Applied Econometrics
Microeconometrics, causal inference, quasi-experimental designs and panel data methods in R, Stata and Python.
Economics · Data · Development
Economist & Data Scientist
I am an economist and data scientist in the final phase of my MSc in Development Economics
at the University of Göttingen, Germany (DAAD Scholar).
I apply econometric, machine learning methods and data science tools, including R, Python, Stata, SQL/BigQuery, and
Power BI, to answer economic policy-relevant and business-critical questions.
My research interests are in the intersection of development economics, environmental economics,
agricultural economics, and machine learning in economics.
Expertise
Microeconometrics, causal inference, quasi-experimental designs and panel data methods in R, Stata and Python.
Development economics, agricultural trade, food security, carbon policy and environmental economics.
Reproducible pipelines, predictive models, NLP, dashboards and geospatial analytics at scale.
Portfolio
A few examples of ongoing and past work.
Panel-data analysis of whether stricter EU environmental policies lead to carbon leakage via agri-food imports.
Global ML index combining climate, conflict and food-security data to predict migration pressure at subnational level.
RA work on TB-focused digital health projects studying technology barriers and health worker facilitation.
Updates