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Abstract

This study uses property-level repeat sales transaction data to test for the presence of a premium for single-family homes within half a mile of stations on the METRO Blue Line in Minneapolis, Minnesota. Using a difference-in-differences approach, we find that the premium for station proximity varies substantially depending on control group and period definitions for “after” light rail. Using homes in the rest of Minneapolis as controls yields growing positive premiums from proximity to light rail stations, while using homes in neighborhoods similar to those near stations yield smaller premiums that fade to zero over time.

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... One aspect of these impacts is the presence or absence of a premium that individuals pay for houses in proximity to LRT stations. Although numerous studies have been published on the relationship between rail infrastructure and home values (Debrezion et al., 2007;Mohammad et al., 2013), only a few have used quasi-experimental approaches that can reliably infer the causal impacts of LRT systems on nearby properties (Billings, 2011;Pilgram and West, 2018;Ransom, 2018;Wagner et al., 2017;Yen et al., 2018). Earlier studies on the subject estimated price gradients with the use of hedonic modeling to demonstrate how prices change with increasing distance to a rail station (Cervero and Duncan, 2002;Hess and Almeida, 2007;Yan et al., 2012;Atkinson-Palombo, 2010). ...
... But lately, researchers have acknowledged the limitations of these approaches and have resorted instead to quasi-experimental methods to explore the hypothesis of capitalization of accessibility benefits into property values for LRT systems. Specifically, recent studies have used difference-in-differences (DID) models to estimate such impacts (Pilgram and West, 2018;Wagner et al., 2017;Yen et al., 2018). DID models account for the effect of unobserved factors, such as national and regional economic forces, over time through the use of a comparison area (''control group'') that has similar characteristics to the area potentially affected by the LRT system (''treated group'') (Rubin, 1974). ...
... Our research takes a comprehensive approach to the analysis of the spatiotemporal impacts of transit systems through the use of advanced DID specifications that enable us to (i) capture the temporal distribution of the transit impacts over an extended period of time, spanning from project announcement through long-term operation, (ii) quantify the spatial distribution of effects at varying distances from station locations, and (iii) assess whether the distribution of effects in space varies over time, from the original announcement, to construction and then operation milestones of an LRT project. Past research that studied temporal effects have typically focused on a subset of these project milestones (Billings, 2011;Pilgram and West, 2018;Wagner et al., 2017), and a detailed analysis of temporal variations is still missing. In addition, our study provides a more complete view of the long-run effects of LRT systems on properties, a topic that has not been thoroughly explored (the majority of past analyses are restricted to approximately five years post beginning of operation). ...
Article
As the successful design and implementation of alternative mechanisms for funding transit infrastructure, such as value-capture schemes, are becoming more critical, identifying the timing, duration, and spatial extent of the capitalization of accessibility benefits for nearby communities is becoming more and more important. This research makes a significant contribution to the analysis of the spatiotemporal impacts of transit systems by quantifying variations in the spatial distribution of causal effects from project announcement to long-run operation. The study develops a quasi-experimental framework based on advanced difference-in-differences specifications that enable us to capture the distribution of average treatment effects in space and time. The methodology is applied to the light rail system in Charlotte, NC, which includes an original line and its extension. A dataset comprised of the single-family house sales from the last thirty years is compiled for the study area, which contains neighborhoods in the vicinity of the light rail and two comparison areas. The estimated impacts demonstrate significant heterogeneity, on multiple facets. We find that although the shape of the spatial distribution of effects changes over time experiencing increasing curvature, the results consistently indicate highest positive impacts for properties located within 0.25 and 0.5 miles of a transit station. Differential effects are also identified between the original light rail line and its extension, such as lack of anticipation effects for the line extension. Although these results are specific to a single locale, the methods demonstrated through this study can be applied to other areas and transit systems of similar scale.
... The results of hedonic analyses (see, for example, Armstrong and Rodríguez 2006;Brandt and Maennig 2011;Strand and Vågnes 2001;Li et al. 2019) are well documented in a number of review and meta-analysis publications, although the focus has primarily been on the impacts of public transit investments (Debrezion et al. 2007;Vessali 1996;Mohammad et al. 2013;Bateman et al. 2001). Recognizing the limited ability of hedonic pricing models to control for the effect of concurrent economic forces and other contributing factors, an increasing number of researchers have employed quasi-experimental approaches to quantify the causal impacts of transportation investments (Gibbons and Machin 2005;Agostini and Palmucci 2008;Dubé et al. 2018;Diao et al. 2017;Mohammad et al. 2017;Bardaka et al. 2018Bardaka et al. , 2019Maciel and Biderman 2013;Pilgram and West 2018;Wagner et al. 2017;Yen et al. 2018;Levkovich et al. 2016). Repeat sales methods have been used by some researchers as well (Devaux et al. 2017;Dubé et al. 2013Dubé et al. , 2014Sun et al. 2015). ...
... Our study uses Euclidean (straight-line) distance as a measure of proximity from a beltway interchange to define the treated group. Although there is a range of definitions of treated groups in the broader literature, previous studies on transportation-induced impacts that have adopted DID techniques have mainly used Euclidean distance from an access point (transit station or highway interchange) to select treated units (Agostini and Palmucci 2008;Bardaka et al. 2019;Dubé et al. 2018;Gibbons and Machin 2005;Maciel and Biderman 2013;Mohammad et al. 2017;Pilgram and West 2018;Wagner et al. 2017;Yen et al. 2018). ...
... We use two control group definitions in an effort to create the most suitable proxy of our treated areas. Our work is in alignment with the small group of DID studies which have tested more than one type of control group definitions (Maciel and Biderman 2013;Pilgram and West 2018). The first control group constitutes of the parcels within a distance from a highway access point. ...
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Article
This study investigates the temporal and spatial distribution of the causal impacts of major beltway facilities on housing prices using quasi-experimental econometric approaches. Difference-in-differences methods are employed to quantify construction and anticipation effects and explore how impacts evolve and differ over space and time. The study particularly focuses on spatial variations and seeks to identify potentially heterogeneous effects in the inner and outer sides of a beltway. Two methods for control group selection are adopted to test the robustness of the estimated treatment effects. Using data from three major beltway facilities in the US, we find that impacts are nonlinear with distance from an interchange, with the maximum effect found between a 0.75 and 1.5-mile distance. In two of the studied beltway projects, properties outside the beltway experienced significant positive effects, while effects on properties inside the beltway were negative within the first 0.25 miles from an interchange and insignificant thereafter. We also find that effects during construction differ by project, while after the end of construction, prices typically increase and fully materialize after 6–8 years. This research makes a significant contribution to the very limited literature on the causal identification of highway impacts on surrounding properties as well as the small group of studies that have investigated the spatial extent and distribution of transportation-induced effects. The results can be used to inform stakeholders and planning decisions of future highway facilities.
... Many of the earlier studies on the transit-home value connection were cross-sectional in nature which prohibited an in-depth examination onto when capitalization effects may begin and end. A more recent study by Pilgram and West (2018) for the case of a new transit line in Minneapolis, MN used repeat sales data found for single family homes, price premiums were present only in the years immediately following the opening of the line and dissipated to zero seven years after service began. The authors controlled for station heterogeneity and tested the robustness of their results on several sets of control groups -limitations present in earlier studies. ...
