Estimating Hampshire’s Population at Output Area level Simon Brown Senior Research Officer Research and Communications.

Slides:



Advertisements
Similar presentations
Household Projections for England Yolanda Ruiz DCLG 16 th July 2012.
Advertisements

1 State & County Characteristics: Overview The basics State –The general method –July 1, 2000 beginning population –Domestic migration IRS pre-processing.
Statistics Estimates and Sample Sizes
Projecting transient populations - pragmatism or technical correctness? BSPS Conference Sep 2004 Richard CooperResearch team Nottinghamshire County Council.
Bosna i Hercegovina Agencija za statistiku Bosne i Hercegovine Bosna i Hercegovina Agencija za statistiku Bosne i Hercegovine Post-enumeration Survey-A.
Life Opportunities Survey (LOS) Wave 2 Weighting Andy Fallows and Sangeetha Gallagher.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 7.3 Estimating a Population mean µ (σ known) Objective Find the confidence.
Population Estimates 2012 Texas State Data Center Conference for Data Users May 22, 2012 Austin, TX.
Dealing With A Future Which Is in Perpetual Construction---Washington State Provisional Projection by Age, Sex And Race/Ethnicity: Office of.
What’s New in ArcGIS 9.3 and SchoolSite 9.3. A Summary of All New Features ArcGIS 9.3
Availability of population estimates and projections Project EASY nowfuture -2-3 ONS Borough Ward LSOA EASY ONS EASY GLA Social Infrastructure Planning.
Sample of Anonymised Records: User Meeting Propensity to migrate by ethnic group: 1991 & 2001 Paul Norman 1, John Stillwell 2 & Serena Hussain 2 School.
Chapter 8 Estimating Single Population Parameters
SADC Course in Statistics Introduction and Study Objectives (Session 01)
Population Modelling in the London Thames Gateway - a new approach for small area geographies Professor Allan J. Brimicombe BA(Hons) M.Phil. Ph.D. C.Geog.
Robin Edwards H ampshire County Council Population and Household Forecasts for Output Areas Methods and Uses.
School Roll Forecasting in Aberdeenshire Richard Belding Aberdeenshire Council.
Household Projections for Northern Ireland 9 th September 2009 Dr David Marshall & Dr Jos IJpelaar Demography & Methodology Branch Northern Ireland Statistics.
Joint Canada/U.S. Health Survey Catherine Simile, National Center for Health Statistics Patrice Mathieu, Statistics Canada Ed Rama, Statistics Canada NCHS.
Economics and Statistics Administration U.S. CENSUS BUREAU U.S. Department of Commerce Comparing IRS Exemptions to 2010 Census Population Counts Esther.
Household projections for Scotland Hugh Mackenzie April 2014.
United Nations Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Amman, Jordan,
Population Estimates and Projections in the U. S. John F. Long
Saadia GreenbergElena Fazio Office of Performance and Evaluation Administration on Aging US Department.
Presented by: Steve Barker Policy, Research and Economic Analysis Oklahoma Population Projections Through 2075.
Liesl Eathington Iowa Community Indicators Program Iowa State University October 2014.
Chapter 7 Sampling and Sampling Distributions Sampling Distribution of Sampling Distribution of Introduction to Sampling Distributions Introduction to.
Sampling The sampling errors are: for sample mean
1 1 Slide © 2005 Thomson/South-Western Chapter 7, Part A Sampling and Sampling Distributions Sampling Distribution of Sampling Distribution of Introduction.
1 Chapter 6. Section 6-1 and 6-2. Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION.
Population All members of a set which have a given characteristic. Population Data Data associated with a certain population. Population Parameter A measure.
Estimates and Sample Sizes Lecture – 7.4
Economics and Statistics Administration U.S. CENSUS BUREAU U.S. Department of Commerce Research on Estimating International Migration of the Foreign-Born.
General Register Office for S C O T L A N D information about Scotland's people General Register Office for Scotland “Information about Scotland’s people”
Register-Based Census 2011 in Slovenia – Some Quality Aspects Danilo Dolenc Statistical Office of the Republic of Slovenia UNECE-Eurostat Expert Group.
Smoothing mortality rates using R Gary Brown & Julie Mills.
Methodology for producing the revised back series of population estimates for Julie Jefferies Population and Demography Division Office for.
Scot Exec Course Nov/Dec 04 Survey design overview Gillian Raab Professor of Applied Statistics Napier University.
Sustainable rural populations: the case of two National Park areas Alan Marshall Ludi Simpson Cathie Marsh Centre for Census and Survey Research.
General Register Office for S C O T L A N D information about Scotland's people Demographic Statistics 2005 Cecilia Macintyre General Register Office for.
1 Measuring Uncertainty in Population Estimates at Local Authority Level Ruth Fulton, Bex Newell, Dorothee Schneider.
Metadata driven application for data processing – from local toward global solution Rudi Seljak Statistical Office of the Republic of Slovenia.
Teaching Research Methods: Resources for HE Social Sciences Practitioners Workshop 2: Using Census 2011.
General Register Office for S C O T L A N D information about Scotland's people Comparison between NHSCR and Community health index sources of migration.
In-depth Analysis of Census Data on Migration Country Course on Analysis and Dissemination of Population and Housing Census Data with Gender Concern
New Mexico Population Projections: Assumptions, Methods, Validation, and Results For the Data User Conference Geospatial and Population Studies University.
WP 19 Assessment of Statistical Disclosure Control Methods for the 2001 UK Census Natalie Shlomo University of Southampton Office for National Statistics.
Data delivery Eileen Howes 10 April Data Management and Analysis Group Summary What we wanted What we got What we want from 2011 Census.
Demographic change at small area level Small area statistics to develop public policy Paul Norman School of Geography, University of Leeds ESRC RES
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 7-5 Estimating a Population Variance.
Panel discussion: Q2a A.S. Young ILO Bureau of Statistics.
1 Chapter 6. Section 6-1 and 6-2. Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION.
Data Management and Analysis 29 th February 2008 John Hollis BSPS Meeting at LSE Data Management and Analysis Projections for London Boroughs.
The micro-geography of UK demographic change Paul Norman School of Geography, University of Leeds Understanding Population Trends & Processes.
Chapter 6: 1 Sampling. Introduction Sampling - the process of selecting observations Often not possible to collect information from all persons or other.
Household Projections Dorothy Watson General Register Office for Scotland Household Estimates and Projections Branch.
The micro-geography of UK demographic change Paul Norman Cathie Marsh Centre for Census & Survey Research (CCSR), University of Manchester ESRC.
United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Evaluation of Internal Migration Data Collected.
Household Projections for Wales Welsh Statistical Liaison Committee 6 th March 2014.
Confidence Intervals for a Population Proportion Excel.
O.Rudnytskyi, O.Gladun Demographic losses of Ukraine and other republics of the former Soviet Union in the Second World War Ptoukha Institute for Demography.
General Register Office for S C O T L A N D information about Scotland's people 1 Small Area Population Estimates for Scotland Quality Assurance Harvey.
Disparities between Metro’s Metroscope Model and the Demographers’ Forecasts Richard Lycan Institute on Aging, Portland State University Oregon Academy.
Data Management and Analysis John Hollis (GLA) BSPS Conference University of St Andrew’s 11 September 2007 Data Management and Analysis Further Alterations.
2011 Census Results.
Professor Allan J. Brimicombe
Piers Elias, Demography & Modelling Officer, TVU
Plans for the next results
Introduction to Sampling Distributions
Presentation transcript:

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 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 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 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: statistics/population.htm Thanks for listening. Any questions?