Spatial Econometrics

A Companion to Theoretical Econometrics

Volumn , Issue , 2007, Pages 310-330

  Anselin, Luc ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84954245560     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470996249.ch15     Document Type: Chapter

References (76)

1. Anselin, L. (1980). Estimation Methods for Spatial Autoregressive Structures. Regional Science Dissertation and Monograph Series 8. Field of Regional Science, Cornell University, Ithaca, N.Y.
2. Anselin, L. (1988a). Spatial Econometrics: Methods and Models. Kluwer Academic, Dordrecht. Anselin, L. (1988b). A test for spatial autocorrelation in seemingly unrelated regressions. Economics Letters 28, 335-41.
3. Anselin, L. (1988c). Lagrange multiplier test diagnostics for spatial dependence and spatial heterogeneity. Geographical Analysis 20, 1-17.
4. Anselin, L. (1990). Some robust approaches to testing and estimation in spatial econometrics. Regional Science and Urban Economics 20, 141-63.
5. Anselin, L. (1992a). Space and applied econometrics. Special Issue, Regional Science and Urban Economics 22.
6. Anselin, L. (1992b). SpaceStat, a Software Program for the Analysis of Spatial Data. National Center for Geographic Information and Analysis, University of California, Santa Barbara, CA.
7. Anselin, L. (1998). SpaceStat Version 1.90. http://www.spacestat.com.
8. Anselin, L. (1999). Spatial econometrics, An updated review. Regional Economics Applications Laboratory (REAL), University of Illinois, Urbana-Champaign.
9. Anselin, L. (2000). Rao's score test in spatial econometrics. Journal of Statistical Planning and Inference (forthcoming).
10. Anselin, L., and A. Bera (1998). Spatial dependence in linear regression models with an introduction to spatial econometrics. In A. Ullah and D.E.A. Giles (eds.) Handbook of Applied Economic Statistics, pp. 237-89. New York: Marcel Dekker.
11. Anselin, L., and R. Florax (1995a). Introduction. In L. Anselin and R. Florax (eds.) New Directions in Spatial Econometrics, pp. 3-18. Berlin: Springer-Verlag.
12. Anselin, L., and R. Florax (1995b). Small sample properties of tests for spatial dependence in regression models: some further results. In L. Anselin and R. Florax (eds.) New Directions in Spatial Econometrics, pp. 21-74. Berlin: Springer-Verlag.
13. Anselin, L., and R. Florax (2000). Advances in Spatial Econometrics. Heidelberg: Springer- Verlag.
14. Anselin, L., and S. Hudak (1992). Spatial econometrics in practice, a review of software options. Regional Science and Urban Economics 22, 509-36.
15. Anselin, L., and H.H. Kelejian (1997). Testing for spatial error autocorrelation in the presence of endogenous regressors. International Regional Science Review 20, 153-82.
16. Anselin, L., and S. Rey (1991). Properties of tests for spatial dependence in linear regression models. Geographical Analysis 23, 112-31.
17. Anselin, L., and S. Rey (1997). Introduction to the special issue on spatial econometrics. International Regional Science Review 20, 1-7.
18. Anselin, L., A. Bera, R. Florax, and M. Yoon (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics 26, 77-104.
19. Baltagi, B., and D. Li (2000a). Double length artificial regressions for testing spatial dependence. Econometric Review, forthcoming.
20. Baltagi, B., and D. Li (2000b). Prediction in the panel data model with spatial correlation. In L. Anselin and R. Florax (eds.) Advances in Spatial Econometrics. Heidelberg: Springer- Verlag.
21. Barry, R.P., and R.K. Pace (1999). Monte Carlo estimates of the log determinant of large sparse matrices. Linear Algebra and its Applications 289, 41-54.
22. Basu, S., and T.G. Thibodeau (1998). Analysis of spatial autocorrelation in housing prices. Journal of Real Estate Finance and Economics 17, 61-85.
23. Bell, K.P., and N.E. Bockstael (2000). Applying the generalized moments estimation approach to spatial problems involving micro-level data. Review of Economics and Statistics 82, 72-82.
24. Beron, K.J., and W.P.M. Vijverberg (2000). Probit in a spatial context: a Monte Carlo approach. In L. Anselin and R. Florax (eds.) Advances in Spatial Econometrics. Heidelberg: Springer-Verlag.
25. Besag, J. (1974). Spatial interaction and the statistical analysis of lattice systems. Journal of the Royal Statistical Society B 36, 192-225.
26. Besag, J., and P.A.P. Moran (1975). On the estimation and testing of spatial interaction in Gaussian lattice processes. Biometrika 62, 555-62.
27. Bolthausen, E. (1982). On the central limit theorem for stationary mixing random fields. Annals of Probability 10, 1047-50.
28. Brett, C., and J. Pinkse (1997). Those taxes all over the map! A test for spatial independence of municipal tax rates in British Columbia. International Regional Science Review 20, 131-51.
29. Brock, W.A., and S.N. Durlauf (1995). Discrete choice with social interactions I: Theory. NBER Working Paper No. W5291. Cambridge, MA: National Bureau of Economic Research.
30. Burridge, P. (1980). On the Cliff-Ord test for spatial autocorrelation. Journal of the Royal Statistical Society B 42, 107-8.
31. Case, A. (1992). Neighborhood influence and technological change. Regional Science and Urban Economics 22, 491-508.
32. Case, A., H.S. Rosen, and J.R. Hines (1993). Budget spillovers and fiscal policy interdependence: evidence from the States. Journal of Public Economics 52, 285-307.
33. Cliff, A., and J.K. Ord (1973). Spatial Autocorrelation. London: Pion.
34. Cliff, A., and J.K. Ord (1981). Spatial Processes: Models and Applications. London: Pion.
