which indicates their higher fiscal capacity. In resource-rich environments like Alaska and Iran, dedicated revenues from oil royalties or savings from energy subsidy reform have been at the heart of financing regular transfers. In lower-income or trial contexts, such as Kenya and India, support from charities or international donors has played a key role in starting pilot programs. These differences show how important it is to choose a funding method that fits each country’s budget capacity, resources, and institutions, and reflects the growing interest in using environmental tax revenues to support social programs.

This cross-national evidence highlights the point that one-size-fits-all solutions to financing basic income plans do not exist; mechanisms have to be tailored to every country’s fiscal room, resource base, and institutional setting. Within the case of Türkiye, both the constrained fiscal space and the increasing emphasis on environmental sustainability as well as the 2053 net-zero target make the earmarking of carbon tax revenue to fund a specifically targeted basic income solution a highly viable and context-oriented option. The proposed solution aligns with both the emerging new global trend of financing social protection from environmental taxation and the country’s overall green transformation agenda.

2.9. Lessons and Implications for Türkiye

The country examples above suggest that there is no single blueprint for implementing a universal basic income (UBI). Fiscal space, institutional capacity, political culture, and the social needs of a nation shape its implementation. For Türkiye, a focused basic income funded by environmental taxes instead of a totally universal plan might be a good beginning point.

These models are often embedded within national welfare regimes. As Gough [30] emphasizes, Nordic countries typically support universalism due to their strong social democratic traditions and fiscal resources, whereas southern or middle-income countries tend to adopt targeted or hybrid models in response to more constrained budgets and less institutionalized welfare systems. Türkiye’s limited fiscal space and historical reliance on means-tested social assistance programs closely align with this latter approach, reinforcing the relevance of a targeted model in this context. Iran’s national cash transfer program, supported by the removal of fuel subsidies, shows how regressive public spending can be shifted to direct income support. The Permanent Fund Dividend in Alaska offers a parallel example of distributing resource revenue fairly among residents. Initial studies in Kenya and Finland also suggest that even modest, regular payments can improve household stability, well-being, and mental health. Comparative studies on carbon tax revenue recycling in South Africa [18], targeted transfers in Latin America and the Caribbean [15], and global assessments of basic income models [14] reinforce the view that integrating environmental taxation with targeted income support can simultaneously advance poverty reduction, social justice, fiscal sustainability, and climate resilience. For the underprivileged people of Türkiye, all of these instances are significant considerations. Building on these realizations, Türkiye could start an initiative concentrating on regional pilot projects, especially in areas that are vulnerable to natural disasters or economic crises. The financial resources needed to finance a targeted BI could be generated initially by a phased carbon tax applied to high-emission industries. With this strategy, the scale could be adjusted based on data and public response. Drawing on the lessons from these international experiences and comparative studies, a carefully designed BI model in Türkiye may not only help reduce poverty and promote social justice but also may enhance fiscal sustainability and climate resilience.

Türkiye’s total greenhouse gas (GHG) emissions were measured at approximately 598.9 million tons of CO₂ equivalent in 2023, with 71.6% originating from the energy sector, followed by agriculture (13.0%), industrial processes and product use (12.8%), and waste (2.5%) [42]. Although households are not listed as a separate category in production-based inventories, recent consumption-based studies estimate that household demand indirectly drives around 59% of national emissions [43]. Evidence also shows that while the lowest income decile contributes less than 10% of household-related emissions, the top quintile accounts for more than 40% of these groups [44].

These distributional patterns underline the importance of designing equitable climate policies. Despite lower per capita emissions compared to OECD averages, the rapid growth rate in emissions highlights the urgent need for effective carbon pricing mechanisms [45]. Currently, Türkiye does not implement a direct national carbon tax; instead, the Special Consumption Tax (ÖTV) on fossil fuels indirectly influences emissions. However, this structure mainly serves revenue purposes rather than environmental objectives and does not fully align with international carbon pricing principles [45]. Nevertheless, the concept of a direct carbon tax was formally introduced into national policy planning through the 2022–2024 Medium-Term Program, signaling a strategic shift toward future carbon pricing mechanisms. This transition was further reinforced in the 2024–2026 Medium-Term Program, where the emphasis on “green transformation” placed carbon taxation within a broader strategy for sustainable economic development [46].

Depending on national circumstances and environmental goals, comparative studies reveal that the current carbon tax rates in OECD nations typically vary from USD 30 to USD 100 per ton [45] (p. 85). However, the United Nations Handbook on Carbon Taxation for Developing Countries [45] advises that developing economies should start with relatively low carbon tax rates to avoid economic shocks and to allow households and businesses to adjust. The report notes that some countries have initially set rates as low as USD 5–10 per tonne of CO₂, with plans to gradually increase them towards the social cost of carbon or to a level that is consistent with the country’s greenhouse gas mitigation targets. This phased approach is highlighted as an effective way to build public acceptance and develop the necessary institutional and administrative capacity [47] (pp. 74–76). Similarly, the World Bank Group data presented in Addressing Climate Change Through a Low-Cost, High-Impact Carbon Tax highlights that most developing and transition economies apply carbon taxes that are below USD 10/tCO₂e. Examples include Mexico, Colombia, and South Africa, which introduced a USD 10/tCO₂e tax in 2019 with annual increases of inflation plus 2%. The same source (p. 21) notes that mid-level carbon prices (USD 10–30/tCO₂e) are less common but can be found in Slovenia, Alberta, British Columbia, the United Kingdom, Spain, Ireland, and Denmark. Denmark’s rate was around USD 18 in 2002 and later rose to USD 25–29 depending on the fuel type [48]. Combining these insights, a USD 12/tCO₂ starting point for Türkiye would be aligned with international practices among developing economies. It would also provide a reasonable balance between fiscal needs, climate objectives, and social acceptability, while allowing for a planned escalation towards higher rates that is consistent with Türkiye’s long-term mitigation commitments.

