Demographic Change

The population of the world has more than doubled since the 1960s, exceeding 7 billion in 2014 and it is predicted this will rise to 9.1 billion by 2050. Low levels of fertility and continuous improvements in life expectancy are ageing the world's population at an unprecedented rate.

In the UK, 2010 marked a turning point as the first of the baby boomers born between 1945 and 1970 turned 65. In the next quarter century, as population cohorts move into the older ages, there will be even greater ageing with wide-ranging implications for health care, wealth distribution, pension provision, housing, transport and employment policies.

Edge Analytics is expert in demographic forecasting and scenario planning.

Demographic Forecasting

Planning Policy

Demographic change is a key issue for the 21st century. The inevitability of population ageing, the global economic recession and increasing fears over the long-term threat of climate change, combine to present a hugely uncertain future.

At a time of such uncertainty, robust and timely 'evidence' is key to effective policy formulation for national and local government, to support economic development and to deliver targeted public services.

Likewise, in the business sector, knowledge development underpins economic growth and the provision of goods and services to an evolving consumer profile. Demographic analysis lies at the heart of a Scenario Planning process that facilitates the evaluation of alternative outcomes and delivers the evidence-based planning so crucial to policy-makers

Demographic Forecasting

Methods & Models

The most effective planning infrastructure is one which combines the experience and local knowledge of an analyst, with relevant data sources and a robust and appropriate suite of modelling utilities. Cohort-component models allow demographic estimation and projection and test policy-based forecasts of economic and demographic growth.

A similar cohort-based approach enables forecasts of school and pupil numbers to be derived.

Optimisation models provide a flexible evaluation of cost/distance minimisation scenarios, the maximisation of service provision or the equalisation of catchment/territory size. Spatial interaction methods provide the most elegant replication of consumer behaviour, modelling the interaction between where people live and where they work, shop, go to school, keep fit, receive health care etc.


News & Press

POPGROUP User Group Meeting 2016 Update

22nd November 2016

A list of speakers for this year's POPGROUP User Group meeting has now been confirmed.

The annual POPGROUP User Group meeting will be held in Birmingham on Wednesday 7th December

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POPGROUP Training Course November 2016 Reminder

24th October 2016

This is a final reminder of our POPGROUP Training Course which will be held on 23rd November 2016 at Rose Bowl, Leeds Beckett University.

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