Effects of Exchange Rate Changes on Real Estate Prices in Russia During the Russian-Ukrainian War

As a result of the Russian-Ukrainian war which started at February 24, 2022, some of Russia's economic indicators have been affected, including the ruble's exchange rate, Russia's inflation rate, and GDP. With this in mind, this paper assumes that there is a linear relationship between real estate prices and the exchange rate, inflation rate, and GDP as follows: ln_repx = ß0 + ß1 ln_exr + ß2ln_inf + ß3ln_Y + c.c.. Based on the information collected, the StataSE 15.0 tool is used to perform regression operations to derive the correlation coefficients and to explore the relationship between house prices and each price factor. Afterwards, it was concluded that under the influence of the Russian-Ukrainian war, changes in the exchange rate of the Russian domestic currency against the US dollar would have some negative impact on real estate prices. Overall, these results shed light on guiding further exploration of continuous influence from war on Russia’s real estate market and pave a path for government to make efficient response.

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Publication Details

Journal
Highlights in Business Economics and Management
Published
2024-08-08
DOI
https://doi.org/10.54097/6a5ewr46
Primary Topic
Market Dynamics and Volatility
Type
article
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article

Effects of Exchange Rate Changes on Real Estate Prices in Russia During the Russian-Ukrainian War

Zhengrong Han
Highlights in Business Economics and Management
Market Dynamics and Volatility
article

Effects of Exchange Rate Changes on Real Estate Prices in Russia During the Russian-Ukrainian War

Zhengrong Han
article en

Abstract

As a result of the Russian-Ukrainian war which started at February 24, 2022, some of Russia's economic indicators have been affected, including the ruble's exchange rate, Russia's inflation rate, and GDP. With this in mind, this paper assumes that there is a linear relationship between real estate prices and the exchange rate, inflation rate, and GDP as follows: ln_repx = ß0 + ß1 ln_exr + ß2ln_inf + ß3ln_Y + c.c.. Based on the information collected, the StataSE 15.0 tool is used to perform regression operations to derive the correlation coefficients and to explore the relationship between house prices and each price factor. Afterwards, it was concluded that under the influence of the Russian-Ukrainian war, changes in the exchange rate of the Russian domestic currency against the US dollar would have some negative impact on real estate prices. Overall, these results shed light on guiding further exploration of continuous influence from war on Russia’s real estate market and pave a path for government to make efficient response.

Highlights in Business Economics and ManagementVol. 39
Beijing Normal-Hong Kong Baptist University (CN), Hong Kong Baptist University (HK), Beijing Normal University (CN)
Decent work and economic growth
Openalex Percentile: Top 83%
Market Dynamics and Volatility
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