Hall, Joshua C.; Lacombe, Donald J.; Neto, Amir; Young, James. (2022). Bayesian Estimation of the Hierarchical SLX Model with an Application to Housing Markets. Journal Of Economics & Finance, 46(2), 360 – 373.
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Abstract
Hierarchical or multilevel models have long been used in hedonic models to delineate housing submarket boundaries in order to improve model accuracy. School districts are one important delineator of housing submarkets in an MSA. Spatial hedonic models have been extensively employed to deal with unobserved spatial heterogeneity and spatial spillovers. In this paper, we develop the spatially lagged X (or SLX) hierarchical model to integrate these two approaches to better understanding local housing markets. We apply the SLX hierarchical model to housing and school district test score data from Cincinnati Ohio. Our results highlight the importance of accounting for spatial spillovers and the fact that houses are embedded in school districts which vary in quality. [ABSTRACT FROM AUTHOR]; Copyright of Journal of Economics & Finance is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Housing Market; Multilevel Models; Test Scoring; Cincinnati (ohio); Ohio; Bayesian Methods; Slx Model; Spatial Econometrics; Spatial Hierarchical Models
Stover, Victor W.; Bae, C.-H. Christine. (2011). Impact of Gasoline Prices on Transit Ridership in Washington State. Transportation Research Record, 2217, 1 – 10.
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Abstract
Gasoline prices in the United States have been extremely volatile in recent years and rose to record high levels during the summer of 2008. According to the U.S. Energy Information Administration, the average U.S. gasoline price for the year 2008 was $3.26 a gallon, which was the second highest yearly average in history when adjusted for inflation. Transportation agencies reported changes in travel behavior as a result of the price spike, with transit systems experiencing record ridership and state departments of transportation reporting reductions in traffic volumes. This study examined the impact of changing gasoline prices on transit ridership in Washington State by measuring the price elasticity of demand of ridership with respect to gasoline price. Ordinary least-squares regression was used to model transit ridership for transit agencies in 11 counties in Washington State during 2004 to 2008. The price of gasoline had a statistically significant effect on transit ridership for seven systems studied, with elasticities ranging from 0.09 to 0.47. A panel data model was estimated with data from all 11 agencies to measure the overall impact of gasoline prices on transit ridership in the state. The elasticity from the panel data model was 0.17. Results indicated that transit ridership increased as gasoline prices increased during the study period. The findings were consistent with those from previous studies on the topic.
Keywords
Time-series Analysis; Gas Prices; Elasticities; Demand
Choi, Kunhee; Lee, Hyun Woo. (2016). Deconstructing the Construction Industry: A Spatiotemporal Clustering Approach to Profitability Modeling. Journal Of Construction Engineering And Management, 142(10).
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Abstract
In spite of the strong influence of the construction industry on the national health of the United States' economy, very little research has specifically aimed at evaluating the key performance parameters and trends (KPPT) of the industry. Due to this knowledge gap, concerns have been constantly raised over lack of accurate measures of KPPT. To circumvent these challenges, this study investigates and models the macroeconomic KPPT of the industry through spatiotemporal clustering modeling. This study specifically aims to analyze the industry in 14 of its subsectors and subsequently, by 51 geographic spatial areas at a 15-year temporal scale. KPPT and their interdependence were firstly examined by utilizing the interpolated comprehensive U.S. economic census data. A hierarchical spatiotemporal clustering analysis was then performed to create predictive models that can reliably determine firm's profitability as a function of the key parameters. Lastly, the robustness of the predictive models was tested by a cross-validation technique called the predicted error sum of square. This study yields a notable conclusion that three key performance parameterslabor productivity, gross margin, and labor wageshave steadily improved over the study period from 1992 to 2007. This study also reveals that labor productivity is the most critical factor; the states and subsectors with the highest productivity are the most profitable. This study should be of value to decision-makers when plotting a roadmap for future growth and rendering a strategic business decisions.
Keywords
Construction Industry; Decision Making; Knowledge Management; Labour Resources; Macroeconomics; Organisational Aspects; Productivity; Profitability; Salaries; Statistical Analysis; Strategic Planning; Hierarchical Spatiotemporal Clustering Approach; National Health; Macroeconomic Kppt; Knowledge Gap; Spatiotemporal Clustering Modeling; Interpolated Comprehensive U.s. Economic Census Data; Parameters-labor Productivity; Gross Margin; Labor Wages; Strategic Business Decisions; Deconstructing; Key Performance Parameters And Trends; Firms Profitability; Error Sum Of Square; Labor Productivity; Projects; Firms; Performance; Performance Measurement; Cluster Analysis; Economic Census; Project Planning And Design
Idziorek, Katherine; Chalana, Manish. (2019). Managing Change: Seattle’s 21st Century Urban Renaissance. Journal Of Urbanism, 12(3), 320 – 345.
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Abstract
Evolution of the urban planning and historic preservation disciplines has resulted in an “uneasy alliance” in practice, one further complicated by the back-to-the-city movement and increased development pressure in older urban neighbourhoods. In Seattle, as in other U.S. cities, the pace, intensity and scale of redevelopment has caused dramatic spatial and social transformations. Although research has shown that older built fabric provides economic and social benefit for cities, neither regulations created by planners for guiding redevelopment nor strategies created by preservationists for retaining urban heritage have been successful in reconciling these different, yet interconnected, sets of values. We engage three Seattle neighbourhood case studies to clarify and evaluate policies, programs and strategies used by planners and preservationists for reimagining neighbourhood transformations. This work suggests a need for more creative, integrative collaboration between the two fields to simultaneously engage – and reconcile – social and economic tensions caused by urban redevelopment.
