Shishir Mathur

The Effect of Impact Fees on the Price of New Single-family Housing

This paper provides new evidence on the effects of impact fees on housing prices, using an inventory of single-family housing sale transactions in the 38 cities and towns within King County, Washington, for the period 1991-2000. Although the effect of impact fees on housing prices has been examined previously, earlier studies have been limited by methodological deficiencies. This paper examines the effect of impact fees on new housing and their differential effect on housing price based on the quality of housing, and finds that the effect of impact fees on the price of new housing is quite significant and elastic, raising new home prices by about 166 per cent of the amount of the fee. The increase is 358 per cent for the higher-quality homes and is statistically insignificant for the lower-quality homes.

Do impact fees raise the price of existing housing

Abstract This article uses 1991–2000 data on single‐family housing sales from King County, WA, to provide new evidence relating to the effects of impact fees on housing prices. The hedonic regression method is used to examine the effects of these fees on existing housing as well as their differential effects on price as determined by housing quality. Impact fees raise existing home prices by about 83 percent of the amount of the fee. The increase is 103 percent for high‐quality homes and is not statistically significant for low‐quality homes. The owners of high‐quality homes realize capital gains from impact fees. However, such fees do not raise the price of low‐quality homes. To the extent that low‐quality housing is more likely to be owned by low‐ and moderate‐income households, which are often composed of racial and ethnic minorities, this finding has significant policy implications for the supporters of impact fees.

Influences of neighborhood crime on mode choice

It is understood that the threats posed by possible criminal activity in a neighborhood can play a major role in the decision to drive, take transit, walk, or ride a bicycle, but little empirical evidence has yet been gathered to support this notion, let alone guide public infrastructure investments, land use planning, or the allocation of police services. This study found that high-crime neighborhoods tend to discourage residents from walking or riding a bicycle. When a high-crime neighborhood is compared with a lower-crime neighborhood, the odds of choosing walking over driving decrease by 17% for work trips and 61% for nonwork trips. However, transit trips appear to respond to neighborhood crime in a way similar to auto trips; that is, high-crime neighborhoods appear to encourage transit use. The odds of choosing transit over the auto increase by 17% for work trips and 164% for nonwork trips. The study found that transit access trips (walking, bicycling, or driving to a transit station) are sensitive to neighborhood crimes in keeping with theoretical expectations: high-crime neighborhoods discourage walking and bicycling and encourage driving to transit stations. Specifically, for transit access to work trips, the odds of choosing to walk or bike to a transit station instead of driving decrease by 48%.

Impact of Urban Growth Boundary on Housing and Land Prices: Evidence from King County, Washington

This study provides evidence of the impact of an urban growth boundary (UGB) on housing and land prices. The study uses a data-set that inventories sales transactions of single-family homes and of vacant lots zoned for single-family homes within two miles of either side of the eastern boundary of the primary UGB in King County, Washington. The results show that although the UGB increases land prices by 230 per cent, it decreases housing prices by 1.3 per cent. These findings should encourage policy-makers to adopt a policy framework in which a UGBs anticipated inflationary land price effect is mitigated by policies that increase housing supply. Such policies could include minimum density requirements, zoning for multifamily housing, and ordinances enabling the construction of accessory dwelling units.

The Myth of “Free” Public Education Impact of School Quality on House Prices in the Fremont Unified School District, California

Using the Fremont Unified School District in Fremont, California, as the study area, this study estimates the impact of school quality on house prices and finds that a one-standard-deviation increase in the quality of elementary, middle, and high schools significantly increases house prices—by 20 percent for an average-priced house. I urge urban planners and policy makers to explicitly recognize the impact of schools on residential segregation, to consider access to high-quality K–12 education when developing plans and policies, to collaborate with school districts to improve educational quality, and to provide incentives for the construction of affordable housing in neighborhoods with high-quality schools.