... Two studies found that incomes and housing values or rents increased in new transit neighborhoods (Bardaka, Delgado, & Florax, 2018;Pollack, Bluestone, & Billingham, 2010), however, both of these analyses compared transit neighborhoods to the city or metro-area as a whole. Other research has pointed out that city-wide comparisons tend to inflate price capitalization impacts (Pilgram & West, 2018). The use of a set of control neighborhoods that closely match the 'treatment' or transit neighborhoods is the more desirable method. ...
... As reported in the review by Padeiro et al. (2019), many of the neighborhood-scale analyses fail to utilize a proper set of control neighborhoods to test whether trends differ from other similar neighborhoods in a metropolitan area. As the price capitalization literature has increasingly shown, this can have a significant impact on results and needs to become the norm in the neighborhood studies (Pilgram & West, 2018). Likewise, controlling for heterogeneity and isolating transit from other confounding factors remains a challenge. ...
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Chapter
Investments in new transportation infrastructure hold the potential to transform the urban socioeconomic landscape by reshaping accessibility and by encouraging new developments around these investments. This chapter outlines the theoretical arguments for why and how transport, specifically rail transit, is expected to impact the socioeconomic composition of neighborhoods and reviews the relevant empirical literature on the subject. Neighborhood socioeconomic change, including gentrification, can be viewed as the product of shifts in residential sorting of residents reacting to the placement of a new (transit) amenity which may place increased demand for living in a particular area. This demand may place an upward pressure on nearby housing values and rents, affecting the socioeconomic composition of those willing and able to afford these price premiums, thus spurring or accelerating gentrification. Rising land values may also lead to the disproportionate exit of lower-income residents unable to keep up with elevated rents or property taxes. To date, the empirical evidence on the link between transport investments and gentrification has mixed findings, very often underscoring the importance of local context in directing a neighborhood's path. Research has overwhelmingly centered on aggregate neighborhood changes, but several studies have recently emerged that center on individual movements that give rise to these neighborhood-scale outcomes.
... Many of the earlier studies on the transit-home value connection were cross-sectional in nature which prohibited an in-depth examination onto when capitalization effects may begin and end. A more recent study by Pilgram and West (2018) for the case of a new transit line in Minneapolis, MN used repeat sales data found for single family homes, price premiums were present only in the years immediately following the opening of the line and dissipated to zero seven years after service began. The authors controlled for station heterogeneity and tested the robustness of their results on several sets of control groups -limitations present in earlier studies. ...
... Two studies found that incomes and housing values or rents increased in new transit neighborhoods (Bardaka, Delgado, & Florax, 2018;Pollack, Bluestone, & Billingham, 2010), however, both of these analyses compared transit neighborhoods to the city or metro-area as a whole. Other research has pointed out that city-wide comparisons tend to inflate price capitalization impacts (Pilgram & West, 2018). The use of a set of control neighborhoods that closely match the 'treatment' or transit neighborhoods is the more desirable method. ...
... As reported in the review by Padeiro et al. (2019), many of the neighborhood-scale analyses fail to utilize a proper set of control neighborhoods to test whether trends differ from other similar neighborhoods in a metropolitan area. As the price capitalization literature has increasingly shown, this can have a significant impact on results and needs to become the norm in the neighborhood studies (Pilgram & West, 2018). Likewise, controlling for heterogeneity and isolating transit from other confounding factors remains a challenge. ...
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Preprint
Investments in new transportation infrastructure hold the potential to transform the urban socioeconomic landscape by reshaping accessibility and by encouraging new developments around these investments. This chapter outlines the theoretical arguments for why and how transport, specifically rail transit, is expected to impact the socioeconomic composition of neighborhoods and reviews the relevant empirical literature on the subject. Neighborhood socioeconomic change, including gentrification, can be viewed as the product of shifts in residential sorting of residents reacting to the placement of a new (transit) amenity which may place increased demand for living in a particular area. This demand may place an upward pressure on nearby housing values and rents, affecting the socioeconomic composition of those willing and able to afford these price premiums, thus spurring or accelerating gentrification. Rising land values may also lead to the disproportionate exit of lower-income residents unable to keep up with elevated rents or property taxes. To date, the empirical evidence on the link between transport investments and gentrification has mixed findings, very often underscoring the importance of local context in directing a neighborhood’s path. Research has overwhelmingly centered on aggregate neighborhood changes, but several studies have recently emerged that center on individual movements that give rise to these neighborhood-scale outcomes.
... If the increases in residential costs outrun the benefits of TOD, such as an increase in incomes due to the revitalization and/or decrease in transportation costs, transit-induced gentrification can result. There have been arguments that transit-induced gentrification (TIG) can accompany and/or trigger displacement of minorities and lower-income families [8][9][10]. Even if there turns out to be no displacement with TIG, TOD can disadvantage existing residents due to affordability problems [6,11,12]. ...
... In theory, gentrification can trigger population displacement because improved accessibility, walkability, and the environment are capitalized into land values, which thus increases housing prices and rent [5][6][7][8]. Consequently, lower-income households may relocate because housing has become unaffordable, and even if they stay, they may be excluded from the benefits of TOD because increases in residential costs cancel out the benefits of accessibility, i.e., transit-induced gentrification [8][9][10]. ...
... This study specifically splits gentrification into two categories, although most studies consider gentrification as a single concept. Here, the term "residential gentrification" is used to refer to the phenomena on that the capitalization of better accessibilities and environments into land and housing values increases residential costs [8][9][10]. "Commercial gentrification" refers to the fact that local and inexpensive commerce is often displaced as a result of rising rents. ...
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Article
Transit-oriented development (TOD) is often considered a solution for automobile dependency in the pursuit of sustainability. Although TOD has shown various benefits as sustainable development and smart growth, there are potential downsides, such as transit-induced gentrification (TIG). Even if there were no displacement issues with TIG, existing residents could be disadvantaged by a TOD due to affordability problems. This study focuses on these potential affordability issues and aims to evaluate the effects of TOD using residents’ discretionary income (DI) as an indicator of affordability. The light rail transit-oriented development (LRTOD) in Phoenix, AZ, is selected because of the timing of the introduction of development and the simplicity of the light rail transit line. In order to counteract problems induced by a non-random location of TODS, propensity score matching is used. The results indicate that LRTOD can give benefit to all TOD residents. Moreover, the effects of LRTOD on discretionary income of various types of households are not statistically significantly different. We have identified the different magnitudes of the effects of TOD between propensity score matching (PSM)-controlled and uncontrolled models. These indicate the existence of the selection bias of TOD implementation, justifying the adoption of the PSM method.
... Based on this thought, they show that the magnitude of property value effects after opening tends to regress to a conservative status. Pilgram and West (2018) and Diao, Leonard, and Sing (2017) apply similar DID model and also demonstrate that significant price effects diminish over time. This temporal variation mentioned above can explain some insignificant generalized effects (Gatzlaff & Smith, 1993;Lawhon, Nilsson, Silver, Ernstson, & Lwasa, 2018). ...
... Furthermore, a potential buyer that purchases different kinds of properties may have varying preference or requirements for public goods (Pilgram & West, 2018). The housing market may be segmented into several sub-markets and property prices are not affected evenly by a subway (Devaux, Dub� e, & Apparicio, 2017;Gatzlaff & Smith, 1993;Lawhon et al., 2018). ...
... In summary, previous studies identify price effects of subway construction with unobserved factors controlled. Some of them address price adjustment (Agostini & Palmucci, 2010;Diao et al., 2017) and some others show the differential effects (Pilgram & West, 2018). However, an estimation of this differential effects over time and across sub-markets simultaneously is still needed to explain the mixed results and investigate the heterogeneous preference. ...
