Effects of socioeconomic factors on regional housing prices in the USA

Abstract

Purpose – This paper aims to examine the determinants of socioeconomic factors on housing prices and their differential effects among regions. Design/methodology/approach – This study employs a hierarchical linear model to analyze the housing and socioeconomic data of 363 metropolitan statistical areas (MSAs) in the USA. Findings – This study generates four findings. First, the population, the percentage of the elderly in population, violent crime rates, and foreclosure rates produce greater effects on housing prices in the Northeast than those in the West. Second, the population produces a greater effect on housing prices in the Northeast than those in the Midwest. Third, mortgage rates produce less significant effects on housing prices in the Northeast than those in the Midwest. Fourth, the population, the percentage of the elderly in population, and rent-income ratio produce greater effects on housing prices in the Northeast than those in the South. Research limitations/implications – Based on data collected for 2010, this study analyzes socioeconomic factors on the demand side under the implicit assumption that supply side remains constant. Future research can lift the restriction on fixed supply assumption. Practical implications – The results can provide information to buyers and sellers about how socioeconomic factors affect housing prices. Moreover, this study also provides useful information for the government to design and implement relevant housing policies. Originality/value – This is the pioneering study to examine the differential effect of socioeconomic factors on metropolitan housing prices among regions by employing dummy regional variables to detect changes in slope coefficients. These detailed conclusions would enhance the efficiency of transaction in housing markets.

The Impact of Macro Factors on Apartment Prices in Polish Counties: A Two-Stage Quantile Spatial Regression Approach

“…An increase of this determinant leads to higher financial costs for housing purchases, which may discourage potential buyers and decrease the liquidity of the housing market. A negative relationship between interest rates and the prices of residential properties has been confirmed in numerous studies (LIN et al 2014;CIARLONE 2015;APERGIS 2003;EGERT, MIHALJEK 2007;REICHERT 1990;NISTOR, REIANU 2018;KHOLODILIN et al 2010).…”

“…including residential property prices. Previous studies have noted the positive impact of GDP on the prices of residential properties (KASPAROVA, WHITE 2001;EGERT, MIHALJEK 2007;VALADEZ 2010;LIN et al 2014;BEŁEJ, CELLMER 2014).…”

“…In regions with a low unemployment rate, the population has higher purchasing power, which subsequently increases the prices. A significant negative relationship between unemployment rate and the prices of residential properties had been demonstrated in numerous studies (LIN et al 2014;LEE 2009;CIARLONE 2015;BEŁEJ, CELLMER 2014;EGERT, MIHALJEK 2007;GRUM, GOVEKAR 2016;AKBARI, AYDEDE 2012;NISTOR, REIANU 2018). Several studies have also investigated the impact of employment rate on the prices of residential properties (APERGIS 2003;REICHERT 1990).…”

“…A growing number of inhabitants within a given area increases demand on the local housing market, which leads to higher prices. Previous research has indicated a positive correlation between population and the prices of residential properties (LIN et al 2014;LEE 2009;EGERT, MIHALJEK 2007;REICHERT 1990;AKBARI, AYDEDE 2012;KHOLODILIN et al 2010;POTEPAN 1996).…”

“…In this case, an increase in income leads to an increase in customer purchasing power, which contributes to higher demand, thus driving up prices. A number of studies have demonstrated the positive impact of income on residential property prices (LIN et al 2014;LEE 2009;CIARLONE 2015;REICHERT 1990;AKBARI, AYDEDE 2012;NISTOR, REIANU 2018;KHOLODILIN et al 2010;POTEPAN 1996;HORTON, THOMAS 1998;LEWIN-EPSTEIN et al 1997).…”