Projects (revised June 2026)

I am broadly interested in climate change economics. More specifically, my research focuses on materials and resource efficiency, sustainable development, input substitution, convergence, and — increasingly — the economic and environmental implications of artificial intelligence. The majority of my studies are empirical, and I generally apply panel-data econometric techniques, decomposition methods, and stochastic frontier analysis to country- and industry-level datasets. My current research agenda is organized around four strands: (i) the emerging role of material demand and material efficiency as a mitigation policy, (ii) the discrepancies between production-based and consumption-based emissions for international climate negotiations and national climate policy-making, (iii) the growing concerns about the environmental and distributional impact of income inequality, and (iv) the economic and environmental implications of artificial intelligence. In this statement, I summarize the contributions of my past and current research and outline my future research plans.

Before completing my doctoral research, I was awarded a scholarship to participate in the Advanced Studies Program organized by the Kiel Institute for the World Economy in Germany. During my stay in Kiel, I wrote a research paper on strategies to mitigate CO2 emissions through the input substitution channel at the industry level in Germany. This was the first study to investigate the degree of substitution in Germany for a wide range of industries by incorporating the slow response of substitution adjustment. This paper, supervised by Dr. Eckhardt Bode, was published in Environmental Science and Pollution Research in 2020. During the writing-up process of my PhD dissertation, I also wrote three papers on convergence in CO2 emissions: one published in Energy Economics replicating an influential study on convergence among industrial countries; a second performing a similar analysis while distinguishing production- and consumption-based emissions; and a third, published in Energy Efficiency, examining stochastic conditional convergence in sectoral energy consumption from a developing-country perspective, with a special emphasis on Turkey.

After defending my PhD thesis, I joined the Laboratory for Climate Change Economics at HSE University (Moscow) as a Postdoctoral Research Fellow (2022–2023), later returning as a Visiting Lecturer (2022, 2023). This period initiated a sustained collaboration with Igor Makarov on the production- versus consumption-based emissions accounting agenda described below, which has since produced several joint publications and two international policy briefs.

Since completing my PhD, I have published more than twenty peer-reviewed articles in journals indexed in the Web of Science core collection, including Energy Economics, Applied Energy, Resources Policy, Resources, Conservation & Recycling, Journal of Environmental Management, Research in Transportation Economics, Sustainable Development, and Sustainable Production and Consumption. My recent work centers on four themes: the technology–environment nexus, the environmental effect of income inequality, the critical role of materials in mitigating emissions, and — most recently — the economics of artificial intelligence.

Regarding the impact of technology on the environment, I have published two solo-authored papers exploring the effect of information and communication technologies (ICTs) on the environment using panel-data cointegration techniques. The paper in Research in Transportation Economics investigates the relationship between environmental technologies and CO2 emissions from the transport sector for the EU15 for the first time, while the article in the Journal of Environmental Management analyses the ICT–environment nexus for a large sample of countries classified endogenously by the transitional behaviour of per-capita CO2 emissions.

On the environment–inequality nexus, beyond my book chapter on income distribution and environmental quality (Springer, 2022, in a volume co-edited by scholars from Harvard and Tulane), I have also published an empirical paper in the Journal of Environmental Planning and Management (2022, with Tuğba Akın) examining the sectoral-level impact of income inequality on environmental quality across a large country panel.

The topic I have worked on most intensively is the role of material use in greenhouse gas mitigation. Beyond the three articles described in earlier versions of this statement (in Sustainable Production and Consumption, Resources Policy, and Resources, Conservation & Recycling), I have completed several further studies. My article in Environmental Science and Pollution Research (2023, with five co-authors) decomposes the contribution of material and energy efficiency to the decoupling of CO2 emissions from economic growth among the world's top emitters. My paper in Sustainable Development (2024, with Etem Karakaya and Burcu Hiçyılmaz) applies stochastic frontier analysis to material efficiency and material demand across EU countries. Most directly relevant to a research direction I identified two years ago, my paper in Energy Economics (2024, with five co-authors) empirically tests the rebound effect of material and energy efficiency for the EU and its major trading partners. My book chapter on critical raw materials — previously announced as forthcoming — has now been published as "Critical Raw Materials in the Clean Energy Transition: Evaluating Circular Economy and Investment Strategies for Mitigating Supply Risk" (Lexington Books, 2024, with Etem Karakaya and Burcu Hiçyılmaz), and I have since extended this line of work into two encyclopedia chapters: "Convergence in CO2 Emissions" (Edward Elgar Encyclopedia of Energy Economics, 2025) and, with Igor Makarov, "Production- and Consumption-based Accounting of Emissions" (Encyclopedia of Monetary Policy, Financial Markets and Banking, 2025).