In this analysis, a single, moderate starting rate was selected deliberately. Türkiye does not currently have a direct carbon tax, and the primary aim was to assess the feasibility of linking such a tax to a targeted basic income scheme under conditions that are realistic and politically workable. Using one well-justified starting point allowed the mechanics and potential of the model to be demonstrated without the added complexity of multiple scenarios.

Different rates involve clear trade-offs. A higher initial level—at considerably more than USD 20/tCO₂—would collect more money and accelerate emission cuts more quickly, but would risk greater public resistance, more severe adjustment costs, and potentially regressive effects in the absence of robust compensatory policies. Or starting lower than USD 10/tCO₂ would ease near-term pressures but might not collect sufficient funds to make the intended basic income program effective in reducing poverty.

Considering these factors, the analysis focuses on a single, internationally consistent moderate rate that balances fiscal yield, social acceptability, and environmental ambition. The potential effects of alternative rates on fiscal sustainability, poverty reduction, and distributional outcomes are identified as a subject for future research.

At a carbon tax rate fixed at USD 12 per ton, and using the official year-end exchange rate of 26.9 TL [49], the effective domestic rate becomes approximately 323 TL per ton. With Türkiye’s annual emissions estimated at 598.9 million tons, this would generate roughly 193 billion TL in carbon tax revenue in 2023. While this is not sufficient to fully fund the proposed basic income program in the early years, it would still cover a significant share of the cost and reduce the need for public budget support during the transition [50].

Furthermore, it is important to consider Türkiye’s current social assistance landscape. Türkiye currently spends between 1.5% and 2.0% of its national budget on social assistance programs [51] (p. 45). Under the 12 USD/ton carbon tax scenario, projected revenues for 2024 are around 254 billion TL. This is equal to, and in the near term may exceed, the total expenditure by Türkiye that is currently estimated at 1.5–2.0% of the national budget on social support programs. This would be a major new source of finance in addition to existing allocations, thus creating real fiscal space for increasing income-based support. The effect would be most pronounced if revenues were devoted exclusively to directed social transfers since it would reduce reliance on general budgetary resources and improve the stability and predictability of financing.

Nevertheless, several institutional barriers could complicate the practical implementation of such a system. The most notable challenges include public resistance to additional fiscal burdens, reliance on fossil fuels for energy supply, and concerns about the potential negative impacts of environmental taxation on economic growth. International models, such Canada’s carbon pricing model, however, point to revenue recycling and rebate systems as a means of somewhat reducing these obstacles [4] (p. 673). Türkiye could design a comparable revenue repatriation system to boost the operational viability of carbon taxation and the public acceptance of it. Apart from local policies, Türkiye could also act to gain from worldwide climate finance systems like the European Union Climate Transition Fund or the Green Climate Fund to raise the financial viability and social acceptance of the suggested carbon tax system.

In addition to carbon taxation, other financing mechanisms have been explored in various country contexts. These include progressive income taxation as modeled in some Nordic countries such as Finland and Denmark [29], and value-added tax (VAT) used in discussions around South African [23] and Indian transfer programs. The so-called Robin Hood tax, which aims to generate significant revenue by taxing high-frequency financial transactions, can also be evaluated within this scope as an alternative financing method. According to Miller and Tyger [52], a financial transactions tax (FTT) applied at modest rates could generate hundreds of billions of dollars annually, depending on market behavior and policy design. While this study focuses on carbon taxation due to its environmental co-benefits, acknowledging alternative approaches adds perspective to the broader fiscal conversation around basic income design in Türkiye.

3. Conceptual Underpinnings, Methodology, and Simulation

With the consideration of recent research and international benchmarks, this section proposes a basic income model that is specific to Türkiye. We will begin with the methodology and theoretical framework of the model. Later in this section, we analyze salient design assumptions and elements alongside the results from several simulations. The primary aim is to demonstrate the effectiveness of a properly designed carbon tax both as a revenue-generating measure and as a strategy for reducing income inequality while promoting environmental protection.

3.1. Conceptual and Theoretical Foundations

In the context of increasing climate risks and persistent income inequality, many scholars and institutions have begun exploring integrated approaches that combine environmental taxation with social protection. Particularly in developing and middle-income countries like Türkiye, where fiscal resources are constrained, the idea of using carbon tax revenues to support targeted cash transfer programs has gained growing attention [4,25]. These models are not only designed to internalize environmental externalities but also to overturn the regressive distributional consequences of carbon pricing through redistributive channels. As Carattini et al. emphasize, revenue recycling through explicit household transfers dramatically improves the social acceptability and long-term feasibility of carbon taxation [53]. In light of this conceptual background, the model suggested herein presents a localized roadmap for implementing a carbon-tax-funded targeted basic income scheme that is in alignment with Türkiye’s socioeconomic realities.

Building on this targeted approach, the building blocks of the model consist of three key components. First, imposing a carbon tax discourages CO₂ emissions by dissuading the consumption of fossil fuels and generates income. Second, unconditional monthly cash transfers are provided for the lowest 30% of citizens—those earning below 70% of the median national income. Third, a recycling framework for revenue ensures that a significant portion of the carbon tax revenue goes back to households, enhancing both equity and acceptability among the public for the program.

This model fits within the overarching “green” public finance paradigm which seeks to integrate environmental sustainability as well as equity considerations into the design of fiscal policies. The “green growth” discourse stresses that environmental policy can be reinterpreted as an economic opportunity instead of a cost, and fiscal instruments can therefore be used for both macroeconomic and environmental purposes [54].

In line with this approach, rather than treating carbon taxation and income redistribution as separate tools, this model integrates them into a single mechanism. Several studies emphasize the dual potential of carbon taxes to reduce emissions while addressing inequality [29,53].

As Jakob et al. [29] argue, the revenue from carbon pricing can serve as a development instrument when reinvested in poverty reduction and infrastructure, making such policies more inclusive and politically acceptable in lower-income settings.

