A Study on Information of Price Change of Real Estate by Macroeconomic Fluctuation - Focused on Real Estate of Housing and Shopping -

2021 ◽  
Vol 34 (3) ◽  
pp. 631-660
Author(s):  
YONG-KYUNG SHIN
Keyword(s):  
Real Estate ◽  
Price Change ◽  
Macroeconomic Fluctuation

scholarly journals Did the COVID-19 Pandemic Crisis Affect Housing Prices Evenly in the U.S.?

2021 ◽  
Vol 13 (21) ◽  
pp. 12277
Author(s):  
Xinba Li ◽  
Chuanrong Zhang
Keyword(s):  
Real Estate ◽  
Spatial Patterns ◽  
Price Change ◽  
Housing Prices ◽  
Housing Price ◽  
Real Estate Market ◽  
Moran’S I ◽  
Moran's I ◽  
Price Changes ◽  
The U.S

While it is well-known that housing prices generally increased in the United States (U.S.) during the COVID-19 pandemic crisis, to the best of our knowledge, there has been no research conducted to understand the spatial patterns and heterogeneity of housing price changes in the U.S. real estate market during the crisis. There has been less attention on the consequences of this pandemic, in terms of the spatial distribution of housing price changes in the U.S. The objective of this study was to explore the spatial patterns and heterogeneous distribution of housing price change rates across different areas of the U.S. real estate market during the COVID-19 pandemic. We calculated the global Moran’s I, Anselin’s local Moran’s I, and Getis-Ord’s statistics of the housing price change rates in 2856 U.S. counties. The following two major findings were obtained: (1) The influence of the COVID-19 pandemic crisis on housing price change varied across space in the U.S. The patterns not only differed from metropolitan areas to rural areas, but also varied from one metropolitan area to another. (2) It seems that COVID-19 made Americans more cautious about buying property in densely populated urban downtowns that had higher levels of virus infection; therefore, it was found that during the COVID-19 pandemic year of 2020–2021, the housing price hot spots were typically located in more affordable suburbs, smaller cities, and areas away from high-cost, high-density urban downtowns. This study may be helpful for understanding the relationship between the COVID-19 pandemic and the real estate market, as well as human behaviors in response to the pandemic.

scholarly journals DYNAMICS OF REGIONAL RESIDENTIAL REAL ESTATE MARKETS IN UKRAINE

2019 ◽  
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Price Change ◽  
Supply And Demand ◽  
Real Estate Market ◽  
Average Price ◽  
Residential Real Estate ◽  
Real Estate Markets ◽  
Regional Centers ◽  
The Given

The dynamics of the general price index and price index on the primary and secondary residential real estate market (2015–2019) for one-room, two-room and three-room apartments is constructed in the article. The state and tendencies of development of the residential real estate market are considered, which in turn is characterized by: imperfection, problems of uneven development of certain parts of the market, closeness, unreliability and insufficient information about: value, subjects, objects, real supply and demand in the given economic sphere of our country in the conditions of disintegration processes. The regulatory framework by which the control and regulation of this type of market is carried out is not perfect enough. Different scientists, both domestic and foreign, have conducted research and determined a set of factors and methods used in the study of real estate, its assessment, analysis of trends in a certain period of time. A map of Ukraine, containing data on the average price per square meter of housing in all regional centers as of September 2019 is presented and comparative analysis with September 2018 is done; the cities with the largest or smallest price change has occurred are identified. The dynamics of the construction price index (2015–2019) was analyzed; it characterizes the changes and has a significant impact on the final value of real estate in a certain period of time during the construction process, the factors that influence the change of this index are identified. The dynamics of the average price per square meter of residential real estate in different regions of Ukraine is also presented, the factors that determine this dynamics for 2012–2019 were identified – in such cities as Kiev, Lviv, Donetsk, Kharkiv, Odessa, Sevastopol, Simferopol. Psychological factors that influence rise or fall in the value of residential property in selected major cities of Ukraine and in the cities near hostilities (Severodonetsk, Lisichansk) during and after the pre-war period were also identified.

The determinants of real estate prices in a European context: a four-level analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Antonio M. Cunha ◽  
Júlio Lobão
Keyword(s):  
European Union ◽  
Real Estate ◽  
Interest Rates ◽  
Regression Models ◽  
Important Determinant ◽  
Price Change ◽  
Content Type ◽  
Real Estate Price ◽  
Price Determinants ◽  
Real Estate Prices

PurposeThis paper explores the real estate price determinants at four geographical levels: in the European Union as a whole, in the 28 European Union countries, in one European Union country (Portugal) and in 25 Portuguese metropolitan statistical areas (MSAs).Design/methodology/approachThe authors run two time series regression models and two panel data regression models with observations of potential real estate price determinants and House Price Indices collected from Eurostat.FindingsThe results show that price determinants, such as gross domestic product (GDP), interest rates, housing starts and tourism, are statistically significant, but not in all the four geographical levels of analysis. The results also confirm the autoregressive characteristic of real estate prices, with the last period price change being the most important determinant of current period real estate price change.Practical implicationsForecasting real estate prices can be made more effective by knowing that each geographical level of analysis implies different price determinants and that momentum is an important determinant in real estate returns.Originality/valueTo the best of the authors knowledge, this is the first study to develop and test a real estate price equilibrium model at several different geographical levels of the same political space.

Real Estate Fraud

2008 ◽  
Author(s):  
Daniel Bradley
Keyword(s):  
Real Estate
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