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A Functional Connectivity Approach for Modeling Cross-Sectional Dependence with an Application to the Estimation of Hedonic Housing Prices in Paris

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  • BRESSON G.
  • HSIAO C.

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Paper provided by ERMES, University Paris 2 in its series Working Papers ERMES with number 0810.

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Date of creation: 2008
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Handle: RePEc:erm:papers:0810

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References

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  1. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
  2. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  3. Bowman, F. Dubois, 2007. "Spatiotemporal Models for Region of Interest Analyses of Functional Neuroimaging Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 442-453, June.
  4. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
  5. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
  6. Conley, T.G. & Topa, G., 1999. "Socio-Economic Distance and Spatial Patterns in Unemployment," Working Papers 99-04, C.V. Starr Center for Applied Economics, New York University.
  7. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
  8. Dr. Peter Kenning & Hilke Plassmann, 2004. "NeuroEconomics," Experimental 0412005, EconWPA.
  9. Baltagi, Badi H. & Bresson, Georges, 2011. "Maximum likelihood estimation and Lagrange multiplier tests for panel seemingly unrelated regressions with spatial lag and spatial errors: An application to hedonic housing prices in Paris," Journal of Urban Economics, Elsevier, vol. 69(1), pages 24-42, January.
  10. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
  11. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
  12. Bresson G. & Hsiao C. & Pirotte A., 2007. "Assessing the Contribution of R&D to Total Factor Productivity – a Bayesian Approach to Account for Heterogeneity And Heteroscedasticity," Working Papers ERMES 0708, ERMES, University Paris 2.
  13. Peter C. B. Phillips & Donggyu Sul, 2003. "Dynamic panel estimation and homogeneity testing under cross section dependence *," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 217-259, 06.
  14. Swamy, P A V B, 1970. "Efficient Inference in a Random Coefficient Regression Model," Econometrica, Econometric Society, vol. 38(2), pages 311-23, March.
  15. Basu S. & Chib S., 2003. "Marginal Likelihood and Bayes Factors for Dirichlet Process Mixture Models," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 224-235, January.
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Cited by:
  1. Georges Bresson & Jean-Michel Etienne & Pierre Mohnen, 2011. "How important is innovation? A Bayesian factor-augmented productivity model on panel data," TEPP Working Paper 2011-06, TEPP.
  2. Harry Haupt & Cheng Hsiao, 2011. "Introduction to the special issue: interdisciplinary aspects of panel data analysis," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 325-327, December.
  3. Hermann Singer, 2011. "Continuous-discrete state-space modeling of panel data with nonlinear filter algorithms," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 375-413, December.
  4. Ertur, C. & Musolesi, A., 2013. "Weak and strong cross-sectional dependence: a panel data analysis of international technology diffusion," Working Papers 2013-09, Grenoble Applied Economics Laboratory (GAEL).
  5. Cern Ertur & Antonio Musolesi, 2012. "Spatial autoregressive spillovers vs unobserved common factors models. A panel data analysis of international technology diffusion," INRA UMR CESAER Working Papers 2012/9, INRA UMR CESAER, Centre d'’Economie et Sociologie appliquées à l'’Agriculture et aux Espaces Ruraux.

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