Article
This study investigates the property price premium brought by the opening of a subway to illustrate temporal dynamics and heterogeneous mechanism of property value effects. The estimation of changes caused by subways on property value can aid in assessing the benefits of public transit investments well. On the basis of residential property transaction records in Hangzhou, China in 2009–2013, hedonic models in a difference-in-differences framework are applied to handle certain endogeneity problems of estimation by eliminating unobserved factors. Results show that treatment groups located within 1000 m of a subway have an average price increase of 444 yuan per m2 from the opening of Line1. High-cost houses constantly gain significant increment and their price premium regress during the research period. However, for their counterparts in low-cost communities, the insignificant price effects are negative for a short time, and then become positive. The generalized results are robust when subway radius is adjusted.
... When the price effects from reconstruction is eliminated in Model 3 and 4, the changing pattern of the multi-period price effects is consistent with our theory that without an advanced project announcement and reconstruction planning, the price effects are much smaller than that in Model 1 and 2. There is some discrepancy upon the anticipatory effects in model 3, 4 and Model 3,4 in Table 7. Though this discrepancy does not mean violation of our theory and is acceptable when different control group is used (Pilgram and West, 2018), a simple explanation is provided. When buffer radius is 500 ms, the anticipatory effect is positive. ...
... The slight decline shows that public investment tends to activate the real estate market, but when the information is gradually released, the excessive premium will not last for long. This regression coincides with results of previous studies showing a fading price premium caused by public investments (Pilgram and West, 2018;Tian et al., 2020). ...
Article
The removal and reconstruction of urban villages can improve the residential environment in the vicinity and promote the willingness of buyers to pay. A detailed investigation of the price effects on nearby housing generated by urban village redevelopment helps to capture the added value of public investment. Previous studies often ignore the temporal variation of the price effects. Furthermore, they confuse the price effects from the removal of dilapidated housing and the construction of new buildings. Based on the listing prices in 2017–2018 and transaction data in 2015 of secondhand residential housing in Hangzhou, China, this paper built a multi-period difference-in-differences model to examine the multi-period price effects from urban village redevelopment on nearby housing and to isolate the removal effects of old buildings and the amenity effects of reconstruction. The results show that (1) An anticipatory effect of up to 13% occurs before the urban village redevelopment; removal and reconstruction will bring a total premium of 20% to nearby housing prices; and the total price effects gradually increase in time and slightly fall back after four years. (2) Less than 15% of the added value comes from the removal of dilapidated housing in an urban village, while more than 85% comes from the reconstruction of new buildings. (3) The price effects of large-scale urban village redevelopment are much more obvious.
... vided by Sarah West and Clemens Pilgram, who study the housing price premiums of the Minneapolis Blue Line light rail (Pilgram and West 2018). Neighborhood characteristics are drawn from the 1990 and 2000 U.S. Census and complemented by the estimates of the Environmental Systems Research Institute (ESRI) available through the proprietary ESRI 2011/2016 Updated Demographic Data dataset. ...
... Given a sample period from 1990 through 2014, missing values are linearly interpolated. 23 For further details on the exact matching between block characteristics and parcel data, we refer the reader to Pilgram and West (2018). ...
... First, public goods, such as education, need to be allocated in the housing market, as residents often decide the residential location in accordance with their income, supply, and policy constraints. The relationship between schooling and housing prices can vary (Cheshire & Sheppard, 2004) and, therefore, the pattern of capitalization effects can help explain the different public good allocation mechanisms among various groups, regions, and times (Kirstine, 2014;Pilgram & West, 2018;Turnbull, Zahirovic-Herbert, & Zheng, 2018). Second, the purpose of public good allocations is to effectively meet the varying needs of residents through policy implementation. ...
... where HP represents the transaction price of each set of second-hand houses; Edu represents the education quality of the public primary school designated to the second-hand house; coefficient α 1 measures the capitalization effects; S i is the structural features of the second-hand house i, including Floor (Christopher, 2019), Age (Mulligan, Franklin, & Esparza, 2002); L j is the location features of the community j in which the second-hand house i is located, including the distance to CBD (D_CBD) (Alonso, 1964) and the transportation accessibility (Q_transport) (Pilgram & West, 2018); and N j is the neighborhood features of the second-hand house, including Q_nature, Q_community, and Q_sports (Wen et al., 2017). η is a term for unobserved features and ε i is the error term. ...
Article
A quality promotion of neighborhood primary schools no doubt elevates nearby housing price. But which houses benefit from the public policy is important to improve educational equity. Accurate identification of such capitalization effects will help policymakers optimize the allocation of scarce public goods. Previous studies on this issue have been biased due to endogeneity and overlooking the impacts of facility quality change. Based on the Hangzhou's school district adjustment in 2012, the current work contributes to housing price effects of policies and education quality changes, rather than a static educational facility. The difference-in-differences model with quantile regression is constructed to obtain a more precise and detailed estimation among the different sub-markets. Results show that the average price effect estimated by the difference-in-differences is up to nearly 800 yuan/m², higher than cross-sectional estimation. Only housing with better schools after reassignment witness a price premium. Low-priced and small houses earn more than 1000 yuan/m², whereas high-priced and large houses are not significantly affected. The results demonstrate that future policies should ensure the rights of low-income groups to attend high quality primary school and guard against the gentrification of low-priced houses.
... Part of these studies has evaluated the impacts of newly constructed or improved bus rapid transit on the property values (Cervero and Kang 2011;Deng et al. 2016;Mulley and Tsai 2016;Rodriguez et al. 2016;Shen et al. 2018). Similarly, a substantial number of researchers also explored the impacts of light rail (Camins-Esakov and Vandegrift 2018;Dubé et al. 2013;Dziauddin et al. 2015;Mulley et al. 2018;Papon et al. 2015;Pilgram and West 2018;Wagner et al. 2017;Yen et al. 2018) on property values. Table 1 also indicates that many studies have estimated the influence of metro rail (Forouhar and Hasankhani 2018;Li 2018;Mohammad et al. 2017;Sharma and Newman 2018;Zhong and Li 2016) on property values. ...
... Every one-unit increase of PM2.5 is associated with about 29 Yuan/m 2 reduction in housing prices in 282 Chinese cities (Zou 2019). However, some other studies have indicated no evidence of the influence of transportation infrastructure on property value (Camins-Esakov and Vandegrift 2018;Pilgram and West 2018). Thus, these inconclusive results warrant further investigation. ...
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Article
Transportation interventions influence land use patterns of the city and transport activities of the people. For example, construction and improvement of transportation infrastructure (e.g., road, rail, road widening) improve the accessibility for the people to transportation facilities and thereby influence surrounding residential property values. Many studies have investigated the impacts of transportation infrastructure on property values using a hedonic price model (HPM). However, there is inadequate evidence of the relationship between transport infrastructure and property values in the developing context, such as in Khulna Metropolitan City, Bangladesh. Thus, this study has empirically investigated the impact of accessibility to transport infrastructure on residential housing rent using the HPM approach. For performing the analysis, data (e.g., property value, structural attributes, locational attributes, transportation, land use characteristics) were collected from a household-based questionnaire survey by Khulna Development Authority (KDA), Khulna City Corporation (KCC), and Bangladesh Bureau of Statistics (BBS). A linear regression model (LRM), semilog regression model (SLR), and stepwise regression model were used to determine the factors that affect housing rent. The results indicate that structural attributes (e.g., floor space, rooms) are the prime factors that influence monthly housing rent. One unit increase in floor space, drawing rooms, and bathrooms are associated with a 32.4%, 15.8%, and 11.4% increase in housing rent, respectively. Similarly, distance to the central business district (CBD) and major roads significantly affect housing rent. A one-unit increase in the distance to CBD and major roads is associated with a 17.3% and 13.7% reduction in housing rent. This study described that the exclusion of transportation attributes reduces model performance by 3.1%. Thus, transportation attributes have a significant influence on property value.
