Location Premium Research Articles

Social justice in spatial change:transition from autonomous rural development to integrated urbanization in China

Village-based bottom-up industrialization and urbanization in high-density dynamic regions give rise to prevalent rural sprawl in a form of considerable fragmentation in land uses, which begs for planning intervention. A paradigm of compact city is aiming to cure the rural sprawl. Nevertheless, spatial restructuring entails reconfiguration of villages' landed interests, which beckons spatial justice discourses. Market-driven rural non-agricultural development without fair allocation of land development rights between villages has given rise to market bias due to the location premium in the land market. Plan-led spatial change without corrective mediation between villages constitutes planning bias. Transition from rural sprawl to urban compactness suggests institutional change in governance jurisdiction from rural villages to urban districts. Inequality between villages caused by market and planning biases has to be dealt with so as to create initial equality based on socio-spatial justice for villages as rural entities to be incorporated into an integrated city. This paper builds up the narratives of social injustice inflicted by spatial change. Gentrification and informal in situ urbanization are two phenomenal spatial changes that do injustice to certain social classes and groups. Implementation of new planning paradigm entailing spatial change could also incur injustice to some of the stakeholders, which beckons institutional intervention to address spatial injustice.

Marginal and average prices of land lots should not be equal: A critique of Glaeser and Gyourko’s method for identifying residential price effects of town planning regulations

Glaeser and Gyourko’s method of measuring the gap between marginal and average land prices of housing lots has become a popular way of demonstrating the degree to which planning controls, or ‘regulatory taxes’, increase residential land prices. This has led policy-makers across the globe to focus on town planning as a critical determinant of rising home prices. We show, however, that Glaeser and Gyourko’s method shows no such thing. Instead, the price gap is a product of the location premium of land, diminishing returns to buyers of residential land size, and historical city development patterns. Numerous shortcomings are identified in their theoretical model, including that (a) they ignore that development happens over time; (b) their ‘regulatory tax’ is simply the location value of land; (c) they reason inconsistently about the source of land prices, arguing that land at the margins is scarce but locations for whole housing lots are not; and (d) there are no optimal lot sizes nor subdivision incentives in their model. Standard price-taking models of residential land markets that recognize that locations are scarce contain none of these limitations and provide a better interpretation of land price patterns. Empirically, we show that Glaeser and Gyourko’s method finds a high ‘regulatory tax’ even in the absence of regulatory constraints using both simulated suburb development scenarios and historical land sales data from colonial Australia and ancient Mesopotamia. In short, there is no information regarding the effect of planning controls on the supply of new dwellings in a comparison of marginal and average land prices, and this method should not be relied upon to inform planning and housing policy decisions.

Learning from man or machine: Spatial fixed effects in urban econometrics

Econometric models with spatial fixed effects (FE) require some kind of spatial aggregation. This aggregation may be based on postcode, school district, county or some other spatial subdivision. Common sense would suggest that the less aggregated, the better inasmuch as aggregation over larger areas tends to gloss over systematic spatial variation. On the other hand, low spatial aggregation results in thin data sets and potentially noisy spatial fixed effects. We show, however, how this trade-off can be substantially lessened if we allow for more flexible aggregations. The key insight is that if we aggregate over areas with similar location premiums, we obtain robust location premiums without glossing over too much of the spatial variation. We use machine learning in the form of a genetic algorithm to identify areas with similar location premiums. The best aggregations found by the genetic algorithm outperform a conventional FE by postcode, even with an order of magnitude fewer spatial controls. This opens the door for spatially sparse FEs, if economy in the number of variables is important. The major takeaway, however, is that the genetic algorithm can find spatial aggregations that are both refined and robust, and thus significantly, lessen the trade-off between robust and refined location premium estimates.

Efficient Wine Pricing Using Stochastic Frontier Models

AbstractWe specify a two-tier stochastic frontier model to estimate a price equation for U.S. Rieslings and determine overpricing and underpricing of specific wines. The data is for 2000–2016. Using tasting score and tasting score squared as sole independent variables, we found evidence of overpricing and underpricing of wines. When additional location variables were entered, empirical estimates for this two-tier model were infeasible, suggesting that both underpricing and overpricing did not occur simultaneously in this market. Separate one-sided stochastic frontier models were then specified and estimated to test for either under or overpricing in this market. Results showed that overpricing exists and not underpricing, but the extent of overpricing is minor, suggesting that wineries do an efficient job pricing their wines, given tasting scores, conditional on regional location premiums or discounts. We also investigated the effect of scale on pricing for a smaller set of wineries. (JEL Classifications: C4, D4, Q1)

Marginal and Average Prices of Land Lots Should Not Be Equal: A Critique of Glaeser and Gyourko's Method for Identifying Residential Price Effects of Town Planning Regulations

