Urban areas worldwide are undergoing rapid population expansions, helping to drive economic growth, which is arguably accelerated through benefits associated with agglomeration. However, this growth comes with a critical challenge – the impact on housing affordability. As cities swell with new residents, the demand for housing skyrockets and often outpaces housing supply, which drives costs higher. This phenomenon poses significant implications for societal well-being and economic equality including both income and wealth equalities, and inter-generational effects.
The Role of Population in Urban Development
Urban planners and policymakers grapple with the dual nature of population expansions. On one hand, a growing population contributes to urban agglomeration, which foster productivity and economic growth. On the other hand, the surge in residents drives up the demand for housing and creates a social cost that manifests in soaring housing prices and widening inequalities.
While the economic benefits of larger cities have been extensively studied, there is a noticeable gap in quantifying the specific costs associated with population growth, particularly in relation to housing. Understanding these costs is crucial for informed decision-making among policymakers as they navigate the juxtaposed opportunities and challenges of urban expansion.
Understanding the Dynamics
The relationship between population growth and housing costs is complex and often confounded by several issues that make estimating this relationship challenging. Unobserved location-specific attributes, measurement errors, and the potential bi-directional relationship between population and housing costs all contribute to the complexity. These issues could cause estimates to be biased and inconsistent, and potentially misrepresent the true relationship between population and housing costs.
Therefore, estimating the effects of city population on housing costs requires a meticulous approach. But how do we identify such effects? Here, we propose a novel approach using Australian panel data. Our work employs a fixed effects model to eliminate the confounding effects of unobserved heterogeneity, known as fixed effects, such as unobserved location attributes that might jointly influence population growth and housing cost. To address the confounding issues of reverse causality and measurement error, we propose a new instrumental variable (IV) for city population to identify its effect on housing cost.
For our IV to be applicable within a panel fixed effects framework (i.e. not get washed away from the regression by the fixed effects), it must contain both cross-sectional and time variations. To this end, we construct our IV by interacting data on city climate with the volume of visas issued (visa issuance). This exploits the fact that regions with a better climate tend to attract more migrants. The combination of climate quality and visa issuance will contribute to differences in population growth across Australia and across time.
Insights from the Instrumental Variable Analysis
Implementing two-stage least squares (2SLS) regression using our climate-visas IV as an instrument for city population yields insightful results. The positive relationship between the number of visas issued and population, particularly in cities with favourable climates, aligns with the hypothesis that attractive climates attract more migrants, leading to greater population growth in these regions compared with places with poorer climates.
The second-stage estimates reveal a concerning trend – housing costs, especially rental costs, tend to rise more quickly than population growth. The estimates show that a 1% increase in city population is associated with an average increase in home prices ranging from 1.16% to 1.59% and an average increase in rental prices ranging from 1.84% to 1.97%. This suggests that housing costs escalate at a faster rate than the growth in population. The findings are also consistent with the idea that migration has a greater impact, at least in the short run, on rental than home ownership markets.
Implications for Inequality
The widening gap in housing costs poses a direct threat to income inequality. Individuals and households with lower incomes already allocate a larger proportion of their earnings to housing expenses. An upward trajectory of housing costs induced by population growth exacerbates this inequality, creating a scenario in which the affordability of shelter becomes a significant determinant of overall economic well-being.
As urban areas continue to burgeon with new residents, the challenge of housing affordability looms larger than ever. Our study sheds light on the intricate dynamics between population growth and housing costs, emphasizing the need for proactive measures to address the widening gap. Policymakers must not only consider the economic benefits of urban agglomeration but also carefully navigate the social costs, ensuring that the benefits of growth are equitably distributed.
Our findings speak to the importance of future research and policy interventions to foster more equitable urban communities in the face of rapidly rising housing costs. As the global urban landscape evolves and prosperous countries such as Australia continue to draw in more migrants, more strategic policy initiatives must be in place to ensure that housing affordability remains within reach for all. There is a current strong focus on the importance of increasing new housing supply to mitigate the housing affordability crisis. Yet, the construction sector and associated supply chains in Australia and in many other countries have proven unable to respond effectively to the challenge. Our own research shows that increasing migration (partly in the hope of boosting construction capacity) also triggers greater pressures on housing markets, and particularly rental markets. This conundrum shows very clearly that migration, skills, housing, and a host of other policy frameworks cannot be developed independently but must be properly thought through and joined up.