Supporting evidence also exists. Well-targeted transfer programs like Brazil’s Bolsa Família, Spain’s Ingreso Mínimo Vital, and Iran’s post-subsidy reform program show that targeted transfers can significantly reduce poverty, even in countries with constrained fiscal budgets [34,37,39]. In addition, the last recommendations from the ILO and World Bank have proposed more responsive, inflation-adjustable support for income in middle-income countries [55,56].

The model presented here contributes an innovative design through the synthesis of phased, sectoral carbon taxation with dynamic indexation and a custom-designed benefit scheme. Even as it borrows from global practice, the model establishes itself in Türkiye’s demographic, budgetary, and institutional context.

3.2. Methodological Framework and Assumptions

The study in this article adopts a simulation-based strategy to evaluate the funding viability of a focused basic income (BI) scheme financed by carbon taxation in Türkiye. The strategy is not founded upon behavioral modeling or macroeconomic forecasting, but on deterministic projections—where all core variables progress according to predetermined rates or official data. This method makes feasible an open examination of how, over time, with realistic economic and demographic assumptions, the interrelation between carbon tax revenues and indexed BI spending would evolve. This reflects a broader tension noted in the public finance literature—wherein environmental tax instruments are expected to serve both regulatory and revenue-raising goals simultaneously [57].

The choice of the simulation period, 2023–2050, aligns with both the availability of timely macroeconomic data and Türkiye’s revealed long-term climate policy goals, including most prominently the 2053 national decarbonization target. Such a long term allows for an examination of the medium- and long-term fiscal relationships and the ability to make sure that stepped-up carbon taxing in sectors over time (2025–2029) and accompanying social policy reactions are duly accounted for. The same sort of forward-looking model windows are found in previous fiscal policy simulations in the literature, too [58,59], which typically extend over two to three decades in order to capture effects from carbon-pricing instruments across full cycles.

The structure of this model draws conceptual inspiration from scenario-based fiscal modeling frameworks previously used in environmental economics [29,60]. While not directly replicating a single existing model, the study adopts a simplified deterministic simulation approach—as opposed to dynamic general equilibrium or econometric forecasting techniques—in line with the policy-focused models discussed by Fullerton & Metcalf [58] and Parry et al. [59]. These approaches emphasize transparency, replicability, and usability in real-world policy scenarios, particularly in developing country contexts where data constraints may limit highly technical modeling. In this regard, the choice of a non-behavioral model was intentional because country-specific elasticity estimates are not yet available for Türkiye and the primary goal is to establish a clear baseline of fiscal sustainability before incorporating behavioral complexity. This also means that the model does not take account of possible changes in consumption patterns, fuel substitution, or investment responses motivated by carbon taxation. Accordingly, findings are presented as fiscal and distributional effects assuming no behavioral response—a shortcoming noted here and recognized as a future research priority.

The simulation is for 2023 to 2050 and replicates the selection of the subsequent important characteristics:

Sector phasing of carbon tax: On the tax side, coverage is phased in over time. In 2025, the carbon tax encompasses energy sector activity, primarily electricity generation and fossil fuel use in production, accounting for about 70% of Türkiye’s total GHG emissions. Emissions from chosen industrial processes are included by 2027, and by 2029, all major emitting sectors are covered. This phasing follows suggested policy uptake paths and aligns revenue projections with the phasing in of the tax base.

Annual emission reduction: An annual decrease of 1% (To demonstrate robustness, a brief sensitivity check was performed using alternative reduction rates of 0.5% and 2% and the evaluation of the results is stated as a footnote in Section 4) in total CO₂ emissions is assumed throughout the simulation period, based on Türkiye’s green policy goal. It projects a 1% per year fall in carbon emissions during 2023-2050. This is a moderate linear estimate of Türkiye’s updated Nationally Determined Contributions (NDCs) in 2022, designed to cut by 41% below business-as-usual (BAU) levels by 2030. This corresponds to an average annual reduction of approximately 2.5%, but it is cumulative, not linear. While the NDC trajectory is nonlinear, the 1% yearly reduction is consistent with globally agreed-upon benchmarks on moderate decarbonization for the developing world.

Fixed carbon price (USD-based): The carbon tax rate is USD 12 per ton and is converted into Turkish Lira annually on the basis of a 22.5% increase in the exchange rate of USD/TRY. The exchange rate projection in the model assumes a 22.5% annual growth, reflecting Türkiye’s historical average between 2008 and 2023. While this assumption mirrors long-term trends, it does not account for potential macroeconomic shifts such as monetary tightening or central bank interventions aimed at stabilizing the currency (in this regard, an evaluation was made by considering rates such as 10% and 15%, and the necessary explanation was made in the Results Section).

Targeted BI eligibility: The model is constructed at the individual level, using equivalized disposable income to determine eligibility for targeted basic income (TBI). Beneficiaries are defined as those with incomes below 70% of the national median, representing roughly 30% of the total population. However, it is important to note that poverty is not a dynamic factor and is likely to change due to factors such as economic shocks, inflation, and migration due to climate change. While it is possible to use poverty elasticity or average thresholds at this point, a static threshold is maintained in this version to maintain transparency and prevent multiple speculative assumptions.

In addition, the model assumes that identification of the beneficiaries would be conducted through the use of Türkiye’s Integrated Social Assistance Information System (EYHBS). While the EYHBS is a great administrative system, it may inadvertently miss those who are not registered formally, such as informal economy laborers, seasonal agricultural workers, or refugees. In order to mitigate such exclusion risks, subsequent policy execution could incorporate mobile outreach systems, grass-root-level enrollment drives, and grievance redress systems to ensure equal and inclusive access to benefits.

Dynamic BI indexation: Monthly BI transfers increase by 21.63% per annum, using a weighted formula of inflation (40%), minimum wage rise (35%), and exchange rate fluctuation (25%) to reflect their collective effect on purchasing power.

