| Abstract [eng] |
Assessing asset returns in both emerging and developed capital markets identifies several aspects of investor behavior that lead to increases or decreases in investment in various assets. When studying the behavior of investors, it is observed that they invest in different assets according to their current needs. Investors who expect faster returns invest in one of the riskiest - stock markets. However, those investors who expect higher returns, but not as fast, invest in the real estate market, since real estate investments are more attractive in the long term compared to the stock market. Based on historical data, the speculative behavior of investors in the real estate market can lead to the formation of a real estate bubble, and its bursting can have negative consequences for the economy. The first part of the work reveals the problems of investments in the real estate market, which allowed us to set the main goal - whether investments in real estate in Lithuania and Sweden can lead to an increase in real estate prices and signal the emerging real estate bubble. The object of the research is the real estate market. The period of analysis is 2006–2022. The tasks are to reveal the problem of investments in real estate and their influence on the real estate market; analyze different models and their application to detect real estate bubbles; to develop a methodology for investigating the possibilities of detecting real estate bubbles in Lithuania and Sweden; to conduct an empirical study of the impact of investments in real estate on the formation of bubbles in Lithuania and Sweden. The methods used in the research are the analysis of scientific literature; comparison and analysis of statistical data; analysis of relative indicators; graphical data analysis and time series econometric analysis are performed with the help of statistical packages. The second part of the work analyzes different models and their application to detect real estate bubbles. Based on the scientific literature, it has been established that there is no single model that is suitable for assessing whether a real estate bubble has formed, so it is necessary to compare the models with each other. The models analyzed in the theoretical part are the indicator analysis model, which allows detection of unsustainable housing price growth when relative indicators deviate from long-term averages; the analysis of the fundamental factors influencing demand and supply allows us to discover what factors affect housing prices in different countries, the main factors identified are housing rent price index, GDP, inflation, consumer price index, construction price, housing interest rate, etc.; the model of the spread of real estate bubbles between countries allows to assess how real estate bubbles can migrate from one country to another; the housing price level determination model allows you to assess the current level of real estate prices and check whether the prices do not deviate from the real value. By applying different models and comparing them with each other, it is possible to identify a real estate bubble. In the third part of the work, the methodology of the empirical study of the impact of investments in real estate on the formation of bubbles in Lithuania and Sweden is prepared. For further research, it was decided to use three analyzed real estate bubble detection models - the housing price level determination model, the analysis of fundamental factors affecting demand and supply, and the indicator analysis model. In the fourth part of the work, an empirical study is carried out with the aim of detecting real estate bubble formation episodes in Lithuania and Sweden by applying different models. All models used in the study detected episodes of real estate bubbles in Lithuania and Sweden. The appropriateness of the application of the models is confirmed by the real estate bubble that existed historically and was discovered in the study during the financial crisis of 2007–2009. This real estate bubble in Lithuania was detected by the housing price level determination model, using the SADF test, the study of the analysis of the fundamental factors affecting demand and supply, using the multiple linear regression equation and the indicator analysis model, using the relative index of housing prices and rental prices, housing prices and wages index indicator and housing price and consumer price index indicator. This housing bubble in Sweden is not detected by the relative index of housing prices and rents and the ratio of housing prices to wages. Sweden stood out in the results of the study because the housing bubble recorded in Sweden during the financial crisis lasted significantly shorter than in Lithuania, which shows that Sweden was able to deal with volatile housing prices faster than Lithuania. A housing bubble in Lithuania and Sweden was also recorded in 2021–2022, which shows that house prices have risen unsustainably and may have been caused by various events in the world, such as the recession caused by the COVID-19 pandemic, the Russian invasion of Ukraine and the behavior of investors in the market. The work ends with conclusions and recommendations. |
