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Browse: Home / A Statistical Analysis of the Effects of Access, Traffic Exposure, and Frontage Parameters upon Sale Price of Commercial Real Property in Kansas

A Statistical Analysis of the Effects of Access, Traffic Exposure, and Frontage Parameters upon Sale Price of Commercial Real Property in Kansas

By Stan Longhofer on 02/21/2018

Chris Huffman and Stanley D. Longhofer

Final draft: April 2016
Transportation Research Record: Journal of the Transportation Research Board, no. 2556, 2016, pp. 10-19.

Past research has demonstrated the effectiveness of access management in improving or preserving the safety of the traveling public, the capacity and quality of the flow of traffic, and in supporting and sustaining economic activity. Nevertheless, fear of economic hardship perceived to arise from effective implementation of access management remains a barrier to mainstream implementation. Work in NCHRP 420: Impacts of Access Management Techniques (1999) shows how effective access management at the network level preserves or restores market penetration of commercial activities in a given area. Work done in Florida (1991), Iowa (1997), and Texas (1999) studied the effects of access management retrofits at the corridor level, and found minimal to positive changes in economic activity overall. Likewise, small studies of economic impacts to individual sites have been conducted in Kansas (1999), and Minnesota (2006) and have demonstrated little to positive impacts to highest and best use arising from access management retrofits.

The site (microscopic) level studies are of individual corridors or smaller data sets, and are largely qualitative analyses of economic effects of access at the microscopic level. Quantitative analysis is needed on a large data population to examine the factors that most impact sale price of income producing properties. The purpose of this paper is to present the effects of access and other transportation characteristics upon sale price of income producing real property, and to present a model that shows which variables contribute to sale price, the interactions of those variables, and the effectiveness of the model.

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Posted in Academic Research, Research & Data, Uncategorized | Tagged Longhofer

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