Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
references
Anselin, L. (1988a). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers, Dordrecht, The Netherlands.
Anselin, L. (1988b). A test for spatial autocorrelation in seemingly unrelated regressions. Economics Letters, 28:335–341.
Anselin, L. (1990).Some robust approaches to testing and estimation in spatial econometrics.Regional Science and Urban Economics, 20:141–163.
Anselin, L. (2001a). Rao’s score test in spatial econometrics. Journal of Statistical Planning and Inference, 97:113–139.
Anselin, L. (2001b). Spatial econometrics. In Baltagi, Badi, editor, A Companion to Theoretical Econometrics, pages 310–330. Blackwell, Oxford.
Anselin, L. (2002). Under the hood. Issues in the specification and interpretation of spatial regression models.Agricultural Economics, 27(3):247–267.
Anselin, L. (2003). Spatial externalities, spatial multipliers and spatial econometrics. International Regional Science Review, 26(2):153–166.
Anselin, L. and Bera, A. (1998). Spatial dependence in linear regression models with an introduction to spatial econometrics.In Ullah, Amman and Giles, David E.A., editors, Handbook of Applied Economic Statistics, pages 237–289. Marcel Dekker, New York.
Anselin, L., Bera, A., Florax, Raymond J.G.M., and Yoon, M. (1996).Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics, 26:77–104.
Anselin, L. and Florax, Raymond J.G.M. (1995). New Directions in Spatial Econometrics. Springer-Verlag, Berlin.
Anselin, L., Florax, Raymond J.G.M., and Rey, Sergio J. (2004). Econometrics for spatial models, recent advances. In Anselin, Luc, Florax, Raymond J.G.M., and Rey, Sergio J., editors,Advances in Spatial Econometrics. Methodology, Tools and Applications,pages 1–25. Springer-Verlag, Berlin.
Anselin, L. and Le Gallo, J. (2004). Panel Data Spatial Econometrics with PySpace. Spatial Analysis Laboratory (SAL). Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign, IL.
Anselin, L. and Moreno, R. (2003). Properties of tests for spatial error components.Regional Science and Urban Economics, 33(5):595–618.
Anselin, L., Syabri, I., and Kho, Y. (2006). Geoda, an introduction to spatial data analysis. Geographical Analysis. 38(1):5–22.
Arellano, M. (2003). Panel Data Econometrics. Oxford University Press, Oxford, United Kingdom.
Baltagi, Badi H. (2001). Econometric Analysis of Panel Data (Second Edition). John Wiley & Sons, Chichester, United Kingdom.
Baltagi, Badi H., Egger, P., and Pfaffermayr, M. (2006). A generalized spatial panel data model with random effects. Working paper, Syracuse University, Syracuse, NY.
Baltagi, Badi H., Song, Seuck H., Jung, Byoung C., and Koh, W. (2007). Testing for serial correlation, spatial autocorrelation and random effects using panel data.Journal of Econometrics, 140(1):5–51.
Baltagi, Badi H., Song, Seuck H., and Koh, W. (2003). Testing panel data regression models with spatial error correlation. Journal of Econometrics, 117:123–150.
Banerjee, S., Carlin, Bradley P., and Gelfand, Alan E. (2004). Hierarchical Modeling and Analysis for Spatial Data. Chapman & Hall/CRC, Boca Raton, FL.
Barry, Ronald P. and Pace, R. Kelley (1999). Monte Carlo estimates of the log determinant of large sparse matrices.Linear Algebra and its Applications, 289:41–54.
Bivand, R. (2002).Spatial econometrics functions in R: Classes and methods.Journal of Geographical Systems, 4:405–421.
Brock, William A. and Durlauf, Steven N. (2001). Discrete choice with social interactions. Review of Economic Studies, 68(2):235–260.
Brueckner, Jan K. (2003). Strategic interaction among governments: An overview of empirical studies.International Regional Science Review, 26(2):175–188.
Burridge, P. (1980). On the Cliff-Ord test for spatial autocorrelation. Journal of the Royal Statistical Society B, 42:107–108.
Case, Anne C. (1991). Spatial patterns in household demand. Econometrica, 59:953–965.
Case, Anne C. (1992). Neighborhood influence and technological change. Regional Science and Urban Economics, 22:491–508.
Case, Anne C., Rosen, Harvey S., and Hines, James R. (1993). Budget spillovers and fiscal policy interdependence: Evidence from the states.Journal of Public Economics, 52:285–307.
Casetti, E. (1997). The expansion method, mathematical modeling, and spatial econometrics.International Regional Science Review, 20:9–33.
