The Cathie Marsh Centre for Census and Survey Research

 Making local population statistics
Researchers: Ludi Simpson (CCSR), with Ian Diamond, University of Southampton.
ESRC, ALCD - 1997 - 1998

 Population estimates for small areas are used for a wide range of planning and policy development in government and business, throughout the developed world. Population totals and age structures derived from the national census quickly become out of date for most areas.

This project has provided a written guide to the available materials and methods for updating local census demography between census years. The work builds on the successful examination of the accuracy of different methods, which formed part of the ESRC’s Analysis of Large and Complex Datasets program 1993-1996. It draws on the experience of local authority practitioners in each country of Britain, to provide a critical view of current practice and best practice. It was piloted at workshops in London and Edinburgh.

The book comprises:

  1. What population statistics do you need? A guide for commissioners
  2. Making local population statistics: a checklist to work through
  3. Methods: three review sections, and three case studies
  4. Data sources: nine comprehensive resource chapters, including on patient records and government statistics
  5. Issues: Accuracy, dealing with uncertainty, census quality, forecasting and others
  6. Index.

The guide discusses the feasibility of a consistent national set of population estimates for electoral wards and smaller areas, which is the subject of a current proposal from CCSR to ESRC.

Making local population statistics: a guide for practitioners.

Edited by Stephen Ludi Simpson for the Estimating with Confidence project. Published 1998 by LARIA, the Local Authorities Research and Intelligence Association. £40 (postage and packing included, from LARIA, 9 Cortland Road, Nunthorpe, Middlesbrough, TS7 OJX Tel: 01642 316576 Fax: 01642 314892 Email: lariaoffice@aol.com

Funded by ESRC as a training project within phase 2 of the Analysis of Large and Complex Datasets programme

University of Manchester CCSR