Keywords
Renaissance; Urban Planning; Biological Evolution; Historic Preservation; Seattle (wash.); Everyday Heritage; Seattle; Urban Conservation; Urban Renaissance; Redevelopment; Change Management; Neighborhoods; Regulation; Urban Renewal; Transformations; Cities; Preservation; Urban Areas; Planners; 21st Century; Cultural Heritage
Shang, Luming; Aziz, Ahmed M. Abdel. (2020). Stackelberg Game Theory-Based Optimization Model for Design of Payment Mechanism in Performance-Based PPPs. Journal Of Construction Engineering And Management, 146(4).
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Abstract
Payment mechanisms lie at the heart of public-private partnership (PPP) contracts. A good design of the payment mechanism should consider the owner's goals in the project, allocate risks appropriately to stakeholders, and assure satisfactory performance by providing reasonable compensation to the private developer. This paper proposes a Stackelberg game theory-based model to assist public agencies in designing payment mechanisms for PPP transportation projects. The interests of both public and private sectors are considered and reflected by a bilevel objective function. The model aims to search for solutions that maximize a project's overall performance for the sake of social welfare while simultaneously maximizing return for the sake of private investment. A variable elimination method and genetic algorithm are used to solve the optimization model. A case study based on a real PPP project is discussed to validate the effectiveness of the proposed model. The solutions provided by the model reveal that the optimal payment mechanism structure could be established such that it would satisfy owners' requirements for overall project performance while optimizing project total payments to contractors.
Keywords
Construction Industry; Contracts; Financial Management; Game Theory; Genetic Algorithms; Investment; Optimisation; Organisational Aspects; Project Management; Public Administration; Transportation; Public-private Partnership Contracts; Good Design; Private Developer; Stackelberg Game Theory-based Model; Ppp Transportation Projects; Public Sectors; Private Sectors; Private Investment; Ppp Project; Optimal Payment Mechanism Structure; Project Performance; Project Total Payments; Stackelberg Game Theory-based Optimization Model; Performance-based Ppps; Public-private Partnerships; Analytic Hierarchy Process; Weighted Sum Method; Multiobjective Optimization; Algorithm; Incentives; Projects; Network; Success; Branch
Acolin, Arthur; Colburn, Gregg; Walter, Rebecca J. (2022). How Do Single-Family Homeowners Value Residential and Commercial Density? It Depends. Land Use Policy, 113.
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Abstract
This paper develops estimates of the relationship between local density and single-family home values using 2017 transactions for five U.S. metropolitan regions: Chicago, Los Angeles, Minneapolis, Philadelphia, Seattle. Proposals to build new commercial and residential development projects that would increase local density commonly face opposition from local homeowners. Academic literature links the response from homeowners to concerns that higher density is associated with lower property values but there is limited empirical evidence establishing this relationship at the local level. We find a positive and significant relationship between density and house value in the core area of the five metropolitan regions we analyze. Within 7.5 miles of the center of these metropolitan regions, a 10% increase in surrounding built area density is associated with a 1.1–1.9% increase in house prices per square foot. For outlying areas, the estimates are smaller and even negative in several cases. We instrument density based on topographic and soil characteristics and find similar results. These findings point to the need for a more nuanced discussion of the relationship between local density and housing values.
Keywords
Population Density; Soil Density; Single Family Housing; Home Ownership; Housing Development; Housing Discrimination; Home Prices; Los Angeles (calif.); Density; Single-family House Value; Urban Form; Residential Development; Real Estate; Property Values; Residential Density; Development Programs; Housing; Estimates; Metropolitan Areas; Development Projects; Empirical Analysis; Families & Family Life; Soil Characteristics
Though Transit Equity Day is just one day, the issue of equity on Seattle’s public transit is an ongoing and important conversation to Seattle and King County residents. Neighborhoods across the county have unequal access to transit lines; bus stops are often located in inconvenient or dangerous places due to oncoming traffic and lack of sidewalks; and bus schedules are irregular or sparse, with long wait times. These are just a few of the challenges folks might experience before getting…
Congratulations to Assistant Professor of Real Estate and CSDE Affiliate Arthur Acolin for being awarded a $10,000 Tier 2 seed grant for his project, “Accessory Dwelling Units as Potential Source of Affordable Housing Across Generations”. This grant is part of CSDE’s quarterly call for seed grant applications and is intended to help faculty initiate new research endeavors that have high relevance to population science and a strong chance of building towards extramural funding. Acolin will be conducting a joint project…
College is a time of exploration and discovery for all students. It is a time that often shapes how we view the world. Going through this transition during a moment of turbulence in the world can shape that experience significantly, which is exactly what happened for Assistant Professor of Real Estate, Arthur Acolin. As an undergraduate, international student in the US in 2008, the housing bubble and subsequent recession shaped Acolin’s future as a researcher and professor. “The subprime crisis…
The Pacific Northwest Transportation Consortium (PacTrans) announced in January 2021 the project proposals selected for funding. Qing Shen, Professor of Urban Design and Planning and Chair of the Interdisciplinary PhD Program in Urban Design and Planning is among those selected for project funding. Shen is working alongside Co-Principal Investigator Catherine (Casey) Gifford–Innovative Mobility Senior Planner–on the applied research project titled “Supplementing fixed-route transit with dynamic shared mobility services: a marginal cost comparison approach”. The project goal is to address a…