... In developed countries, Mayer and Trevien (2017) analyse the opening and progressive extension of a new railroad facility in the Paris metropolitan region to measure the impact on firm location, employment, and population growth. Pilgram and West (2018) use a DiD approach to measure the premium over residential property values due to the proximity to a light rail station in Minnesota. ...
... However, in general, studies find it easier to observe a direct and immediate impact over market variables (e.g., land prices and property values) than over socio-economic variables such as population or business activitieswhich require more time and must be accompanied by complementary political, economic and social measures (Fariña Tojo et al., 2000). Thus, Pilgram and West (2018) observe that there is a premium for residential property values due to the proximity to a light rail station, but the premium varies depending how the control group is defined. Firms are also frequently benefited from improved connections. ...
Article
The natural experiment provided by the opening of a section that completed the A8 motorway in Mariña de Lugo, a rural area in Galicia (Spain), offers an opportunity to identify whether spread or backwash effects in economic activity are observed. The new section directly affects only a small strip of the territory, ‐ where the transition from the inland rural areas to the more dynamic coastal area takes place. This allows us to test a separate dual inner‐coastal socio‐economic performance after the opening of the new road – an analysis that has rarely been performed for rural areas in developed countries. We study the impact over population growth, employment and business financial results, using the differences‐in‐differences approach. The results we obtain are consistent with the spread hypothesis for the nearest municipality to the new road section, while the spread effects did not disseminate to the neighbouring municipalities. These global results hide a different performance at the sector level, positive for transport and manufacturing companies, and negative for retail firms and hospitality.
... Sumber: Pilgram & West, 2018 Kecenderungan yang sama juga terjadi untuk dampak fasilitas transportasi berbasis LRT dengan nilai rumah tinggal. Hal tersebut dilakukan dengan membandingkan jarak rumah terhadap rata-rata nilai rumah. ...
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Article
Dampak dari masifnya pertumbuhan ekonomi Jakarta dan daerah sekitarnya mengakibatkan banyak orang tertarik untuk melakukan urbanisasi dengan motif ekonomi, baik investasi, ataupun pencarian pekerjaan yang mengakibatkan terjadinya aglomerasi perkotaan secara signifikan. Jabodetabek sebagai pusat bisnis dan pusat pemerintahan telah mengalami peningkatan populasi sebesar 1,3 kali selama periode 2000 - 2010 dengan rata-rata pertumbuhan penduduk sebesar 2,8% yang menyentuh total populasi sebesar 31 juta orang. Tren tersebut mengakitbatkan beberapa masalah serius, antara lain adalah backlog perumahan, urban sprawl, dan kemacetan tranportasi.
... Given that the concept of economic development is quite broad, most studies have focused on the changes in property values by public transportation in urban areas. For railways, Zhong and Li [23] investigated the effect of proximity to railway stations on property values in Los Angeles, while Pilgram and West [24] examined the effect of light rail systems on property values in Minneapolis in the USA. In other countries, Gallo [25] showed the relationship between the frequency of metro lines in Naples, Italy to real estate values, and Li [26] checked the influence of metro accessibility on property values in Xi'an, China. ...
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Article
Previous studies regarding transportation impacts on economic development in urban areas have three major issues—the limited scope of analysis mostly with the change of property values, the exclusion of smart transportation systems as features despite their potential for urban areas, and stereotyped approaches with limited types of variables. To surmount such limitations, this research adopted the concept of Big Data with machine learning techniques. As such, a total of 67 features from main categories, including the change of business, geographical boundary, socio-economic, land value, transportation, smart transportation, sales, and floating population were analyzed with XGBoost and SHAP algorithms. Given that the rise and fall of business is a major consideration for economic development in urban areas, the change in the total number of sales was selected as a target value. As a result, sales-related features showed the largest contribution to the rise of business, among others. It was also noted that features related to smart transportation systems obviously affected the success of business, even more than traditional ones from transportation. It is thus expected that the findings from this research will provide insights for decision-makers and researchers to make customized policies for boosting economic development in urban areas that are a major part of the urban economy to achieve sustainability.
... Within local conditions, the HPM was the basic tool for determining, e.g., the nature of the impact of selected factors that are related to noise generated by air traffic or the accessibility of urban green areas on the value of residential properties in several major Polish cities, such as Warsaw [56,57], Krakow [58,59], or Poznań [60,61]. On the other hand, in terms of advantages (transport accessibility) or disadvantages (emitted noise) resulting from the accessibility of the public transport infrastructure on the value of residential properties, the analyses were conducted mainly in the United States [62][63][64][65], the southern European countries [66,67], and Asia [68][69][70]. ...
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Article
This study aims to determine the magnitude and nature of the impact of public urban transport accessibility on the value of residential properties in Poznań. The study was based on 2561 residential transactions completed within the study area in 2020. The input data obtained from the Board of Geodesy and Municipal Cadastre “GEOPOZ” were analysed statistically and spatially. The main part of both the spatial and the statistical analysis was performed using the hedonic pricing method (HPM)-OLS (ordinary least squares) and WLS (weighted least squares). The use of statistical tools enabled the finding of evidence to prove that the convenient accessibility of trams is positively related to housing prices. This has also been confirmed by previous research works conducted in other parts of the world. However, the collected data did not enable the identification of statistically significant relationships between housing prices and the distance from bus stops. The study also attempts to use spatial choropleth maps to clearly illustrate the mechanisms within the local housing market.
... In other words, it is important, when conducting such an analysis, to adequately identify the treatment area, but also to restrict the spatial area to identify the control zone. The latter has already been underlined by Pilgram and West [56], who state that using a too large "control area" may bias the estimated premiums. ...
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Article
This paper aims to estimate and decompose the spatial and temporal effect of a flood event oc-curring in the city of Laval in 1998 using a hedonic pricing model (HPM) based on a differ-ence-in-differences (DID) estimator. The empirical investigation of the impact of flood as a natural disaster must take into account the fact that the negotiation process between buyers and sellers may well occur before the event. It is argued that the evaluation procedure needs to be adjusted to account for this reality because the estimation of the effects may otherwise be biased and isolate other effects. To test this hypothesis, the study focuses on transactions occurring between (1995 and 2001) and within designated floodplains to adequately isolate and decompose the impact of flood. The original database contains information on 252 single-family houses transactions. The results suggest that the estimation of the impact is time dependent, with a measured negative ef-fect appearing several months after the flood, suggesting that the impact is hard to establish right after the event since transactions, and the final sale price, could have been fixed by negotiations well before the event. The statistical methodological framework of flood research should be adapted to account for the negotiation process occurring prior to the flood event to be able to correctly isolate the impact for the after event. The flooded area also needs to be precisely identi-fied to be able to correctly estimate the flood impact on houses that have faced flood.
