Assessing the Space-Time Structure with a Multidimensional Perspective

Authors

DOI:

https://doi.org/10.18778/0208-6018.292.04

Abstract

This study presents some remarks on procedure for space-time process investigation by the use of multidimensional panel spatial autoregressive model. It is shown that information on the strength and significance of the spatial interactions is given by the model. Motivation for the use of multidimensional dependence structure as well as some empirical examples are provided. It is argued that such approach could allow for more accurate description of the spatial dependence, whose true form often has a spatio-temporal character. It is emphasised that failure to recognise these multidimensional effects may lead to incorrect inference and therefore to biased conclusions.

Downloads

Download data is not yet available.

References

Anselin L. (1988), Spatial Econometrics: Methods and Models, Kluwer, Dordrecht.
Google Scholar DOI: https://doi.org/10.1007/978-94-015-7799-1

Anselin L., Bera A.K. (1998), Spatial dependence in linear regression models with an introduction to spatial econometrics, (in:) Ullah A., Giles D. (eds.), Handbook of Applied Economic Statistics, Marcel Dekker, New York.
Google Scholar

Anselin L., Smirnov O. (1996), Efficient algorithms for constructing proper higher order spatial lag operators, Journal of Regional Science, Wiley, 36.
Google Scholar DOI: https://doi.org/10.1111/j.1467-9787.1996.tb01101.x

Besner C. (2002), A Spatial Autoregressive Specification with a Comparable Sales Weighting Scheme, Journal of Real Estate Research, American Real Estate Society, New York, 24
Google Scholar DOI: https://doi.org/10.1080/10835547.2002.12091092

Bodson P., Peeters D. (1975), Estimations of the Coefficients of a Linear Regression in the Presence of Spatial Autocorrelation: An Application to a Belgian Labour-Demand Function,'Environment and Planning' A 7 (4)
Google Scholar DOI: https://doi.org/10.1068/a070455

Cliff A., Ord, J.K. (1981), Spatial Processes: Models and Applications, London: Pion.
Google Scholar

Dacey M.F. (1968), A Review of Measures of Contiguity for Two and K-Color Maps, (in): Englewood Cliffs Spatial Analysis: A Reader in Statistical Geography, Prentice-Hall.
Google Scholar

Deng M. (2008), An anisotropic Model For Spatial Processes, Geographical Analysis, Wiley 40(1).
Google Scholar DOI: https://doi.org/10.1111/j.0016-7363.2007.00712.x

EUROSTAT (2002), European Regional Statistics. Reference guide, European Communities, Luxembourg.
Google Scholar

Fingleton B. (2006), The new economic geography versus urban economics: an evaluation using local wage rates in Great Britain, Oxford Economic Papers, 58.
Google Scholar DOI: https://doi.org/10.1093/oep/gpl006

Fujita M., Krugman P., Venables A. (1999), The Spatial Economy: Cities, Regions, and International Trade, MIT Press, Cambridge MA.
Google Scholar DOI: https://doi.org/10.7551/mitpress/6389.001.0001

Getis A., Aldstadt J.(2004), Constructing the Spatial Weights Matrix Using A Local Stearic,'Geographical Analysis', Wiley, 36
Google Scholar DOI: https://doi.org/10.1353/geo.2004.0002

Kelejian H.H., Prucha I.R. (1998), A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances, 'Journal of Real Estate Finance and Economies', Springer, 17
Google Scholar

Mankiw N., Romer D. Weil D. (1992), A contribution to the Empirics of Growth, Quarterly Journal of Economics, 107.
Google Scholar DOI: https://doi.org/10.2307/2118477

Olejnik A. (2008), Using the spatial autoregressively distributed lag model in assessing the regional convergence of per-capita income in the EU25, Papers in Regional Science, Wiley, 87/3.
Google Scholar DOI: https://doi.org/10.1111/j.1435-5957.2008.00190.x

Olejnik A. (2012a), Multidimensional spatial process of productivity growth in EU 22, working paper.
Google Scholar

Olejnik A. (2012b), Spatial autoregressive model - a multidimensional perspective with an example study of the spatial income process in the EU 25, working paper.
Google Scholar

Ord J.K., Getis A. (1995), Local Spatial Autocorrelation Statistics: Distributional Issues and an Application, 'Geographical Analysis' 27.
Google Scholar DOI: https://doi.org/10.1111/j.1538-4632.1995.tb00912.x

Downloads

Published

2013-01-01

How to Cite

Olejnik, A. (2013). Assessing the Space-Time Structure with a Multidimensional Perspective. Acta Universitatis Lodziensis. Folia Oeconomica, (292), 37–45. https://doi.org/10.18778/0208-6018.292.04

Issue

Section

Articles