Do All Impact Fees Affect Housing Prices the Same

The study empirically estimates the effects of four types of impact fees (road, school, park, and fire protection impact fees) on new and existing housing, as well as the fees’ differential effects on price as determined by housing quality. The results indicate that impact fees generally raise the price of new housing. Further, the magnitude and the direction of the housing price effect of individual impact fees vary substantially. For example, the park impact fee increases the price of new and existing housing, whereas the fire protection impact fee has no effect or has a negative effect on housing prices.

A cloud-based framework for smart permit system for buildings

In this paper we propose a novel cloud-based platform for building permit system that is efficient, user-friendly, transparent, and has quick turn-around time for homeowners. Compared to the existing permit systems, the proposed smart city permit framework provides a pre-permitting decision workflow, and incorporates a data analytics and mining module that enables the continuous improvement of a) the end user experience, by analyzing explicit and implicit user feedback, and b) the permitting and urban planning process, allowing a gleaning of key insights for real estate development and city planning purposes, by analyzing how users interact with the system depending on location, time, and type of request. The novelty of the proposed framework lies in the integration of the pre-permit processing front-end with permit processing and data analytics & mining modules, along with utilization of techniques for extracting knowledge from the data generated through the use of the system.

Funding Public Transportation Through Special Assessment Districts: Addressing the Equity Concerns.

Little scholarly attention has been paid to the equity impacts of special assessment districts (SADs) established to fund public transportation projects. This article uses three recent public transportation projects funded using SADs in the United States and finds that the case study SADs’ performance is mixed. Although the districts use a variety of criteria, such as property value, parcel area, and distance from the transportation project, to calculate assessments in a way that promotes horizontal equity, the assessment methodologies do not take into account the disamenity associated with certain elements of public transportation projects, such as the rail line. Furthermore, owner-occupied residential properties are often exempt from paying assessments to garner support for SADs, rather than to satisfy equity concerns. Finally, the low-interest, long-term payment of assessments enhances vertical equity which can be further enhanced if assessment exemptions or deferments are consistently provided to seniors on fixed incomes and low-income households.

A Building Permit System for Smart Cities: A Cloud-based Framework

Abstract In this paper we propose a novel, cloud-based framework to support citizens and city officials in the building permit process. The proposed framework is efficient, user-friendly, and transparent with a quick turn-around time for homeowners. Compared to existing permit systems, the proposed smart city permit framework provides a pre-permitting decision workflow, and incorporates a data analytics and mining module that enables the continuous improvement of both the end user experience and the permitting and urban planning processes. This is enabled through a data mining-powered permit recommendation engine as well as a data analytics process that allow a gleaning of key insights for real estate development and city planning purposes, by analyzing how users interact with the system depending on their location, time, and type of request. The novelty of the proposed framework lies in the integration of a pre-permit processing front-end with permit processing and data analytics & mining modules, along with utilization of techniques for extracting knowledge from the data generated through the use of the system. The proposed framework is completely cloud-based, such that any city can deploy it with lower initial as well as maintenance costs. We also present a proof-of-concept use case, using real permit data from New York City.

Using Tax Increment Financing to Fund Public Transportation: Enabling Environment and Equity Impacts

Through a review of three public transport projects developed across the United States using tax increment financing (TIF) revenues, this article examines the robustness of state- and local-level enabling statutes and the strategies used to minimize TIF’s horizontal and vertical inequities. The article finds that although TIF is widely used to fund transit-related facilities, such as rail lines and train stations, it is not used to purchase or maintain the rolling stock (e.g., train cars and buses). Furthermore, the use of TIF revenues for public transport enhances vertical equity to the extent that public transit users are likely to have lower incomes than auto users. However, in all case study projects, TIF primarily helped develop rail projects, not bus systems, with the latter more likely to be used by lower income people. Finally, setting aside TIF funds for affordable housing, job training, and relocation and rehabilitation can help reduce vertical inequities.