Glaeser and Gyourko’s (2003) (henceforth G&G’s) method of measuring the gap between marginal and average land prices of housing lots has become a popular way of demonstrating the degree to which planning controls, or “regulatory taxes”, increase residential land prices. This has led policy-makers across the globe to focus on town planning as a critical determinant of rising home prices. We show, however, that G&G’s method shows no such thing. Instead, even according to their own model, the price gap is a product of the location premium of land, diminishing returns to buyers of residential land size, and historical city development patterns. Additional flaws and contradictions identified in their model are (1) that they confuse total lot supply with land supply per lot, (2) that minimum lot size restrictions will increase the marginal land value compared to the average rather than decrease it, (3) that the economic incidence of taxes on land matters to the outcome whereas they claim it does not, and (4) that there are no subdivision incentives for landowners. Standard price-taking models of residential land markets contain none of these flaws and provide a better interpretation of land price patterns. Empirically, we show that G&G’s method will find a high “regulatory tax” even in the absence of regulatory constraints using both simulated data and historical land sales data from colonial Australia and ancient Mesopotamia. This exercise demonstrates that G&G’s method cannot differentiate between planning-constrained and unconstrained development patterns. In short, there is no information regarding the effect of planning controls on the supply of new dwellings in a comparison of marginal and average land prices and this method should not be relied upon to inform planning and housing policy decisions.

The impact of industrial districts on the pricing of IPOs

This paper examines the impact that industrial districts–a concentration of industry peers in the same geographic area–have on the pricing of initial public offerings (IPOs). I provide robust evidence that firms going public in more concentrated districts are more heavily underpriced than other IPO firms. In general, the results support the notion that the competitive pressures within industrial districts raise the risk profile of IPOs and discourage voluntary disclosure of value-relevant information because of increased proprietary costs. There is also strong evidence to suggest that the increased underpricing of IPOs in industrial districts partially represents investor compensation for the location premium associated with more isolated areas.

“Waiting on the train”: The anticipatory (causal) effects of Crossrail in Ealing

This paper estimates the willingness-to-pay for anticipated journey-time savings introduced by the Crossrail intervention in the London Borough of Ealing. Given Crossrail remains under construction, we estimate how the anticipated benefit of Crossrail's announcement enters the house price determination process. Anticipated journey-time savings should enter the home-buyer's pricing equation because these benefits are speculatively internalised even before the service becomes operational. Using a experimental method that accounts for the possibility of a spatial autoregressive process in housing values, we test the hypotheses that the announcement of a new commuter rail service generated a location premium, and that house price appreciation reflected proximity to Crossrail terminals. Our evidence suggests home-buyers significantly valued proximity to planned Crossrail terminals following the post-announcement period.

A logit-based model for measuring the effects of transportation infrastructure on land value

ABSTRACTMutual interactions between transportation and land use have long been debated. Despite progress made in computational technology, the study of these interactions is not adequately developed. The most important aspect of such interactions is given by the changes in land values due to changes in transportation infrastructures. We consider the behavioural features of these interactions along with the constraints on the land and/or zoning restrictions and propose a reliable model for the first time to predict land value changes with respect to changes in transportation facilities and accessibility. The proposed model is a logit-based mathematical programming methodology where the relative price of land is predicted with respect to transportation accessibility, neighbourhood amenities, location premium, availability of land, and zoning regulations. A real-world case study is used to exhibit the applicability of the proposed methodology and demonstrate the efficacy of the algorithms and procedures.

Admissions Quotas in Metropolitan Areas and Competition between Universities in Korea

The excessive demand for universities in metropolitan areas as a result of location premiums and regulated admissions quotas diminishes the competition between universities and the incentive to enhance educational performance to attract more students. Cases in point are the lower graduate employment rates (a measure of educational performance) of universities in metropolitan areas compared to those in non-metropolitan areas despite higher quality students. Additionally, the graduate employment rates of non-metropolitan universities are influenced by educational input factors such as an increase in the percentage of courses taught by full-time faculty, while those of metropolitan universities are contingent merely on enrollees’ entrance scores. Ergo, a structure that revitalizes the competition between universities and encourages them to improve their educational services must be established in order to enhance the quality of higher education.

Local IPOs, local delistings, and the firm location premium

Abstract Borrowing a measure from ecology, we introduce a spatial dispersion index to quantify the firm traits related to firm geographic location and investigate firm exposure to local home bias and local investor risk tolerance as determinants of corporate market value. Consistent with the investor preference for local stocks, we find listed firms benefit from a location premium that increases with firm isolation and local investor wealth. IPOs and delistings are found to affect the market value of neighboring listed firms: isolated firms decrease in value when they cluster due to local IPOs while clustered firms increase in value as they become more isolated due to local delistings. Local firm clustering and risk tolerance also affect IPO underpricing. Empirical findings depict a framework where IPOs and delistings are locally jointly determined.

