understand and plan for demand on services and resources • To allow governments to formulate policy based on evidence • Demography is at the heart of all human systems • Planning, environment, inclusion, health
world’s fastest growing populations Puts pressure on already strained resources However, where young populations are growing this provides an opportunity for rapid economic growth known as the demographic dividend
people for each person aged over 65 • Provides a measure of the ‘burden’ placed on the working age population • Implications for health and social care as well as economic pressures 0 2 4 6 8 10 12 14 1950 1970 1990 2000 2005 2010 2015 2020 2030 2050 2075 2100 number working age to 65+ Potential Support Ratio Sub-Saharan Africa Spain Source: Author’s calculations from https://population.un.org/wpp/
Kaa 1987): fertility falls below replacement (due to the rise in contraception use and women in the workforce) Third demographic transition (Coleman 2006): when smaller birth cohorts reach the labour market, the demand for labour rises, and is filled by international migration Fourth demographic transition (Frey 2015): the spatial distribution of ethnic minorities (of immigrant origin) shifts from their initial places of settlement (mainly large cities) to other parts of the country
you use • Can create scenarios where you alter the assumptions about the input data Deterministic • Based on running the model many times, sampling from a range of possibilities in the component dataset • Usually report the average and quantify the uncertainty that exists Probabilistic
assumes high fertility, life expectancy and net migration 4.3 million above principal projection "low population" variant assumes low fertility, life expectancy and net migration 5.2 million below principal projection
with the General Register Office and this is a legal requirement. Age of mother and sex of child is recorded Deaths are registered with the General Register Office and this is a legal requirement. Reported by age, sex and local authority of residence International migration data comes primarily from a survey at the border called the International Passenger Survey Internal migration data comes from re-registrations with a doctor reported in NHS data (and other adjustments, e.g. for university students)
Resident population in base year •e.g. an 18 year old becomes 19 Age on the resident population •Age specific fertility rate calculated from most recent five-year trend Add births •Age specific mortality rate calculated from most recent five-year trend •In migration assigned using a migration matrix Subtract deaths •Age specific out migration rate calculated from most recent two-year trend Add and subtract internal migrants •Age and sex international migration trend – most recent five-year average Add and subtract international migrants
0.30 0.40 0.50 4 9 141924293439444954596469747984899499 Probability of dying Age Age Specific Mortality Male Female Source: ONS, https://bit.ly/3dw9NKW Source: author calculations from ONS, https://bit.ly/2UdrW9o
80.0 100.0 120.0 140.0 160.0 under 18 under 20 20-24 25-29 30-34 35-39 40-44 45 and over Births per 1,000 women Age Specific Fertility Rates (2019) Islington Camden Bradford Slough Source: https://www.ons.gov.uk/visualisations/dvc417/index.html
education have fewer children. Better education is associated with lower mortality, better health, and different migration patterns” • Lutz and Samir (2011) It is well established that demographic rates vary substantially by ethnic group • Coleman (2010) Lutz, W. and Samir, K.C., 2011. Global human capital: Integrating education and population. Science, 333(6042), pp.587-592. Coleman, D. (2006). Immigration and ethnic change in low-fertility countries: A third demographic transition. Population and development Review, 401-446.
2061 • Baseline scenario results Immigration Emigration Net White British 6,338,023 7,822,886 -1,484,863 Black Caribbean 177,491 301,973 -124,482 Bangladeshi 266,143 232,433 33,709 Other Black 164,182 116,796 47,386 Mixed 802,122 435,129 366,993 Pakistani 1,077,808 501,435 576,373 Other 1,237,843 419,949 817,894 Black African 1,368,427 417,984 950,444 Other Asian 1,864,125 787,998 1,076,127 Chinese 2,070,552 774,963 1,295,588 Indian 2,345,361 756,360 1,589,001 White Other 10,203,796 3,671,332 6,532,464 Total 27,915,872 16,239,237 11,676,635
fit to previous migration data, continuation of trends and interpretation of policy Lomax, N., Wohland, P., Rees, P. and Norman, P., 2020. The impacts of international migration on the UK’s ethnic populations. Journal of Ethnic and Migration Studies, 46(1), pp.177-199.
population estimates year to June 2020 have just been released Provides a glimpse of the effects of COVID-19 on population change Deaths 13% higher than the previous year Internal migration down 11% on the previous year International migration very similar to previous year Number of births was lowest since 2003 (but continuation of trend) Lowest growth in two decades
and assumptions used in population projections • Global data from the United Nations • UK data from the ONS Think about (and challenge) the validity of model outputs • “All models are wrong, but some are useful” (George E. P. Box)
https://population.un.org/wpp • Office for National Statistics National population projection data and method: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/pop ulationprojections/bulletins/nationalpopulationprojections/2018based • Office for National Statistics subnational population projection data and methods: https://www.ons.gov.uk/releases/subnationalpopulationprojectionsforengland2018base d • CDRC maps: https://maps.cdrc.ac.uk • Van de Kaa, D. J. (1987). Europe's second demographic transition. Population bulletin, 42, 1-59. • Coleman, D. (2006). Immigration and ethnic change in low-fertility countries: A third demographic transition. Population and development Review, 401-446. • Frey, W. H. (2015). Diversity explosion: How new racial demographics are remaking America. Brookings Institution Press.