-1May 2008
UK Centre for the Measurement of
Government Activity
Proposals for a Satellite Account on
Human Capital Resource Formation
1. Introduction
1.1.
For over three centuries economists have been interested in
valuing the productive capacity of the workers in an economy 1 .
Despite advances in accounting systems, present day national
accounts are still considered by some to be limited in their
analysis of human capital.
Partly, as a reaction to this
deficiency, recommendation 7.5 of the Atkinson Review
(Atkinson, 2005) was that, “ONS should explore ways of
analysing and publishing information about public service
outputs in parallel to the National Accounts, such as satellite
accounts. In particular, it would be useful to have a satellite
account on human capital resource formation.”
1.2.
The motivation for this paper comes from work that ONS has
done following the Atkinson review to improve the analysis of
public service outputs, inputs and productivity.
In 2007,
general government expenditure on education in the UK 2 was
over £52bn equivalent to 3.8 per cent of GDP. Whilst this is a
large component of investment in human capital, it is not
entire amount since organisations and individuals also devote a
significant amount of resources to this activity.
1.3.
This paper presents proposals to extend UKCeMGA’s work on
education productivity by producing a human capital satellite
account. More specifically, in this paper, we define human
capital and discuss its economic and social importance. We go
on to outline how expenditures on human capital are treated in
the standard National Accounts and how they might be treated
differently in a satellite account, and the benefits of this
treatment. We then consider some of the methods that might
be used to measure human capital. We describe how this work
fits in with other work being carried out by ONS and the target
audience for a human capital satellite. Finally, we suggest how
this project could be taken forward.
2. What is Human Capital?
2.1.
1
OECD (2001, p18) defined human capital as “the knowledge,
skills, competencies and attributes embodied in individuals that
facilitate the creation of personal, social and economic wellbeing.” Any activity that increases the quality of labour may be
thought of as investment in human capital. Examples include
expenditures on formal education and on-the-job training.
The first attempt at valuing human capital was made by William Petty in 1676 (Petty,
1676). Adam Smith was one of the first economists to identify the importance of human
capital (Smith, 1776).
2
ONS code QYSE.
More generally, expenditures on health, migration, job search
and the pre-school nurturing of children can also be thought of
as investments in human capital since they increase the
productivity of workers by improving their physical or mental
health or by moving them to jobs and locations where their
productivity is higher.
In a wider sense, activities that
increase personal and social well-being can be viewed as
human capital investments. For example, parenting classes
can be thought of as an investment in future family stability
2.2.
We can differentiate between individual and collective human
capital.
Collective
human
capital
encompasses
work
organisation, work processes, information networks and other
forms of intangible, non-visible knowledge which is embedded
in a group of people rather than in individuals. Loosely, it can
be thought of as the knowledge that will remain in the
organisation even if individuals are replaced (Edvinsson,
1997). Outside of the workforce, collective human capital is an
important component of social capital. 3
2.3.
Becker (1975) distinguishes between general and specific
human capital. Specific human capital is closely allied with
organizational capital, a person's contribution to a specific
organization, the value of which is lost and must be
reproduced by costly investment when the employment
relationship is terminated. General human capital represents
skills that are not specifically tied to a single firm and whose
employment can be transferred from one firm to another
without significant loss of value.
3. Why is Human Capital Important?
3.1.
Macroeconomic Effect
Human capital is recognized as having important economic
impacts. At a macroeconomic level, the accumulation of human
capital is theorised as being an important driver of output
growth (Solow, 1988; Romer, 1989a, 1989b and 1994).
However, difficulties in controlling for other influences on
growth, establishing the direction of causation 4 and data
limitations meant that the link between human capital and
growth was not always fully supported by empirical work. For
example, Pritchett (1999) found that increases in educational
enrolment or attainment had no significant positive impact on
the rate of growth of productivity or economic growth. More
recent work in this area, using better data and more
sophisticated analytical techniques is more supportive of the
growth and human capital relationship (Barro et al, 2004;
Durlauf et al 2005).
3
Putnam (1993) defines social capital as ‘features of social organisation, such as trust,
norms, and networks that can improve the efficiency of society by facilitating coordinated actions.’ We do not examine this concept in detail in this paper. For a
comprehensive examination of the relationship between human capital see OECD 2001.
4
It may be that as countries become richer they are able to devote more resources to
education and training etc.
2
3.2.
Microeconomic Effect
A microeconomic level, individuals' labour market outcomes are
linked to their human capital. Steedman (1996) reports that in
UK the adult population, individuals with low skills or levels of
education are more likely to be unemployment and face social
exclusion. Using data from the Labour Force Survey, Sloane
and O’Leary (2004) estimate that on average having a higher
degree increases hourly earnings by 113.76 per cent for a man
(relative to a similar man with no qualifications), while the
comparable figure for a woman is 131.52 per cent. Similar
positive associations between human capital (in particular
education) and earnings are reported throughout the literature
(e.g. Card, 1999, Psacharopoulos and Patrinos, 2004);
however, there is disagreement over the reason(s) for this
association.
