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contributor authorXiaoxia Xiong
contributor authorKara Kockelman
date accessioned2017-05-08T22:14:12Z
date available2017-05-08T22:14:12Z
date copyrightDecember 2014
date issued2014
identifier other39940174.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/74664
description abstractThe costs of acquiring parcels by condemnation are usually significantly higher than those of property acquired by negotiation, suggesting that right-of-way (R/W) acquisition costs may best be described by two different regression equations. This paper develops a switching regression model of acquisition cost to simultaneously predict the probability of whether a parcel will go to condemnation rather than be acquired through negotiation and the corresponding acquisition costs under these two regimes. The error terms of the selection equation and the two cost equations follow a trivariate normal distribution to reflect codependence on unobserved factors (such as a land owner’s tenacity or a site’s view value). When applied to the properties acquired across the state of Texas for transportation probjects between 2008 and 2011, the results of this switching regression model suggest that R/W appraisers and staff should pay special attention to parcels in commercial use involving a partial taking with a relatively small remainder and located in more urbanized areas. Comparison of cost estimates between the two regimes (condemnation versus negotiation) suggests that condemned parcels will have, on average, 78% higher acquisition costs and 51% greater price variation across the 1,710 acquired properties. These results suggest that it is much more costly to acquire a property and more difficult to accurately predict its costs if it cannot be acquired through negotiation. The application of model estimates to an example corridor highlights the value of simulation to capture all modeling uncertainties.
publisherAmerican Society of Civil Engineers
titleCost of Right-of-Way Acquisition: Recognizing the Impact of Condemnation via a Switching Regression Model
typeJournal Paper
journal volume20
journal issue4
journal titleJournal of Infrastructure Systems
identifier doi10.1061/(ASCE)IS.1943-555X.0000195
treeJournal of Infrastructure Systems:;2014:;Volume ( 020 ):;issue: 004
contenttypeFulltext


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