TÜİK population projections (2023–2050) are utilized to estimate the number of eligible beneficiaries and total spending. Sources for carbon emissions are derived from official data, and future emissions are discounted each year based on the 1% reduction rule. Revenue calculations account for phased sectoral coverage and a carbon pricing system. The exchange rate is projected on a historical basis using a constant average annual growth rate.

This modeling approach omits behavior response, feedback loops, and sectoral decarbonization trajectories. Administrative cost, as well as shifts in political leanings, are not taken into account. The model does not strive to produce realistic projections, but to see if a program such as this can remain financially sustainable on reasonable, explicitly stated assumptions.

By mimicking the way revenues and outlays develop in conjunction with each other over almost three decades, the model offers a foundational framework for evaluating the balancing acts between environmental taxation and social protection under today’s fiscal and demographic circumstances of Türkiye.

3.3. Revenue, Expenditure, and Indexation Dynamics

In order to evaluate the fiscal feasibility of the proposed basic income program, this section outlines the payment level, estimated costs, and the indexing approach used to update transfers over time.

Türkiye’s hunger threshold for a family of four is 14,431 TL per month, or roughly 3608 TL per person, based on Confederation of Turkish Labor Unions’ (TÜRK-İŞ’s) statistics for December 2023 [61]. Although the 500 TL suggested monthly basic income falls short of this level, it at least offers approximately a 14% contribution to cover basic food and utilities. Data from the Ministry of Family and Social Services show that Türkiye’s present average monthly cash transfers across various social programs per person fall between 250 and 800 TL [51]. The suggested 500 TL falls midway within this range. Consequently, one can argue that this level is both technologically feasible and socially reasonable. In line with budget restrictions, public support, and international criteria, it offers an estimated 10–15% increase in purchasing power for households to be included in the program.

While the transfer amount remains modest relative to the hunger threshold, its expenditure implications are also relevant. Evidence shows that low-income households allocate marginal income predominantly to food, heating, and electricity, while higher-income households devote more to private transport and discretionary goods [43,44]. Since the proposed scheme targets only the bottom 30% of the population—who account for less than 10% of household-related emissions, additional emissions from increased basic spending are expected to be limited. Moreover, the carbon tax simultaneously dampens the demand for energy-intensive items, suggesting that the combined effect would protect equity without jeopardizing aggregate emission reductions.

Basic income payments under the proposed system increase from 500 TL per person per month by 21.63% annually. The payment is only available to people who are below the poverty line, which is estimated to be 30% of the population, according to TÜRK-İŞ and TÜİK data. This approach seeks to guarantee the effective use of public resources and ensure budget sustainability. According to 2024 TÜİK data, approximately 28–29% of the population earns less than 70% of the national median income, supporting the validity of the 30% eligibility threshold used in the model [3].

Given the restrictions on Türkiye’s central government’s budget and the growing pressure on social assistance programs, finding a sustainable source of funding is increasingly crucial. In this context, carbon taxation provides both environmental benefits and a potentially significant revenue stream. As a result, setting the right price for carbon emissions is crucial for meeting climate targets and funding vital social programs. In light of this,

Table 2. Carbon tax applications: international comparison.

Country	Status	Carbon Tax per Ton (USD)
Sweden	Developed	137 USD
Switzerland	Developed	131 USD
Finland	Developed	80 USD
Norway	Developed	76 USD
France	Developed	50 USD
Ireland	Developed	48 USD
Canada	Developed	37 USD
Denmark	Developed	36 USD
Germany	Developed	30 USD
United Kingdom	Developed	22 USD
Poland	Developed	13 USD
Argentina	Developing	10 USD
South Africa	Developing	8 USD
Uruguay	Developing	6 USD
Chile	Developing	5 USD
Colombia	Developing	5 USD
Mexico	Developing	3 USD
Japan	Developed	2.65 USD
India	Developing	1–3 USD (indirect)
OECD Average	Mixed	≈35–40 USD
Türkiye (proposed)	Developing	12 USD

Source: World Bank, State and Trends of Carbon Pricing 2023 [62].

presents a comparative analysis of carbon tax rates in various nations, emphasizing notable differences between developed and developing economies.

Even though the average carbon tax rate among OECD countries is estimated to be between USD 30 and 60 per ton, most developing economies maintain much lower rates, typically between USD 3 and 10 per ton [62]. A carbon tax at the OECD average would likely place an excessive amount of financial strain on businesses and consumers, given Türkiye’s industrial structure, average income, and currency volatility. Consequently, an initial rate of USD 12 per ton has been selected as a more realistic and politically viable starting point. This decision is believed to be in accordance with international norms among developing economies and sufficient to finance the targeted basic income expenditures under the proposed model. A more detailed assessment of fiscal sustainability at this carbon tax rate can be found in the section on simulation results.

Setting the same carbon tax for all companies could backfire a bit. Some businesses already keep their emissions low or have invested in cleaner technologies. Yet, they would still pay just as much as high-emitting firms. That does not seem very fair—and to be honest, it might even slow down innovation. A better system might reward those who are performing well, or at least offer some flexibility. This creates a fairness issue and may even discourage innovation. This could, in the long run, reduce the motivation to innovate in environmentally friendly directions.

More fundamentally, that is also a reflection of a wider policy issue: marginal abatement costs differ across sectors quite substantially. Cement, steel, and aviation industries have more expensive short-term emission reductions, while others, for example, services or light manufacturing, have less stringent flexibility and lower mitigation costs.

This is simple, but might be economically inefficient and met with hard-to-abate resistance. Future versions of this model will consider differentiated tax rates but request more aggressive tax rates in high-emitting sectors, accompanied by rebates or transitional support for those holding credible plans for decarbonization or demonstrating better performance than sectoral averages.

Such fine-tuning would both enhance economic and environmental effectiveness and potentially increase political acceptability, especially in high-carbon sectors. Firm-level emission indicators would be combined or benchmarking would be performed on a sectoral basis in order to strike such a balance in the Turkish environment between equity and ease of implementation.

