Economic Commission for Europe
Conference of European Statisticians
Group of Experts on National Accounts
Twenty-third session
Geneva, 23-25 April 2024
Item 2 (b) of the provisional agenda
Towards the 2025 System of National Accounts: Well-being and sustainability
GDP and Welfare: Empirical Estimates of a spectrum of
opportunity
Prepared by Office for National Statistics, United Kingdom1
Summary
The National Accounts and GDP provide an internally coherent view of the economy,
focussed on those goods and services produced by humanity and validated by at least one
other human through market transactions. Whilst a meaningful measure, this fails to reflect
value generated without human input or validation, excluding natural and human capital and
the resultant flows from these. These exclusions make GDP a poor measure of welfare,
despite the constant utility assumption underpinning the price deflators used to derive real
estimates. In a world where policy-makers increasingly need to consider the trade-offs
between the economic, environmental, and social realms, this paper applies proven methods
from National Accounts to a wider set of pre-existing UK data, accepting that activity outside
the market can be measured and accounted for in a similar fashion. The resultant indices,
Gross Inclusive Income (GII) and Net Inclusive Income (NII) are conceptually comparable
to GDP and Net National Disposable Income. This paper also presents and comments on
experimental results, revealing remaining statistical challenges and policy trade-offs. The
substantial shift out of market-based activity towards home production, (for example) may
help reveal new causes for the UK productivity puzzle, as the resultant extra output is not
visible via existing GVA estimates. Another key insight comes from combining carbon
emissions and carbon prices in a volume framework, which reveals that the UK’s net
contribution to atmospheric degradation continues to grow despite falling emissions because
the price of emissions has grown at a faster rate, resulting in continued increasing damage.
1 Prepared by Richard Heys, Robert Bucknall, Stephen Christie, and Cliodhna Taylor.
United Nations ECE/CES/GE.20/2024/13
Economic and Social Council Distr.: General
4 April 2024
English only
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I. Introduction
1. Many policymakers globally are unsatisfied with the present state of statistical
information about the economy and society, in particular the effective treatment by many of
Gross Domestic Product (GDP) as the dominant indicator of economic welfare2 (see Stiglitz
et al, 2009). As has been noted (e.g. Coyle (2015) and Dynan and Sheiner (2018)), whilst real
GDP is a welfare measure due to the constant utility assumptions underlying the price
deflators which convert nominal data to volume, it is a weak measure because of what it
omits. Nevertheless, there appears to be an increasing gap between the information contained
in GDP and the factors which contribute towards people’s well-being. Recognising that value
can be generated in different domains, (e.g. the environment) with different levels of human
participation and finding a way to measure this in a form which is consistent with National
Accounts should enable better policy-making by exposing the inherent trade-offs.
2. This paper aims to contribute to this debate by demonstrating a practical empirical
application of what can already be produced to deliver objective, monetised measures of
economic welfare in a country which has well-developed National Accounts, a Household
Satellite Account produced in line with the System of National Accounts 2008 (UN(2008)),
a set of Natural Capital Accounts produced in line with the System of Environmental
Economic Accounts (SEEA) (UN(2021)), and a measure of Human Capital stocks produced
in line with the relevant UN statistical guidance (UN(2016)). By applying proven National
Accounts methods, whilst accepting that activity outside the market can be measured and
accounted for in a similar fashion, this paper utilises pre-existing data to implement an
extension of the national accounts framework. This paper captures a wider range of capitals
alongside the flows of benefits received by consumers arising from these to widen the
National Accounts asset and production boundaries to integrate natural capital (together with
their corresponding ecosystem services) as well as begin to integrate human capital,
alongside the outputs consumers receive from these in a simple additive framework, which
is coherent with GDP and other national accounts metrics.
3. This paper discusses the measurement challenge (section II), proposed methods
(section III), exclusions and areas for future work (section IV), empirical results (section V),
and conclusions (section VI).
II. The measurement challenge
4. GDP as a single-measure index is often preferred for decision-making over other more
complex presentations because it has a range of attractive analytical qualities – simplicity,
international and historical comparability, objectivity of weights, regularity and frequency of
publication, accuracy in terms of measuring the volume of output produced in the market,
and the ability to be broken down into its component parts. These attributes make GDP
dominant in many user’s eyes, even if it is not conceptually aligned with the item of interest.
Production of more suitable metrics alone is insufficient – there are plenty of alternatives to
GDP already. To be successful, any new metric has to be better aligned conceptually and
achieve equivalence in terms of the above attributes if it aspires to better serve users.
Pragmatically this requires the use of pre-existing data, at least in terms of providing
meaningful historical time series, but also to ensure budget constrained national statistics
institutes (NSIs) can deliver these data at a low marginal cost. Nevertheless, it is important
to ask how to improve conceptual alignment if we are looking to use pre-existing data.
