IDEAS home Printed from https://ideas.repec.org/a/taf/specan/v12y2017i4p452-471.html
   My bibliography  Save this article

A two-step approach to account for unobserved spatial heterogeneity

Author

Listed:
  • Anna Gloria Billé
  • Roberto Benedetti
  • Paolo Postiglione

Abstract

A two-step approach to account for unobserved spatial heterogeneity. Spatial Economic Analysis. Empirical analysis in economics often faces the difficulty that the data are correlated and heterogeneous in some unknown form. Spatial econometric models have been widely used to account for dependence structures, but the problem of directly dealing with unobserved spatial heterogeneity has been largely unexplored. The problem can be serious particularly if we have no prior information justified by economic theory. In this paper we propose a two-step procedure to identify endogenously spatial regimes in the first step and to account for spatial dependence in the second step. This procedure is applied to hedonic house price analysis.

Suggested Citation

  • Anna Gloria Billé & Roberto Benedetti & Paolo Postiglione, 2017. "A two-step approach to account for unobserved spatial heterogeneity," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(4), pages 452-471, October.
  • Handle: RePEc:taf:specan:v:12:y:2017:i:4:p:452-471
    DOI: 10.1080/17421772.2017.1286373
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/17421772.2017.1286373
    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. Marie Lebreton, 2005. "A NCSTAR model as an alternative to the GWR model," Post-Print hal-00282161, HAL.
    2. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    3. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    4. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2013. "Estimation of the spatial weights matrix under structural constraints," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 617-634.
    5. Holly, Sean & Hashem Pesaran, M. & Yamagata, Takashi, 2011. "The spatial and temporal diffusion of house prices in the UK," Journal of Urban Economics, Elsevier, vol. 69(1), pages 2-23, January.
    6. A S Fotheringham & M E Charlton & C Brunsdon, 1998. "Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis," Environment and Planning A, , vol. 30(11), pages 1905-1927, November.
    7. Lung-Fei Lee & Jihai Yu, 2009. "Spatial Nonstationarity and Spurious Regression: the Case with a Row-normalized Spatial Weights Matrix," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(3), pages 301-327.
    8. LeSage, James P. & Kelley Pace, R., 2007. "A matrix exponential spatial specification," Journal of Econometrics, Elsevier, vol. 140(1), pages 190-214, September.
    9. McMillen Daniel P., 1994. "Vintage Growth and Population Density: An Empirical Investigation," Journal of Urban Economics, Elsevier, vol. 36(3), pages 333-352, November.
    10. James P. LeSage & R. Kelley Pace, 2014. "The Biggest Myth in Spatial Econometrics," Econometrics, MDPI, Open Access Journal, vol. 2(4), pages 1-33, December.
    11. Dubin, Robin A., 1992. "Spatial autocorrelation and neighborhood quality," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 433-452, September.
    12. Seya, Hajime & Yamagata, Yoshiki & Tsutsumi, Morito, 2013. "Automatic selection of a spatial weight matrix in spatial econometrics: Application to a spatial hedonic approach," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 429-444.
    13. Paolo Postiglione & M. Andreano & Roberto Benedetti, 2013. "Using Constrained Optimization for the Identification of Convergence Clubs," Computational Economics, Springer;Society for Computational Economics, vol. 42(2), pages 151-174, August.
    14. Craig A Watkins, 2001. "The Definition and Identification of Housing Submarkets," Environment and Planning A, , vol. 33(12), pages 2235-2253, December.
    15. Thomas De Graaff & Raymond J.C.M. Florax & Peter Nijkamp & Aura Reggiani, 2001. "A General Misspecification Test for Spatial Regression Models: Dependence, Heterogeneity, and Nonlinearity," Journal of Regional Science, Wiley Blackwell, vol. 41(2), pages 255-276, May.
    16. Getis, Arthur, 2007. "Reflections on spatial autocorrelation," Regional Science and Urban Economics, Elsevier, vol. 37(4), pages 491-496, July.
    17. Lebreton, Marie, 2005. "The NCSTAR model as an alternative to the GWR model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 77-84.
    18. Pede, Valerien O. & Florax, Raymond J.G.M. & Lambert, Dayton M., 2014. "Spatial econometric STAR models: Lagrange multiplier tests, Monte Carlo simulations and an empirical application," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 118-128.
    19. Daniel P. McMillen, 2003. "Spatial Autocorrelation Or Model Misspecification?," International Regional Science Review, , vol. 26(2), pages 208-217, April.
    20. Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B., 2011. "Inference with dependent data using cluster covariance estimators," Journal of Econometrics, Elsevier, vol. 165(2), pages 137-151.
    21. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    22. Jørgen Lauridsen & Reinhold Kosfeld, 2006. "A test strategy for spurious spatial regression, spatial nonstationarity, and spatial cointegration," Papers in Regional Science, Wiley Blackwell, vol. 85(3), pages 363-377, August.
    23. J. Polzehl & V. G. Spokoiny, 2000. "Adaptive weights smoothing with applications to image restoration," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 335-354.
    24. Bernard Fingleton, 1999. "Estimates of Time to Economic Convergence: An Analysis of Regions of the European Union," International Regional Science Review, , vol. 22(1), pages 5-34, April.
    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. Burhan Can Karahasan, 2020. "Winners and losers of rapid growth in Turkey: Analysis of the spatial variability of convergence," Papers in Regional Science, Wiley Blackwell, vol. 99(3), pages 603-644, June.
    2. Luca Salvati & Margherita Carlucci, 2020. "Shaping Dimensions of Urban Complexity: The Role of Economic Structure and Socio-Demographic Local Contexts," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(1), pages 263-285, January.
    3. Richard H. Rijnks & Stephen Sheppard, 2018. "Occupant Well-Being and House Values," Department of Economics Working Papers 2018-05, Department of Economics, Williams College.
    4. A. G. Billé & C. Salvioni & R. Benedetti, 2018. "Modelling spatial regimes in farms technologies," Journal of Productivity Analysis, Springer, vol. 49(2), pages 173-185, June.
    5. Sabina Buczkowska & Nicolas Coulombel & Matthieu Lapparent, 2019. "A comparison of Euclidean Distance, Travel Times, and Network Distances in Location Choice Mixture Models," Networks and Spatial Economics, Springer, vol. 19(4), pages 1215-1248, December.
    6. Richard H. Rijnks & Stephen Sheppard, 2020. "Occupant Well-Being and House Values," Department of Economics Working Papers 2020-09, Department of Economics, Williams College.

    More about this item

    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:12:y:2017:i:4:p:452-471. 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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.