An urban growth boundary (UGB) restricts urban development beyond a legally fixed line and must periodically be expanded to maintain the supply of developable land. Jun (2006), studying Portland's UGB with block-group-level hedonic regressions for 1990 and 2000, found no statistically detectable inside-versus-outside housing price premium and reported Hausman tests that rejected the absence of simultaneity between housing density and housing prices, while treating density as exogenous. The paper's open research need is a joint model of a boundary's land and housing market effects, in which land prices, housing density, and housing prices are simultaneously determined, that yields empirically tested predictions of under what conditions, and by how much, a UGB ought to be expanded. The later literature treats the two markets in isolation (reduced-form price studies) or in uncalibrated theory, while quantitative spatial general-equilibrium modeling (Koster 2023, on English greenbelts) has demonstrated joint estimation of amenity, supply, and agglomeration interactions together with counterfactual boundary changes. What remains open is the empirically implemented joint land-housing system applied to an actual urban growth boundary, together with validated, condition-dependent expansion criteria.

Background

An urban growth boundary (UGB) is a legally drawn line around an urbanized area outside of which urban-density development and urban services are prohibited; it is the strictest form of urban containment policy. A greenbelt is a related instrument, a ring of protected open land around a city that likewise forbids development beyond the urban fringe. Oregon's 1973 statewide land-use planning law required every Oregon city to adopt a UGB, and the Portland metropolitan boundary is administered by the regional government Metro, which must maintain a supply of developable land sufficient for roughly twenty years of growth inside the line and must therefore decide, periodically and under political contestation, whether and by how much to expand it (Lewis et al. 2018).

Whether containment raises land and housing prices has been contested since Knaap (1985) measured the price effects of metropolitan Portland's UGB on land, and the question was actively debated in the housing-policy literature around 2000 (Lang 2002). Jun (2006) regressed the natural logarithm of average owner-occupied housing value across census block groups on structural, housing-market, sociodemographic, accessibility, and county covariates, with an indicator for location inside the UGB. A hedonic regression of this kind recovers the implicit price of a location's attributes from observed property values. The estimated coefficient on the inside-UGB indicator was statistically insignificant in both 1990 and 2000, supporting the interpretation that housing inside and outside the boundary belonged to a single housing market rather than two distinct markets.

That null result was hedged by an unresolved econometric obstacle the paper itself documented: land prices, housing density, and housing prices are jointly determined. Higher land prices need not translate into higher housing prices, because developers can economize on land by building smaller lots and higher-density multifamily units, so density and price respond to the same demand and supply shifts simultaneously; the paper's Hausman tests (statistical tests for whether a regressor can be treated as exogenous) rejected the absence of simultaneity between housing density and housing prices, yet the estimation proceeded with density as an exogenous regressor. Related complications established later include land-market anticipation of future boundary changes (Ball et al. 2014 detect them for Melbourne's UGB) and general-equilibrium feedbacks: shifting a boundary reallocates residents, commuting patterns, road congestion, and agglomeration economies (the productivity gains from workers and firms being near one another) across the whole metropolitan area.

Theoretical work has long been available without empirical calibration: Ding, Knaap, and Hopkins (1999) analyze growth management with urban growth boundaries in a dynamic urban model and was already cited by Jun (2006); Anas and Rhee (2007) characterize when boundaries are second-best policies relative to congestion tolls; Tan and Xu (2023) build a theoretical model of the joint effect of a UGB and subway development on urban land price. On the empirical side, contemporary work measured land-use regulation's effects on housing and land prices (Ihlanfeldt 2007) and UGB impacts on one market at a time (Mathur 2014, 2019; Ball et al. 2014; Jeon 2019), but not as a simultaneous land-housing system calibrated for boundary-expansion counterfactuals.

The methodological landscape changed with quantitative spatial general-equilibrium models, computational models in which households choose residential and workplace locations, firms and residents compete for floor space, and prices and densities clear simultaneously across all locations. Koster (2023) provides reduced-form estimates and estimates such a model of English greenbelts, embedding supply restrictions, amenity decay with distance, road congestion, and agglomeration, and evaluating counterfactual boundary changes including a 10 percent reduction in greenbelt land (shifting inner boundaries about 800 meters outward) and complete removal. This demonstrates how the interactions the Portland debate could not handle can be jointly estimated, but it is set in England, evaluates uniform counterfactual shifts rather than expansion decision rules, and does not validate predictions against realized boundary expansions. The research need stated by Jun (2006) is therefore only partially served: no study has applied such a jointly determined model to an operational UGB and used it to derive empirically tested predictions of when, and by how much, the boundary should be expanded.

Problem Statement

Develop and empirically implement a model of a metropolitan area subject to an urban growth boundary in which land prices, housing density, and housing prices are jointly and simultaneously determined, and use this model to derive and empirically test predictions indicating under what conditions, and by how much, the boundary ought to be expanded. The overarching objective is a validated predictive basis for boundary-expansion decisions, in which the joint model underpins the expansion criteria and the tested expansion predictions validate the model's answer to the policy question. The research goal is to (i) specify and estimate the simultaneous land-housing system for a real urban growth boundary metropolitan area, with an identification strategy that confronts the simultaneity the source study documented rather than assuming it away; (ii) demonstrate predictive validity for land and housing market outcomes, not only within-sample fit; and (iii) generate condition-dependent predictions of expansion timing and magnitude that are empirically tested against realized boundary-expansion episodes, with the associated land-price, housing-density, and housing-price outcomes as an additional check. The problem retains the generality of the source question: it concerns urban growth boundaries as such (not only Portland's) and does not prescribe a particular functional form, estimator, or model class. It likewise does not fix the evaluative criterion behind 'ought': stating and justifying the criterion by which a proposed expansion is judged warranted is itself part of the research output.

References

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