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A two-step approach to account for unobserved spatial heterogeneity

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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