3.3.
The obvious explanation is that education directly increases
the productivity of individuals. Early empirical studies by
Denison, (1962), Kendrick (1976), Jorgenson and Griliches
(1967) and others found that the impact of human capital on
productivity is positive.
3.4.
An alternative explanation may be that those people who
acquire more education are more able and/or more motivated
than those who do not, and earn more because of this. Closely
related to this is the idea that educational attainments perform
a signalling function by identifying more productive workers
rather than directly raising productivity. The intuition being
that more able individuals find it less costly, in terms of time
and effort, to acquire higher levels of education. Thus,
qualifications are an indicator of an individual’s ability rather
than directly increasing productivity. (Spence, 1973, Weiss
1996) 5 .
3.5.
Dual labour or segmented market theory proposes that the
labour market is divided into a primary segment and a lowwage secondary segment (Doeringer and Piore, 1971).
Working conditions in the primary segment are generally
favourable with steady employment and job security, and well
defined and equitable rules governing the organisation of
employment. The characteristics of secondary employment, on
the other hand, are less favourable. Work here has little job
security and there are high turnover rates. There are few
opportunities for training or advancement and the work tends
to be menial and repetitive. Earnings in the primary sector are,
by definition, higher than those in the secondary sector.
Earnings in the secondary sector are no longer a consequence
of the individual characteristics and hence human capital of
workers instead they arise from the characteristics of jobs.
3.6.
Higher earnings may understate the value of acquiring human
capital since jobs which require more schooling are likely to be
more desirable on both monetary and non-monetary grounds
(Rosen, 1985).
3
3.7.
Externalities
Investment in human capital may also generate externalities.
These are outcomes that are due to the investment decision of
some individuals but affect people who did not invest in
education and for which no compensation is paid. 6 Several
examples have been suggested in the literature. Lucas (1988)
and Jovanovic and Rob (1989) consider technological
externalities, where the free movement of workers between
firms within the same industry sectors and similar production
technologies facilitates the transfer of knowledge and ideas.
Acemoglu (1996) presents a model in which imperfect
information in the employer-employee matching process
generates an externality 7 .
3.8.
Inequality and Human Capital
During the 1980s, the demand for less-skilled workers in
developed countries fell sharply. Bartel and Lichtenberg (1987)
argued that technological innovation alters demand in favour of
better educated workers because they have a comparative
advantage in implementing new technologies. This has led to a
relative fall in the real wages of low-skilled workers. This in
turn contributed to the widening of the income distribution in
many industrialized nations including the UK and the US
(Berman et al, 1998).
3.9.
Part of the observed pay gap between men and women is
related to the acquisition of human capital. On average,
women have a weaker attachment to the labour market than
men so have less incentive to acquire human capital other
things being equal (Mincer and Polachek, 1974).
3.10.
Inequality might also persist over time as educational
attainments are highly correlated between generations in
families (Gang and Zimmerman, 2000; Francesconi et al,
2005) and parental educational attainment has an impact on
their children’s future outcomes. Greenwood (1997) and
Maynard and McGrath (1997) summarize the literature on
these effects. They report that higher parental education is
associated with lower incidence of teenage childbearing; lower
levels of child abuse and neglect; better performance in school
and in the labour market by the children; lower criminal
propensities in children; and better health. These impacts are
significant even after controlling for parental income.
3.11.
Evidence on many of the social effects of human capital and in
particular educations is reviewed by Behrman and Stacey
6
The presence of positive externalities is one of the justifications for government
subsidies for education and training. From society’s point of view, individuals might
under-invest in certain kinds of education since they do not take into account the wider
benefits to society of their decision.
7
In his model, workers and firms are complementary in the production process. This
means that additions to human capital that raise productivity also increase the rate of
return on investments in physical capital7. Thus, increases in the average level of human
capital can lead firms to make greater investments in physical capital. Since the
matching process is inefficient, the firms that have invested more in physical capital are
not necessarily matched with the workers who have invested more in human capital. As
a result, some of the other workers will gain from the increase in average human capital,
since they are matched with firms using more physical capital than before.
4
(1997) and Haveman and Wolfe (1984).
Some of the
important areas identified are discussed briefly here.
3.12.
Health
There is a consensus that higher educational attainment has a
positive impact on health outcomes (e.g. Taubman and Rosen
1982 and Grossman and Kaestner 1996).
There is less
evidence on the mechanism by which education impacts on
health.