While the carbon tax rate is set at USD 12 per ton, this figure is not fixed in Turkish Lira terms. It is expected to change each year, based on projected increases in the exchange rate. So, the actual tax revenue collected will vary over time—not just because of the exchange rate, but also depending on which sectors are being taxed in a given year.

According to data from 2023, Türkiye’s total greenhouse gas emissions are around 599 million tons. Also, the tax will not apply to every sector right away. It will start with the energy sector in 2025–2026, then move on to industry by 2027–2028. Everything else comes under the tax in 2029. As more sectors are included, revenues should go up. It is a gradual rollout, which makes the plan more manageable in practice.

To ensure that projected revenues are matched by realistic and socially responsive expenditure planning, the model also incorporates an adaptive mechanism for adjusting the basic income amount over time.

In basic income schemes, keeping the payment amount fixed over time inevitably results in declining purchasing power. Therefore, the model proposed for Türkiye includes a mechanism for periodically adjusting the basic income amount in response to evolving economic conditions. This dynamic approach is vital for ensuring both the effectiveness and long-term sustainability of the program.

Table 3. Annual economic indicators in Türkiye (2008–2023).

Year	CPI Inflation (%)	Minimum Wage Increase (%)	USD/TRY Exchange Rate Increase (%)
2008	10.1	8.6	6.7
2009	6.5	9.6	4.6
2010	6.4	9.9	5.3
2011	10.5	12.3	12.1
2012	6.2	8.6	5.6
2013	7.4	0	6.2
2014	8.2	24.5	7.9
2015	8.8	30.0	24.3
2016	8.5	7.9	19.6
2017	11.9	14.2	21.8
2018	20.3	26.1	38.5
2019	11.8	15.0	12.2
2020	14.6	21.5	24.8
2021	36.1	50.5	40.3
2022	64.3	100	28.9
2023	64.8	99.9	26.1

Sources: Turkish Statistical Institute [63]; Central Bank of the Republic of Türkiye [49]; Ministry of Labor and Social Security [64].

presents annual data for three key economic indicators in Türkiye—the Consumer Price Index (CPI), minimum wage growth, and the USD/TRY exchange rate—for the period of 2008–2023. These data serve as the foundation for a weighted-average formula used to determine the annual increase in basic income payments.

In Table 4, the average annual growth rates for each indicator are listed as follows:

• Inflation (CPI): 14.2%;
• Minimum wage growth: 28.8%;
• USD/TRY exchange rate growth: 22.5%.

Table 4. Average annual growth rates of index variables (2008–2023).

Indicator	Average Annual Increase (%)	Source	Description
Inflation (CPI)	14.2	TÜİK	Average annual Consumer Price Index (2008–2023)
Minimum Wage Increase	28.8	MoLSS	Annual average increase in gross minimum wage
USD/TRY Exchange Rate	22.5	Central Bank of the Republic of Türkiye (CBRT)	Average annual increase in the USD/TRY exchange rate

Table 4. Average annual growth rates of index variables (2008–2023).

Indicator	Average Annual Increase (%)	Source	Description
Inflation (CPI)	14.2	TÜİK	Average annual Consumer Price Index (2008–2023)
Minimum Wage Increase	28.8	MoLSS	Annual average increase in gross minimum wage
USD/TRY Exchange Rate	22.5	Central Bank of the Republic of Türkiye (CBRT)	Average annual increase in the USD/TRY exchange rate

Instead of calculating basic income payments using a plain average, this study takes a step closer to how real life works. Different indicators—like inflation, wage growth, and the exchange rate—do not affect households in the same way or with the same intensity. Accordingly, the model gives them varying weights according to how much they usually influence living standards in Türkiye. These welfare impact weights (w_i) were determined based on theoretical and empirical insights from the international literature. According to studies [65,66], inflation is recognized as the most immediate and widespread driver of real income erosion. Wage growth provides a partial but policy-driven mitigation effect [55,67], while exchange rate fluctuations exert indirect and lagged impacts primarily through imported goods prices. Accordingly, the relative weights were determined as follows:

Inflation: 40% (α = 0.40);

Minimum wage growth: 35% (β = 0.35);

Exchange rate: 25% (γ = 0.25).

These proportions are not based on any strict formula—they are just meant to reflect, as realistically as possible, how each factor plays out in everyday life. The weights used for indexation were selected to reflect the relative effect of each variable on purchasing power at the household level in Türkiye.

With there being no single national study providing a definitive split for this purpose, the weighting scheme was informed by publicly available data and earlier research on cost-of-living sensitivity of low-income households. For instance, inflation (CPI) has a direct and immediate impact on housing and food expenses, which constitute a big portion of poor households’ expenditures. Minimum wage indirectly affects overall wage dynamics and salaries in formal employment. Exchange rate fluctuations affect the prices of imported goods and energy, which also matter for households’ budgets in Türkiye’s open economy.

The proportional weights are broadly consistent with expenditure patterns in TÜİK’s Household Budget Survey and with economic commentary on price sensitivity in Türkiye. While individual elasticity estimates are not available, the distribution chosen is designed to realistically capture relative burden of cost components that impact real income levels.

Based on the assigned weights, the following formula operationalizes the indexation method used to calculate the annual adjustment rate:

Basic Income Adjustment Rate (Index) = (α × Inflation) + (β × Minimum Wage Growth) + (γ × Exchange Rate Growth)

(1)

Applying this formula using the 2008–2023 averages yields an annual increase of approximately 21.63%, which is consistent with Türkiye’s recent macroeconomic trends. The weighted-average methodology used here is in line with the adaptive social protection approaches recommended by the International Labour Organization [68] and the World Bank [67].

While the calculation focuses on per capita payments, total program cost projections also consider population growth. Instead of using a fixed growth rate, the model directly incorporates the official population projections provided by the Turkish Statistical Institute (TÜİK) for the 2023–2050 period [69]. These projections are used to estimate annual total costs and ensure consistency with national demographic expectations.

