Curriculum vitae
Appointments, degrees, and experience
Highlights
Economist working where poverty, fiscal policy and land meet, with a decade of quantitative policy analysis at the World Bank, FAO and in academia. At the World Bank I build the tools behind poverty and distributional analysis: Commitment to Equity (CEQ) fiscal incidence microsimulations for eight countries and the devCEQ R package that scales them, the data pipelines that link macroeconomic scenarios to household microdata, small area estimates for poverty mapping, and GeoPov, which joins geospatial and micro data to measure spatial welfare disparities. My research is in land economics and impact evaluation: peer-reviewed work on farmland markets, valuation and taxation in Ukraine — including analysis code adopted by the State Cadaster as the basis for regression-based agricultural land valuation — and a quasi-experimental evaluation of land privatization in Kazakhstan. I have built equilibrium models in GAMS for the OECD-FAO Agricultural Outlook and a CGE project, and work across survey, administrative and geospatial data in R, Stata, Python and Google Earth Engine. I have taught econometrics at master’s level, trained government counterparts and national statistical offices, and built a course on AI-assisted coding taken by more than 600 World Bank staff.
Economist working on poverty, fiscal policy and land, with a decade of quantitative policy analysis at the World Bank, FAO and in academia. Builds fiscal incidence microsimulations (CEQ) and poverty-mapping tools; peer-reviewed research on land markets, valuation and taxation in Ukraine and on land reform in Kazakhstan, with analysis code adopted by the Ukrainian State Cadaster. Fluent across survey, administrative and geospatial data (R, Stata, Python, Google Earth Engine).
Experience
Feb 2025 — present Economist, Global Poverty (full-time: 40 h/week) The World Bank · Washington DC Build client-ready tools for poverty mapping and small area estimation; contribute to fiscal incidence analysis and to the distributional analysis of macroeconomic shocks on households; lead the Bank-wide adoption of AI-assisted coding in R and Stata; and research the impact of land reforms with the Development Research Group (DEC).
Highlights:
- Land economics and Ukraine. Research on the Ukrainian land market and technical assistance to the State Cadaster: consulting on the Land Parcel Identification System (LPIS) and on mass valuation of agricultural land, and piloting the mass appraisal of urban land.
- Microdata analysis, small area estimation and poverty mapping. Contributed to EU-wide poverty mapping and to missions to Poland, and trained the Polish national statistical office to produce its own small area estimates.
- AI-assisted coding. Launched a seminar series and internal training, including the ai4coding course, which reached 600+ staff through the Open Learning Campus; introduced Positron and Quarto as Bank-standard tools for reproducible research.
- GeoPov. Co-initiated the GeoPov work programme, which combines remotely sensed geospatial data with microdata to measure the extent and determinants of spatial income and welfare disparities. Led the development of the Project Targeting Index and its application across countries.
- Micro-Modelling Lab (MML). Engineered the data pipelines behind macro–micro simulations and guided economists in scaling and replicating these methods across countries. Built the infrastructure for the fiscal incidence dashboards in R Shiny (devCEQ) and supported countries in implementing the analysis.
Jan 2020 — Dec 2024 Lecturer and researcher (part-time: 20 h/week) Justus Liebig University Giessen · Germany Researched a range of micro- and macroeconomic topics at the Institute for Agricultural Policy and Market Research, focusing on land markets and policy impact evaluation. Also taught two master’s-level courses in statistics and econometrics for the social sciences, and worked on my PhD thesis.
Highlights:
- Teaching. The challenge was to give an interdisciplinary cohort of development economists an intuition for causal thinking and the know-how to run statistical analysis and hypothesis testing. Taught the introductory course to the full cohort, and the advanced course, which I introduced, to a self-selected group.
- Research. A microeconometric portfolio on land market efficiency in Ukraine and the land privatization reform in Kazakhstan, which yielded several publications in Land Use Policy and other journals. On ROCHADE — a project funded by the German Federal Ministry of Education and Research (BMBF, 01LA1828A/B/C/D) — I worked as a macroeconomist, trade data analyst, CGE modeller and GAMS programmer, publishing in Environmental and Resource Economics and Environmental Research Letters.