... Residents tend to favor heavy rail services more than light rail services. Studies in Minneapolis, Minnesota found that proximity to rail stations yields positive premiums when the researchers used homes not within a half-mile of stations as the control group [8]. However, there are also exceptions in which rail services did not yield a positive effect. ...
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Article
Public transit infrastructure may increase residential property values by improving accessibility and reducing commute expenses in urban areas. Prior studies have investigated the impacts of the proximity to public transportation on property values and obtained mixed conclusions. Many of these studies were focused on one transit mode for a single city. In this study, a hedonic pricing model is constructed to investigate the impacts of commuter rail/Bus Rapid Transit (BRT) and bus lines separately in two different areas: the Stamford area (Stamford–Darien–New Canaan) and the Hartford area (Hartford–West Hartford–East Hartford), Connecticut. Comparison of the results from Ordinary Least Square and Geographically Weighted Regression (GWR) indicates that estimation accuracy can be improved by considering local variation. Results from GWR show that impacts of proximity to bus and rail/BRT on property values vary spatially in the Hartford area. Negative impacts of bus stops are found in downtown Hartford and positive impacts in the west and east sides of Hartford. Impacts from rail/BRT are relatively minor compared with bus lines, partly due to the relatively recent launching of the BRT and Hartford rail line. In contrast, most properties in the Stamford area show appreciation towards rail service and depreciation to bus service. This study reveals the roles of different public transit systems in affecting residential property values. It also provides empirical evidence for future transit-oriented development in this region for uplifting the real estate market.
... Multiple-gauge net-2 Further research has estimated the economic effects of other types of infrastructure and often using related techniques. This includes work on roads (Michaels, 2008;Duranton and Turner, 2012;Duranton, Morrow and Turner, 2014;Garcia-López, Holl and Viladecans-Marsal, 2015;Allen and Arkolakis, 2019), light rail (Wagner, Komarek and Martin, 2017;Pilgram and West, 2018), bus rapid transit (Tsivanidis, 2019), and airports (Sheard, 2014;Blonigen and Cristea, 2015;McGraw, 2017;2020;Gibbons and Wu, 2019). Redding and Turner (2015) provide a recent review of research on the effects of railways and other types of transport infrastructure. ...
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The mainline railways in Australia were initially built in three different gauges, with ‘breaks-of-gauge’ where passengers and goods transferred between them. The lack of a uniform gauge meant higher transport costs and presumably restricted trade, but its other consequences are less obvious. This paper studies the effects of the gauge situation on regional development and the form of the railway network using difference-in-difference, propensity-score matching, and synthetic controls techniques. There is no clear evidence for railways promoting local growth and line closings appear to follow rather than cause a region’s decline. The regional breaks-of-gauge generated local growth and led to 50% higher local population and employment levels within a decade relative to otherwise similar places along railway lines. However, these growth effects were unwound in around a decade after the closing of a break-of-gauge. There is little evidence of a gauge-segmented railway network leading to different paces of regional development, as railway lines gauge-separated from the core of the network actually appear to grow faster overall. The eventual resolution of the gauge muddle appears to have left a more limited regional railway network than would have existed had the gauge been unified from the beginning.
... An effective method of estimating the potential uplift in property values would very usefully inform public planning agencies on the potential contribution that such an uplift might contribute to development and construction costs, and to private investors who might be considering a joint public-private project arrangement. A number of empirical studies have been undertaken to examine the actual and potential value uplift in TOD-impacted property prices (Zhong and Li, 2016;Wagner et al., 2017;Pilgram and West, 2018;Mohammad et al., 2013;Camins-Esakov and Vandegrift, 2018). However, key gaps in the research literature still remain. ...
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The development of new and upgraded transport infrastructure projects are driving economic benefits for business, the environment and society. Major transport projects can fundamentally reshape the very fabric of urban development. However, they are also incredibly expensive to build and can represent a significant burden on the public purse. A vexed question is how the broader benefit of improved transport infrastructure in operation might usefully be leveraged to contribute to the capital investment cost. The Transit-Oriented Development impact of new transportation infrastructure on the value of local property is gaining increasing attention as a potential source of capital contribution. This study investigates the extent of value uplift in property brought about by the announcement and construction of a major transport infrastructure development in Sydney, Australia. A Hedonic Price Model approach is used to assess data on the market valuation of nearby properties and relevant Census data over two distinct project stages: project announcement (2008–2012), and project construction (2013–2019). Findings of the case study show that the impact of rail transit on property prices is significant, but are generally negative at the announcement stage and positive at the construction stage. At the construction stage, residential prices rose an average of 0.037% for every 1% reduction in the distance to the nearest metro station. Of the three models considered for the Hedonic Price Model the Log-linear model (elastic model) has been shown to perform best in representing the relationships in this particular case.
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While urban rail transit relieves traffic pressure and improves the urban transportation network, it also has a certain impact on the prices of commercial residential properties along the line, and more and more scholars have begun to pay attention to the relationship between rail transit and real estate prices. By sorting out the relevant domestic and foreign research, the existing research results are analyzed from three aspects: research objects, research methods, and research contents, and it is found that Hedonic Price Model is most commonly adopted, and the research in the fields of spatial effect, temporal effect and sub-market effect of rail transit on real estate prices is gradually becoming a hot spot.
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Increasing access to public transportation (including metro rail) can help alleviate traffic congestion and address climate and environmental priorities. Living close to a metro line may be especially important in terms of providing improved commuting options. However, proximity to metro lines can also be associated with negative externalities, such as noise and crime, that may make living near a station less desirable. One way to assess the net value that residents place on metro rail access is to examine how proximity to metro lines is capitalized into house prices. Using a hedonic spatial difference‐in‐differences model, we analyze the impact of proximity to the stations on the Gold and Expo Lines in Los Angeles, California, on nearby house prices. Our findings suggest that the capitalization effect is heterogeneous. Some residents value living near new metro stations, while others do not. Overall, our results provide evidence that the value residents place on metro rail access varies based on their income levels and other demographics. This article is protected by copyright. All rights reserved
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We use difference‐in‐differences approaches and parcel‐level data from Minneapolis to estimate the effects of light rail on land use change using alternate definitions of treatment area. Results using circular buffers corroborate previous findings that light rail has virtually no effect on land use change in our study area. In contrast, light rail increases the likelihood of land use change along arterial streets that cross the line at station areas. To accurately model the effects of public transit projects on urban land use, one must consider how potential riders access station areas, rather than assuming accessibility improves radially around a station. This article is protected by copyright. All rights reserved
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The metro (or underground railways) has become a backbone in the transit systems of many cities. It has numerous externalities, such as ameliorating traffic congestion and enhancing nearby property prices. Previous studies extensively focused on the relationship between metro accessibility and property prices and obtained various interesting findings and enriched practical implications. However, this relationship in the era of the coronavirus disease 2019 (COVID-19) and other epidemic shocks has not been investigated. Based on a unique property transaction dataset (including tens of thousands of transactions stretching from 2018 to 2020) in Chengdu, China, this study develops a battery of hedonic pricing models and difference-indifferences models to decipher the time-varying relationship between metro accessibility and residential property prices. The results show that the implicit price of metro accessibility modestly decreases in COVID-19, which can be explained by the declining role of the metro in the pandemic. Specifically, the price elasticity of distance to the metro is −0.024 before COVID-19, but it turns to −0.018 during the pandemic. The relative price of properties within 500 m from metro stations to properties farther away (500 m − 3 km) decreases by 15.4% during the pandemic. Additionally, COVID-19 does not jeopardize property prices in the city. The plausibility and robustness of the core findings have been confirmed through alternative treatment groups, alternative model specifications, and placebo tests.
