A framework that connects land markets, housing production, and related factors to provide new insights into how urban and suburban areas grow
Housing development and crop fields; Image created using AI (Copilot)
What Is the Issue?
A fundamental challenge in understanding urban/suburban development lies in identifying the factors that drive the conversion of undeveloped land into housing. Although the role of land markets is well recognized, empirical evidence has been limited due to a lack of detailed data on undeveloped land prices and the complexity of isolating causal relationships. Urban models emphasize that a landowner’s conversion decision depends on the cost of conversion and the present value of future agricultural rents. However, empirical models rarely integrate these insights with micro-level land-market data. This gap is critical because undeveloped land markets function as a key input in the production of housing, where locational attributes affect land prices and residential housing values.
Our research develops a framework that connects land markets, housing production, and related factors to provide new insights into how urban and suburban areas grow. Without this integration, policymakers risk overlooking the spatial variation in how land and housing policies affect development, leading to inefficient or inequitable growth. We highlight the critical role that interactions between agricultural and urban policy play in shaping where and how communities expand. Since housing supply and land prices vary significantly across locations, policies that ignore this variation may result in missed housing targets, inefficient land use, or added pressure on farmland and open space. Our simulations further show that a parcel’s development potential depends heavily on the level of surrounding urbanization. For policymakers, these results underscore the importance of aligning housing and land conservation goals at the local level to support smarter development.
What Did We Find?
Our results show that the housing supply is responsive to housing prices, but that residential development is less sensitive to land prices. This lower responsiveness likely reflects the rural nature of our study area, where most land remains undeveloped, and demand plays a larger role in shaping development. When we simulate how development responds to changes in housing and land prices, we find that ignoring land price dynamics leads to a 50% underestimation of the effects of land market policies. This means that policies like ecosystem service payments—designed to influence land use—may have much stronger effects on urban growth than commonly assumed if land price responses are not properly accounted for.
What Did We Do?
Our investigation into the determinants of residential land development is supported by detailed land-use data and rich housing and land transaction records, all organized at the micro-neighborhood level using a 4 km grid. Housing and land price indices are derived from statistical models, following established methods in the literature. Land cover distribution over time within each grid cell is aggregated from the National Land Cover Database (NLCD), which provides 30-meter resolution data across multiple years (2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019). By combining physical landscape features with land and housing prices from both local and surrounding neighborhoods, we can identify the impacts of land markets on housing supply. To examine the timing of development decisions, we estimate a statistical model that captures the probability over time of a parcel of undeveloped land being converted into residential use.
Publication completed for this work
Hua, J., Klaiber, A., & Wrenn, D. H. (2024). The impacts of agricultural land markets, climate, and weather on urban development. SSRN. https://doi.org/10.2139/ssrn.4760450
Contact: Douglas Wrenn, dhw121@psu.edu