Mar 2018 — Jan 2025 Economist, short-term consultant (part-time: 100-150 days/year) The World Bank · Poverty & Equity Global Practice Analysed fiscal incidence with the Commitment to Equity (CEQ) methodology and simulated how alternative fiscal and social-spending policies would affect welfare and inequality. Led geospatial analysis for project targeting and country-level capacity building, and developed R Shiny tools that let clients and internal users work with large data and complex models.
Highlights:
- Fiscal incidence and distributional analysis. Developed the devCEQ R package — infrastructure for scaling up country-specific simulations — and built simulations for Senegal, Côte d’Ivoire, Benin, Indonesia, Romania, Türkiye, El Salvador and Armenia, with the country code and dashboards open at the Equity Policy Lab. Trained government counterparts in Indonesia and Georgia.
- Project Targeting Index (PTI). Developed the methodology and infrastructure for geospatial analysis that improves the spatial targeting of development projects. The devPTIpack R package underpins more than 30 country-specific PTI analyses; the package, the dashboard guidelines and the country applications are open at github.com/wbPTI.
- Land economics. Supported DEC’s Transparent Land Governance in Ukraine project and co-authored several papers.
Oct 2017 — Dec 2019 Researcher (part-time: 20 h/week) Leibniz Institute of Agricultural Development in Transition Economies (IAMO) · Halle (Saale), Germany Researched land and labour relations in agriculture, focusing on principal–agent problems and land contracts in Ukraine and Central Asia. Led the second wave of the IAMO Farm Survey in Kazakhstan and other Central Asian countries: questionnaire design, pre-testing, interviewer training, and QA/QC of 600 collected responses.
Also contributed to projects on the Ukrainian land market, whose results appear in a series of articles and reports.
Jun 2015 — Jan 2018 Trade economist and statistician (full-time) Food and Agriculture Organization of the United Nations · Rome As a statistician, contributed to FAOSTAT’s Agri-Environmental Indicators and Emissions databases; as a trade economist, to the OECD-FAO Agricultural Outlook 2017–2026 and to FAO’s trade policy work.
Highlights:
- Emissions statistics. Implemented the greenhouse gas (GHG) estimation methodology, coded the computation in R (tidyverse, git) and built the QA/QC validation; developed the first version of FAOSTAT’s emissions intensities database; updated the agricultural inputs domains from UN Comtrade data.
- AGLINK-COSIMO and the Outlook. Maintained FAO’s country modules of the AGLINK-COSIMO partial equilibrium model — database and parameters — for the meat market, prepared the 2017–2026 meat projections, and co-wrote the meat commodity snapshot and commodity chapter. Supported the team’s GAMS modelling and automated its reporting in R Markdown.
- Trade policy. Wrote FAO policy briefs for the WTO 11th Ministerial Conference in Buenos Aires, contributed to FAO’s review of import surges and price depressions, and organized a workshop on WTO dispute settlement in Kyiv.
- Trade data tools. Analysed UN Comtrade data for reporting and for trade and nutrition research; built an R package, a teaching website and R Shiny apps for managing and exploring trade data.
2010 — 2015 Earlier positions and internships Pretoria · Kyiv · Twann Alongside my studies: research posts in Ukraine, household survey fieldwork in South Africa, and five months on a Swiss vineyard.
- 2014–2015, eight months — Intern, Postgraduate School of Agriculture and Rural Development, University of Pretoria. Led fieldwork and household data collection for an impact assessment of inclusive business models on emerging farmers, across four case studies.
- 2012–2013 — Junior researcher, National University of the State Tax Service of Ukraine. Studied transfer pricing in agricultural exports.
- 2011, five months — Farm worker and intern, Kapfgut wine estate, Twann, Switzerland. Grape growing and wine production.
- 2010–2011 — Junior researcher, Information Systems Department, National University of Life and Environmental Sciences of Ukraine. Research data management and analysis in R and PostgreSQL.
Education
2024 — present PhD, Agricultural Economics Justus Liebig University Giessen Thesis: “Land privatization and pasture quality in southern Kazakhstan: evaluating the impact of a natural experiment.” Supervisor: Prof. Dr. Martin Petrick.
