ESRC Research Methods Festival
St Catherine’s College, Oxford, 6 July 2010
Session 20
Research Methods for Population Projection
Convenors
John Stillwell, UPTAP, University of Leeds
and
James Raymer, CPC, University of Southampton
Abstract
This strand of the Festival is aimed at demonstrating the alternative methods that
researchers adopt when confronted with the task of producing population projections.
The session is organised jointly by two ESRC investments - Understanding
Population Trends and Processes (UPTAP) and the Centre of Population Change
(CPC). The focus of the session will be twofold: (i) methods of projecting ethnic
populations (continuing the ethnic theme of the UPTAP morning session) and (ii)
population modelling more generally. The former will demonstrate the methods used
to project the various components (fertility, mortality and migration) of ethnic
population change whilst the latter will include the construction of multistate (matrix)
population model, adding uncertainty to population modelling, and parameterising the
age patterns of demographic variables in projection models.
Chair: John Stillwell, University of Leeds
14.00-14.25 Dynamic multistate population models
James Raymer, University of Southampton
Dynamic multistate population models provide a general and flexible platform for
modelling and analysing population change over time. They allow the combination of
all the main components of population change by age and sex with various transitions
that population group may experience throughout their life course. The transitions
may include those between states of residences, employment, marriage or health.
Furthermore, disaggregations by subnational areas and characteristics (e.g., nativity)
are also possible. However, despite the many theoretical and analytical advantages,
these models have been relatively unexplored because of the large amount of input
data required (which are not always available over time) and complex calculations
required to perform the estimations and analyses. In this presentation, we outline the
general population modelling framework currently being developed as part of the new
ESRC Centre for Population Change.
14.25-14.50 Estimating fertility by ethnic group and other subpopulations
Sylvie Dubuc, University of Oxford
Projecting fertility by ethnic and other sub-populations remains a challenge for national
projection models. Apart from census data, little data is available, at least in the UK, to
estimate fertility rates and thus fertility trends by ethnic and religious groups between
censuses. Previously, the Labour Force Survey (LFS) has been exploited to produce
national total fertility rates (TFR) by ethnic groups up to 2001 using the reverse-survival
Own Children Method (OCM). Here the LFS-OCM is assessed and refined to improve
accuracy and tested against official statistics. The LFS-OCM is compared with results
obtained using more straightforward techniques based on Child-Women Ratios (CWR)
using the same LFS data, and differences are discussed. The refined method is applied to
produce recent fertility profiles by ethnic groups, including trends in the TFR and age
specific fertility rates (ASFR), showing significant and decreasing differences between
groups. Furthermore, the method allows to reliably investigating TFR within one ethnic
group by other criteria, as illustrated by religious belonging and country of births enabling
a more subtle understanding of fertility dynamic within major ethnic groups.
14.50-15.15 The future ethnic mix of UK local populations, 2007 to 2057
Pia Wohland, Paul Norman, Peter Boden and Phil Rees, University of Leeds
This presentation describes a model used to project the ethnic populations of UK local
areas. Estimates of ethnic mortality, fertility, international and internal migration are
updated from a 2001 benchmark to 2007 to establish new jump off populations and
trends. Assumptions for the next fifty years are then developed using a combination of
those in the principal national projection and our ethnic analysis. The results reveal
that profound changes are in train for the ethnic mix of the UK’s population and its
local areas.
15.15-15.30 Discussion
15.30-16.00 Tea
Chair: James Raymer, University of Southampton
16.00-16.25 Bayesian forecasting and issues of uncertainty
Jakub Bijak, University of Southampton
Bayesian methods for forecasting populations are introduced in this presentation.
These methods allow the combination of empirical data and expert judgements, as
well as measures of data and model uncertainty. They also provide a more transparent
approach to population modelling. The general Bayesian framework will be compared
against other (classical) approaches to modelling populations with uncertainty
measures.
16.25-16.50 Alternative futures for the UK’s local ethnic populations: sensitivity
and scenario analyses
Paul Norman, Pia Wohland, Peter Boden and Phil Rees, University of Leeds
This presentation will discusses the uncertainties of a projection of the UK’s local
ethnic populations. The sensitivity of the projections to alternative mortality, fertility,
international and internal migration assumptions is tested. For example, we compare
trend projections (Wohland et al., 2010) with projections with no ethnic differences.
We also explore scenarios where ethnic differences converge, remain stable or
diverge. The results provide a range of outcomes around a trend projection which
indicate the aspects of population development in UK local areas which are certain
and which are uncertain.
16.50-17.15 Modelling the age patterns of demographic events
Guy Abel, University of Southampton
Demographic events, such as fertility, mortality and migration, tend to exhibit strong
regularities in their age patterns. Modelling these age patterns over time permits a
relatively concise representation of the history of demographic patterns. In addition,
time series methods can be implemented to allow histories to be extended to project
future patterns. This can be done in numerous ways. In this presentation, parametric
functions and relational models are compared for historical mortality and fertility data
in the UK. Finally, some strategies for incorporating these models into projections are
explored.
17.15-17.30 Discussion