Data on geographical concentrations of economic activities, such as manufacturing, construction, wholesale and retail trade, financial services, etc., are important for identifying clusters of economic activities (EAs) and concentrations of forces behind them. However, such data are essentially sparse due to limited reporting by individual countries and administrative entities. For example, at present, Eurostat provides EA data for <50% of all regional subdivisions of the third tier of the Nomenclature of Territorial Units for Statistics (NUTS3). Measurements of light at night (LAN), as captured by satellite sensors, are likely to differ in intensity, depending on the source. As a result, LAN levels can become a marker for EAs; the present study attempts to verify this possibility. As the present analysis indicates, the inclusion of LAN intensities in multivariate models (in addition to standard economic and locational variables) helps to explain up to 88.8% of the EA variation, performing especially well for manufacturing, construction, and agriculture (the adjusted coefficient of determination (R2-adjusted) is in the range of 0.754–0.888). The study thus confirms the feasibility of using LAN satellite measurements for reconstructing geographical patterns of EAs, information that may be restricted or is unavailable due to sparse or incomplete reporting.
Bibliographical notePublisher Copyright:
© 2014, Taylor & Francis.
ASJC Scopus subject areas
- Earth and Planetary Sciences (all)