Urban growth boundaries (UGBs) — regulatory lines that restrict dense development beyond a city's edge in order to preserve open space — have well-measured costs: Bigelow and Plantinga (2017) estimated, in an equilibrium sorting framework with two household types, that Oregon's UGBs raised the relative price of developed land inside the boundary through a scarcity effect (restricted supply of exurban land) and a quality effect (changed attributes of newly developed land). But their analysis deliberately measured only this cost side. The amenity benefits of preserved open space and compact development capitalize into essentially all property prices in the same market, so they cannot be netted against the cost estimates without a separate or joint valuation, and the paper's model predicts the utility losses fall unevenly on households who prefer exurban versus urban amenities. The open problem is to complete this welfare evaluation: estimate the value of the open-space amenities generated by a UGB within the same market framework as its scarcity and quality cost effects, compute the policy's net welfare effect, and quantify how net benefits and costs are distributed across households with different location preferences. No study in the literature is known to have done so.

Background

An urban growth boundary (UGB) is a line drawn around an urbanized area by a regional or state government beyond which high-density development is legally restricted; Oregon's statewide land-use program, which requires every city to adopt a UGB, is the canonical example and the setting of the source study. The economic case for growth controls rests on a trade-off: restricting development at the fringe preserves open space and contains sprawl (a benefit), but by making developable land scarcer it raises land and housing prices (a cost). Classical theory already established the cost logic — in an open city (an urban-economics model of a city with free migration in and out, so that residents' utility is pinned down by the outside option), growth controls raise land rents and redistribute income toward landowners (Brueckner 1990; Engle, Navarro, and Carson 1992) — and empirical work confirmed that Oregon's UGBs contained development (Dempsey and Plantinga 2013).

Bigelow and Plantinga (2017) advanced this literature by combining an equilibrium sorting model with land-price econometrics. An equilibrium sorting model is one in which heterogeneous households choose locations given prices and locational amenities, and prices adjust so that markets clear; their model features two household types, colloquially 'town mice' (preferring urban amenities) and 'country mice' (preferring exurban amenities such as open space). Using a parcel-level panel of developed land values in four Willamette Valley, Oregon counties from 1973 to 2000, they separated two channels by which a UGB changes the price of developed land inside relative to outside the boundary: a scarcity effect (restricting the supply of exurban land for development) and a quality effect (changing which parcels get developed and hence the attributes of the developed stock). They found the scarcity effect dominates. A hedonic price model — a regression of property values on location and attribute characteristics — recovers how prices vary with amenity levels, and this is exactly the tool by which open-space amenities show up as capitalized value in property prices (e.g., Bolitzer and Netusil 2000 for Portland open space).

The machinery needed for the benefit side also exists, but only outside the UGB question. Wu, Adams, and Plantinga (2004) embedded amenities in an urban equilibrium model of Portland development; Walsh (2007) made open space endogenous in a locational equilibrium model and simulated preservation policies; Klaiber and Phaneuf (2010) valued open space within a residential sorting model; and Turner, Haughwout, and van der Klaauw (2014) measured the welfare effects of land-use regulation in a spatial equilibrium framework, though for regulation's supply-restriction and externality margins generally rather than for the amenity benefits of a specific growth boundary. The gap identified by Bigelow and Plantinga (2017) is that none of these is combined with cost-side estimates of the kind they produced: because UGB-generated amenity benefits are capitalized into all property prices in the market, not just regulated ones, their hedonic analysis of developed-land prices cannot by itself determine whether the policy's benefits exceed its costs. Their model further implies the welfare losses differ systematically across household types — residents who prefer exurban amenities lose more utility from a UGB than those who prefer urban amenities — an incidence dimension their empirical design did not quantify. An adjacent theoretical literature treats UGBs as a second-best instrument for unpriced traffic congestion (Brueckner 2007), again bypassing the open-space amenity benefit channel.

Problem Statement

Complete the welfare evaluation of urban growth boundaries opened by Bigelow and Plantinga (2017). In an actual land market subject to a UGB (the source setting is urbanizing Oregon), the problem is to (i) estimate — separately or jointly within one model — the value of the open-space and related amenities preserved or generated by the boundary and its compact-development pattern, benefits that capitalize into all property prices in the market and are therefore not identified by the already-estimated scarcity and quality effects on developed-land prices inside versus outside the boundary; (ii) combine the amenity-benefit estimates with the cost-side scarcity and quality effects to compute the net welfare effect of the UGB policy; and (iii) quantify the distribution of these net welfare impacts across households with heterogeneous location preferences — urban-amenity versus exurban-amenity types — whose utility losses the source model predicts to be systematically unequal. These three deliverables jointly constitute one objective, the total net benefit and incidence of growth controls.

