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A Spatial Quantile Regression Hedonic Model of Agricultural Land Prices


  • Philip Kostov


Abstract Land price studies typically employ hedonic analysis to identify the impact of land characteristics on price. Owing to the spatial fixity of land, however, the question of possible spatial dependence in agricultural land prices arises. The presence of spatial dependence in agricultural land prices can have serious consequences for the hedonic model analysis. Ignoring spatial autocorrelation can lead to biased estimates in land price hedonic models. We propose using a flexible quantile regression-based estimation of the spatial lag hedonic model allowing for varying effects of the characteristics and, more importantly, varying degrees of spatial autocorrelation. In applying this approach to a sample of agricultural land sales in Northern Ireland we find that the market effectively consists of two relatively separate segments. The larger of these two segments conforms to the conventional hedonic model with no spatial lag dependence, while the smaller, much thinner market segment exhibits considerable spatial lag dependence. Un modèle hédonique à régression quantile spatiale des prix des terrains agricoles Résumé Les études sur le prix des terrains font généralement usage d'une analyse hédonique pour identifier l'impact des caractéristiques des terrains sur le prix. Toutefois, du fait de la fixité spatiale des terrains, la question d'une éventuelle dépendance spatiale sur la valeur des terrains agricoles se pose. L'existence d'une dépendance spatiale dans le prix des terrains agricoles peut avoir des conséquences importantes sur l'analyse du modèle hédonique. En ignorant cette corrélation sérielle, on s'expose au risque d'évaluations biaisées des modèles hédoniques du prix des terrains. Nous proposons l'emploi d'une estimation à base de régression flexible du modèle hédonique à décalage spatial, tenant compte de différents effets des caractéristiques, et surtout de différents degrés de corrélations sérielles spatiales. En appliquant ce principe à un échantillon de ventes de terrains agricoles en Irlande du Nord, nous découvrons que le marché se compose de deux segments relativement distincts. Le plus important de ces deux segments est conforme au modèle hédonique traditionnel, sans dépendance du décalage spatial, tandis que le deuxième segment du marché, plus petit et beaucoup plus étroit, présente une dépendance considérable du décalage spatial. Un modelo hedónico de regresión cuantil espacial de los precios del terreno agrícola Resumen Típicamente, los estudios del precio de la tierra emplean un análisis hedónico para identificar el impacto de las características de la tierra sobre el precio. No obstante, debido a la fijeza espacial de la tierra, surge la cuestión de una posible dependencia espacial en los precios del terreno agrícola. La presencia de dependencia espacial en los precios del terreno agrícola puede tener consecuencias graves para el modelo de análisis hedónico. Ignorar la autocorrelación espacial puede conducir a estimados parciales en los modelos hedónicos del precio de la tierra. Proponemos el uso de una valoración basada en una regresión cuantil flexible del modelo hedónico del lapso espacial que tenga en cuenta los diversos efectos de las características y, particularmente, los diversos grados de autocorrelación espacial. Al aplicar este planteamiento a una muestra de ventas de terreno agrícola en Irlanda del Norte, descubrimos que el mercado consiste efectivamente de dos segmento relativamente separados. El más grande de estos dos segmentos se ajusta al modelo hedónico convencional sin dependencia del lapso espacial, mientras que el segmento más pequeño, y mucho más fino, muestra una dependencia considerable del lapso espacial.

Suggested Citation

  • Philip Kostov, 2009. "A Spatial Quantile Regression Hedonic Model of Agricultural Land Prices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(1), pages 53-72.
  • Handle: RePEc:taf:specan:v:4:y:2009:i:1:p:53-72 DOI: 10.1080/17421770802625957

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    References listed on IDEAS

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    Cited by:

    1. Paul Feichtinger & Klaus Salhofer, 2016. "The Fischler Reform of the Common Agricultural Policy and Agricultural Land Prices," Land Economics, University of Wisconsin Press, pages 411-432.
    2. Federico Belotti & Gordon Hughes & Andrea Piano Mortari, 2017. "Spatial panel-data models using Stata," Stata Journal, StataCorp LP, vol. 17(1), pages 139-180, March.
    3. O'Donoghue, Cathal & Lopez, Jeremey & O’Neill, Stephen & Ryan, Mary, 2015. "AHedonic Price Model of Self-Assessed Agricultural Land Values," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212639, European Association of Agricultural Economists.
    4. Zhang, Lei & Leonard, Tammy, 2014. "Neighborhood impact of foreclosure: A quantile regression approach," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 133-143.
    5. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
    6. V. Chernozhukov & C. Hansen, 2013. "Quantile Models with Endogeneity," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 57-81, May.
    7. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
    8. McMillen, Daniel, 2015. "Conditionally parametric quantile regression for spatial data: An analysis of land values in early nineteenth century Chicago," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 28-38.
    9. Claudio Othón Cruz Martínez, 2016. "Una aproximación al valor social y ambiental de las áreas verdes urbanas de la Ciudad de México," Graduate theses (Spanish) TESG 011, CIDE, División de Economía.
    10. Atella, Vincenzo & Belotti, Federico & Depalo, Domenico & Piano Mortari, Andrea, 2014. "Measuring spatial effects in the presence of institutional constraints: The case of Italian Local Health Authority expenditure," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 232-241.
    11. Rafael González-Val, 2015. "Cross-sectional growth in US cities from 1990 to 2000," Journal of Geographical Systems, Springer, vol. 17(1), pages 83-106, January.
    12. Brunes, Fredrik & Hermansson, Cecilia & Song, Han-Suck & Wilhelmsson, Mats, 2016. "NIMBYs for the rich and YIMBYs for the poor: Analyzing the property price effects of infill development," Working Paper Series 16/2, Royal Institute of Technology, Department of Real Estate and Construction Management & Centre for Banking and Finance (cefin).
    13. Vincenzo Atella & Federico Belotti & Domenico Depalo & Andrea Piano Mortari, 2013. "Measuring spatial effects in presence of institutional constraints: the case of Italian Local Health Authority expenditure," CEIS Research Paper 278, Tor Vergata University, CEIS, revised 08 May 2013.
    14. McMillen, Daniel & Shimizu, Chihiro, 2017. "Decompositions of Spatially Varying Quantile Distribution Estimates: The Rise and Fall of Tokyo House Prices," HIT-REFINED Working Paper Series 74, Institute of Economic Research, Hitotsubashi University.
    15. Uematsu, Hiroki & Mishra, Ashok K., 2012. "The Impact of Natural Amenity on Farmland Values: A Quantile Regression Approach," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119804, Southern Agricultural Economics Association.
    16. Maria Marino & Alessio Farcomeni, 2015. "Linear quantile regression models for longitudinal experiments: an overview," METRON, Springer;Sapienza Università di Roma, pages 229-247.
    17. Gautier, Pieter & Siegmann, Arjen & van Vuuren , Aico, 2017. "Real-Estate Agent Commission Structure and Sales Performance," Working Papers in Economics 692, University of Gothenburg, Department of Economics.
    18. Stephen Matthews & Daniel M. Parker, 2013. "Progress in Spatial Demography," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(10), pages 271-312, February.
    19. Salman Khan & Ghaffar Ali & Syed Attaullah Shah & Abbas Ullah Jan & Dawood Jan & M. Fayaz, 2016. "A hedonic analysis of agricultural land prices in Pakistan`s Peshawar district," Asian Journal of Agriculture and rural Development, Asian Economic and Social Society, pages 59-67.

    More about this item


    Spatial lag; quantile regression; hedonic model; C13; C14; C21; Q24;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land


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