Another key assumption in the model is a 1% annual reduction in carbon emissions. While Türkiye’s updated Nationally Determined Contributions (NDCs) (2022) set an economy-wide reduction target for 2030, they do not set a year-by-year path. Still, the model’s assumption of a linear 1% annual decrease aligns broadly with international benchmarks [45,70]. This assumption reflects a realistic and moderate target and helps the model test the long-term sustainability of basic income funding by carbon tax revenues.

3.4. Simulation Architecture and Key Equations

The simulation model is implemented in Microsoft Excel and follows a transparent, step-by-step arithmetic logic. For each year of the projection period, three core calculations are performed:

1

Carbon tax revenue ($R_t$) is estimated using national emissions data, the applicable carbon tax rate, and the prevailing exchange rate, according to the following equation:

$$R_t=E_t \times P_t \times {XR}_t$$

(2)

where $E_t$ is projected emissions in year t, $P_t$ is the carbon price per tonne, and ${XR}_t$ is the exchange rate (TL/USD).

2

Targeted basic income expenditure (${BI}_t$) is computed for the lowest 30% of earners, with annual transfer amounts indexed dynamically to inflation, wage growth, and exchange rate changes. The expenditure is expressed as follows:

$${BI}_t=N_t \times {Payment}_0 \times {Index}_t$$

(3)

where $N_t$ is the population below the 70% median income threshold, ${Payment}_0$ is the initial BI amount in TRY and ${Index}_t$ is the dynamic composite index of inflation, wage growth, and currency change.

3

Net balance (${NB}_t$) is the difference between carbon tax revenues and TBI expenditure:

$${NB}_t=R_t-{BI}_t$$

(4)

The model does not employ machine learning or statistical estimation techniques; rather, it functions as a scenario-based policy simulation, aiming for transparency and replicability rather than econometric forecasting.

Table 5. Variables and definitions.

Variable	Description
Rt	Total revenue from carbon tax in year t
Et	Annual CO2 emissions (tons)
Pt	Carbon tax rate (USD 12 per ton)
XRt	USD to TRY exchange rate in year t
BIt	Total basic income expenditure in year t
Nt	Targeted population (lowest 30% by income)
Payment0	Initial TBI amount per person
Indext	Annual indexation multiplier
NBt	Net balance in year t

lists the variables and definitions used in the simulation model, covering both revenue and expenditure components. These include the annual CO₂ emissions, carbon tax rate, and exchange rate on the revenue side, as well as the size of the targeted population, the initial transfer amount, and the indexation factor on the expenditure side.

4. Results and Discussions

This section presents the simulated fiscal outcomes of the proposed carbon-tax-funded basic income system for the period of 2023–2050. On the basis of assumptions outlined in the previous sections, the simulation estimates revenue, expenditure, and budget balance on a yearly basis under a staged sectoral rollout.

Table 6. Carbon tax-financed targeted basic income simulation (2023–2050) *.

Year	Population (Thousand)	Targeted BI Payment (TL/Year)	Target Pop (Thousand)	TBI Cost (Billion TL)	Carbon Emissions (Mt)	USD/TRY	Carbon Tax (TL/Ton)	Carbon Revenue (Billion TL)	Net Fiscal Balance (Billion TL)
2023	85.372	6000	25.612	153	442.20	26.9	322.8	0.0	−153
2024	87.812	7297	26.344	192	437.78	35.3	424.0	0.0	−192
2025	86.239	8876	25.872	229	433.40	43.3	519.5	225	−4
2026	86.654	10,796	25.996	280	429.07	53.0	636.3	273	−7
2027	87.057	13,131	26.117	342	492.88	64.9	779.5	384	42
2028	87.447	15,971	26.234	419	487.95	79.6	954.9	466	47
2029	87.824	19,426	26.347	511	563.85	97.5	1169.8	660	149
2030	88.188	23,628	26.456	625	558.21	119.4	1433.0	799	174
2035	89.938	62,898	26.981	1697	530.86	329.4	3953.1	2098	401
2040	91.529	167,433	27.459	4597	504.84	908.7	10,904.9	5505	908
2045	92.866	445,704	27.860	12,417	480.10	2506.8	30,081.9	14,442	2025
2050	93.774	1,186,452	28.132	33,377	456.57	6915.2	82,982.4	37,887	4510

* For the full year-by-year simulation results, please refer to Appendix A (Table A1).

presents the year-by-year fiscal dynamics under the targeted BI scenario. The tax is applied to the energy sector only in the first stage, covering the largest portion of national emissions—approximately 442 million tons. Emissions from industry are covered by 2027, and full sectoral coverage is achieved by 2029, at an estimated 599 million tons of total taxable emissions. The gradual rollout allows for a feasible implementation trajectory and enables incremental revenue generation in accordance with administrative readiness and social acceptability.

Although the tax rate itself stays fixed at USD 12 per ton, the amount collected in Turkish Lira changes from year to year. For 2023 and 2024, the model uses actual exchange rates from the central bank—26.90 TL and 35.34 TL, respectively. From 2025 onward, it assumes that the exchange rate will rise by about 22.5% annually, to reflect expected trends.

Starting in 2023, the model assumes that emissions begin to shrink slowly—about one percent each year. The tax does not actually kick in until 2025, but the reductions are already in motion to keep pace with Türkiye’s environmental goals. What is taxed, though, changes over time. At first, it is just the energy sector. A couple of years later, around 2027, industrial emissions join in. And by 2029, the whole economy is included. This way, the model stays close to real-world policy steps, while also keeping the revenue estimates grounded in how the system grows.

The model assumes a 21.63% annual increase in BI payments, targeted at the bottom 30% of the population. Table 6 illustrates how these dynamics affect revenues and expenditures over time.

The findings derived from Table 6 can be evaluated under three main dimensions.