Article
This study explores differences in the effects of rail transit investment across various types of lands with different values and locations, using the development of Seoul Metro Line 9 (SML9) in Korea as a case. Seoul Metro Line 9′s proximity, neighbourhood and wider economic effects are assessed. A spatial autoregressive difference-in-difference (SAR-DID) model is developed to control for the issue of spatial autocorrelation, together with a standard difference-in-difference model and a quantile regression model. The findings of these analyses are as follows. First, office and apartment lands received the largest proximity and wider economic benefits from SML9 development in their respective category. Second, SML9′s neighbourhood effects are larger for lands that increased their business and development opportunities due to the opening of SML9, such as retail and low-rise multi-family house lands. Third, the proximity and wider economic effects of rail transit investment and its neighbourhood effect generally increase with proximity to a rail station. Finally, residential and commercial lands at low price levels received fewer benefits from the completion of SML9 than those at the upper price levels. These differences are related to the various factors presented in this paper, such as the amount of capital accumulated on the lands, the number of users of the network on the lands and the different nature of each type of residential and commercial land. Based on the improved understanding of the relationship between the effects of rail transit investment and land characteristics, a well-organised land use plan for new rail transit projects can be formulated. An important implication for policymakers is that a well-organised land use plan can not only regulate land uses in the area of rail stations, but is also one of key tools to promote successful rail transit projects in urban areas.
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Intercity air transportation has grown rapidly in recent decades and creates significant noise pollution that affects health. Previous research quantifies the losses that are capitalized into home values. Much research relies heavily on spatially restrictive noise contour plots to identify the house price discounts and determine economic damages. We break new ground by investigating whether residential noise complaints can offer insights on aircraft noise pollution and housing price impacts experienced by residents near Minneapolis-Saint-Paul International Airport outside of contour boundaries. Our findings indicate noise complaints are a reliable measure of residential noise annoyance and have a significant adverse effect on home prices extending nearly twice as far (10 km) as contours. Reevaluating economic damages based on our results indicates contour-based calculations severely underestimate aircraft-noise-pollution-induced losses incurred by homeowners and suggests $154 million of $167 million in post-abatement damages are borne by residents located outside the regulated Minneapolis contour area.
Article
Introduction Light rail transit (LRT) has become a popular intervention for addressing the social and economic complexities associated with urban growth. LRT development can exert influence on neighborhood characteristics, such as property values, employment opportunities, and service access. Many of these changes can impact the health of nearby residents by influencing their exposure to the social determinants of health (SDOH). This study maps the literature on LRT development through an SDOH lens and comments on gaps and implications for neighborhood health and transit planning. Methods The Arksey and O'Malley scoping review methodology was used to examine existing literature on neighborhood-level impacts of LRT development related to the SDOH. Peer-reviewed articles were included if they focused on an LRT project in an urban center in Canada or the United States, reported on a neighborhood-level impact related to the SDOH, and were published in English between 2004 and 2019. Standardized information was extracted from each included article and thematic analysis was applied to generate impact themes. Results A search of three databases yielded 767 non-duplicate records and 29 studies were included in the review. Six impact themes were identified: property values, neighborhood demography, economy, development, transit, and neighborhood perceptions. LRT development was associated with residential property value increases, high-density residential development, new business openings, and increases in neighborhood household income. Articles had limited recognition of the role of LRT development in creating health disparities. Conclusions This review demonstrates that transit development can influence the living conditions and resource availability of surrounding areas. Since many of the impacts identified in this study can further social stratification or have differential effects by socioeconomic status, LRT development can be conceptualized as a driver of health inequities. In order to design more effective and equitable transit policy, future research should position transit development as an SDOH.
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RESUMEN/ Existe evidencia de que uno de los impactos urbanos provocados por la implementación de un sistema de transporte masivo es la fluctuación en los valores del suelo. Esta investigación busca dar una visión sobre la percepción que tienen los propietarios de viviendas sobre la posible variación en los valores de sus inmuebles, al considerar la implementación de un sistema de tranvía en la ciudad de Cuenca-Ecuador. Para ello, se realizó una encuesta de hogares, la cual fue procesada usando métodos estadísticos, tanto descriptivos como inferenciales. Los resultados apuntan a que la mayor parte de los propietarios del área de estudio considera que los valores de venta de sus propiedades no sufrirán cambios; además, se logra inferir que, en aquellos casos en que se especula un aumento, el porcentaje de incremento no tiene relación con la distancia al eje tranviario.
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In this article, we examine the effects of rail transit investments on residents' stated mobility intentions and perceptions of neighborhood changes using a survey analysis in Charlotte, North Carolina. We ask residents in neighborhoods along a new light rail line about their reasons for residing in their current neighborhood, thoughts about moving and the light rail's effect on their neighborhood. To control for city-wide housing market pressures, responses from one station-adjacent neighborhood are compared to responses from residents in a similar neighborhood elsewhere in the city while controlling for individual characteristics. Using a mixed-methods research approach, we find that while residents attribute some changes in their property values and rents to the light rail, it is only one of many factors affecting their neighborhood. Light rail also does not appear to affect residents' stated propensity to move out of these neighborhoods. Survey respondents' view of the light rail's effect on their neighborhood is also positive, on average. We find that the stated likelihood of moving is not related to the distance to the station nor to how frequently a resident uses the light rail. This article contributes to debates on transit-induced displacement and gentrification and provides context to neighborhood-scale quantitative analyses from residents' perspective.
Article
A widely used approach to valuing transport infrastructure is to look at its effects on housing prices, in treated vs control regions, before and after it is built. But anticipation effects mean that housing prices may start changing as soon as a project is announced. This creates complications for an analysis of the capitalization effects on prices. A long span of data is potentially required—because the time from a project’s announcement to completion may be many years—and the assumption of common price trends between the treated and control regions must be maintained over this time span. An alternative approach is to use rents. This may be advantageous as rents are more directly related to the infrastructure’s service-flow. Though account needs to be taken of the fact that those homes which are rented are often not representative of the housing stock as a whole. We investigate these issues for a new train line in Sydney and contrast the results from using both prices and rents.
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Conference Paper
Transportation has an important role in the economics of a counrty. Transportation is vital to the way one lead his life and eventually the success of national economy. Also, it has important interactions with environment. Transportation facilities sometimes even shapes the attitudes of people. In other words, transportation investments result in sequence effects on many factors. Therefore, transportation investments and their certain and uncertain effects have been a very popular area of study in the literature. Many studies have revealed that transportation investments affect productivity of countries through the level of public investment, the rate of private capital formation, employment, use of labor by production firms, real wages, rate of return, accessibility and so on. On the other hand, transportation investments has also some effects on socioeconomic features such as happiness and wellbeing, improvement and preservation of environment, the noise caused by traffic, air quality, noncommercial travel time, greenhouse gases, and journey quality. Transportation investments also affect the economic growth and output, prices of residential and commercial properties, land uses, location and output decisions, option values, ,labour market participation. Many different models such as spatial hedonic models, semi log hedonic model, vector error correction model, spatial regression model, difference in difference model (DID), spatial pricing model, linear pricing model are used to understand the relation between transportation investments and the factors mentioned above. In order to analyze these models, DID estimator, multiple linear regression, ordinary least square (OLS), Spatial Autoregressive Regression (SARR) and Geographical Weighted Regression (GWR) are some of the methods used by the researchers. This article review the literature and aims to perform a comprehensive evaluation of the studies concerning the effects of transportation investments.
