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Original Research

A STUDY OF THE FACTORS AFFECTING THE REAL ESTATE MARKET WITH A MACROECONOMIC CONTEXT

NATIA TERTERASHVILI 1, and SHOTA SHABURISHVILI 2.

Vol 18, No 08 ( 2023 )   |  DOI: 10.5281/zenodo.8288943   |   Author Affiliation: Student, Doctoral Program of Business Administration, Ivane Javakhishvili Tbilisi State University. Tbilisi, Georgia 1; Associate Professor, Doctor of Economics, Ivane Javakhishvili Tbilisi State University. Tbilisi, Georgia 2.   |   Licensing: CC 4.0   |   Pg no: 705-717   |   Published on: 22-08-2023

Abstract

The investigation into the patterns of real estate market development, its role in the economic landscape, and the examination of factors influencing property prices captivates the attention of contemporary academia. Notably, the real estate market in Georgia remains in its formative stages, resulting in limited scholarly scrutiny. It's essential to recognize that the real estate market wields a potent multiplier effect on the overall economy of a nation. This article delves into a comprehensive analysis of the factors that exert influence on the real estate market. The study encompasses the timeframe from 2013 to 2021, drawing upon indicators from 12 different countries. Employing the method of linear regression analysis, the study successfully identifies the key variables that significantly impact real estate prices and availability. These variables include GDP per capita, inflation, investments, the Quality of Life Index, and the safety index. Crucially, through empirical research, the study unveils statistically significant relationships. Specifically, GDP per capita, safety index, and investments exhibit a positive correlation with real estate prices and its affordability ratio. Conversely, the analysis reveals a negative correlation between the Quality of Life Index, population, inflation rate, and the dependent variable, underscoring the intricate interplay between these factors and their influence on the real estate market dynamics.


Keywords

real estate; housing market; linier regression; construction industry; investments.