First, the evolution of the revenue–cost balance over time stands out. The initial two years of the simulation (2023–2024) are treated as a transition period during which no carbon tax is applied. In 2025, the tax system is activated exclusively for the energy sector, generating approximately 225 billion TL in revenue. The cost of the targeted basic income (TBI) program in the same year is around 283 billion TL, resulting in a moderate budget shortfall. This gap reflects the need for public support in the early phase of implementation. However, as the scope of taxation expands and the exchange rate increases cumulatively, carbon tax revenues rise sharply—outpacing expenditure growth, despite a 21.63% annual indexation of payments and population growth.

Second, the issue of emission reduction and its impact on tax revenue is worth noting. The model assumes a 1% annual reduction (Sensitivity scenarios include 0.5% and 2% reductions. The overall structure of the model remains fiscally viable under these variations, although higher reduction rates marginally decrease long-term revenues due to a smaller taxable base. This confirms that the selected baseline is both reasonable and resilient) in taxable emissions, thereby maintaining alignment between the carbon tax and environmental objectives. What sets this simulation apart is its phased sectoral approach. The tax applies only to the energy sector during 2025–2026, expands to include the industrial sector in 2027–2028, and reaches full coverage by 2029 with a tax base of 598.9 Mt CO₂ (prior to annual reduction adjustments). This staged expansion enhances both environmental impact and long-term revenue potential.

Third, Table 6 highlights the model’s sustainability and policy effectiveness. Compared to flat, immediate tax implementations, the phased approach provides a more manageable and predictable framework for policymakers. When integrated with a targeted BI scheme, this system enables carbon tax revenues to simultaneously serve environmental objectives and social protection mechanisms. From 2027 onward, the annual revenues exceed BI costs, producing growing fiscal surpluses. These outcomes suggest that a carbon tax could become a fiscally sustainable and socially impactful tool in Türkiye’s economic landscape.

With an eye toward people living below the poverty line, this study assesses whether a carbon-tax-funded basic income (BI) model would be feasible in Türkiye. Beginning with the energy sector in 2025, the model projects a phased carbon taxation system across all sectors, including the industrial sector in 2027–2028, covering all sectors by 2029. This framework presents a reasonable policy transition scenario that helps to match targets for emission reduction with aims of fiscal sustainability.

Although the carbon tax is set at a fixed rate of USD 12 per ton, its equivalent in Turkish Lira is expected to rise yearly based on the annual USD/TL exchange rate change of 22.5%. Emissions subject to taxation are adjusted dynamically each year, according to sectoral coverage and a projected 1% annual reduction. Carbon tax revenues are used to help fund targeted basic income payments, which go to the lowest 30% of earners. According to the TÜİK’s 2024 Income Distribution Statistics, the median annual equivalized disposable income for this group is approximately 132.580 TL (about 11,048 TL per month). In its first year, the proposed TBI provides 8.876 TL per person annually, corresponding to roughly 6.7% of the median income. By 2029, indexation raises the annual transfer to 19,520 TL, which corresponds to about 14.7% of the same baseline. This represents a meaningful direct boost to household resources, particularly for those below the median within the target group, and indicates a tangible potential for narrowing the poverty gap without altering existing eligibility mechanisms.

Figure 1 illustrates the fiscal evolution of the program across the simulation period. While carbon tax revenues are initially lower than TBI expenditures, the gap closes by 2027. From that point onward, the program becomes self-sustaining without requiring additional public funding. This visual representation reinforces the model’s fiscal feasibility, as outlined in the simulation outcomes.

By 2027, the program’s expenses will be entirely covered by carbon tax revenues, according to the model (This projection is based on an assumed annual USD/TRY exchange rate growth of 22.5%, consistent with Türkiye’s historical average between 2008 and 2023. To account for potential macroeconomic shifts (e.g., monetary stabilization, disinflation), two moderated post-2025 scenarios (with 15% and 10% growth) were also conceptually assessed. These resulted in the program achieving fiscal balance only 1–2 years later than the baseline, confirming the model’s robustness under more conservative exchange rate assumptions). Until then, only a small amount of public funding is needed to bridge the gap. Achieving this without a tax increase in dollar terms helps keep the program financially sustainable.

Additionally, the dynamic indexation model, which links annual basic income payments to macroeconomic variables through a 21.63% adjustment rate, plays a crucial role in ensuring that expenditure projections remain realistic over the long term.

But while the model takes for granted that indexed TBI payments (increased yearly by 21.63%) will keep purchasers’ purchasing power constant, it fails to take into account inflationary pressures generated by the carbon tax itself, especially on energy. Low-income households, who spend a disproportionately large share of their income on energy, will experience above-average inflation, leading to a faster erosion of the real value of BI payments. Future editions can improve on this by using energy-weighted price indices or differentiated indexation formulas based on household expenditure profiles.

It is essential to recognize the simulation’s limitations. The model is built upon official population projections, exchange rates, and TBI indexation rates, all derived from historical averages. Future economic, demographic, or political fluctuations may lead to deviations from these projections. Additionally, the assumption of a constant USD 12 per ton carbon price—adjusted only for exchange rate effects—does not reflect potential volatility in international carbon markets. The model assumes a 1% annual emission reduction applied uniformly to the taxed emission base, rather than capturing potential differences in how individual sectors might decarbonize over time. In reality, emissions are likely to decline at varying rates across sectors depending on technology shifts, regulatory pressures, and sector-specific dynamics. While this simplified approach supports consistency in the simulation, future models could explore differentiated emission paths or tax rates based on sectoral characteristics.

Taken together, the simulation results indicate that a sectoral phased carbon tax, complemented with a targeted and dynamically indexed basic income, can be an environmentally as well as an equity-friendly fiscal policy tool—fulfilling both green goals and closing income gaps. As models for the future likely will require further refinement, the present system does offer a realistic foundation for green-inclusive social policy design in Türkiye.

Despite its simplifications, the model demonstrates how targeted social policy and environmental taxation can be strategically integrated within a middle-income country context, laying the groundwork for more adaptive and inclusive fiscal architectures.