5. GDP is a poor indicator of a society’s standard of living, of overall economic welfare,
because it is a partial measure which excludes important components to focus primarily on
2 This paper refers to “welfare” in a narrow sense – as “economic” welfare measured as the flow of
goods and services received by consumers. We reserve “well-being” for a more expansive and general
definition. "Welfare” is therefore neutral toward the impact of the use of resources – whether they do
in fact raise life satisfaction, decrease anxiety, etc. or not. This is to be contrasted with more direct
measures of well-being, for example that directly ask about life satisfaction or anxiety.
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the market. GDP does not directly account for activities conducted outside the market, such
as unpaid work in the home or community, leisure, and the value that society may place on
services provided ‘free at the point of delivery’3. Therefore, it does not portray a complete
picture of household consumption. It equally tells us little about the distribution of income
or the impact of increases in variety and technology. GDP can be argued to also measure the
outcomes of public services poorly and pays little attention to environmental quality or the
impact of health and education services on human capital, the latter two of which are
deliberately excluded. These are just a few examples of goods and services which affect
people’s welfare, whether or not they are bought and sold, and whose social value is not fully
captured in their price even when they are transacted in the market.
6. This paper does not present a micro-data based solution to this challenge, and is not
explicitly predicated on an underlying social welfare function. Rather, it presents an
accounting-based approach4 to tackling this question, which is predicated on utility being a
function of consumption. Using pre-existing data sources, this paper takes the existing
framework and making simple extensions to the stock and flow concepts to widen the range
of consumption goods and services in scope. Throughout we shall rely on the standard
national accounts methods which (on the non-financial side) can be simplified as a flows
argument:
GDP = Y1 = f(K1,L1) = r1K1 + w1L1 = C1 + I1 + G1 + (X1 – M1) (1)
a stocks argument:
K1 = K0 + I0 - δ0 + revaluation0 – destruction0 (2)
And from which we can also develop a net statement of flows:
YN
1 = Y1 – δ1 (3)
7. Where Y represents output (GDP), K represents capital assets, L represents labour, r
is the rate of return on capital, w is average wages and salaries, C is consumption, I is
investment, G is government expenditure, W is exports, M is imports, and δ is depreciation,
with sub-scripts indicating time periods and super-script N indicates a net measure. The SNA
definition of each of these variables is defined by a set of constraints or ‘boundaries’ defining
what is in scope and not, alongside well-established methods to determine the value of each
component. Within the current national accounts, key to the decision whether an item is in
scope is whether there is clear human intervention in its creation / use through a meaningful
economic transaction.
8. However, if one is willing to extend these ‘boundaries’ to capture relevant concepts
there is little to prevent the application of essentially the same ‘stocks and flows’ national
accounts methods to wider data to develop new measures of welfare on the same monetisable,
exchange value basis (i.e. excluding consumer surplus and externalities5), in both current
price (CP) and real chained-linked volume measure (CVM) terms, through widening the
definitions of which assets and flows can be included within these variable definitions. To
do this, we need to understand GDP’s limitations.
9. Output (Y) is increasingly derived from capital (K) rather than labour inputs (L) (see
Piketty 2014), and when one looks at capital, one sees authors and measurement authorities
(e.g. Dasgupta (2021), World Bank (2022) and UNEP (2023)) considering an extended set
of permissible factors in three broad classes; produced (both tangible and intangible
3 Excluding those delivered by the public sector and ‘paid for’ via taxation; a meaningful economic
transaction.
4 Developed via two discussion papers in the Economic Statistics Centre of Excellence Discussion
Paper series - Heys, Martin, and Mkandawire (2019), and Bucknall, Christie, Heys, and Taylor (2021)
5 Noting that the flow of benefits received from natural assets, such as carbon sequestration, could be
considered externalities because of the absence of a market. In this work we look to capture this in
line with the general trend in the measurement and policy communities to recognise that the
environmental impact of economic and other human activity is an essential component of
understanding the economy.
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(Corrado, Hulten and Sichel 2009)), natural, and human6. Of these three, only the first is
included in the national accounts, and is broadly equivalent to K within the current national
accounts model, noting that not all intangible assets are currently included (‘capitalised’) into
the accounts. Only a subset of natural capital is capitalised (“cultivated assets”), whilst human
capital exists in a ‘halfway house’ where the human capital stock itself is not captured in the
accounts but the resultant flows are. Salary differentials received as a result of human capital
acquisition are included, but only as a labour reward in the form of ‘compensation of
employees’ (broadly equivalent to w in (1)), and the investment to create human capital,
either in the form of education or health services, or in-firm training, is included as recurrent
spending (C or G), but not as investment (I), and hence not flowing into (2).