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This study uses the opening of the new Circle Line (CCL) in Singapore as a natural experiment to test the effects of urban rail transit networks on non-landed private housing values. We use a network distance measure and a local-polynomial-regression approach to identify the CCL impact zone with discontinuity in housing price gradient between a treatment zone and a control zone. We then estimate the spatial difference-in-differences models that account for spatial autocorrelation in housing price changes in the two zones “before and after” the opening of the CCL. We find that the opening of the CCL increases housing value in the treated neighborhoods located within the 600-metre network distance from the new CCL stations by approximately 8.6%, relative to other properties in the untreated neighborhoods controlling for heterogeneities in housing attributes and local amenities, and spatial and temporal fixed effects. We find significant “anticipation” effects as early as 1 year prior to the opening of the CCL line, but the effects diminish closer to the actual opening date. The results imply that the inter-dependent spatial structure between the treated and the untreated neighborhoods, if neglected, may lead to over-estimation of the capitalization effects of the new transit lines on housing values.
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The impact of proximity to transit on property values has become a key question in the debate on the relationships between public infrastructure investment and economic development. The focus has been on value captured by residential properties, with far fewer studies examining non-residential properties. Furthermore, few studies differentiate the effect of rail access and the effect of access to major interactions that later become station sites, and even fewer addressed the gradient of the accessibility effect. Based on the economic theory of firm location choice, this study develops hedonic pricing models to assess the value-added of the Hiawatha LRT on commercial and industrial properties, using data on properties sold before and after its completion. The results show that the LRT has induced a significant price premium for properties nearby and that the impact extends to almost 0.9 miles away from LRT stations.
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Using data on vacant land sales in Washington County, Oregon, the authors find that plans for light rail investments have positive effects on land values in proposed station areas. These findings suggest that such capitalization is likely to discourage the development of low-density housing in station areas and encourage high-density, transportation-oriented development. More important, the results provide support for a model in which planning is rational behavior by a local government and that plans—independent of regulations— can be used to alter urban development patterns for the purpose of increasing social welfare. To the extent that these results hold more generally, these results suggest that plans indeed matter.
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Railway stations function as nodes in transport networks and places in an urban environment. They have accessibility and environmental impacts, which contribute to property value. The literature on the effects of railway stations on property value is mixed in its finding in respect to the impact magnitude and direction, ranging from a negative to an insignificant or a positive impact. This paper attempts to explain the variation in the findings by meta-analytical procedures. Generally the variations are attributed to the nature of data, particular spatial characteristics, temporal effects and methodology. Railway station proximity is addressed from two spatial considerations: a local station effect measuring the effect for properties with in 1/4 mile range and a global station effect measuring the effect of coming 250 m closer to the station. We find that the effect of railway stations on commercial property value mainly takes place at short distances. Commercial properties within 1/4 mile rang are 12.2% more expensive than residential properties. Where the price gap between the railway station zone and the rest is about 4.2% for the average residence, it is about 16.4% for the average commercial property. At longer distances the effect on residential property values dominate. We find that for every 250 m a residence is located closer to a station its price is 2.3% higher than commercial properties. Commuter railway stations have a consistently higher positive impact on the property value compared to light and heavy railway/Metro stations. The inclusion of other accessibility variables (such as highways) in the models reduces the level of reported railway station impact.
Article
In recent years, land value capture has attracted increasing attention because of its potential for funding transport infrastructure. It is well acknowledged that transport infrastructure can improve accessibility to employment and amenities; thus one might expect that it is the improved accessibility that adds value to land. Therefore, the issues in the relationship between transport accessibility and land value rise in connection with the concept of land value capture. A study looked at the relationship between transport accessibility and land value with the implication of a local model, geographically weighted regression (GWR). Traditional techniques, such as hedonic models, used to understand the attributes of land value, are global models that could be misleading in examining the spatially varying relationships, such as transport accessibility and land value. By using the Tyne and Wear region in the United Kingdom as a case study, the study revealed that nonstationarity existing in the relationship between transport accessibility and land value indicates that transport accessibility may have a positive effect on land value in some areas but a negative or no effect in others; this suggests that a uniform land value capture would be inappropriate. The use of GWR allows such spatially varying relationships to be revealed, leading to a better understanding of the factors determining positive land value uplift and the implications of spatially dependent transport access premiums in housing values in the context of value capture policies.
Article
Studies quantifying value added of transit often cannot differentiate whether the premiums are transit effects or location effects. Limited studies have examined the timing of value added. Using before and after data, this study explores the impact of the Green Line LRT on housing sales prices. Compared to the studied period before its funding announcement, its announcement increased housing values by $9.2/sq ft and its commencement increased sales prices by $13.7/sq ft. Further analyses show that housing value appreciation actually occurred after the announcement but before the commencement. Thus, using the right timing of value added is critical for value capture programs and benefit–cost analysis.
Article
In this paper we examine the effect of light rail transit on the residential real estate market in Hampton Roads, Virginia. Norfolk's Tide light rail began operations in August of 2011 and has experienced disappointing levels of ridership compared to other light rail systems. We estimate the effect of the Tide using a difference-in-differences model and consider several outcome variables for the residential housing market, including sale price, sale-list price spread and the time-on-market. Our identification strategy exploits a proposed rail line in neighboring Virginia Beach, Virginia that was rejected by a referendum in 1999. Overall, the results show negative consequences from the constructed light rail line. Properties within 1,500 meters experienced a decline in sale price of nearly 8%, while the sale-list price spread declined by approximately 2%. Our results highlight the potential negative effects of light rail when potential accessibility benefits do not out weigh apparent local costs.
Article
Although transit accessibility premiums have been rigorously studied at the local and regional levels for more than 40 years, drawing conclusions about premiums on a national scale requires a meta-analysis. Estimating effect size is a primary purpose of a meta-analysis. Effect size was calculated in 2007 by using pre-2003 studies but has not been studied since. This study sought to fill gaps in the literature by conducting a regression analysis and a thorough meta-analysis that reviewed 114 studies published from 1976 to 2014. Of 114 U.S. and Canadian single-family studies, a sample of 45 single-family studies was selected for further analysis. Compared with the previous meta-analysis, the current analysis found that, overall, U.S. and Canadian studies reported lower premiums on average for single-family houses. The average single-family home premium of 2.3% was significantly lower than the 4.2% premium calculated by the previous meta-analysis. It was found that reported transit premiums were decreasing over time as more variables, such as walkability of station areas, were statistically controlled. It was also found that compact regions with greater accessibility via transit produced higher transit premiums and transit premiums were neutral with respect to technology (light versus heavy rail) once regional compactness was controlled for. These findings suggest that to get the most out of transit investments, planners and public officials must make an effort to create compact regional development patterns and that single-family housing may not be the best use in areas close to transit.
