Hedonic, residual, and matching methods for residential land valuation
被引:6
|
作者:
Bourassa, Steven C.
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h-index: 0
机构:
Univ Washington, Runstad Dept Real Estate, 3950 Univ Way NE, Seattle, WA 98105 USAUniv Washington, Runstad Dept Real Estate, 3950 Univ Way NE, Seattle, WA 98105 USA
Bourassa, Steven C.
[1
]
Hoesli, Martin
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机构:
Univ Geneva, Geneva Sch Econ & Management, 40 Blvd Pont Arve, CH-1211 Geneva 4, Switzerland
Univ Aberdeen, Kings Coll, Business Sch, Aberdeen AB24 3FX, ScotlandUniv Washington, Runstad Dept Real Estate, 3950 Univ Way NE, Seattle, WA 98105 USA
Hoesli, Martin
[2
,3
]
机构:
[1] Univ Washington, Runstad Dept Real Estate, 3950 Univ Way NE, Seattle, WA 98105 USA
Land valuation;
Hedonic method;
Residual approach;
Land leverage;
Matching approach;
PRICE;
VALUES;
CHICAGO;
D O I:
10.1016/j.jhe.2022.101870
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
Accurate estimates of land values on a property-by-property basis are an important requirement for the effective implementation of land-based property taxes. We compare hedonic, residual, and matching techniques for mass appraisal of residential land values, using data from Maricopa County, Arizona. The first method involves a hedonic valuation model estimated for transactions of vacant lots. The second approach subtracts the depreciated cost of improvements from the value of improved properties to obtain land value as a residual. The third approach matches the sales of vacant lots with subsequent sales of the same properties once they have been developed. For each pair, we use a land price index to inflate the land price to the time of the improved property transaction and then calculate land leverage (the ratio of land to total property value). A hedonic model is estimated and used to predict land leverage for all improved properties. We conclude that the matching approach is the most promising of the methods considered.
机构:
Minist Educ, Key Lab Geog Informat Syst, Wuhan 430079, Peoples R China
Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R ChinaHuazhong Univ Sci & Technol, Coll Publ Adm, Wuhan 430074, Peoples R China
Liu, Yaolin
Zheng, Bin
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机构:
Huazhong Univ Sci & Technol, Coll Publ Adm, Wuhan 430074, Peoples R China
HUST Land & Resources & Real Estate Res Ctr, Wuhan 430074, Peoples R ChinaHuazhong Univ Sci & Technol, Coll Publ Adm, Wuhan 430074, Peoples R China
Zheng, Bin
Turkstra, Jan
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h-index: 0
机构:
UN Habitat, Global Urban Observ, Nairobi 00100, KenyaHuazhong Univ Sci & Technol, Coll Publ Adm, Wuhan 430074, Peoples R China
Turkstra, Jan
Huang, Lina
论文数: 0引用数: 0
h-index: 0
机构:
Minist Educ, Key Lab Geog Informat Syst, Wuhan 430079, Peoples R China
Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R ChinaHuazhong Univ Sci & Technol, Coll Publ Adm, Wuhan 430074, Peoples R China