Abstract
Like in the economic literature (see discussion in 3) space does not play an important role in the econometric literature. Although geographers and regional scientists have been interested in the quantitative analysis of spatial processes for quite a long time1, econometricians (if we distinguish between econometrics and statistics as the first being driven by economic models whereas the latter is driven rather by data) discovered the phenomenon of space only recently and (as is true for virtually all economic textbooks) space is absent in all major econometric textbooks. Anselin [1988] is one of the first comprehensive textbooks that discusses the problems the inclusion of space will cause in econometric analysis and suggests different methods to tackle them.
Everything is related to everything else, but near things are more related than distant things Waldo
Tobler
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References
See Garrison [1967], Berry and Marble [1968], Cliff and Ord [1972, 1973, 1981] or Upton and Fingleton [1985].
See Lützel [1971], Deitmer [1993] or Keilbach [1993] for a detailed description of this method.
This assumption has been investigated in a number of studies. See e.g. Seitz [1993], Seitz [1995b], Seitz and Licht [1995] or Mas, Maudo, Perez and Uriel [1996].
see e.g. Wolfram [1994, p.212] or Gaylord and Wellin [1995]
Cited from Anselin [1988].
See the discussion in Anselin [1988, p.21].
See e.g. Anselin [1988, p.9] or Klotz [1996, p.4].
Anselin [1988, p.34] considered a more general model where he allowed for heteroscedasticity in the error term, i.e. u ~ N(0, Ω), where Ω ii = h i = 0. As discussed above however, I will not consider the case of heteroscedasticity here.
See e.g. Greene [1991] or Griffiths, Hill and Judge [1993].
See e.g. Greene [1991, p.388] or Griffiths et al. [1993, part V] for a detailed description of the GLS or EGLS pocedures and how it is related to ML estimation.
See e.g. Griffiths et al. [l993, p.453] for a description.
See again the discussion Seitz [1993], Seitz [1995b], Seitz and Licht [1995] or Mas et al. [1996] and the results published there.
Seitz [1998] suggested this approach in a discussion.
Details on the MRW-data will not be discussed here, nor will the data be reproduced. The interested reader might want to refer to the original publication. The dataset is however extended to account for spatial relationships. Ciccone [1997] also used the MRW-data to investigate international diffusion of technology, where he used a similar approach.
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Keilbach, M. (2000). Spatial Processes in the Economy — an Empirical Investigation. In: Spatial Knowledge Spillovers and the Dynamics of Agglomeration and Regional Growth. Contributions to Economics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57698-0_6
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DOI: https://doi.org/10.1007/978-3-642-57698-0_6
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