Skip to content

Research & Projects

UKRAINE DEMOGRAPHIC RESILIENCE 2035

Ukraine Demographic Resilience 2035: Population, Families, Migration and Human Capital for National Recovery

Concept Status

Concept — Seeking Research & Funding Partners

Funding Status

funding_sought

Why this matters

Ukraine faces interacting pressures from low birth rates, high mortality, displacement and migration, labour shortages, family uncertainty and long-term war-related human-capital loss. Infrastructure recovery alone cannot produce sustainable recovery without sufficient people to work, form families, finance public systems and sustain institutions.

Why this matters now

Ukraine’s demographic challenge is not a single fertility indicator but a system linking mortality, migration, return, family formation, labour supply, skills, regional inequality and fiscal capacity. Recovery policy needs scenarios that connect these variables rather than treating population change as a headline number or a short-term migration balance.

Primary objective

Build an independent interdisciplinary Demographic Resilience 2035 research platform that integrates population scenarios, migration and return, family policy, labour-force dynamics, human-capital development and fiscal sustainability into evidence-based options for national and regional recovery.

Specific objectives

Develop transparent national and regional demographic scenarios to 2035 using documented assumptions and uncertainty ranges.
Study migration, return, retention, family formation and reproductive intentions without converting border-crossing counts into unsupported population-loss claims.
Model interactions between population structure, labour supply, skills, taxation, social expenditure and recovery capacity.
Translate scenarios into policy options for families, return and reintegration, labour inclusion, human capital and regional planning.
Create an annual Demographic Resilience Brief and reusable public indicator framework for evidence-based dialogue.

Methodology

  • Demographic scenario modelling with transparent assumptions, sensitivity analysis and explicit uncertainty rather than deterministic forecasts.
  • Triangulation of civil-registration, survey, migration, labour-market and administrative data while documenting methodological limitations.
  • Repeated or panel survey components on migration, return, family and work decisions where feasible and ethically appropriate.
  • Labour-economics and public-finance modelling linking demographic scenarios to skills, tax base, social expenditure and recovery constraints.
  • Comparative policy analysis of European demographic resilience, return, family-support and labour-inclusion approaches.
  • Regional meetings to jointly explore future scenarios: communities, local institutions, employers and researchers will compare demographic projections with regional needs and identify possible development responses.

Core Research Question

What demographic, legal, social, fiscal and economic conditions are required for Ukraine to retain, return and reproduce its human capital after prolonged war?

Proposed Work Packages

Demographic scenario modelling
Migration and return research
Family and reproductive decision research
Labour-force and skills modelling
Fiscal and tax-base implications
Family and child-support policy analysis
International comparative policy review
Regional scenarios
Foresight to 2035

Geography

Ukraine with comparative European and international policy cases

Target Groups

Families and working-age population
Returnees and diaspora communities
Policy institutions
Employers and labour-market actors
Regional and national authorities

Expected Outputs

Demographic scenario report
Policy options paper
Interactive indicators/dashboard concept
Return and retention policy matrix
Fiscal-sustainability analysis
Annual Demographic Resilience Brief

Intended Outcomes

Better evidence for population and human-capital recovery policy
Integrated demographic, labour and fiscal planning
Stronger return and retention policy options

Proposed Indicators

Scenario-based return and retention measures
Family-policy coverage
Labour-force participation
Tax-base sensitivity
Regional human-capital indicators
Birth and family-intention measures where ethically and methodologically appropriate

Partners Sought

Demographic institutes and universities
Economics and public-policy schools
Statistical, migration and labour-market researchers
Foundations supporting recovery and governance
International financial and development institutions where appropriate

External Expertise Sought

Demography
Migration studies
Labour economics
Public finance
Statistics and data science
Family policy

Relevant SDGs

1, 3, 4, 5, 8, 10, 16, 17

Implementation architecture

Recommended duration: 36 months

  • 12 months: A 12-month analytical phase would consolidate datasets, define transparent demographic scenarios, study migration and family decisions, and build the first integrated population–labour–fiscal framework for policy dialogue.
  • 24 months: A 24-month standard programme would add regional scenarios, longitudinal or repeated survey components where feasible, return-and-retention policy modelling, fiscal sensitivity analysis and a public indicators prototype.
  • 36 months: A 36-month research platform would institutionalise annual demographic resilience monitoring, compare policy options with European experience, deepen regional foresight, and maintain a durable university–policy–data consortium through 2035-oriented planning.

Beneficiaries

Primary beneficiaries

National and regional policy actors designing population, migration, family, labour, education and recovery policy.
Ukrainian communities and institutions planning human-capital, workforce and service capacity under demographic uncertainty.

Secondary beneficiaries

Universities, statistical and demographic researchers needing an integrated reproducible evidence framework.
Employers, civil society, development partners and international institutions using demographic evidence for recovery decisions.

Consortium profile

A credible consortium combines demographic and statistical leadership with migration studies, labour economics, public finance, family policy, regional development and secure data expertise; TNESC contributes governance, legal, fiscal and interdisciplinary coordination rather than claiming all quantitative competences internally.

Required consortium roles

Demography/population-science lead with scenario-modelling competence.
Statistics/data-science partner able to document data quality and uncertainty.
Migration and return-mobility research partner.
Labour-economics and human-capital modelling partner.
Public-finance/fiscal-policy and family-policy expertise.
Regional implementation/policy sites and independent methodological review.

Budget logic

Main cost drivers

Senior demographic, statistical, economic and fiscal research capacity.
Secure data acquisition, cleaning, harmonisation and reproducible modelling infrastructure.
Survey or repeated-measure components where ethically and methodologically justified.
Regional fieldwork, meetings to explore future scenarios, and engagement with communities, institutions and employers.
Indicator/dashboard prototype, documentation and open-methods dissemination.
Independent methodological review, quality assurance and annual policy translation products.

The 12-month scenario funds a rigorous analytical baseline; 24 months adds repeated data collection, regional modelling and an indicators prototype; 36 months establishes an annual research platform with more detailed exploration of regional future scenarios, policy modelling and sustained consortium/data infrastructure.

Risks & safeguards

Population estimates can be politicised or oversimplified, especially when border-crossing flows are mechanically interpreted as unique emigrants or permanent population loss.

Publish methods, assumptions, denominators and uncertainty ranges; triangulate sources; maintain a formal rule that border-crossing counts are not equivalent to net migration or permanent population change.

Strong normative claims about fertility or return can stigmatise women, families, people abroad or those who choose not to return.

Use a demographic-resilience rather than pronatalist framework, treat reproductive and migration decisions as rights-bearing individual choices, and focus policy analysis on enabling conditions rather than coercive targets.

War-time datasets can be incomplete, delayed, non-comparable or geographically biased, undermining model precision.

Use scenario ranges, sensitivity analysis, data-quality grading and multiple sources; distinguish observed data, modelled estimates and expert assumptions in every public output.

A large interdisciplinary programme can produce disconnected demographic, labour and fiscal outputs that do not converge into usable policy choices.

Use a shared scenario architecture and common policy questions across work packages, with annual synthesis products that explicitly trace how population assumptions affect labour, fiscal and regional outcomes.

Funding alignment

Funding-framework references indicate thematic fit only. They do not imply eligibility, funding, partnership or endorsement.

Evidence Sources

  • Opendatabot citing Ministry-of-Justice-derived registration data — Births and deaths in Ukraine, January–June 2026

Evidence sources are cited for context and do not imply partnership or endorsement.