I study the economic consequences of climate change, with a focus on agriculture, food security, and social cost estimation. I bridge rigorous academic research with applied data consulting for policy and industry.
I am a PhD student in Environmental & Resource Economics at the University of Delaware, where I investigate how climate change reshapes agricultural systems, food security, and national economic output.
My work combines panel econometrics, causal inference, and machine learning to translate climate science into policy-relevant economic insights. Beyond academia, I offer consulting services in climate risk analysis, data science, and quantitative policy evaluation.
I also run EconCode with Taky — a YouTube channel dedicated to teaching R, Python, and applied econometrics to students and practitioners.
33 countries across Sub-Saharan Africa, South Asia, Southeast Asia, Latin America, and beyond — studying climate impacts on food security and agriculture.
Click any keyword to explore key findings, data, and visualizations from my work.
Peer-reviewed work, working papers, and ongoing investigations at the frontier of climate economics.
A first meta-analysis of divergent results across 58 statistical models from 8 key papers, using machine learning to develop a "best estimate." Integrates persistence of damages, sea-level rise, trade spillovers, and capital loss.
Two-stage IV framework examining how persistent temperature and precipitation anomalies affect agricultural GDP growth and propagate to household food security across 33 countries (1961–2022).
Harmonizing and bias-adjusting CMIP6 climate model outputs to produce credible crop yield impact projections, with metrics analysis, spatial mapping, and conference-ready visualizations.
Extending MimiGIVE and MimiPAGE integrated assessment models to incorporate national-level damage functions, mortality effects, and updated prior-to-posterior calibration approaches.
Assessed 130+ datasets across six activity categories for spatial and temporal coverage to support Delaware Bay and Ocean Spatial Planning, in partnership with DNREC.
Empirical investigation of how climate variability and long-run climate trends affect labor productivity and wage outcomes across sectors and geographies.
Bringing academic rigor to real-world decisions in climate risk, policy analysis, and data science.
Quantitative assessment of physical and transition climate risks for businesses, governments, and NGOs.
Causal inference methods — difference-in-differences, IV, RDD — to evaluate program and policy impact.
ML pipeline development for economic forecasting, causal ML, and large-dataset econometric analysis.
GIS analysis, satellite data processing, and spatial panel econometrics for environmental research.
Publication-quality charts, dashboards, and interactive visualizations using R (ggplot2/plotly) and Python.
Hands-on training in R, Python, and applied econometrics for research teams and organizations.
Free tutorials at the intersection of economics and data science — for students, researchers, and practitioners.
Watch on YouTubeMy tutorials are designed to help economists and social scientists get practical with modern data tools — from cleaning messy datasets to running advanced regressions and producing publication-quality visuals.
Download my full CV for a detailed overview of my academic background, research experience, publications, and technical skills.
Download CV (PDF)Interested in collaboration, consulting, or just want to connect? I'd love to hear from you.
Whether you're a researcher looking to collaborate, an organization seeking climate data expertise, or a student with questions — feel free to reach out.