Abstract copyright UK Data Service and data collection copyright owner.
This research project aims to provide an in-depth study of the problems encountered in developing quantitative socio-economic indicators for urban and regional policy analysis in Britain. The project consisted of two stages. The data from the first stage of the study are held under SN:3973. The aims of this part of the study, the second stage, are to address two main objectives, through : 1. The compilation of a meta-database to assess the quality of information sources that are relevant to Local Economic Development (LED), which will provide useful guidelines for future public data compilation practice and will be of use to other researchers in the field. 2. The compilation of an up-to-date database of indicators for LED for the analysis of the following : what extent the existence of information gaps in public statistical sources affects indicator research on LED; which particular dimension of LED is most affected; what other non-public sources of information are available for the measurement of LED; what are the best data handling techniques to explore the statistical properties of indicators and to carry out preliminary validation analysis of the assembled database; in what ways could innovative data processing and analysis enhance the interpretation of indicators and maximise the intelligence yielded from the information available; in what form should indicators be aggregated to gear to the needs of policy-makers; what are the most appropriate weighting methods to create multivariate indexes; in what ways do different weighting methods affect the outcome of the final analysis.
Main Topics:
The data file for this study contains 61 variables from the 366 Local Authority Districts in England (before the 1996 local government reorganisation of boundaries). Apart from the LAD (Local Authority District) code and the matching UALAD (Unitary Authority and Local Authority District) code, the other 59 variables are indicators measuring different contributing factors to the process of LED. Eleven key factors were identified, through literature review and a survey of policy-makers, to be important to the process of LED : locational factors, physical factors, infrastructure, human resources, finance and capital, knowledge and technology, industrial structure, business culture, community image and identity, institutional capacity and quality of life. Standardisation was applied to the raw data to develop some indicators to enhance interpretation. In some cases, the raw data are expressed as a percentage share of the national sum; in other cases, the case value is expressed as a ratio of the national (English) average value.
No sampling (total universe)
Compilation or synthesis of existing material