Building on my collaboration with Igor Makarov, I have also made substantial progress on the production- versus consumption-based emissions agenda. Our paper in Applied Energy (2024) tests the Environmental Kuznets Curve hypothesis separately for production- and consumption-based emissions across a large panel of carbon exporters and importers. We have translated this research into policy outputs as well, including a T20 Brazil policy brief, "Looking Beyond National Borders: Integrating Consumption-based Accounting Approach into Climate Mitigation Policy" (2024, with Elizaveta Smolovik), and an article in the International Organisations Research Journal, "Towards Consumption-based GHG Emissions Accounting: From Calculation to Policymaking" (2024). I also contributed to a T20 India policy brief on wellbeing measurement beyond GDP (2023) and reviewed the IPCC Sixth Assessment Report (Working Group III) in 2021.

Since 2024, I have begun extending my empirical toolkit toward a new and rapidly growing topic: the economic and environmental implications of artificial intelligence. With Sefa Takmaz, Arslan Austin, and Darlington Agbonifi, I am currently working on papers examining AI's role in the energy transition, the relationship between AI adoption and firm performance, and the environmental implications of AI adoption among German firms.

Beyond climate change economics, I continue to study other topics on a smaller scale, including production functions, income convergence, and elasticity of substitution from my doctoral dissertation (Journal of Economic Studies; Journal of Economic and Administrative Sciences), regional disparities in public expenditure in Turkey (Social Indicators Research), and provincial inequality in financial inclusion in Turkey (Applied Economics Letters, 2024, with Sefa Takmaz and Erkam Sarı).

Building on the progress described above, I intend to continue pursuing four main research directions: the critical role of materials for a sustainable future, discrepancies between production-based and consumption-based emissions, the environmental effect of income inequality, and the economic and environmental implications of artificial intelligence.

(i) The critical role of materials for a sustainable future

As many countries set net-zero emission targets following COP26, the green energy transition is becoming more viable, but it will require an enormous amount of materials. According to International Resource Panel data, material extraction grew 3.4-fold between 1970 and 2017 — faster than fossil energy extraction (2.5-fold) — and material use now accounts for roughly a quarter of global GHG emissions and about half the carbon footprint of major material-using value chains. Material efficiency has lagged behind labour and energy efficiency, despite arguably larger mitigation potential. I plan to continue this agenda by:

(ii) Production- and consumption-based emissions

National emissions targets and international climate negotiations still rely predominantly on production-based emissions (PBE), even though consumption-based emissions (CBE) — calculated from domestic final consumption including imports — can shift the geographical distribution of responsibility without changing the global total. This distinction matters for the political economy of climate agreements, carbon leakage, and embodied emissions in trade. Having tested the EKC hypothesis for both PBE and CBE (Applied Energy, 2024), I plan to:

(iii) The environmental effect of income inequality

Income inequality and climate change are two of the defining challenges of this century, and recent data suggest both are worsening in tandem: the IPCC (2018) estimates that limiting warming requires cutting net anthropogenic emissions by about 45% from 2010 levels by 2030, while the UN (2020) reports a widening per-capita income gap between high- and low-income countries. Oxfam (2020) data showing that the richest 10% account for 46% of emissions growth, against 6% for the poorest half, underline why the balance of power between rich and poor may shape environmental degradation. I intend to: 

(iv) The economic and environmental implications of artificial intelligence

Artificial intelligence is diffusing rapidly across firms and economies, yet its implications for productivity, energy demand, and environmental outcomes remain poorly understood empirically. Drawing on the same panel-data and efficiency-analysis toolkit I have applied to materials and emissions, I plan to: