Does an economically active population matter in housing prices?

ABSTRACT

This article examines the link between the population structure and housing prices. We use a panel of 23 countries from 1976 to 2013 in our empirical analysis. We find statistically significant impacts of the proportion of the economically active population aged 15–64 to the total population on housing-price growth. Our study supports a policy for stable population growth to moderate housing-price growth and economic cycles.

KEYWORDS:

• Population structure
• economically active population
• housing prices
• housing-price growth equation
• panel data

JEL CLASSIFICATION:

• C2
• J1
• R2

Acknowledgements

We are grateful to the anonymous referee and Professor Ki Beom Binh for their helpful comments on an earlier version of this article. This work was supported by 2014 Research Fund of Myongji University.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Previous studies have identified population structures in relation to housing prices in different ways. For example, Fortin and Leclerc (2002) focused on the annual growth rate of the population across the age groups while Shimizu and Watanabe (2010) used first-house buyers, aged 35–44. Essafi and Simon (2015) considered old-age dependency ratios, which are constructed as the proportion of the population not actively working to the active working population.

² Australia, Belgium, Canada, Croatia, Denmark, Finland, France, Germany, Ireland, Israel, Italy, Japan, Luxembourg, Netherlands, New Zealand, Norway, South Africa, South Korea, Spain, Sweden, Switzerland, the United Kingdom, and the United States of America

³ For a detailed description of housing-price growth, see Mack and Martínez-García (2011).

⁴ As shown in Table 2, the Kleibergen and Paap (2006) rk LM statistic enables us to reject the null hypothesis that Equation 1 is underidentified at the 5% significance level, indicating that the equation is identified. We also perform an overidentification test. Hansen’s J statistic fails to reject the null hypothesis that the instruments are valid even at the 10% significance level. Excluded instrument variables are listed below Table 2.

⁵ The detailed test results are available upon request.

Additional information

Funding

This work was supported by the 2014 Research Fund of Myongji University.