E T Consultant - Regional Statistical Team

World Bank Group•Washington, DC

1d•Remote

About The Position

The World Bank's South Asia Regional Statistical Team provides technical support to client countries across the region in the areas of poverty measurement, distributional analysis, and economic modeling. As countries in the region face growing demands for rigorous, policy-relevant analytics — particularly in the context of fiscal reforms, economic shocks, and climate vulnerability — the team requires additional capacity to deliver high-quality analytical support in a timely and flexible manner. The Regional Statistical Team is seeking an Extended Term Consultant (ETC) with deep technical expertise in distributional analysis, microsimulation modeling, and geospatial analytics. The consultant will work across multiple country engagements, often simultaneously, in close collaboration with country economists, regional specialists, and government counterparts. The consultant will support the Regional Statistical Team in delivering analytical and capacity-building activities for South Asian countries, with a focus on four priority areas: (i) fiscal distributional analysis, (ii) survey-to-survey imputation and welfare estimation, (iii) macro-microsimulation modeling for policy reform evaluation, forecasting, and shock analysis, and (iv) geospatial data analysis for poverty and welfare assessments.

Requirements

Master's degree (required) or PhD (preferred) in Economics, Applied Economics, Statistics, or a closely related field.
A minimum of five (5) years of demonstrated, hands-on experience in at least two of the following technical areas: fiscal distributional analysis using the CEQ framework; survey-to-survey imputation or poverty estimation methodologies; macro-microsimulation modeling; and geospatial analysis for welfare or development applications.
Proven experience working with large household survey microdata and administrative datasets, including data cleaning, harmonization, and analysis.
Strong proficiency in at least two of the following programming environments: Stata, R, or Python, with the ability to produce clean, reproducible, and well-documented code.
Demonstrated experience using AI-assisted coding tools (e.g., Positron IDE, GitHub Copilot, or equivalent) to accelerate analytical workflows and improve code quality.
Experience modeling the welfare impacts of economic shocks (e.g., inflation, growth slowdowns, labor market disruptions) or climate change on household welfare.
Strong written and verbal communication skills in English; ability to translate complex technical findings into clear, audience-appropriate outputs.
Demonstrated capacity to work effectively in a remote/virtual setting, across multiple time zones, and in culturally diverse team environments.
Flexibility to travel to client countries for in-person missions when required.
Strong collaborative mindset, with the ability to work both independently and as part of multidisciplinary teams.

Nice To Haves

PhD in Economics, Applied Economics, Statistics, or a closely related field.
Prior experience working in or on South Asian countries, with familiarity with the data landscape and policy environment of the region.
Experience working directly with national statistical offices or government counterparts in a technical advisory or capacity-building role.
Familiarity with World Bank poverty measurement standards, the Global Monitoring Database (GMD), and the Poverty and Inequality Platform (PIP).
Experience with geospatial software and libraries (e.g., QGIS, ArcGIS, sf/terra in R, geopandas in Python).

Responsibilities

Conduct and support the design and implementation of Commitment to Equity (CEQ) assessments for selected South Asian countries, covering the distributional impact of taxes, transfers, and public expenditures on household welfare.
Build and maintain CEQ models using household survey microdata, integrating administrative data and national accounts where applicable.
Analyze the progressivity and redistributive effects of fiscal instruments, including direct taxes, indirect taxes, cash transfers, subsidies, and in-kind benefits (education, health).
Prepare technical notes, policy briefs, and presentations summarizing findings for government counterparts and World Bank management.
Support capacity building of national statistical offices and ministry counterparts in the application of the CEQ methodology.
Design and implement survey-to-survey imputation models to produce welfare estimates in countries or periods with limited or outdated data availability, following established World Bank methodologies (e.g., small area estimation, cross-survey imputation).
Support the construction and validation of consumption or income aggregates, and the harmonization of survey microdata across rounds and data sources.
Document model assumptions, data inputs, and limitations in a transparent and reproducible manner, ensuring full replicability of results.
Provide technical guidance and hands-on support to country poverty economists in applying imputation methodologies as part of poverty monitoring and reporting workflows.
Support poverty economists across South Asian country teams in the design, implementation, and application of macro-microsimulation models tailored to their specific country contexts and policy questions.
Develop and maintain models that link macroeconomic projections — including growth, inflation, labor market dynamics, and sectoral shifts — to household-level distributional outcomes, enabling poverty and inequality nowcasting and forecasting.
Simulate and assess the welfare effects of economic and climate-related shocks, including commodity price volatility and natural disasters, translating macro-level projections into household-level poverty and inequality estimates.
Work closely with country economists to adapt model assumptions, calibrate parameters, and interpret results in the context of country-specific institutional and data environments.
Build the capacity of regional and country-level economists to independently operate and extend microsimulation tools, including through hands-on training, documentation, and code walkthroughs.
Produce scenario analysis outputs — including poverty headcount projections, distributional charts, and sensitivity analyses — suitable for policy dialogue with government counterparts and World Bank management.
Apply geospatial data and methodologies — including satellite imagery, remote sensing, and geographic information systems (GIS) — to support small area poverty estimation and disaggregated welfare analysis.
Combine household survey data with high-resolution spatial datasets (nighttime lights, vegetation indices, climate hazard layers, infrastructure data) to produce subnational poverty maps and vulnerability assessments.
Support the integration of climate exposure and disaster risk data into welfare analysis, contributing to climate-poverty analytics for the region.
Produce maps, visualizations, and spatial datasets suitable for policy dialogue and dissemination.