Article
This paper analyses the impact of the Hudson-Bergen Light Rail (HBLR) on residential property prices. Unlike similar studies that use a hedonic model with cross-sectional data, this one uses repeat-sales data of properties that sold at least twice between 1991 and 2009. It shows how proximity to the nearest HBLR station, relative accessibility gains across stations, and anticipation of the commencement date of the HBLR station influence home price change. Our results show that properties near the two commuting stations farthest from the revitalized central business district experienced high appreciation. It also reveals that different accessibility gains across areas were produced based on the availability of existing public transportation options. Using a negative–exponential gradient, we find that these higher appreciation rates tended to dissipate about 1/4 mile (402 m) from stations. This supports that properties around urban commuting stations enjoy higher marginal benefits through improved transit accessibility and reduced transportation costs as Alonso's model predicts.
Article
This study assesses the impact of proximity to light rail transit stations on residential property values in Buffalo, New York, where light rail has been in service for 20 years, but population is declining and ridership is decreasing. Hedonic models are constructed of assessed value for residential properties within half a mile of 14 light rail stations and independent variables are included that describe property characteristics, neighbourhood characteristics and locational amenities. The model suggests that, for homes located in the study area, every foot closer to a light rail station increases average property values by $2.31 (using geographical straight-line distance) and $0.99 (using network distance). Consequently, a home located within one-quarter of a mile radius of a light rail station can earn a premium of $1300-3000, or 2-5 per cent of the city's median home value. Model results further suggest that three independent variables-the number of bathrooms, size of the parcel and location on the East side or West side of Buffalo-are more influential than rail proximity in predicting property values. Individual regression models for each of the light rail system's 14 stations suggest that effects are not felt evenly throughout the system. Proximity effects are positive in high-income station areas and negative in low-income station areas. An analysis of the actual walking distance to stations (along the street network) versus the perceived proximity to stations (measured by straight-line distance) reveals that the results are statistically more significant in the network distance than the straight-line distance model, but the effects are greater in the straight-line distance model, which suggests that apparent proximity to rail stations is an added locational advantage compared with physical walking distance to the station.
Article
This research analyzes and compares the effects that rail transit stations have on values of condominiums and single-family homes in San Diego, California. It is hypothesized that households on the market for a condominium will value proximity to rail stations more than those on the market for a single-family home will and therefore the capitalization benefits are greater for condominiums. Past research has shown that property near rail stations sells at a modest premium (between 0% and 10%) in many U.S. cities. However, most of these studies focus on single-family homes. The hedonic price analysis presented in this paper indicates that condominiums receive capitalization benefits in excess of 10%, whereas the benefits received by single-family properties fall within the more typical range (
Article
Transit-oriented development has gained favor as a means of reducing traffic congestion, promoting affordable housing, and curbing sprawl. The effects of proximity to light and commuter rail stations are modeled as are the effects of freeway interchanges on commercial-retail and office properties in fast-growing Santa Clara County, California. From hedonic price models, substantial capitalization benefits were found, on the order of 23% for a typical commercial parcel near a light rail transit stop and more than 120% for commercial land in a business district and within 0.25 mi of a commuter rail station. Such evidence is of use not only to developers and lenders but also to transit agencies facing lawsuits over purported negative externalities associated with being near rail. It can also help in the design of creative financing, such as value-capture programs.
Article
The research presented here argues that identifying the impacts of rail transit on property values is not possible without estimates of both price gradients to transit stations as well as overall property value trends in transit neighborhoods. The latter may highlight a number of secondary impacts of rail transit on nuisance elements such as crime and parking as well as targeted public and private investment along rail tran-sit corridors. In order to estimate neighborhood property values, one must establish relevant control neighborhoods. In the case of Charlotte, North Carolina, the public planning and funding process provides information on proposed light rail-transit (LRT) corridors that were ultimately not selected as the first alignment in Charlotte's light rail transit system in 2000. Estimation incorporates a difference-in-difference estimator across a range of hedonic models. Preferred estimates highlight that LRT provides a neighborhood impact of 4.0% for single-family properties and 11.3% for condominiums sold within 1 mile of LRT stations. No neighborhood impacts are realized for com-mercial properties and estimated price gradients provide insignificant impacts across a number of models. Results suggest that LRT investment may be used more as an economic development tool for specific neighborhoods rather than a transportation amenity in cities like Charlotte, which contain sparser development patterns and lower transit ridership.
Article
Economic benefits are sometimes used to justify transport investments. Such was the case with the River Line of southern New Jersey, USA, which broke ground in 2000 and began operating in 2004. Recently, the line has been performing near full capacity and there is evidence that it has spurred development. Disaggregate data on owned-home appreciation are used to investigate the initial economic impacts of the line, looking carefully at non-linearity in the appreciation gradient, differential effects of station ridership and parking, redistribution of property appreciation gains and differences by property and neighbourhood type. At this time, the net impact of the line on the owned housing market is neutral to slightly negative. While lower-income census tracts and smaller houses seem to appreciate near the station, this may be a value transfer from farther-away properties not favoured with access. Few studies have previously looked for such effects.
Article
A majority of statistical methods used in the analysis of land use and transportation systems implicitly carry the assumption that relationships are constant across locations or individuals, thus ignoring contextual variation due to geographical or socio-economic heterogeneity. In some cases, where the assumption of constant relationships is questionable, market segmentation procedures are used to study varying relationships. More recently, methodological developments, and a greater awareness of the importance of geography, have led to increasingly sophisticated ways to explore varying relationships in land use and transportation modeling. The objective of this paper is to propose a simple probit model to explore contextual variability in continuous-space. Some conceptual and technical issues are discussed, and an example is presented that reanalyzes land use change using data from California’s BART system. The results of the example suggest that considerable parametric variation exists across geographical space, and thus underlines the relevance of contextual effects.
Article
Prior studies that have empirically investigated the impact of rail station proximity on property values have not fully investigated the factors that may account for this relationship. Stations may raise the value of nearby properties by reducing commuting costs or by attracting retail activity to the neighborhood. Possibly countering these positive effects are negative externalities emitted by stations and the access to neighborhoods that stations provide to criminals. This paper sorts out these effects by presenting the results from estimating a hedonic price model and auxiliary models for neighborhood crime and retail activity. Results show that all four effects play a role in defining the relationship between property values and rail stations, but the relative importance of these effects varies with distance from downtown and the median income of the neighborhood.
Article
This study examines the effect of the new rapid transit line from downtown Chicago to Midway Airport on single-family house prices before and after the opening of the line. The results show that the housing market anticipated the opening of the line. House prices were being affected by proximity to the stations in the late 1980s and early 1990s-after the plans for the line were well known. The difference between the increase in the value of homes within the sample area as compared with properties farther away from the new transit stations was approximately $216 million between 1986 and 1999. Copyright 2004 by the American Real Estate and Urban Economics Association
Article
We investigate the salary returns to the ability to play football with both feet. The majority of footballers are predominantly right footed. Using two data sets, a cross-section of footballers in the five main European leagues and a panel of players in the German Bundesliga, we find robust evidence of a substantial salary premium for two-footed ability, even after controlling for available player performance measures. We assess how this premium varies across the salary distribution and by player position.
The Hiawatha Line Impacts on Land Use and Residential Housing Value
  • E G Goetz
  • K Ko
  • A Hagar
  • H Ton
  • J Matson
Goetz, E.G., Ko, K., Hagar, A., Ton, H., Matson, J., 2010. The Hiawatha Line Impacts on Land Use and Residential Housing Value. Center for Transportation Studies. University of Minnesota, Minneapolis, MN.
Before & after Study: Hiawatha Light Rail Transit Line
  • Metro Transit
Metro Transit, 2010. Before & after Study: Hiawatha Light Rail Transit Line. Metro Transit, Minneapolis, MN.