How the Ageing Population Contributes to UK Economic Activity: A Microsimulation Analysis

AuthorTony Lawson
Publication Date01 November 2016
Date01 November 2016
Tony Lawson
In the United Kingdom, as in several other countries, increasing life expectancy
is leading to a shift in the age distribution of the population. Meanwhile, at the
level of individuals, spending patterns change as people age. This paper investi-
gates the extent to which demographic change is likely to affect household
spending patterns by combining the techniques of dynamic microsimulation with
an imputation method known as random assignment. While there has been signif-
icant concern about the economic cost of the ageing population, this paper finds
a potentially beneficial effect in the form of an increase in total spending for
most expenditure categories.
In many industrialised countries, increasing life expectancy and falling birth
rates are leading to structural population ageing where there is a rise in the
proportion of pensioners compared with those of working age. One of the
central issues in population economics has been concern about the fiscal
effects of this phenomenon and in particular, the affordability of the expected
increases in demand for pensions and healthcare. According to (Brown et al.,
2011), the debate on population ageing can be divided into two sides. One is
the ‘crisis’ perspective which sees the ageing population as being unaffordable
and a threat to the stability of welfare systems (World Bank, 1994). The other
is the ‘manageability’ perspective which argues that by taking into account a
range of other factors, such as the compression of morbidity and the long-
term trend towards increasing industrial productivity, the ageing population
presents less of a problem that it appears when considering its costs in isola-
tion (Mullan, 2000).
This paper focuses on a further consequence of population ageing which is
a change in aggregate household spending patterns. As people move through
the life-course, their income and spending preferences vary. Consequently, as
University of Strathclyde
Scottish Journal of Political Economy, DOI: 10.1111/sjpe.12106, Vol. 63, No. 5, November 2016
©2016 Scottish Economic Society.
the age distribution of the population changes, there will be a shift in the way
aggregate household spending is allocated. This may have significant implica-
tions for the demand for goods in different economic sectors and then on
employment and the demand for resources. It will also have an effect on the
characteristics of consumers such as age and household composition which
will have implications for the production and marketing of goods.
It is not surprising therefore that there have been a number of attempts, in
several countries, to analyse the effect of an ageing population on household
spending patterns. Lefebvre (2006) used a pseudo panel method to project
spending for 10 composite goods in Belgium. Takeuchi (2009) investigated
household expenditure for a range of goods in Japan by re-weighting
observed spending patterns according to official population projections. Luhr-
mann (2008) used a Quadratic Almost Ideal Demand System (QAIDS: Banks
et al., 1997) to project spending for 11 categories of good in the United
One of the difficulties that previous work has encountered is a reliance on
official projections. The parameters chosen by the various agencies, to project
demographic characteristics into the future, are not necessarily the ones that
are the most appropriate for modelling expenditure. Another limitation of
previous work is that the usual econometric methods have a number of asso-
ciated problems, one of which is known as ‘dimensionality’. This restricts the
number of goods that can be modelled and the level of disaggregation in
household characteristics that can be represented, due to the number of
parameters necessary to estimate the equation. It is also difficult to allow for
unobserved heterogeneity because this is embedded in the error term which
is constant (Christensen, 2007). Despite a range of attempts to overcome
these problems (Hausman, 1996; Lancaster, 1971; Berry et al., 1995), they
have not so far, all been addressed simultaneously in the same econometric
One method that is able to model at the micro-level and project all relevant
features of a given cross-sectional population into the future is dynamic
microsimulation modelling as first described in Orcutt (1957). This approach
relies on representing every unit in a population, whether they are individuals,
households, firms, etc., and modelling how they change by means of a transi-
tion probability which determines how each unit’s characteristics change over
time. This makes it possible to derive independent projections for household
characteristics which may be aligned with official projections while still retain-
ing the micro-level distribution of particular parameters of interest. The
method has no equations to estimate (Klevmarken, 1997) so does not suffer
from dimensionality problems. It can also account for unobserved heterogene-
ity (Imhoff and Post, 1998). In addition, the representation of all units in a
sample population makes it possible to produce output at any level of disag-
These advantages have led to microsimulation becoming an important tool
for informing policy in response to the ageing population. Its ability to repre-
sent the rules of the pension system and requirements for healthcare as they
Scottish Journal of Political Economy
©2016 Scottish Economic Society

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