Seoul National University · Economics, Econometrics and Finance
Professor Bahareh Oryani's research lab focuses on sustainable development, with a strong emphasis on energy systems, environmental economics, and industrial policy. Her work explores the integration of waste-to-energy technologies, renewable energy transitions, and energy efficiency standards within the framework of circular economy and climate change mitigation. The lab employs advanced econometric models—such as ARDL, SVAR, and SUR—to analyze the interplay between economic growth, energy consumption, environmental degradation, and industrial competitiveness, particularly in developing economies like Iran. The research also examines macroeconomic and institutional drivers of environmental performance, including globalization, financial development, and energy standards.
Figures are computed from collected data and may differ slightly.
International interest in using waste-to-energy (WtE) technology toward a circular economy (CE) is developing, spurred by environmental challenges such as inefficient solid waste dumping, pollution, and resource depletion. Incineration, pyrolysis, gasification, landfill, and anaerobic digestion are standard WtE technologies. Although these methods have been used for many decades, all countries try to implement the best plans based on their technologies and capacities. Therefore, an up-to-date co
This study intends to examine the validity of the Environmental Kuznets Curve (EKC) in the United States of America (USA), considering the vital role of macroeconomic variables, such as economic growth, institutional quality, globalization, energy consumption, financial development, urbanization, and remittance from 1985 to 2020. The impact of positive/negative shock in a regressor on CO 2 emissions keeps other regressors unchanged and has been investigated using the novel dynamic stimulated aut
This research attempts to evaluate the impact of renewable electricity generation mix on economic growth and CO2 emissions in Iran from 1980 to 2016. In this regard, by using EViews 10, the Structural Vector Autoregressive model (SVAR) is estimated by imposing the Blanchard and Quah long-run restrictions. The yearly data on real Gross Domestic Production (GDP), the share of electricity generation from renewable sources, and carbon dioxide emissions (CO2) caused by liquid, solid, and gaseous fuel
This research tends to investigate how industrial competitiveness could be affected by energy standards in case of Iran. Annual data on Competitiveness Industrial Index (CIP), Export Value Index (PX), Export Market Share (EMS), Industrial Energy Intensity (IEI), Manufacturing Price Index (MPI), and Total Factor Productivity (TFP) was used spanning the period 1990-2014. The results of the Seemingly Unrelated Regression (SUR) model confirmed the positive impact of PX, EMS, and TFP versus the negat
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