The thesis evaluates the impact of land privatization on pasture quality with quasi-experimental methods, combining cadastral records with remotely sensed measures of climate, vegetation and land cover. Part of it is published as The effects of land privatization on pasture productivity in south-eastern Kazakhstan in Land Use Policy (2025).
2013 — 2015 MSc, Rural Development — magna cum laude Ghent · Humboldt Berlin · Pisa · Pretoria — Erasmus Mundus Erasmus Mundus International Master of Science in Rural Development (130 ECTS): development economics and agricultural and development policy analysis, applying empirical methods and econometrics.
A joint degree taught across four universities: Ghent University (Belgium), the University of Pisa (Italy), the University of Pretoria (South Africa) and Humboldt University of Berlin (Germany), where I defended my thesis.
Thesis: “Improving competitiveness of the Ukrainian sugar industry: economic instability and policy implications”, which built and interpreted a partial equilibrium model in GAMS for agricultural policy analysis. Supervisor: Prof. Dr. Jeroen Buysse.
2008 — 2013 MSc & BSc, Economic Cybernetics — summa cum laude National University of Life and Environmental Sciences of Ukraine · Kyiv Five years of quantitative economics straight after school: applied mathematics, optimization, statistics and econometrics, used for agricultural policy at the macro level and farm management at the micro level.
BSc (240 ECTS) and MSc (70 ECTS). Contributed to several academic papers published in Ukraine. Supervisor: Prof. Dr. Andrii Skrypnyk.
Teaching
2026 AI-assisted coding for economists The World Bank · Open Learning Campus Designed and taught the Bank’s internal course on using AI assistants and GitHub Copilot to write R and Stata code; taken by more than 600 staff. Materials — worldbank.github.io/ai4coding (source).
Delivering it meant changing the toolchain as well as teaching it: I had Quarto and the Positron IDE made available as Bank-wide software so that participants could practise reproducible workflows rather than only hear about them.
2025 Small area estimation and poverty mapping Statistics Poland (GUS) · Poznań · with The World Bank A week with the national statistical office, teaching its statisticians to produce their own small area estimates of poverty for Poland at NUTS-2 and NUTS-3 level: the method, the R code that runs it, and how to maintain and extend the toolbox afterwards. Curriculum and code — github.com/wbEUPM/eupm-pl.
I wrote the software the course teaches before teaching it — R packages and structured data pipelines carrying the office’s survey and census inputs through direct estimation and Fay–Herriot modelling to a subnational poverty map — and then delivered it in person at the Poznań centre. The week ran against the office’s own data rather than a worked example, so the code was being improved and handed over at the same time, and it closed on the part that decides whether a toolbox outlives the project: how to maintain it and develop it further without me.
2018 — 2025 Fiscal incidence microsimulation with the CEQ method Ministries of finance and social policy · The World Bank A week-long course per country for government analysts: the theory and mechanics of tax-and-transfer incidence on household survey microdata, the R and Stata code that implements it, and the R Shiny application that leaves the analysis in their hands. Tooling — Equity Policy Lab · devCEQ (source).
I took the lead on the analysis these courses teach — country by country, the microsimulations that measure on household survey data how taxes and subsidies reach household welfare — and then adapted that methodology into web-based applications in R Shiny, deployed on Posit Connect and Shiny Server. What the client receives is therefore a tool rather than a report: ministries of finance and social policy simulate counterfactual tax and subsidy policies themselves and read off the distributional, poverty and inequality consequences for households. Each engagement hands over the simulation code in R and Stata alongside the dashboard.
In Indonesia and Georgia I joined the country missions to teach it: a week each, opening on the incidence theory and the mechanics behind the numbers, moving to the code behind the tools, and closing on the capacity to develop them further — in R or in whichever language the counterpart team already works in.
2020 — 2024 Introduction to Statistics and Econometrics MSc · English · JLU Giessen Compulsory course in the Transition Management master’s programme: about 50 students a year for five consecutive years, taught in English and delivered in R throughout. Materials, one set per cohort — 2023–24 (source) · 2022–23 (source) · 2021–22 (source).
