Aspects of the Analysis and Interpretation of Temporal and Spatial Data

Granger, Clive W. J.

doi:10.2307/2987783

Cited by 17 publications

(5 citation statements)

References 11 publications

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“…19–27), but otherwise does not touch upon statistical concerns related to model parameters. Early approaches towards explicit spatial methods were reflected in Granger (1969, 1974) and Fisher (1971). The latter dealt with ‘Econometric estimation with spatial dependence’.…”

Section: Stage 1 – Preconditions For Growthmentioning

confidence: 99%

Thirty years of spatial econometrics

Anselin¹

2010

Papers in Regional Science

573

333

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In this paper, I give a personal view on the development of the field of spatial econometrics during the past 30 years. I argue that it has moved from the margins to the mainstream of applied econometrics and social science methodology. I distinguish three broad phases in the development, which I refer to as preconditions, take off and maturity. For each of these phases I describe the main methodological focus and list major contributions. I conclude with some speculations about future directions. Copyright (c) 2010 the author(s). Journal compilation (c) 2010 RSAI.

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Section: Stage 1 – Preconditions For Growthmentioning

confidence: 99%

Thirty years of spatial econometrics

Anselin¹

2010

Papers in Regional Science

573

333

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“…*These problems include limitations of data, ambiguity regarding the proper units for the vertical axis, and what Stommel (1965) called the 'desperate thing' of assuming statistical staLionarity in physical and biological processes that most certainly do depend on absolute locations in space and time. The situation is even worse in terrestrial contexts (see Curry and Bannister, 1974;Cliff and 0rd, 1975;Granger, 1975;Haggett, 1976). Haury et al, 1978).…”

Section: The Significance Of Relative Scalementioning

confidence: 99%

Scales of climate impacts

Clark

1985

Climatic Change

171

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Climates, ecosystems, and societies interact over a tremendous range of temporal and spatial scales. Scholarly work on climate impacts has tended to emphasize ~fferent questions, variables, and modes of explanation depending on the primary scale of interest. Much of the current debate on cause and effect, vulnerability, marginality, and the like stems from uncritical or unconscious efforts to transfer experience, eonciusions, and insights across scales. This paper sketches a perspective from which the relative temporal and spatial dimensions of climatic, ecological, and social processes can be more clearly perceived, and their potential interactions more critically evaluated. Quantitative estimates of a variety of charaeterisLic scales are derived and compared, leading to specific recommendations for the design of climate impact studies.

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“…In the cross‐sectional setting, possible solutions in the mid‐1970s appeared to be “very dependent on the assumption of spatial stationarity. Without this assumption, or something very near it, I can see little hope for model building … I am, therefore, very pessimistic about the possibility of model building with purely spatial data” (Granger, 1975, p. 208).…”

Section: Space and Spatial Statisticsmentioning

confidence: 99%

“…Since then, the spatial statistics literature has shown strong growth, in particular among applied statisticians. Granger's concluding remark, that: “the quality of the data that geographers, economists or regional scientists have to deal with is too poor for the use of complicated methods to be worthwhile” (Granger, 1975, p. 209), now seems overly pessimistic. Giacomini and Granger (2004) find that aggregating forecasts from space‐time autoregressive models outperforms other aggregate forecasting methods in the presence of spatial correlation.…”

Section: Space and Spatial Statisticsmentioning

confidence: 99%

Implementing Representations of Space in Economic Geography*

Bivand

2008

Journal of Regional Science

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Since spatial issues have become more important in economic theory, it is of interest to examine how space is represented. In empirical terms, this concerns at least the representation of distance and proximity. Both of these may be represented and operationalized in a number of ways, with possible consequences for inferences when modeling. This question is related to the representation of spatial entities, and itself plays into the treatment of spatial dependence as substantive and/or just a nuisance. Because other disciplines face similar questions-for example ecology or epidemiology, their conceptualizations and operationalizations of space will also be used for comparative purposes.

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Aspects of the Analysis and Interpretation of Temporal and Spatial Data

Cited by 17 publications

References 11 publications

Thirty years of spatial econometrics

Thirty years of spatial econometrics

Scales of climate impacts

Implementing Representations of Space in Economic Geography*

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