35. Conley, T.G. (1996). Econometric modelling of cross-sectional dependence. Ph.D. dissertation. Department of Economics, University of Chicago, Chicago, IL.
36. Cressie, N. (1993). Statistics for Spatial Data. New York: Wiley.
37. Davidson, J. (1994). Stochastic Limit Theory. Oxford: Oxford University Press.
38. Davidson, R. and J.G. MacKinnon (1988). Double-length artificial regressions. Oxford Bulletin of Economics and Statistics 50, 203-17.
39. Driscoll, J.C., and A.C. Kraay (1998). Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics 80, 549-60.
40. Dubin, R. (1988). Estimation of regression coefficients in the presence of spatially autocorrelated error terms. Review of Economics and Statistics 70, 466-74.
41. Dubin, R. (1992). Spatial autocorrelation and neighborhood quality. Regional Science and Urban Economics 22, 433-52.
42. Frees, E.W. (1995). Assessing cross-sectional correlation in panel data. Journal of Econometrics 69, 393-414.
43. Haining, R. (1990). Spatial Data Analysis in the Social and Environmental Sciences. Cambridge: Cambridge University Press.
44. Hansen, L.P. (1982). Large sample properties of generalized method of moments estimators. Econometrica 50, 1029-54.
45. Kelejian, H., and I. Prucha (1997). Estimation of spatial regression models with autoregressive errors by two stage least squares procedures: a serious problem. International Regional Science Review 20, 103-11.
46. Kelejian, H., and I. Prucha (1998). A generalized spatial two stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbances. Journal of Real Estate Finance and Economics 17, 99-121.
47. Kelejian, H., and I. Prucha (1999a). A generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review 40, 509-33.
48. Kelejian, H.H., and I. Prucha (1999b). On the asymptotic distribution of the Moran I test statistic with applications. Working Paper, Department of Economics, University of Maryland, College Park, MD.
49. Kelejian, H.H., and D.P. Robinson (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.
50. Kelejian, H.H., and D.P. Robinson (1998). A suggested test for spatial autocorrelation and/or heteroskedasticity and corresponding Monte Carlo results. Regional Science and Urban Economics 28, 389-417.
51. Kelejian, H.H., and D.P. Robinson (2000). The influence of spatially correlated heteroskedasticity on tests for spatial correlation. In L. Anselin and R. Florax (eds.) Advances in Spatial Econometrics. Heidelberg: Springer-Verlag (forthcoming).
52. King, M. (1981). A small sample property of the Cliff-Ord test for spatial correlation. Journal of the Royal Statistical Society B 43, 263-4.
53. Lahiri, S.N. (1996). On the inconsistency of estimators under infill asymptotics for spatial data. Sankhya A 58, 403-17.
54. 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).
55. Mardia, K.V., and R.J. Marshall (1984). Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71, 135-46.
56. MathSoft (1996). S+SpatialStats User's Manual for Windows and Unix. Seattle, WA: MathSoft, Inc.
57. McMillen, D.P. (1992). Probit with spatial autocorrelation. Journal of Regional Science 32, 335-48.
58. Moran, P.A.P. (1948). The interpretation of statistical maps. Biometrika 35, 255-60.
59. Newey, W.K., and K.D. West (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55, 703-8.
60. Ord, J.K. (1975). Estimation methods for models of spatial interaction. Journal of the American Statistical Association 70, 120-6.
61. Pace, R.K., and R. Barry (1997a). Sparse spatial autoregressions. Statistics and Probability Letters 33, 291-7.
62. Pace, R.K., and R. Barry (1997b). Quick computation of spatial autoregressive estimators. Geographical Analysis 29, 232-46.
63. Pace, R.K., and R. Barry (1998). Spatial Statistics Toolbox 1.0. Real Estate Research Institute, Lousiana State University, Baton Rouge, LA.
64. Pace, R.K., R. Barry, C.F. Sirmans (1998). Spatial statistics and real estate. Journal of Real Estate Finance and Economics 17, 5-13.
65. Paelinck, J., and L. Klaassen (1979). Spatial Econometrics. Farnborough: Saxon House.
66. Pinkse, J. (1998). Asymptotic properties of the Moran and related tests and a test for spatial correlation in probit models. Working Paper, Department of Economics, University of British Columbia, Vancouver, BC.
67. Pinkse, J. (2000). Moran-flavored tests with nuisance parameters. In L. Anselin and R. Florax (eds.) Advances in Spatial Econometrics. Heidelberg: Springer-Verlag.
68. Pinkse, J., and M.E. Slade (1998). Contracting in space: an application of spatial statistics to discrete-choice models. Journal of Econometrics 85, 125-54.
69. Poirier, D.J., and P.A. Ruud (1988). Probit with dependent observations. Review of Economic Studies 55, 593-614.
70. Pötscher, B.M., and I.R. Prucha (1997). Dynamic Nonlinear Econometric Models. Berlin: Springer.
71. Rao, C.R. (1973). Linear Statistical Inference and its Applications (2nd edn). New York: Wiley.
72. Schmidt, P. (1976). Econometrics. New York: Marcel Dekker.
73. Smirnov, O., and L. Anselin (2000). Fast maximum likelihood estimation of very large spatial autoregressive models: a characteristic polynomial approach. Computational Statistics and Data Analysis.
74. Upton, G.J., and B. Fingleton (1985). Spatial Data Analysis by Example. Volume 1: Point Pattern and Quantitative Data. New York: Wiley.
75. Vijverberg, W. (1997). Monte Carlo evaluation of multivariate normal probabilities. Journal of Econometrics 76, 281-307.
76. Whittle, P. (1954). On stationary processes in the plane. Biometrika 41, 434-49.