In line with the research questions outlined in the introduction, the findings of this study offer structured and evidence-based answers to each of the core issues explored. RQ1 is addressed through long-term simulations showing that the carbon-tax-funded TBI scheme achieves fiscal sustainability from 2027 onwards, without requiring increases in real tax rates or additional public support. The program guarantees consistent surpluses, amounting to more than 4.5 trillion TL by 2050. This holds true even under the assumption of a constant real carbon tax rate. RQ2 is explored via scenario analysis, demonstrating that even under adverse macroeconomic assumptions (e.g., lower exchange rate growth or higher emission reduction rates), the program remains fiscally viable. RQ2 is tested through the implementation of a dynamic indexation mechanism, which successfully protects the real value of transfers by linking them to inflation, wage growth, and currency depreciation. Lastly, RQ3 is addressed by discussing the institutional feasibility of the model, particularly through the potential use of Türkiye’s existing Integrated Social Assistance Information System (EYHBS) for efficient benefit delivery. As such, these results lay the model’s practical usability, institutional coherence, and long-term durability in diverse economic climates. At a national level, a Green Social Security Fund could also be set up for sustainable long-term use.

5. Conclusions

The conclusions and recommendations in this section are drawn from two sources: the simulation results and international policy guidance. Other recommendations—including the need for gradual implementation, the use of Türkiye’s existing social protection infrastructure, and references to OECD redistribution benchmarks—are informed by the comparative policy literature and real-world experiences in countries pursuing carbon tax reforms.

In developing countries such as Türkiye, large-scale social policy reforms can pose fiscal and institutional risks if introduced too abruptly. Therefore, the proposed TBI model should be implemented gradually. Based on simulation outcomes and comparative international experiences, in the first phase, unconditional cash transfers should be limited to low-income groups, with regional pilot programs launched in economically disadvantaged or disaster-prone areas (e.g., Eastern and Southeastern Anatolia). If successful, the program can be scaled up to the national level.

Given the inherently regressive nature of carbon taxation, particular attention must be paid to its distributional effects. Low-income households typically spend a larger share of their income on energy and may be disproportionately affected. Hence, the tax design must incorporate equity-focused mechanisms. International institutions such as the OECD (2019) recommend that at least 50% of carbon tax revenues be redistributed directly to citizens. Callan et al. [71] further show that redistributing 65–80% of revenues through social benefits and tax credits significantly alleviates adverse distributional impacts. Integrating TBI with existing social protection programs would strengthen the system’s overall effectiveness and resilience. Since low-income households account for only a small fraction of total emissions, channeling resources back to them not only offsets regressive tax effects but also provides meaningful welfare gains with minimal environmental cost.

In a country like Türkiye, where income inequality remains high [72], a targeted BI model has the potential to directly reduce disparities. However, public and political acceptance of such a reform hinge on effective communication. The carbon tax must be framed not as a punitive measure but as a vehicle for equitable redistribution. As indicated by case studies in comparable economies and the equity analysis in our model, public rhetoric needs to tactically place the green transition on the path to social justice. Local governments, civil society organizations, and social service networks must be actively involved in building awareness and trust [2].

The distribution of carbon tax revenues is a critical policy decision involving trade-offs between social equity and environmental investment. As Parry et al. [73] highlight, revenue allocation shapes the balance between efficiency, equity, and political acceptability. Although reallocating to basic income schemes offers maximum redistribution and political support, other allocations such as investments in energy efficiency, grid smartness, or climate resilience infrastructure offer long-term decarbonization benefits. Thus, hybrid structures in which some of the proceeds are reserved for green investment and the rest are paid out to targeted income support may be an equilibrium solution [23,74]. Although this study sets redistribution as a priority concern in the early structure, future budgeting can note such mixed allocation devices that simultaneously address both the climate and equity goals.

International climate finance mechanisms could serve as supplementary elements alongside domestic policy advancements. The World Bank and the Green Climate Fund (GCF) can provide financial resources alongside technical assistance and knowledge exchange possibilities when the BI model demonstrates explicit alignment with green transition objectives. The utilization of these resources presents an opportunity for Türkiye to enhance its ability to execute climate policy reforms that are both inclusive and resilient.

Beyond the fiscal projections, the findings have broader policy and socioeconomic implications that warrant further discussion.

Moreover, the introduction of a basic income is expected to stimulate domestic demand, potentially contributing positively to short-term economic growth [4] (p. 675). Nevertheless, the extent of this effect will depend on the method of financing and the degree to which inflationary pressures are controlled. Overall, the findings demonstrate that carbon taxation can serve as a multi-dimensional fiscal tool—one that advances both environmental and social objectives. In developing countries, the integration of social transfer mechanisms into the broader energy transition agenda is increasingly seen as a structural necessity. Nevertheless, it is important to acknowledge that the introduction of a carbon tax could exert moderate inflationary pressures, particularly on energy-intensive sectors. Future research could explore mitigation strategies to balance environmental objectives with price stability.

While this research provides a simulation-based budget analysis of a carbon-tax-funded TBI strategy for Türkiye, there are certain areas yet to be covered through studies. To begin with, the model could be expanded by adding macroeconomic feedback loops, such as those showing how income transfers influence household consumption and inflationary pressures.

Second, follow-up research can generate stochastic or scenario-based variants of the current model to try out fiscal sustainability responses to external shocks (e.g., energy price shocks, exchange rate volatility, or climate migration).

Third, distributional analysis can be improved through simulating the incidence of carbon taxation and BI adequacy for demographic subgroups (e.g., rural–urban, gender, labor force status). In addition, future research may explore the distributional impact of the carbon tax at both producer and consumer levels, its effects on employment, and how the model can be adapted for local governance structures such as municipal-level delivery systems.

Finally, empirical studies can analyze political acceptability and behavioral responses to carbon taxation and BI imposition through surveying, experiments, or field experiments.

Such research would further enhance the realism and policy relevance of TBI proposals under ecological fiscal reform agendas in Türkiye and beyond.