Commuter rail accessibility and house values: The case of the Montreal South Shore, Canada, 1992–2009

While public transportation (PT) plays a crucial role in the social and environmental dimensions, its impacts on the location rent remain poorly known. However, there is a strong connection between PT infrastructures and real estate markets since the former may generate externalities that can influence sales prices. This paper aims at estimating the actual effect of implementing a commuter train service between a major city (Montreal, Canada) and its southern periphery occurring in 2000–2003. Using a difference-in-differences (DID) estimator in the hedonic price model for single-family house sales between 1992 and 2009, the paper estimates the direct marginal price impact of a new commuter train service following changes in access to stations. Results suggest that the opening of a new commuter train service on the Montreal South Shore generates a location premium for houses located in the stations’ vicinity (as measured through walking distance and car driving time) as opposed to houses that do not experience any improvement in accessibility to the commuter train service, either in space or in time. In addition, the new service raises property tax income for involved municipalities by several million dollars a year through enhanced property values.

Premium or Discount in Hotel Room Rates? The Dual Effects of a Central Downtown Location

The hotel industry generally recognizes the advantages of a central business district location, resulting in higher demand, pricing ability, and profitability. What research has not done is to consider the negative effects of agglomeration and competition among centrally located hotels. Reasoning that hotels engage in price competition through revenue management, the authors developed a theoretical framework of bounded price competition. The authors theorize that rate-based competition would intensify among contiguous hotels, but they also propose that such rate-based competition is contingent on demand levels. When demand is strong, one would not expect rate-based competition. A test of this hypothesis using data from the downtown Chicago hotel market supported that a central location has a dual effect on hotel room rates. Hotels see higher premiums in the peak season, due to strong demand, and steeper discounts in shoulder seasons, as a result of competition with nearby hotels. The findings also suggest that existing models, which do not consider hotel spacing, may have overestimated the central location premium.

The Firm Location Premium

Borrowing a measure from ecology, we introduce a spatial dispersion index to quantify the firm traits related to firm geographic location and investigate firm exposure to local home bias and local investor risk tolerance as determinants of corporate market value. Consistent with the investor preference for local stocks, we find listed firms benefit from a location premium that increases with firm isolation and local investor wealth. IPOs and delistings are found to affect the market value of neighboring listed firms: isolated firms decrease in value when they cluster due to local IPOs while clustered firms increase in value as they become more isolated due to local delistings. Local firm clustering and risk tolerance also affect IPO underpricing. Empirical findings depict a framework where IPOs and delistings are locally jointly determined.

Room Rates of U.S. Airport Hotels: Examining the Dual Effects of Proximities

Location-based premiums for hotels have been observed in various segments, such as downtown and resort hotels. However, the location effect of airport hotels has not yet been studied, despite the longstanding history and significance of this market, which is arguably the most location-sensitive segment. It has also been found that former models for hotel location based on firms’ bid-rent functions were not directly applicable to airport hotels, even when the monocentricity assumption holds. Thus, the current study applied the household bid-rent function to provide a theoretical justification for premiums on airport proximity and estimated their effects on room rates using the hedonic pricing method. Results indicated that location premiums for airport hotels are simultaneously affected by their proximity to the central business district as well as the airport. Implications for the hotel industry and suggestions for future research are discussed.

Flexible Modeling Strategies for Assessing the Influence of Transportation on Accessibility

Despite advances in statistical modeling and estimation, policy modeling and infrastructure impact assessments in the transportation area are almost always conducted by assuming linearity. The focus is on the assessment of location premiums associated with accessibility variables that are key policy variables, estimated via hedonic methods. These variables are invaluable for assessing effects of transportation projects on nearby land uses. Most hedonic studies hypothesize a parametric functional relation between accessibility and the dependent variable in estimating premiums. Unfortunately, common parametric approaches cannot control for functional form misspecification of individual variables. That line of research is extended to investigate and explore these issues with a flexible modeling strategy using a cross-section sample of housing sales. The analysis indicates the presence of significant nonlinearities that have implications for impact assessment approaches and for the assessment of accessibility influences on price premiums. The methods suggested can be extended to other areas as well, areas in which theory does not provide any a priori bounds on behavior of variables included in an analysis.

Using a Geographic Information System to Track Changes in Spatially Segregated Location Premiums: Alternative Method for Assessing Residential Land Use Impact of Transportation Projects

The corridor-level impact of a recent major urban highway reconstruction project on residential property values is investigated. The housing market encompassing the North Central Expressway corridor in Dallas, Texas, is examined. Hedonic property price models are estimated for each specific phase of the reconstruction project between 1979 and 1997. Five phases are considered. Geographic information system (GIS) tools, like buffering and geocoding, enable spatial segmentation of property sales and improved model specification facilitated by the creation of different types of proximity variables. An econometric refinement is made to traditional hedonic models that, in conjunction with GIS, allows an examination of spatiotemporal fluctuations in location premiums and property-value trends. The results show that some parts are negatively affected and others are positively affected. This finding is in agreement with the findings of earlier studies. However, this study adds to this conclusion in many ways. The planning process itself mildly affected premiums for those further away. The short-term reconstruction effects are limited to those properties in the immediate vicinity. The results show that the losses in terms of sales discounts during initial phases of construction are made up in the latter phases for those in the immediate vicinity and rebounding property values. The analysis concludes by suggesting that the cost of increased data requirements is outweighed by the informational advantages of the adopted procedure.