Many in the cohort had never programmed, so the course taught the statistics and the tooling together: descriptive statistics, sampling and estimation, inference and hypothesis testing, each carried out by the students in R on real data. They left able to clean, describe and test a dataset of their own.
2020 — 2024 Advanced Econometrics in the Social Sciences MSc · English · JLU Giessen A causal-inference course I designed and introduced, taught in R to a smaller, self-selected cohort: randomized controlled trials, instrumental variables, difference-in-differences and regression discontinuity. Materials, one set per cohort — 2023 (source) · 2022 (source).
Built on the Mostly Harmless Econometrics toolbox, it trained students to implement each method themselves rather than read about it, and to judge which one a question actually calls for.
- R — 12+ yrs, daily. tidyverse, econometrics, microsimulation, geospatial
- Stata — 10+ yrs. Data management, estimation, household survey microdata
- Python — 8+ yrs. Data processing, geospatial and remote-sensing workflows
- GAMS — 5+ yrs. Partial and general equilibrium models (AGLINK-COSIMO, CGE)
- Git and GitHub — 10+ yrs. Multi-author projects, public repositories, documentation
- R packages — 12+ yrs. Author of devCEQ and devPTIpack (30+ country analyses)
- R Shiny — Client-facing dashboards for policy makers and non-technical users
- Testing — TDD with unit tests, modular design, code review, documentation
- Tooling — Positron IDE, Quarto, R Markdown
- AI-assisted coding — GitHub Copilot and LLM tools in R and Stata; institution-wide training
- LLM integration — Large language models inside data and analysis workflows
- RAG — Retrieval pipelines connecting LLMs to domain documents and data
- Knowledge systems — Knowledge bases built for LLM applications
- Agents — Design and build LLM-based agents
- Pipelines (ETL) — 8+ yrs. Survey, administrative, trade and geospatial data; Databricks
- SQL — PostgreSQL since 2010. Relational design and querying
- PostGIS — Spatial databases and spatial queries
- DuckDB — 3+ yrs. Analytical queries on large datasets
- Data quality — Validation frameworks, QA/QC, harmonisation for official statistics
- Data collection — Survey design, questionnaires, pre-testing, enumerator training
- Analysis — 8+ yrs. Raster and vector processing; climate, vegetation, land cover
- Tools — R, Python, QGIS, Google Earth Engine
- Data — Satellite products, cadastral and parcel data (LPIS), poverty maps
- Model-based estimation — Small area estimation and mass valuation on large microdata
- Predictive ML — 5+ yrs. Training, tuning and cross-validation with tidymodels
- Causal ML — 5+ yrs. Heterogeneous treatment effects
- Causal inference — 8+ yrs. Difference-in-differences, IV, regression discontinuity, RCTs
- Microeconometrics — 10+ yrs. Panel, spatial, efficiency and multilevel models
- Fiscal microsimulation — CEQ tax–benefit incidence, counterfactual reforms, macro–micro models
- Poverty and inequality — Welfare measurement and poverty mapping
- Equilibrium modelling — 5+ yrs. Calibration, parameterisation and scenario projections
- Reproducible research — Version-controlled literate workflows to publication standard
- Standards — Introduced Quarto and Positron as World Bank tools
- Open source — Public R packages and open course materials
- Leadership — Co-initiated GeoPov; led Bank-wide adoption of AI-assisted coding
- Fieldwork — Led a multi-country farm survey in Central Asia
- Mentorship — Guide economists in new methods and in scaling analyses across countries
- Enabling — Seminar series and hands-on training; space to experiment
- Teaching — Master’s-level statistics and econometrics, 5 consecutive years
- Capacity building — Training for government counterparts and national statistical offices
- Policy advice — Technical assistance in Europe, Asia, Africa and Latin America
- Writing — Peer-reviewed articles; policy briefs, reports and outlook chapters
- Presenting — Technical results for policy makers and non-technical audiences
- Teams — 10+ yrs in multicultural, interdisciplinary teams
- Approach — Initiative, problem solving, adaptability, independent work
- Fields — Land governance and markets, agricultural and trade policy
- Statistics — Official statistics, poverty measurement, distributional analysis
Background