Chen, X. and Conley, Timothy G. (2001). A new semiparametric spatial model for panel time series. Journal of Econometrics, 105:59–83.
Cliff, A. and Ord, J. Keith (1981). Spatial Processes: Models and Applications. Pion, London.
Coakley, J., Fuentes, A.-M., and Smith, R. (2002). A principal components approach to cross-section dependence in panels.Working Paper, Department of Economics, Birkbeck College, University of London, London, United Kingdom.
Conley, Timothy G. (1999). GMM estimation with cross-sectional dependence. Journal of Econometrics, 92:1–45.
Conley, Timothy G. and Ligon, E. (2002). Economic distance, spillovers and cross country comparisons. Journal of Economic Growth, 7:157–187.
Conley, Timothy G. and Topa, G. (2002). Socio-economic distance and spatial patterns in unemployment. Journal of Applied Econometrics, 17:303–327.
Cressie, N. and Huang, H.-C. (1999). Classes of nonseparable spatio-temporal stationary covariance functions.Journal of the American Statistical Association, 94:1330–1340.
Cressie, N. (1993).Statistics for Spatial Data. Wiley, New York.
Driscoll, John C. and Kraay, Aart C. (1998). Consistent covariance matrix estimation with spatially dependent panel data.The Review of Economics and Statistics, 80:549–560.
Druska, V. and Horrace, William C. (2004). Generalized moments estimation for spatial panel data: Indonesian rice farming.American Journal of Agricultural Economics, 86(1):185–198.
Dubin, R. (1988). Estimation of regression coefficients in the presence of spatially autocorrelated errors.Review of Economics and Statistics, 70:466–474.
Dubin, R. (1995). Estimating logit models with spatial dependence. In Anselin, Luc and Florax, Raymond J.G.M., editors, New Directions in Spatial Econometrics, pages 229–242. Springer-Verlag, Berlin.
, Elhorst, J. Paul (2001). Dynamic models in space and time. Geographical Analysis, 33:119–140.
Elhorst, J. Paul (2003). Specification and estimation of spatial panel data models. International Regional Science Review, 26(3):244–268.
Fazekas, I., Florax, R., and Folmer, H. (1994). On maximum likelihood estimators of parameters of spatio-temporal econometric models.Technical Report No. 109/1994, Kossuth University, Debrecen,Hungary.
Florax, Raymond J.G.M. and Van Der Vlist, Arno J. (2003). Spatial econometric data analysis: Moving beyond traditional models. International Regional Science Review, 26(3):223–243.
Fotheringham, A. Stewart, Brunsdon, C., and Charlton, M. (2002). Geographically Weighted Regression. John Wiley, Chichester.
Gamerman, D., Moreira, Ajax R.B., and Rue, H. (2003). Space-varying regression models: Specifications and simulation. Computational Statistics & Data Analysis, 42(3):513–533.
Gelfand, Alan E., Kim, H.-J., Sirmans, C.F., and Banerjee, S. (2003). Spatial modeling with spatially varying coefficient processes. Journal of the American Statistical Association, 98:387–396.
Giacomini, R. and Granger, Clive W.J. (2004). Aggregation of space-time processes. Journal of Econometrics, 118:7–26.
Glaeser, Edward L., Sacerdote, Bruce I., and Scheinkman, Jose A. (2002).The social multiplier. Technical Report 9153, NBER, Cambridge, MA 02138.
Haining, R. (1990). Spatial Data Analysis in the Social and Environmental Sciences. Cambridge University Press, Cambridge.
Hsiao, C. (1986). Analysis of Panel Data. Cambridge University Press, Cambridge.
Hsiao, C. and Pesaran, M. Hashem (2008). Random coefficient panel data models. In Matyas L. and Sevestre P., editors, The Econometrics of Panel Data. Kuwer Academic Publishers, Dordrecht.
Hsiao, C., Pesaran, M. Hashem, and Tahmiscioglu, A. Kamil (2002). Maximum likelihood estimation of fixed effects dynamic panel models covering short time periods.Journal of Econometrics, 109:107–150.
Kapoor, M., Kelejian, Harry H., and Prucha, Ingmar R. (2007). Panel data models with spatially correlated error components. Journal of Econometrics, 140(1):97–130.
Kelejian, Harry H. and Prucha, I. (1998). A generalized spatial two stage least squares procedures for estimating a spatial autoregressive model with autoregressive disturbances. Journal of Real Estate Finance and Economics, 17:99–121.