Two suggestions are that education affects how
individuals assess information on how to improve health and
increases the efficiency by which individuals use that
information in lifestyle choices. It may influence the rate of
time preference of individuals, with more educated individuals
discounting the future less, and thus undertaking actions that
improve health (e.g. smoking less). For example, Kenkel
(1991) found that education is not only associated with better
health outcomes but also superior health behaviours such as
reduced smoking, more exercise and lower incidence of heavy
drinking. Kenkel finds that even after controlling for health
knowledge, the estimated impact of additional education is still
positive suggesting that utilization as well as acquisition of
health knowledge is important.
3.13.
Crime
Until recently, the empirical evidence on the relationship
between education and crime was mixed. In their reviews of
the literature Witte (1997) and McMahon (1999) concluded that
the available evidence does not find that educational
attainments does not have an impact on crime once other
factors are controlled for. However, work by Grogger (1998),
Loch (1999) and Mochner And Moretti (2004) focused
specifically on the role of education and did find an impact of
schooling on crime.
3.14.
Civic Participation
There is some evidence to suggest higher education is also
associated with greater civic participation. Helliwell and Putman
(1999) find that education is positively correlated with typical
measures of social capital; trust and social participation.
Milligan, Moretti and Oreopoulos (2003) found that having a
higher level of education does increase the probability of voting
in the U.S. but not in the UK. Using data from the National
Child Development Study, Schuller et al (2001) found a strong
correlation between levels of education and membership of
political organisations, environment or women’s groups and
charity, residents and parent-teacher associations.
3.15.
Happiness
There is some evidence to suggest that education has an
immediate and long-term positive effect on self-reported
happiness, even after controlling for other factors such as
income (Blanchard and Oswald, 2000).
5
4. Accounting Treatment of Human Capital
4.1.
There is an on-going debate about the accounting treating of
human capital, in particular whether expenditure on goods and
services such as education and training should be treated as
consumption or investment expenditures. 8 This debate stems
observation that that individuals invest in their education
incurring direct costs such as tuition fees, books etc and the
indirect cost of the earnings foregone whilst studying.
Individuals then gain a return on this investment in the form of
higher earnings (Shultz, 1960, 1969 and 1971; Becker, 1961
and 1975). Similarly, governments invest significant resources
in the education system in the expectation of realising benefits
to society.
4.2.
The European System of Accounts (1995) defines an economic
asset as, “entities functioning as a store of value over which
ownership rights are enforced by institutional units,
individually or collectively and from which economic benefits
may be derived by their owners by holding them or using them
over a period of time.”
4.3.
OECD (1996) set out four conditions that must be met by a
resource for it to be treated as an asset of an entity for
accounting purposes.
4.3.1. It must be an economic resource.
4.3.2. The resource must be controlled by the entity. The cost
at the time of acquisition must be objectively measurable.
4.3.3. In day-to-day transactions, capital and labour markets
place value on the output potential of the asset.
4.4.
These are stringent conditions but SNA (1993 paragraph 1.52)
acknowledges that investment in human capital investment
exhibits many of the characteristics of a fixed asset in that ‘it
raises the productive potential of the individuals concerned and
is a source of future economic benefit to them.’ However, SNA
(1993) and ESA (1995) exclude human capital from the asset
boundary arguing that human capital is:
4.4.1. Non-physical.
4.4.2. Non-appropriable.
SNA
(1993)
purports
that
expenditure on human capital investments should not
treated as fixed assets because, ‘they are embodied in
the individuals as persons’ and ‘cannot be transferred to
others and cannot be shown in the balance sheets of the
enterprises in which the individuals work.’
4.4.3. Immeasurable.
4.4.4. Incompatible with the conventions and institutions that
guide the day-to-day transactions recorded by financial
accounting and reporting.
4.5.
Appelbaum and Hood (1993) argued that non-appropriability
need not necessarily be a problem since if equipment can be
measured by its original cost, human capital should also be
measured by its original cost. In the event that an employee
leaves the organization, the remaining unamortized cost can
be written off. Wessel, Solomon and Carroll (1986) argued that
in sports teams players are traded and hence thus human
8
There is a similar debate amongst financial accountants over the accounting treatment
of human resources in company accounts e.g. Gall (1988) and Flamholtz et al (2002).
6
capital can have the exchangeability characteristic. However,
widespread application of this appears to very close to slavery.
4.6.
The main implication of reclassifying expenditures on human
capital formation as an investment rather than intermediate
consumption is to increase GDP. Galindo-Rueda (2007) used a
satellite account to perform a similar exercise using
expenditures on research and development. He provisionally
estimates that capitalising research and development raises
the level of GDP in the UK by around 1.5 per cent, but that it
has a limited impact on estimates of recent GDP growth.
4.7.