References

  1. Bigelow, Daniel P., and Andrew J. Plantinga (2017). 'Town mouse and country mouse: Effects of urban growth controls on equilibrium sorting and land prices.' Regional Science and Urban Economics 65: 104–115. DOI: 10.1016/j.regsciurbeco.2017.05.002. https://doi.org/10.1016/j.regsciurbeco.2017.05.002
  2. Walsh, Randy (2007). 'Endogenous open space amenities in a locational equilibrium.' Journal of Urban Economics 61(2): 319–344. DOI: 10.1016/j.jue.2006.09.002. https://doi.org/10.1016/j.jue.2006.09.002
  3. Wu, JunJie, Richard M. Adams, and Andrew J. Plantinga (2004). 'Amenities in an Urban Equilibrium Model: Residential Development in Portland, Oregon.' Land Economics 80(1): 19–32. DOI: 10.2307/3147142. https://doi.org/10.2307/3147142
  4. Klaiber, H. Allen, and Daniel J. Phaneuf (2010). 'Valuing open space in a residential sorting model of the Twin Cities.' Journal of Environmental Economics and Management 60(2): 57–77. DOI: 10.1016/j.jeem.2010.05.002. https://doi.org/10.1016/j.jeem.2010.05.002
  5. Severen, Christopher, and Andrew J. Plantinga (2018). 'Land-use regulations, property values, and rents: Decomposing the effects of the California Coastal Act.' Journal of Urban Economics 107: 65–78. DOI: 10.1016/j.jue.2018.07.001. https://doi.org/10.1016/j.jue.2018.07.001
  6. Fienup, Matthew J., and Andrew J. Plantinga (2021). 'Unintended Effects of Environmental Policies: The Case of Urban Growth Controls and Agricultural Intensification.' Land Economics 97(2): 261–280. DOI: 10.3368/le.97.2.261. https://doi.org/10.3368/le.97.2.261
  7. Turner, Matthew A., Andrew Haughwout, and Wilbert van der Klaauw (2014). 'Land Use Regulation and Welfare.' Econometrica 82(4): 1341–1403. DOI: 10.3982/ecta9823. https://doi.org/10.3982/ecta9823
  8. Brueckner, Jan K. (1990). 'Growth Controls and Land Values in an Open City.' Land Economics 66(3): 237–248. DOI: 10.2307/3146726. https://doi.org/10.2307/3146726
  9. Engle, Robert, Peter Navarro, and Richard Carson (1992). 'On the theory of growth controls.' Journal of Urban Economics 32(3): 269–283. DOI: 10.1016/0094-1190(92)90018-G. https://doi.org/10.1016/0094-1190(92)90018-G
  10. Dempsey, Judith A., and Andrew J. Plantinga (2013). 'How well do urban growth boundaries contain development? Results for Oregon using a difference-in-difference estimator.' Regional Science and Urban Economics 43(6): 996–1007. DOI: 10.1016/j.regsciurbeco.2013.10.002. https://doi.org/10.1016/j.regsciurbeco.2013.10.002
  11. Bolitzer, B., and N. R. Netusil (2000). 'The impact of open spaces on property values in Portland, Oregon.' Journal of Environmental Management 59(3): 185–193. DOI: 10.1006/jema.2000.0351. https://doi.org/10.1006/jema.2000.0351
  12. Brueckner, Jan K. (2007). 'Urban growth boundaries: An effective second-best remedy for unpriced traffic congestion?' Journal of Housing Economics 16(3–4): 263–273. DOI: 10.1016/j.jhe.2007.05.001. https://doi.org/10.1016/j.jhe.2007.05.001
  13. Tan, Ronghui, and Shuxian Xu (2023). 'Urban growth boundary and subway development: A theoretical model for estimating their joint effect on urban land price.' Land Use Policy 129: 106641. DOI: 10.1016/j.landusepol.2023.106641. https://doi.org/10.1016/j.landusepol.2023.106641
  14. Kirby, Matthew G., Alister J. Scott, Jason Luger, and Claire L. Walsh (2023). 'Beyond growth management: A review of the wider functions and effects of urban growth management policies.' Landscape and Urban Planning 230: 104635. DOI: 10.1016/j.landurbplan.2022.104635. https://doi.org/10.1016/j.landurbplan.2022.104635
  15. Li, Liqing, and Mitchell R. Livy (2025). 'Who values urban open spaces? investigating heterogeneity in the capitalization of open space in New York city.' Landscape and Urban Planning 255: 105259. DOI: 10.1016/j.landurbplan.2024.105259. https://doi.org/10.1016/j.landurbplan.2024.105259
  16. Zhu, Shihao, Longfei Zheng, Daquan Huang, and Yanxu Liu (2025). 'How do local governments respond to national urban containment policies? Evidence from China.' Habitat International 157: 103320. DOI: 10.1016/j.habitatint.2025.103320. https://doi.org/10.1016/j.habitatint.2025.103320
  17. Jalali, D., H. MacDonald, A. A. F. Fini, and S. Shi (2022). 'Effects of planning regulations on housing and land markets: A system dynamics modeling approach.' Cities 126: 103670. DOI: 10.1016/j.cities.2022.103670. https://doi.org/10.1016/j.cities.2022.103670