Kelejian, Harry H. and Prucha, I. (1999). A generalized moments estimator for the autoregressive parameter in a spatial model.International Economic Review, 40:509–533.
Kelejian, Harry H. and Robinson, Dennis P. (1993). A suggested method of estimation for spatial interdependent models with autocorrelated errors, and an application to a county expenditure model. Papers in Regional Science, 72:297–312.
, Kelejian, Harry H. and Robinson, Dennis P. (1995). Spatial correlation: A suggested alternative to the autoregressive model.In Anselin, Luc and Florax, Raymond J.G.M., editors, New Directions in Spatial Econometrics, pages 75–95. Springer-Verlag, Berlin.
Kelejian, Harry H. and Robinson, Dennis P. (1998). A suggested test for spatial autocorrelation and/or heteroskedasticity and corresponding Monte Carlo results. Regional Science and Urban Economics, 28:389–417.
Lee, L.-F. (2002). Consistency and efficiency of least squares estimation for mixed regressive, spatial autoregressive models.Econometric Theory, 18(2):252–277.
Lee, L.-F. (2003). Best spatial two-stage least squares estimators for a spatial autoregressive model with autoregressive disturbances. Econometric Reviews, 22:307–335.
Magnus, J. (1978). Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix.Journal of Econometrics, 7:281–312.Corrigenda, Journal of Econometrics 10, 261.
Manski, Charles F. (1993). Identification of endogenous social effects: The reflexion problem. Review of Economic Studies, 60:531–542.
Manski, Charles F. (2000). Economic analysis of social interactions. Journal of Economic Perspectives, 14(3):115–136.
Mardia, K.V. and Goodall, C. (1993). Spatio-temporal analyses of multivariate environmental monitoring data. In Patil, G.P. and Rao, C.R., editors, Multivariate Environmental Statistics, pages 347–386. Elsevier, Amsterdam.
Mardia, K.V. and Marshall, R.J. (1984). Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika, 71:135–146.
Ord, J. Keith (1975). Estimation methods for models of spatial interaction. Journal of the American Statistical Association, 70:120–126.
Pace, R. Kelley and Barry, R. (1997). Sparse spatial autoregressions. Statistics and Probability Letters, 33:291–297.
Paelinck, J. and Klaassen, L. (1979). Spatial Econometrics. Saxon House, Farnborough.
Pesaran, M. Hashem (2002). Estimation and inference in large heterogenous panels with cross section dependence. DAE Working Paper 0305 and CESifo Working Paper no. 869, University of Cambridge, Cambridge, United Kingdom.
Pesaran, M. Hashem (2004). General diagnostic tests for cross section dependence in panels. Working paper, University of Cambridge, Cambridge, United Kingdom.
Rey, Sergio J. and Montouri, Brett D. (1999). US regional income convergence: A spatial econometrics perspective. Regional Studies, 33:143–156.
Smirnov, O. and Anselin, L. (2001). Fast maximum likelihood estimation of very large spatial autoregressive models: A characteristic polynomial approach. Computational Statistics and Data Analysis, 35:301–319.
Stein, Michael L. (1999). Interpolation of Spatial Data, Some Theory for Kriging. Springer-Verlag, New York.
Topa, G. (2001). Social interactions, local spillover and unemployment. Review of Economic Studies, 68(2):261–295.
Upton, Graham J. and Fingleton, B. (1985). Spatial Data Analysis by Example. Vol. 1: Point Pattern and Quantitative Data. Wiley, New York.
Waller, L., Carlin, B., and Xia, H. (1997a). Structuring correlation within hierarchical spatio-temporal models for disease rates. In Grègoire, T., Brillinger, D., Russek-Cohen, P., Warren, W., and Wolfinger, R., editors, Modeling Longitudinal and Spatially Correlated Data, pages 309–319. Springer-Verlag, New York.
Waller, L., Carlin, B., Xia, H., and Gelfand, A. (1997b). Hierarchical spatio-temporal mapping of disease rates. Journal of the American Statistical Association, 92:607–617.
Wikle, Christopher K., Berliner, L. Mark, and Cressie, N. (1998). Hierarchical Bayesian space-time models. Environmental and Ecological Statistics, 5:117–154.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Anselin, L., Gallo, J.L., Jayet, H. (2008). Spatial Panel Econometrics. In: Mátyás, L., Sevestre, P. (eds) The Econometrics of Panel Data. Advanced Studies in Theoretical and Applied Econometrics, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75892-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-75892-1_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75889-1
Online ISBN: 978-3-540-75892-1
eBook Packages: Business and EconomicsEconomics and Finance (R0)