More generally, Haskel (2007) founds that treating expenditure
on intangibles as investments would:
4.7.1. increase Market Gross Value Added (MVGA) by 6 per
cent in 1970 and 13 per cent in 2004;
4.7.2. mean that that the nominal business investment/MVGA
has been rising since 1970 instead of the declining trend
shown by existing figures;
4.7.3. similarly the labour compensation/MGVA ratio has been
falling rather than being stable;
4.7.4. increase estimates of labour productivity and reduce
estimates of total factor productivity;
4.7.5. suggest that total factor productivity has been
accelerating since 1990 in contrast with the slower
productivity growth estimated by conventional methods.
5. Satellite Accounts and Human Capital
5.1.
Satellite accounts are ‘a framework, linked to the central
accounts, which enables attention to be focussed on a certain
field or aspect of economic and social life in the context of
national accounts.’ (SNA93).
One of the benefits of the
satellite accounting framework is that it permits the use of
complementary or alternative concepts, classifications and
accounting frameworks, when needed to introduce additional
dimensions to the conceptual framework of national accounts.
5.2.
Amongst other things, the satellite accounting framework
allows us to identify:
5.2.1. How much is spent on human capital formation?
Whilst it is difficult to determine the optimum level of
human capital investment, it is reasonable to expect
governments to have some view on whether enough
investment in human capital is taking place and whether
further investment is needed.
5.2.2. Who is undertaking the human capital formation
activities?
Possible issues for investigation are about the balance
between activities from pre-school through to further
and higher education and how much investment in
human capital is taking place in the workplace. We
might examine productivity levels in the human capital
producing industries.
This might contribute useful
information on where to allocate scarce resources.
5.2.3. What are
produced?
the
specific
educational
products
being
7
When addressing this question we might be interested in
the pattern of expenditures across different stages of
the education process, for example, the division
between vocational and academic courses or the spilt
between arts and science. The balance between different
fields of study has important implications for the
allocation of education expenditures. Investigating the
impact of human capital on labour productivity growth
for OECD countries during 1950-88, Gittleman and Wolff
(1995) found that the number of scientists and
engineers per capita has a significant positive impact on
productivity. Similarly, Blackaby et al (1999) found that
the earnings premium graduates receive is dependent
on the degree subject.
5.2.4. Who is financing the capital formation?
Here we might investigate the relative contributions of
households, firms and governments. This would help
inform the debate over what the appropriate balance of
public/private spending is 9 .
5.2.5. What are the benefits of human capital formation and
who is appropriating these benefits?
We might be interested in the distribution of gains
benefits to households, firms and society in general.
Improved measurement of these issues might contribute
to the debate on who should be funding human capital
investment. It might also provide information to those
who are considering undertaking investment in human
capital and the distribution of expenditures on human
capital across the equality domains. Neither the stock
nor the pattern of investment in human capital is
distributed evenly across the population. A satellite
account could be used to highlight and monitor these
inequalities. For example, Green et al (2004) provide
some evidence which indicates that the inequality in
skills outcomes are higher in Canada, the United
Kingdom and the United States compared to some
continental and Nordic countries such as Germany and
Sweden.
5.3.
One of the advantages over the standard national accounts is
the identification of non-marketed training within enterprises.
The main units of analysis in the production boundary of the
framework of the SNA, producer units are establishments (or
units of homogeneous production).
These are classified
according to their principal economic activity as defined by the
International Standard Industrial Classification (ISIC). When
these units are not homogenous at a given level of the ISIC
they are classified according to a principal activity and one or
more secondary activities. The output of these secondary
activities is identified according to its nature, following a
product classification, but the inputs of secondary activities are
not separated from the ones of the principal activities.
Ancillary activities 10 are not analysed and classified according
9
Greenaway and Haynes (20039) survey the debate over the funding of higher
education in the UK.
10
Ancillary activities are referred to as auxiliary activities in the SIC.
8
to their own nature but as part of the activities of the
establishment(s) they serve.
Ancillary activities produce
services for immediate consumption within the same
enterprise. The SNA considers internal training of personnel
within enterprises as an ‘ancillary activity’. An analysis of the
education and training sector may be improved by separating
the inputs of the primary, secondary and ancillary activities.
Identifying primary and secondary activities should be
straightforward because the specified activities and products
already appear as such in the classification. However, the
measurement of ancillary services might be more problematic
as it requires additional data. Several potential sources of
data are available for the identification of expenditure on
internal training within enterprises are listed in annex 1.
5.4.
Although not explicitly mentioned in either the SNA 1993 or
the ESA 1995, (market) education expenditure by employers
is treated as intermediate consumption in the regular national
accounts. The general rule is that expenditure by employers,
which is to their own benefit as well as to that of their
employees but which is necessary for the employer’s
production process, should be regarded as intermediate
consumption.
