Residential Real Estate Reconstruction in Ukraine: Challenges and Priorities of Investment Policy

The article substantiates a spatially differentiated investment policy for the reconstruction of residential real estate in Ukraine under conditions of post-war recovery and ongoing security risks. The aim of the study is to combine the analysis of threats to the housing stock with financial assessments of losses and needs in order to determine the sequence and intensity of interventions across regions. The empirical basis includes mapping events that have affected housing infrastructure (February 24, 2022 – December 31, 2024) and summarized assessments of the damage caused, losses, and recovery needs by regions. The methodology is based on the integration of three groups of indicators: risk of damage (spatial density/clusters of events), budget strain (the region’s share in total needs), and depth of interventions (the ratio of «needs/losses» as a guideline for choosing between repairs/renovations and full reconstruction). The results demonstrate a pronounced southeast concentration of both threats and needs; over four-fifths of the total volume of resources is concentrated in a few areas, and the profiles of reconstruction vary significantly even in adjacent regions. On this basis, a three-level typology of recovery zones has been proposed (stable/rear; medium risk; high risk/frontline) and corresponding implementation approaches: scaling permanent housing in stable regions; combined solution packages in areas of medium risk (transitional formats together with permanent construction); priority critical repairs and transitional housing with a phased transition to capital projects in frontline areas. The proposed approach connects the prioritization of investments with the requirements of resilience (build back better), aligns housing interventions with the restoration of engineering infrastructure, and involves the use of risk-sharing tools (in particular, insurance/guarantees for war risks) to broaden the participation of private capital. Investment policy must be risk-adjusted: it should include insurance against war risks/first loss guarantees, and access to financing should be linked to build back better standards (shelters, reinforced structures, energy efficiency, autonomy). Housing investments should be synchronized with the restoration of engineering networks and security measures. The proposed framework enables targeted allocation of limited resources and reduces uncertainty for investors.

Authors

Publication Details

Journal
Business Inform
Published
2025-01-01
DOI
https://doi.org/10.32983/2222-4459-2025-7-278-284
Primary Topic
Regional Socio-Economic Development Trends
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Residential Real Estate Reconstruction in Ukraine: Challenges and Priorities of Investment Policy

Alexander A. Krasnevich
Business Inform
Regional Socio-Economic Development Trends
article

Residential Real Estate Reconstruction in Ukraine: Challenges and Priorities of Investment Policy

Alexander A. Krasnevich
article en

Abstract

The article substantiates a spatially differentiated investment policy for the reconstruction of residential real estate in Ukraine under conditions of post-war recovery and ongoing security risks. The aim of the study is to combine the analysis of threats to the housing stock with financial assessments of losses and needs in order to determine the sequence and intensity of interventions across regions. The empirical basis includes mapping events that have affected housing infrastructure (February 24, 2022 – December 31, 2024) and summarized assessments of the damage caused, losses, and recovery needs by regions. The methodology is based on the integration of three groups of indicators: risk of damage (spatial density/clusters of events), budget strain (the region’s share in total needs), and depth of interventions (the ratio of «needs/losses» as a guideline for choosing between repairs/renovations and full reconstruction). The results demonstrate a pronounced southeast concentration of both threats and needs; over four-fifths of the total volume of resources is concentrated in a few areas, and the profiles of reconstruction vary significantly even in adjacent regions. On this basis, a three-level typology of recovery zones has been proposed (stable/rear; medium risk; high risk/frontline) and corresponding implementation approaches: scaling permanent housing in stable regions; combined solution packages in areas of medium risk (transitional formats together with permanent construction); priority critical repairs and transitional housing with a phased transition to capital projects in frontline areas. The proposed approach connects the prioritization of investments with the requirements of resilience (build back better), aligns housing interventions with the restoration of engineering infrastructure, and involves the use of risk-sharing tools (in particular, insurance/guarantees for war risks) to broaden the participation of private capital. Investment policy must be risk-adjusted: it should include insurance against war risks/first loss guarantees, and access to financing should be linked to build back better standards (shelters, reinforced structures, energy efficiency, autonomy). Housing investments should be synchronized with the restoration of engineering networks and security measures. The proposed framework enables targeted allocation of limited resources and reduces uncertainty for investors.

Business InformVol. 7(569)
Openalex Percentile: Top 51%
Regional Socio-Economic Development Trends
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.