Simultaneous Spatial and Functional Form Transformations

R. Kelley Pace, Ronald Barry, V. Carlos Slawson and C. F. Sirmans
Additional contact information
R. Kelley Pace: Louisiana State University
Ronald Barry: University of Alaska
V. Carlos Slawson: Louisiana State University
C. F. Sirmans: University of Connecticut

Chapter 9 in Advances in Spatial Econometrics, 2004, pp 197-224 from Springer

Abstract: Abstract Technological advances such as the global positioning system (GPS) and low-cost, high-quality geographic information systems (GIS) have led to an explosion in the volume of large data sets with locational coordinates for each observation. For example, the Census provides large amounts of data for over 250,000 locations in the US (block groups). Moreover, geographic information systems can often provide approximate locational coordinates for street addresses (geocoding). Given the volume of business information, which contains a street address field, this allows the creation of extremely large spatial data sets. Such data, as well as other types of spatial data, often exhibit spatial dependence and thus require spatial statistical methods for efficient estimation, valid inference, and optimal prediction.

Keywords: Geographic Information System; Basis Vector; Baton Rouge; Spatial Weight Matrix; Spatial Transformation (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1007/978-3-662-05617-2_9

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