Analysis of House Price Determination in 13 G20 Countries: Random Effect Model
DOI:
https://doi.org/10.12928/jampe.v2i2.7983Keywords:
House, Price, Macroeconomics , Random Effect ModelAbstract
A house or a place to live is a primary need for all beings, but the lack of affordable housing to buy or rent can trigger a global housing crisis. After the collapse of the housing market in the US or the subprime crisis of 2008-2009 there was a revival of focus on the housing market. Empirical research has been conducted to look at the variables that affect house prices. However, it is still rare for researchers to examine the influence of macroeconomic variables in countries that have a strong role in the world economy. Therefore this study aims to determine the effect of the Consumer Price Index, Construction GDP, Unemployment Rate, Population Density, Exchange Rate and Power Purchasing Parity on the House Price Index as an indicator that reflects house prices. So, the contribution of this research is to provide novelty in the use of the house price index to determine the determinants that influence it. This research is a quantitative research using secondary data. The regression model used in this study is the Random Effects Model. The result of this study is the Consumer Price Index and Purchasing Power Parity have a significant positive impact on house prices. Therefore, the government needs to maintain the stability of these two indicators so that house prices remain stable. The Unemployment Rate and Exchange Rate show a significant negative effect on house prices. Therefore, the government needs to monitor and maintain the stability of the exchange rate and reduce the unemployment rate so that there is no significant decline in house prices. Meanwhile, construction GDP and population density show no effect on house prices. Additional studies are urgently needed to identify factors and housing price movements contributing to global and regional levels.
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