A satellite account would allow these
expenditures to be reclassified as capital formation activities.
5.5.
This type of analysis essentially involves reclassifying things
within the central framework’s boundary of production 11 .
Other analysis might involve changes in the boundary itself.
This might involve extending the boundary to included nonmarket activities, for example the education of children by
their parents.
5.6.
Including non-marketed and internally used items provides a
more reliable representation of the education and training
sector. For example when a firm contracts out its internal
training operations to an external provider, an input-output
approach would show an increase in the output of the
training/education sector.
If the firm switches back to
providing training the input-output would show a decrease in
the size of the sector. A satellite account based estimate would
remain unchanged.
5.7.
As noted in Section 3, investment in human capital generates
a number of externalities. It may be possible to measure and
include these in a satellite account.
Similarly it may be
possible to include non-monetary information. For example,
the inclusion of measures of the volume of labour shows how
workers of different skill levels are distributed across the
economy.
11
The production boundary includes (a) the production of all individual or collective
goods or services that are supplied to units other than their producers, or intended to be
so supplied, including the production of goods or services used up in the process of
producing such goods or services; (b) the own-account production of all goods that are
retained by their producers for their own final consumption or gross capital formation;
(c) the own-account production of housing services by owner-occupiers and of domestic
and personal services produced by employing paid domestic staff. SNA(1993)
9
5.8.
At the moment there is no agreed framework for producing a
human capital formation satellite account. The System of
National Accounts (SNA, 1993) does provide some general
guidance on producing satellite accounts.
Thus, there is a
need to develop a framework and methodologies in line with
the SNA guidance. Some of the issues involved in measuring
human capital are discussed in the next section.
6. Measuring Human Capital
6.1.
Despite recognition about the importance of human capital to
economic and non-economic outcomes there is still some
debate over how to measure it. In this section I consider the
issues about measuring the stock of and investment in human
capital.
6.2.
Measuring the Human Capital Stock
Three general approaches to measuring the human capital
stock can be identified; cost-based; income-based; and
educational attainment methods.
6.3.
Cost of Production Method
Using the cost of production method the value of the human
capital stock is calculated as being the depreciated value of the
monetary amount spent on investment in human capital.
Kendrick (1976) and Eisner (1985, 1989) provide seminal
examples of this approach.
6.4.
The strengths of this approach are that it provides an estimate
of the resources invested in the education and other human
capital related sectors, which can be useful for cost-benefit
analyses. It is also relatively easy to apply, because of the
availability of data on public and private spending.
6.5.
This approach has several limitations. The first is that it is only
supply-side based but the value of human capital is also
determined by the demand for it. This makes cross-sectional
and temporal comparisons difficult.
6.6.
This method fails to take account of the heterogeneity of
individuals. As an illustration, consider two children, if one is
innately less able than the other. The less able child will be
more expensive to educate to a particular level, other things
being equal, so the cost-based approach will overestimate his
human capital while underestimating the human capital of the
more able child.
Similarly, differences in the quality of
education providers are ignored in this method. For example,
schools vary in their quality as do the teachers within schools.
After social background, the quality of teaching is the best
predictor of how well students do in school (Hanushek, 1971,
2000; Lavy, 2002).
6.7.
Another of the major issues with this approach is to identify
which costs should be included and how they should be
measured. Simply reclassifying all human capital expenditures
as investment rather than consumption may not be correct.
To the extent that individuals enjoy their courses or have their
range of interests, tastes and activities extended, education
expenditures also provide some consumption benefits. Thus,
10
the difficulty lies in determining which part of educational
expenditure is investment spending and which part is
consumption (see, for Schultz (1961a,b) and Shaffer (1961)
for a discussion. Part of the expenditure on schooling could
also be regarded as a form of childcare in that it provides
children with a safe environment allowing their parents to use
their time in other ways. Similarly, Kendrick (1976) classified
the costs of raising children to the age of fourteen as human
capital investments, reasoning that these expenses, typically
on necessities such as food and clothing, compete with other
types of investment. This contradicts Bowman (1962) and
Machlup (1984) who argued with this view, maintaining that
basic expenditures should be considered as consumption.
6.8.
Calculating the depreciation rate is an important element of this
method. Like physical capital, human capital depreciates over
time, because of:
6.8.1. the wear of skills due to aging, or illness;
6.8.2. the atrophy of skills due to insufficient use;
6.8.3. job-specific obsolescence due to technological and
organizational change;
6.8.4. sector-specific
obsolescence
due
to
shifts
in
employment;
6.8.5. firm-specific skills obsolescence due to displacement
(Grip and Van Loo, 2002)
6.9.
Grip and Van Loo also suggested ways in which the
obsolescence of human capital could be measured:
6.9.1. objective methods such as testing;
6.9.2. subjective method e.g. asking workers or their
employers;
6.9.3. workers’ wages;
6.9.4. the probability of losing employment.
