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Finance and Credit
 

Modeling the mixed funding of social housing construction in the Russian Federation

Vol. 23, Iss. 24, JUNE 2017

PDF  Article PDF Version

Received: 6 March 2017

Received in revised form: 6 April 2017

Accepted: 24 April 2017

Available online: 30 June 2017

Subject Heading: INVESTING

JEL Classification: H53, H54, R21

Pages: 1422-1438

https://doi.org/10.24891/fc.23.24.1422

Baltina A.M. Orenburg State University, Orenburg, Russian Federation
abaltina@osu.mail.ru

Kirilenko L.S. Orenburg State University, Orenburg, Russian Federation
kirilenlyudmila@yandex.ru

Importance The article explores the realization of a mixed model to finance the construction of social housing in the Russian Federation.
Objectives The aim is to identify optimal scenarios to implement a mixed model of financing the social housing construction in the Russian Federation, taking into account the distribution of risks between investors.
Methods A mixed funding model that combines private capital resources and privileges provided by the State is defined as a priority for social housing construction in the Russian Federation. To reveal mathematical relationship between public support and business profitability, we divided the funding scenarios based on three factors, i.e. using borrowed funds, placing some housing on the market, buying out some rental housing.
Results We took the internal rate of return and payback period as indicators of economic efficiency to evaluate the project by a private investor. These indicators change when there is an increase or decrease in State support. Projects with subsidized rents and tax privileges at the initial stage of the project were the most attractive ones. Scenarios with borrowed funds and specified conditions in the project demonstrated the lowest efficiency due to the excess of mortgage constant over the desired rate of return on the project.
Conclusions The findings and recommendations can be used by regional authorities to develop measures of financial support to social housing projects.

Keywords: social housing, housing stock, funding model, investment, rental housing

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