The impact of agricultural conservation easement on nearby house prices: Incorporating spatial autocorrelation and spatial heterogeneity |
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| Institution: | 1. Department of Mechanical Engineering, Graduate University of Advanced Technology, 76318-18356 Kerman, Iran;2. Dynamic and Smart Systems Laboratory, Mechanical Industrial and Manufacturing Engineering Department, The University of Toledo, 2801 West Bancroft St. MS 312, Toledo, OH 43606, USA;3. S.M. Wu Manufacturing Research Center, College of Engineering, Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA;4. Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran;5. Department of Mechanical Engineering, University of Kentucky, KY 40506, USA;1. Departamento de Física, Universitat Autònoma de Barcelona, Bellaterra, 08193, Spain;2. Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina;3. Departamento de Física, Universidad Nacional de Colombia - Sede Bogotá Carrera 45 No 26–85, Bogotá D.C. - Colombia;4. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal, Universidad de Alicante, 03080, Alicante, Spain;5. Departamento de Ciencia de Materiales, Óptica y Tecnología Electrónica, Universidad Miguel Hernández de Elche, 03202 Elche, Spain |
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| Abstract: | The impact of farmland under agricultural conservation easement (ACE) contract on the values of nearby residential properties is investigated using housing sales data in two Pennsylvania counties. ACE-protected farmland had a positive impact on nearby property values in one study county but a negative impact in the other. The paper also looks at the impact of forest land use, and discovers that preserved forest land had a positive impact on the nearby property values in both counties. House prices showed strong spatial correlation in both counties, and a spatial error components (SEC) model fit the data better than the OLS model, a spatial-lag model (SLM), or a spatial autoregressive error model (SEM). Geographically weighted regression (GWR) showed that the impact of ACE-protected farmland on nearby property values varied within one of the two study counties, with positive impacts in some parts of the county and negative impacts in other parts. The impact of forest cover on property values also varied, with positive impacts within both counties. A new hybrid GWR-SEC model is introduced that incorporates both spatial correlation in prices and spatial heterogeneity in the model parameters. Statistical goodness of fit measures showed that the GWR-SEC model fit better than the GWR model or a hybrid GWR-SEM model. |
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| Keywords: | Spatial econometric model Developed and undeveloped land use Agricultural conservation easement Forest land use Hedonic price method |
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