IDEAS home Printed from https://ideas.repec.org/a/taf/specan/v4y2009i1p53-72.html
   My bibliography  Save this article

A Spatial Quantile Regression Hedonic Model of Agricultural Land Prices

Author

Listed:
  • Philip Kostov

Abstract

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
    as

    Download full text from publisher

    File URL: http://www.taylorandfrancisonline.com/doi/abs/10.1080/17421770802625957
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hannu Törmä & Thomas Rutherford, 1993. "Integrating Finnish Agriculture into EC," Research Reports 13, Government Institute for Economic Research Finland (VATT).
    2. Jones, Rich & Whalley, John, 1989. "A Canadian regional general equilibrium model and some applications," Journal of Urban Economics, Elsevier, vol. 25(3), pages 368-404, May.
    3. Hannu Törmä & Thomas Rutherford & Risto Vaittinen, 1995. "What Will EU Membership and the Value-Added Tax Reform Do to Finnish Food Economy? - A Computable General Equilibrium Analysis," Discussion Papers 88, Government Institute for Economic Research Finland (VATT).
    4. Mark D. Partridge & Dan S. Rickman, 1998. "Regional Computable General Equilibrium Modeling: A Survey and Critical Appraisal," International Regional Science Review, , vol. 21(3), pages 205-248, December.
    5. Valkonen, Tarmo, 2002. "Demographic Uncertainty and Taxes," Discussion Papers 816, The Research Institute of the Finnish Economy.
    6. Risto Vaittinen, 2004. "Trade Policies and Integration - Evaluations with CGE Models," Research Reports 109, Government Institute for Economic Research Finland (VATT).
    7. Matthew W. Peter & Mark Horridge & G.A.Meagher & Fazana Naqvi & B.R.Parmenter, 1996. "The Theoretical Structure of MONASH-MRF," Centre of Policy Studies/IMPACT Centre Working Papers op-85, Victoria University, Centre of Policy Studies/IMPACT Centre.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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

    Keywords

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:specan:v:4:y:2009:i:1:p:53-72. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/RSEA20 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.