Transcript Population estimates for census output areas: deriving a base and implementing a forecasting model

Estimating Hampshire’s Population
at Output Area level
Simon Brown
Senior Research Officer
Research and Communications
Objectives
• Estimate the private residential household
population of Hampshire by single year of
age, gender and census output area (OA)
• Estimate the number of students and armed
forces (and their dependants) in private
households
• Residents in communal establishments to be
handled separately
Source data
• All data sourced from the 2001 census
• Data available at OA level by gender and year
of age up to 24, then by 5 year age groups up
to age 90
• Disclosure control means values under 4 have
been replaced with a 0 or 3
The 0-24 year old population
• Desirable to re-introduce values of 1 and 2 to
obtain a more realistic population distribution
• Half of the 3s were replaced with 2s, then a
proportion of 0s were changed to 1s so that
the sum of the OAs matched the ward totals
• The specific 0s and 3s to be changed were
randomly selected
The 25-74 year old population
• Only 5 year age-bands available for OAs, but
individual year of age available for lower super
output areas (LSOAs)
• LSOAs typically contain between 4 and 6 OAs, and
have a population of around 1,500
• OA age-band totals split out into individual years of
age using the age structure from the relevant LSOA
• Estimates then scaled to ward totals by year of age
and gender
The 75 and over population
• Only ward level data available for single year
of age and gender
• OA level data is for 5 year age-groups from
75-89, then for 90 and over (by gender)
• Age-group totals adjusted to introduce values
of ‘1’ and ‘2’
• Split into individual year of age using ward
age structure
Rounding estimates to whole
numbers
• More intuitive to have a base-population
made up of whole numbers
• Estimates for 25-99 year old population
generally not whole numbers due to scaling
• Decimals rounded up or down by
comparison with a rounded number so that
low decimals, such as ‘0.1’, would occasionally
be rounded up
Students & Military
• Need to separately identify these groups in
population forecasting model as their
migration propensities are very different to
other residents
• Net effect is that the size and age of these
populations tends to be roughly constant
Students
• Ward level data available on students living in private
households and not with their parents (Theme Table
2)
• Students assumed to be aged between 18-24
• Commissioned a table showing OA totals for
students in households and not with parents
• Ward population distributed to OAs
• Estimates rounded
Members of the Armed Forces
(AF) and dependants
• Census data only available at district level due
to disclosure control
• Table AF1 contains number of AF members
in private households
• Table AF2 contains number of persons in
households with an AF representative
• Both tables used to estimate total AF
members and dependants by age and gender
Members of the Armed Forces
(AF) and dependants 2
• Commissioned a table based on UV81
showing OA totals for AF members in
households
• OA totals used to distribute district level
estimates for AF members and their
dependants
Running the population forecasting
model
• Produces population estimates by year of age,
gender and output area
• Starts from 2001 base population and
currently runs up to 2012
• Covers population change resulting from:
– Dwellings gains and losses
– Natural change of population
– Other in and out migration
Modelling in Excel
• Model was initially built in Excel with the aim
of transparency
• 4 large files for each district per year
• Total size of model around 12GB (3DVDs)
• Slow to run, even with a macro
• Easy for mistakes to be made in formulae
• Any changes to model would be cumbersome
Moving to model into Visual Basic
• Visual Basic (VB) comes with Excel and is
used to write or record macros
• Initially we used VB to open and close the
Excel files in order and insert correction
factors
• Realised that quite simple code, handling
arrays of data, could be used to run the
whole model
Improvements with VB
• One piece of code used to produce forecasts for all
districts for all years
• Less chance of manual error and much quicker to
make changes
• Model reduced to less than 1mb in size (about 0.1%
of Excel model size)
• Produces population forecasts for a district by OA,
age and gender for 12 years in around 30 seconds
(approx. 1 million values)
Current status of model
• Base population and necessary factors stored
in Excel files
• VB code picks up this data, performs the
calculations and outputs back into Excel
• Model produces a summary showing annual
births, deaths, migration etc. by ward
• Results for wards, parishes and urban areas
are up on our website
Viewing our forecasts
• Our website address:
http://www3.hants.gov.uk/environmentstatistics/population.htm
• Thanks for listening. Any questions?