Time-trend in spatial dependence: Specification strategy in the first-order spatial autoregressive model

López, Fernando and Chasco, Coro (2007): Time-trend in spatial dependence: Specification strategy in the first-order spatial autoregressive model.

Abstract

The purpose of this article is to analyze if spatial dependence is a synchronic effect in the first-order spatial autoregressive model, SAR(1). Spatial dependence can be not only contemporary but also time-lagged in many socio-economic phenomena. In this paper, we use three Moran-based space-time autocorrelation statistics to evaluate the simultaneity of this spatial effect. A simulation study shed some light upon these issues, demonstrating the capacity of these tests to identify the structure (only instant, only time-lagged or both instant and time-lagged) of spatial dependence in most cases.

• Item Type: MPRA Paper
• Institution: Universidad Autónoma de Madrid
• Language: English
• Keywords: Space-time dependence; Spatial autoregressive models; Moran’s I
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions

References

Anselin, L. (1988) Spatial econometrics: methods and models (Boston, Kluwer Academic Publishers) Anselin, L, J. Le Gallo & H. Jayet (2006) Spatial panel econometrics, in: Matyas L & P. Sevestre (eds) The econometrics of panel data (Boston, Kluwer Academic Publishers) Anselin, L, I. Syabri & O. Smirnov (2002) Visualizing multivariate spatial correlation with dynamically linked windows, in: Anselin L & S. Rey (eds) New tools in spatial data analysis. Proceedings of a workshop, Center for Spatially Integrated Social Science, University of California, Santa Barbara, CDROM Baltagi, B.H. & D. Li (2003) Prediction in the panel data model with spatial correlation, in: Anselin L, R. Florax & S. Rey (eds) New Advances in Spatial Econometrics (Berlin, Heidelberg, New York, Springer) Baltagi, B.H., S.H. Song & W. Koh (2003) Testing panel data regression models with spatial error correlation, Journal of Econometrics, 117-1, pp. 123-150 Bennett, R.J. (1979) Spatial time series: forecasting and control (London, Pion) Case, A. (1991) Spatial patterns in household demand. Econometrica, 59, pp. 953–965 Cressie, N. (1993) Statistics for Spatial Data (New York, Wiley) Cliff, A. & Ord, J. (1981) Spatial processes, models and applications. (London, Pion) Elhorst, J.P. (2001) Dynamic models in space and time, Geographical Analysis, 33, pp. 119-140. Elhorst, J.P. (2003). Specification and estimation of spatial panel data models, International Regional Science Review, 26(3), pp. 244–268 Florax, R., H. Folmer & S. Rey (2003) Specification searches in spatial econometrics: the relevance of Hendry’s methodology, Regional Science and Urban Economics, 33, pp. 557-579 Griffith, D.A., J. Arbia (2006) Effects of negative spatial autocorrelation in regression modeling of georeferenced random variables. I Workshop in Spatial Econometrics, Rome, 25-27 2006 Lee, S-I (2001) Developing a bivariate spatial association measure: an integration of Pearson’s r and Moran’s I, Journal of Geographical Systems, 3, pp. 369-385 Martin, R.L., J.E. Oeppen (1975) The identification of regional forecasting models using space: time correlation functions, Transactions of the Institute of British Geographers, 66, pp. 95-118 Mobley, L.R. (2003) Estimating hospital market pricing: an equilibrium approach using spatial econometrics, Regional Science and Urban Economics, 33, pp. 489–516 Pace, R.K., R. Barry, J.M. Clapp & M. Rodríguez (1998) Spatiotemporal autoregressive models of neighborhood effects, Journal of Real State Finance and Economics, 17(1), pp. 15-33 Pace, R.K., R. Barry, O.W. Gilley & C.F. Sirmans (2000) A method for spatial-temporal forecasting with an application to real estate prices, International. Journal of Forecasting, 16, pp. 229-246 Pfeifer, P.E. & S.J. Deutsch (1980) Identification and interpretation of first-order space-time ARMA Models,Technometrics, 22(3), pp. 397-403 Upton, G. & B. Fingleton (1985) Spatial data analysis by example: volume 1 point pattern and quantitative data (New York, Wiley) Whittle, P. (1954) On stationary processes in the plane, Biometrika, 41, pp. 434-449 Yilmaz, S., K.E. Haynes & M. Dinc (2002) Geographic and network neighbors: spillonver effects of telecommunications infrastructure, Journal of Regional Science, 42-2, pp. 339-360