6.10.
All four measures have their restrictions. The last two indirect
methods have the advantage that they measure the labour
market effects of skills obsolescence that are the main concern
on human capital obsolescence in a knowledge economy: a
lower productivity and lower labour market participation.
6.11.
The two main methods used to calculate depreciation in the
literature are: the straight-line method (Eisner, 1988) in which
a constant proportion of the original human capital is assumed
to become obsolete in each period and the (modified) double
declining balance method (Kendrick, 1976), in which
depreciation is assumed to be higher in the early years of an
assets life. The rationale behind this method is that physical
capital depreciates faster in early years of life, so using the
double declining balance method provides consistency across
different types of capital.
6.12.
The appreciation of human capital is often ignored in the
literature, despite some empirical evidence that showed that
human capital can appreciate at younger ages (Mincer, 1958,
1974; Graham and Webb, 1979).
6.13.
Some aspects of education aim to create ‘skills for life’ e.g.
education attainment which enables individuals to enjoy leisure
11
activities during and after their working life. These skills may
appreciate or depreciate depending on use and wider factors.
6.14.
The Income Based Approach
The income-based approach measures human capital by
summing the discounted values of all future income streams
that all individuals in the population expect to earn throughout
their lifetime (Farr, 1853; Jorgenson and Fraumeni, 1989,
1992). This method is ‘forward-looking’ because it focuses on
expected returns to investment, as opposed to the ‘backwardlooking’ method whose focus is on the historical costs of
production.
6.15.
One advantage of this approach is that there is no need to
assume an arbitrary rate of depreciation, as depreciation is
already implicitly captured. The main limitation of this
approach is that it relies on the assumption that labour is paid
according to its marginal productivity. In practice, factors such
as market power, trade unions, discrimination, etc all affect
wages. These measures are also sensitive to the choice of
discount rate and the retirement age. This method relies upon
accurate data on earnings, life tables and (un)-employment
rates.
6.16.
There is disagreement over whether maintenance costs should
be deducted from the measure of human capital. Authors such
as Eisner (1988) argued that physical capital estimates are net
of maintenance costs, thus human capital should also be
treated similarly. Weisbrod (1961) attempted to account for
maintenance, but he encountered many difficulties especially
when deciding types of expenditures should be classified as
maintenance, and how to account for economies of scale and
‘public’ goods when estimating per capita consumption for
different members in the same household.
6.17.
A variation of the income-based approach is presented by
Mulligan and Sala-i-Martin (2000) who calculated an index
measure of human capital. Specifically, they measure human
capital as the total labour income per capita divided by the
wage of the uneducated. The rationale for this method is that
labour income incorporates not only the workers’ human
capital but also the physical capital available to them, such
that for a given level of human capital workers in regions with
higher physical capital will tend to earn higher wages.
Therefore, to obtain a ‘pure’ measure of human capital, the
effect of physical capital should be netted out. This method
assumes that uneducated workers always have the same
human capital, although they do not necessarily earn the same
income. According to Mulligan and Sala-i-Martin, if schooling
has quality and relevance that vary across time and space, any
amount of schooling will introduce inter-temporal and
interregional differences in an individual’s level of skills. Hence,
the only sensible numeraire is the uneducated worker.
6.18.
The Educational Attainment Based Approach
The educational attainment approach estimates human capital
based on educational output indicators. This method is based
on the assumption that these indicators are closely related to
investment in education and this is a key element in human
12
capital formation. Human capital encompasses more
dimensions but education is arguably the most important
component. A variation of this approach is to individuals test
directly to determine whether they have certain attributes
relevant to economic activity.
6.19.
Several measures have been used in the literature e.g. adult
literacy rates (Romer, 1989 and Azariadis and Drazen, 1990);
school enrolment rates (Barro 1991, Mankiw et al. 1992,
Levine and Renelt 1992 and Gemmell 1996); average years of
schooling. The main limitation of these approaches is that
they miss most of the elements that extend beyond that
elementary level, such as numeracy, logical and analytical
reasoning and scientific and technological knowledge. Thus
they are unlikely to be good proxies for human capital in
developed countries Judson (2002). Establishing the direction
of causality may be difficult since high enrolment may result
from high productivity growth, rather than vice versa (Wolff,
2000).
6.20.
Psacharopoulos and Arriagada (1986, 1992), Barro and Lee
(1996) used, a measure that has several advantages over
literacy rates and school enrolment rates. First, it is a valid
stock measure. Second, it quantifies the accumulated
educational investment in the current labour force. Wachtel
(1997) shows that under some reasonable assumptions, the
number of schooling years is equivalent to cost-based
measures of human capital. The studies that have attempted
to develop data series on years of schooling can be divided
into three groups based on the method they employ: the
census/survey-based estimation method (e.g. Psacharopoulos
and Arriagada, 1986 and 1992), the projection method (e.g.
