Abstract
Spatial econometrics is concerned with modelling dependent observations indexed by points in a space. Complicated patterns of interdependence can be parsimoniously described in terms of these points’ locations. Covariances between observations, for example, can be modelled as functions of their distances. Index spaces are not limited to the physical space or times inhabited by economic agents and can be as abstract as required by the economics of the application. This entry discusses the use of generalized method of moments and other common estimators with spatial data, as well as simultaneous equation methods specialized to certain types of spatial data.
Keywords
- Data generation processes
- Generalized method of moments
- Heteroskedasticity and autocovariance
- Index space
- Inference
- Interactions-based models
- Kernels
- Locations/distances
- Maximum likelihood estimators
- Nonparametric estimators
- Simultaneous equations models
- Simultaneous spatial autoregression
- Spatial correlation
- Spatial econometrics
- Spatial weights matrix
- Spectral density
- Spectral methods
- Time series models
- Unobservable variables
JEL Classifications
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsBibliography
Andrews, D. 2005. Cross-section regression with common shocks. Econometrica 73: 1551–1585.
Anselin, L. 1988. Spatial econometrics: Methods and models. Boston: Kluwer Academic Publishers.
Anselin, L. 1995. Local indicators of spatial association. Geographical Analysis 27: 93–115.
Barry, R., and R. Pace. 1999. A Monte Carlo estimator of the log determinant of large sparse matrices. Linear Algebra and its Applications 289: 41–54.
Bartlett, M. 1955. An introduction to stochastic processes. Cambridge: Cambridge University Press.
Bester, C. 2005a. Random field and affine models for interest rates: An empirical comparison. Working paper. University of Chicago.
Bester, C. 2005b. Bond and option pricing in random field models. Working paper. University of Chicago.
Bolthausen, E. 1982. On the central limit theorem for stationary mixing random fields. Annals of Probability 10: 1047–1050.
Brock, W., and S. Durlauf. 2001. Interactions-based models. In Handbook of econometrics, 5th edn., ed. J. Heckman and E. Leamer. Amsterdam: North-Holland.
Case, A., J. Hines, and H. Rosen. 1993. Budget spillovers and fiscal policy interdependence: Evidence from the states. Journal of Public Economics 52: 285–307.
Chen, X., and T. Conley. 2001. A new semiparametric spatial model for panel time series. Journal of Econometrics 105: 59–83.
Cliff, A., and J. Ord. 1981. Spatial processes. London: Pion Limited.
Conley, T. 1996. Econometric modeling of cross-sectional dependence. Ph.D. thesis. University of Chicago.
Conley, T. 1999. GMM estimation with cross sectional dependence. Journal of Econometrics 92: 1–45.
Conley, T., and E. Ligon. 2002. Economic distance, spillovers, and cross country comparisons. Journal of Economic Growth 7: 157–187.
Conley, T., and F. Molinari. 2007. Spatial correlation robust inference with errors in location or distance. Journal of Econometrics 140(1): 76–96.
Conley, T., and G. Topa. 2002. Socio-economic distance and spatial patterns in unemployment. Journal of Applied Econometrics 17: 303–327.
Geary, R. 1954. The contiguity ratio and statistical mapping. Incorporated Statistician 5: 115–145.
Giacomini, F., and C. Granger. 2004. Aggregation of space–time processes. Journal of Econometrics 118: 7–26.
Grenander, U. and M. Rosenblatt. 1957. Some problems in estimating the spectrum of a time series. In: Proceedings of the third berkeley symposium on mathematical statistics and probability, vol. 7. p. 77–93.
Hansen, L. 1982. Large sample properties of generalized method of moments estimators. Econometrica 50: 1029–1054.
Kelejian, H., and I. Prucha. 1999. A Generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review 40: 509–533.
Kelejian, H., and I. Prucha. 2001. On the asymptotic distribution of the Moran I test statistic with applications. Journal of Econometrics 104: 219–257.
Kelejian, H., and I. Prucha. 2007. HAC estimation in a spatial framework. Journal of Econometrics 140(1): 131–154.
Lee, L. 2004a. Asymptotic distributions of quasi-maximum likelihood estimators for spatial autoregressive models. Econometrica 72: 1899–1925.
Lee, L. 2004b. Identification and estimation of spatial econometric models with group interactions, contextual factors and fixed effects. Working paper. Ohio State University.
Lee, L. 2007. GMM and 2SLS estimation of mixed regressive, spatial autoregressive models. Journal of Econometrics 140(1): 155–189.
LeSage, J., and R. Pace. 2007. A matrix exponential spatial specification. Journal of Econometrics 140(1): 190–214.
Mardia, K., and R. Marshall. 1984. Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71: 135–146.
Martellosio, F. 2004. The correlation structure of spatial autoregressions. Working paper. University of Southampton.
Moran, P. 1950. Notes on continuous stochastic phenomena. Biometrika 37: 17–23.
Pace, R., and R. Barry. 1997. Quick computation of regressions with a spatially autoregressive dependent variable. Geographical Analysis 29: 232–247.
Pinkse, J., M. Slade, and C. Brett. 2002. Spatial price competition: A semiparametric approach. Econometrica 70: 1111–1153.
Priestley, M. 1964. Analysis of two-dimensional processes with discontinous spectra. Biometrika 51: 195–217.
Priestley, M. 1981. Spectral analysis and time series, vol. 2, New York: Academic Press.
Takahata, H. 1983. On the rates in the central limit theorem for weakly dependent random fields. Zeitschrift fur Wahrscheinlichkeitstheorie und verwandte Gebiete 64: 445–456.
Wall, M. 2004. A close look at the spatial structure implied by the CAR and SAR models. Journal of Statistical Planning and Inference 121: 311–324.
Whittle, P. 1954. On stationary processes on the plane. Biometrika 2: 434–449.
Wooldridge, J. 2003. Cluster-sample methods in applied econometrics. American Economic Review 93: 133–138.
Author information
Authors and Affiliations
Editor information
Copyright information
© 2018 Macmillan Publishers Ltd.
About this entry
Cite this entry
Conley, T.G. (2018). Spatial Econometrics. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2023
Download citation
DOI: https://doi.org/10.1057/978-1-349-95189-5_2023
Published:
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-95188-8
Online ISBN: 978-1-349-95189-5
eBook Packages: Economics and FinanceReference Module Humanities and Social SciencesReference Module Business, Economics and Social Sciences