Land and Poverty Economist @ the World Bank
PhD Candidate · JLU Giessen
Eddie Bukin
Applied economist and data scientist who turns messy micro-level data into causal evidence, and that evidence into tools that others use. For more than a decade, at the World Bank, FAO and in academia, I have measured how households, farms and land markets respond to policy, pairing quasi-experimental methods with survey, administrative and satellite data. I then build the analysis to scale: open-source R packages, solutions implemented by governments and national statistical offices, and training for the people who carry them forward. Innovation drives my work, and I bring it into the teams and work of my colleagues: helping them put generative AI to use in coding and analysis, adopt modern, reproducible workflows, and build the capacity to keep innovating on their own.
Current focus
Three things occupy me at the moment. I am completing a PhD thesis on the natural experiment of land privatization in southern Kazakhstan and its effects on pasture quality, extending it into a district-level evaluation of thirty years of land reform. In parallel, I am developing urban mass-valuation methods for Ukraine, combining real estate listing data with Cadaster and Registry of Rights records in a deliberately data-scarce environment.
At the World Bank’s Global Poverty Department I co-initiated GeoPov, which joins geospatial and micro data to read spatial welfare disparities, and I lead the Bank-wide effort on responsible AI-assisted coding in R and Stata — a course taken by more than six hundred staff.
Impact evaluation Land markets Geospatial · GEE, PostGIS R · Shiny · Stata