Kyriacou, 1991) and the perpetual inventory method (Lau et
al., 1991).
6.21.
This proxy has a number of short-comings. First, years of
schooling fails to account for the fact that costs and returns of
education vary from level to level. This measure incorrectly
assumes that one year of schooling always raises human
capital by an equal amount. For example, a worker with ten
years of schooling is assumed to have ten times as much
human capital as a worker with one year of schooling. This
assumption is at odds with the empirical literature which has
typically documented diminishing returns to education
(Psacharopoulos, 1994). Second, no allowance is made for
differences in quality of education across time and location.
Behrman and Birdsall (1983) found that neglecting quality of
schooling biased returns to schooling. Since the quality of
schooling varies more considerably across countries than
within one country, overlooking quality is likely to create more
severe biases. Third, this measure unrealistically assumes that
workers of different education categories are perfect
substitutes for each other, as long as their years of schooling
are equal.
6.22.
In an attempt to overcome the limitations of each of the
methods, several authors have tried to combine the methods
e.g. Tao and Stinson (1997); Dagum and Slottje (2000).
13
6.23.
One drawback which is common to all these approaches is that
formal education and training are not the only determinants of
human capital. Some of an individual’s capital is innate to
them and is some sense, a non-produced asset; thus the asset
created by education could be regarded as improvements in
human capital by education and training.
6.24.
Another drawback of these measures is that they focus on
individual’s human capital and aggregate them to arrive at the
population measure. This ignores spillovers between workers
so that the whole may be more than the sum of the parts.
6.25.
Some attempts have been made to measure the social value of
human capital.
The underlying methodology has been to
estimate how much it would cost to purchase the benefits of
human capital for example improved health, through an
alternative means (See Topel and Lange, 2006 for a
comprehensive survey).
7. Measuring Investment In Human Capital
7.1.
Investment in human capital can take place throughout an
individual’s life in a range of environments. OECD (2001)
identifies the four main contexts for human capital
development.
7.2.
Learning within family and early childcare settings
Families contribute to the development of human capital in
their children through direct expenditures on educational
materials etc and through time spent fostering learning habits
and attitudes. In principle, direct expenditure is easier to
measure. More difficult is valuing the time contribution of
families. For example, for children of pre-school age it is
difficult to distinguish what activities constitute ‘care’ and what
constitutes ‘learning’. OECD (2007) gives the example of when
a parent gives his or her toddler a bottle to hold, the parent is
feeding the child (‘care’) and also helping to develop the child’s
autonomy (‘learning’). There is also the question of how to
place a monetary value on this time.
7.3.
Formal Education and Training
This includes activities ranging from early childhood education,
school-based
compulsory
education,
post-compulsory
vocational or general education, tertiary education, public
labour market education, adult education etc. Amongst the
relevant expenditures to be measured here are the wages and
salaries of educators, expenditure on buildings and their
maintenance, expenditures on equipment, grant and the
subsidy elements of student loans etc.
7.4.
Workplace Training
Firms and Organisations invest in human capital to develop
those skills and competences with economic value. They are
generally more difficult to measure as they are not
comprehensively reported in company accounts and much of
the training is informal.
14
7.5.
Informal Learning
This is more difficult to measure as it takes place ‘on-the-job’
and in daily living and through civic participation
7.6.
The general principle for valuing output in National Accounts is
that where output is produced through the market it is valued
on the basis of producers’ receipts and household
consumption 12 . In contrast, where output is produced through
the non-market sector, output is calculated as the total
production cost and household consumption only corresponds
to their partial payment. This suggests, if the acquiring human
capital takes time then the labour costs, or the opportunity
costs of time spent on education, of those receiving education
or training should also be included as resources devoted to
human capital formation.
7.7.
Aggregation Problems
There is a problem with aggregating individual measures of
human capital to estimate an economy’s total human capital.
Such an approach will neglect the importance of “collective
knowledge or skill” residing in organisations and other collective
entities.
Aggregation is also likely to miss the impact of
interactions and spillovers arising from enhanced human capital
in some members. Finally, the highly specific, culturally bound,
non-ommunicative, tacit and heterogeneous dimensions of
human capital are not easy to encapsulate in such aggregate
measures of human capital.
7.8.
Diminishing Returns
The proceeding literature survey has suggested that greater
expenditure on human capital brings important benefits.
However, it is important to note that there may be diminishing
returns to spending on education for higher levels of economic
development (Hanushek and Kim, 1995).
7.9.
