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Spatial Econometric Approaches to Estimating Hedonic Property Value Models. (2005). Ready, Richard ; Wang, LI.
In: 2005 Annual meeting, July 24-27, Providence, RI.
RePEc:ags:aaea05:19174.

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  1. Automating the land valuation process carried out in land consolidation schemes. (2018). Demetriou, Demetris.
    In: Land Use Policy.
    RePEc:eee:lauspo:v:75:y:2018:i:c:p:21-32.

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  2. Spatial heterogeneity and spatial bias analyses in hedonic price models: some practical considerations. (2015). Haniza, Khalid .
    In: Bulletin of Geography. Socio-economic Series.
    RePEc:vrs:buogeo:v:28:y:2015:i:28:p:113-128:n:8.

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  3. Spatial dependence in commercial property prices: micro evidence from the Netherlands. (2014). Özyurt, Selin ; Ozyurt, Selin.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20141627.

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References

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  2. Anselin L. 2001. Raos score test in spatial econometrics. Journal of Statistical Planning and Inference, 97: 113-139.
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  3. Anselin L. 2002. Under the hood: Issue in the specification and interpretation of spatial regression models. Agricultural Economics, 17: 247-267.

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  6. Anselin, L. 2005. Exploring Spatial Data with GeoDa: A Workbook. in https ://www. geoda.uiuc .edu/documentation.php#manuals Anselin L. and Bera A.K. 1998. Spatial dependence in linear regression models with an introduction to spatial econometrics, in Ullah A. and Giles D. (eds.) Handbook of Applied Economic Statistics, Marcel Dekker, New York, NY, 237-289.
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  7. Basu, S. and Thibodeau, T.G. 1998. Analysis of spatial autocorrelation in house prices. Journal of Real Estate Finance and Economics, 17: 6 1-86.

  8. Bell K.P. and Bockstael N.E. 2000. Applying the generalized moments estimation approach to spatial problems involving microlevel data. The Review of Economics and Statistics, 82: 72-82.

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  10. Kelejian H.H. and Prucha I.R. 1999. A generalized moments estimator for the autoregressive parameter in a spatial model. International Economics Review, 40: 509533.

  11. Kelejian H.H. and Robinson D.P. 1993. A suggested method of estimation method for spatial interdependent model with autocorrelatted errors, and an application to a county expenditure model. Papers in Regional Science, 72: 297-3 12.

  12. Kelijian and Robinson 1995. Spatial correlation: a suggested alternative to the autoregressive model. in Anselin L. and Florax R.J.G.M. (eds) New Directions in Spatial Econometrics, Spring-Verlag Germany, p75-96 Kim C.W., Phipps T.T. and Anselin L. 2003. Measure the benefits of air quality improvement: A spatial hedonic approach, Journal of Environmental Economics and Management, 45: 24-39.

  13. LeSage J.P. 1999. The Theory and Practice of Spatial Econometrics. Unpublished manuscript available at: http ://www.spatial-econometrics .com.
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  14. Mur J. 1999. Testing for spatial autocorrelation: Moving average versus autoregressive processes. Environment and Planning A, 31:137-1382.

  15. Pace R.K. and Gilley 0. 1997. Using the spatial configuration of the data to improve estimation, Journal of Real Estate Finance and Economics, 14: 333-340.

  16. Paterson R.W. and Boyle K.J. 2002. Out of sight, out of mind? Using GIS to incorporate visibility in hedonic property value models. Land Economics, 78:417-425 Ready R.C. 2004. Do landfills always depress nearby property values? Working paper, Dept. of Agricultural Economics and Rural Sociology, The Pennsylvania State University Ready R.C. and Abdalla C.W. 2005. The amenity and disamenity impacts of agriculture: Estimates from a hedonic pricing model. American Journal of Agricultural Economics 87(2):3 14-326 Sneek J.M. and Rietveld P. 1997. On the estimation of the spatial moving average model. Tinbergen Institute Discussion Paper, 97-049/4.

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