Over Education
The rapid growth in educational attainment and levels of
literacy in the past decade suggests that human capital is not in
short supply in OECD countries. Moreover, a number of
economists have suggested that there may be some ‘overeducation’ taking place in Europe and the United States (see
Sloane 2003 for a review of the literature).
8. How does a human capital formation satellite
account fit in with other work in ONS?
8.1.
There are several work streams which are closely related to
developing a human satellite account:
8.1.1. One of the recommendations of the ‘National Accounts /
Labour Market Statistics Consistency project’ was the
development of a balanced Labour Accounting System
(LAS), recommended by the International Labour
Organisation (ILO) and Eurostat.
Human resource
12
Household final consumption expenditure is expenditure including imputed
expenditure, incurred by resident households on individual consumption goods and
services, including those that are sold at prices that are not economically significant
(SNA, 1993).
15
accounts (HRA) have already been developed in the
Scandinavian countries, and the European Commission
has identified public sector interests in HRA.
8.1.2. Work on intangible assets.
8.1.3. Work on Quality Adjustment Labour Inputs (QALIs)
(Dey-Chowdhury and Goodridge, 2007)
9. Who is the Target Audience for the Satellite
Account?
9.1.
10.
The target audience for a human capital satellite account
would consist of individuals, private organisations and public
bodies having a direct interest in human capital. Oxfam and
other third sector organisations have also expressed and
interest in the work particularly on measuring the wider
benefits of human capital development and the third sector’s
contribution to the process. There are several international
organisations who are actively involved in measuring human
capital. The OECD has produced several reports on measuring
human capital e.g. OECD (1998, 2001, 2007). In addition to
the macroeconomic and microeconomic concerns discussed in
section 3, Governments have self-interest in human capital
formation based on efficiency of educational provision, for cost
sharing on the further development of society’s stock of human
capital and for internal optimisation of its own stock of human
capital. Trade unions and academics would also be expected to
have an interest in measures of human capital formation.
Proposals for Action
10.1.
We propose that the next step in producing a human capital
formation satellite account is to develop a specification which is
both feasible, making maximum use of existing data/resources
and flexible, in that it can be improved if additional data
becomes available. We can achieve this be concentrating on a
“core” satellite account which covers the most important
aspects of human capital formation and use “sensible” levels of
disaggregation. We need to consider carefully what specific
questions we are trying to answers. Trying to produce a
satellite account which tells us everything about human capital
has too wide a remit to be feasible. However, framing specific
questions such as those in 5.2 would allow us to answer the
important questions using a sensible amount of resources.
10.2.
One of the first stages in the production process involves
defining all the activities that constitute human capital
formation and to extract information on them from National
Accounts 13 . Human capital forming activities could then be
shown explicitly as products. This could be broken down by
industry groups. The second stage is to think of workers as
entrepreneurs selling their labour to employers and to treat
compensation of employees as a payment for a product
instead of a payment for a factor service. The third stage is to
introduce human capital by reclassifying all expenditure on
education or training by households, government or
enterprises as capital formation. Expenditure that relates to
13
It is good practice to show the link between satellite accounts and the central
accounts
16
individuals who have yet to complete their courses is treated
as ‘work-in-progress’. When the student completes his or her
education, this is then reclassified as capital formation.
10.3.
An extended satellite account would recognise that for other
analytic and policy-related purposes, it may be useful to
extend the data coverage of the satellite account system
beyond monetary representations of economic activity. Thus,
we could identify a range of other indicators to be included.
10.4.
Based on the experiences of other statistical agencies in
producing satellite accounts, it is likely to take two people,
working full-time on the satellite account, two years to produce
a core satellite account.
Annex 1
Potential Data Sources
Name
Size
Method
Frequency
Labour
Survey
60000
Households
Household/Person
(Sample) Survey
Quarterly
Continuously
10000
individuals
Initially
15000
at
present.
6414
Longitudinal/panel/
cohort study
Annual
Continuously
Geographical
Coverage
England
Scotland
Wales
United
Kingdom
Cross-sectional
(one-time)
study
United
Kingdom
4010
Repeated
crosssectional study
Annual
England
13698
(obtained)
Sweeps One,
Two
and
Three
combined
Longitudinal/panel/
cohort
Around
2,300
workplaces,
1,000
employee
representativ
es
and
22,500
employees in
2004
2467
Employees
1997
4470 in 2001
7787 in 2006
Cross section and
panel survey
1980,
1990
1998.
Cross section
1997
2001
2006
10.5.
Force
British
Household
Panel Survey
United
Kingdom Time
Use
Survey,
2000
Learning and
Training
at
Work, 2002
Youth Cohort
Study
of
England
and
Wales, 20002002; Cohort
Ten,
Sweep
One, Two and
Three
Workplace
Employees
Relations
Survey
Skills Survey
England
Wales
1984,
and
UK
GB
17
and
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