10. This is the central challenge from which all others flow. It is surely incongruent to ask
policy-makers in an increasingly capitalised world, in which both natural and human capital
have growing importance and impact, to make decisions based on a measure which partially
excludes both in different ways. Even if one believes we should give productive capital
primacy and exclude natural (KN) and human capital (KH), it is odd to focus our attention on
a measure which suffers from only having a partial coverage of productive capital through
the exclusion of a number of intangible assets, which are generally recognised as being
increasingly important in economies utilising advanced technologies (see, for example,
Goodridge and Haskel 2022). It becomes ever clearer a new strategic vision is required.
11. To produce a better measure which is more reflective of the trade-offs policy-makers
are making between the economy, society and the environment, a core assumption in this
paper is that people derive economic utility or value both from what they consume from
within the productive economy as defined in the SNA08, but also from the more broadly
defined productive economy – including the flow of services they produce and consume in
the unpaid household satellite account, and similarly from environmental assets. By
considering each of these in terms of providing either a proxy or equivalent to a flow of
income one can view the summation of these incomes as a total measure of monetised and
non-monetised income and hence a feasible measure of economic welfare. Therefore, one
needs to include into revised equations 1, 2 and 3, all three capitals, alongside the flows of
benefits and costs consumers derive from / incur from these, even if they arise without human
intervention. This paper therefore widens the ‘production boundary’ to include all output
arising from the three capitals, irrespective of whether there is a paid transaction, or indeed
whether there is human involvement in the production process at all. That is, the ‘production
boundary’ is widened in line with the changes implemented to the ‘asset boundary’. As far
as possible, all other national accounts concepts and methods remain untouched.
12. As such we apply changes to the definitions of Y, K and other variables (denoted by
Y*, K* etc), taking account of the need to maintain internal coherency, and prevent double-
counting. Effectively we ‘loosen’ the ‘asset boundary’ to allow the inclusion of all three
capitals, (such that K1* = K1 + KH
1 + KN
1) irrespective of the degree of human intervention,
and make equivalent changes to incorporate the resultant flows from all three capitals within
the ‘production boundary’, that defines which output is in scope of Y in equation 1. In doing
so, we also act to treat produced capital more consistently. Capital purchased by businesses
to deliver goods and services in the market are included in the national accounts. Produced
capital purchased by households to deliver services in the home (as such fridge-freezers,
domestic cars and home computers) are instead treated as consumption items, and not
capitalised in (1).7 I* will now capture this as investment.
6 Social capital is often described as a fourth, but there is a powerful argument by Dasgupta that social
capital is a contextual factor which determines the value of other capitals: a machine might be
valuable to its owner in a country with operating laws and justice functions, but the same machine has
no value in a failed state where it could be immediately stolen. As such, it can be considered to be
‘priced into’ the framework proposed in this paper.
7 The SNA defines the production boundary for GDP as “activity carried out under the control and
responsibility of an institutional unit that uses inputs of labour, capital, and goods and services to
produce outputs of goods or services. There must be an institutional unit that assumes responsibility
for the process of production and owns any resulting goods or knowledge-capturing products or is
entitled to be paid, or otherwise compensated, for the change-effecting or margin services provided.”
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13. Production of services undertaken by households for their own use (i.e. for which they
will receive no pay, and which is not for exchange with another institutional unit – such as
home cooking to be consumed by the family), utilising a combination of labour and
household capital appliances, is, therefore, not included in Y in (1). Since these activities
contribute to living standards, and the consumption of household capital items are a key part
of understanding our environmental impact8 any indicator of welfare would be incomplete
without them, so we need to bring these assets within the definitional scope of K* and I*, but
in doing so we need to also capture the output they produce within Y*9, leading to the
following re-defined equations:
GDP = Y1* = f(K1*,L1*) = r1K1* + w1L1* = C1* + I1* + G1 + (X1 – M1) (1*)10
K1* = K0 + KH
1 + KN
1 + I0 - δ0* + revaluation0* – destruction0* (2*)
YN
1* = Y1* – δ1* (3*)
14. The elements for inclusion are as below, noting that the authors rely wholly on the
wider UK statistical system in terms of the data used. This is predicated on the joint
assumptions that i) statistics have been accurately produced against a relevant international
framework, ii) where measures have been monetised, these are in a consistent market
equivalent price or exchange value form where they can be used, aggregated or compared in
equivalent terms – that is £100 of market output is equivalent to £100 for services received
from trees acting as stores of carbon is equivalent to £100 of home-produced transport
services (e.g.‘dad’s taxi’), and iii) the frameworks under which these statistics are derived
are mutually consistent without double-counting or exclusions. This means that all
production-based welfare measures described in this paper exclude consumer surplus11, as
well as most externalities (i.e. only economic flows which are conducted under mutual
consent are included) – save those generated from natural capital assets as a key aspect of
this work is to ‘internalise’ the impact of humanity on the environment within our
understanding of economic welfare. 12
15. Nevertheless, there are still several areas where data are unavailable or experimental.
As such, the estimates presented in this article should be treated as experimental and as proofs
of concept. Contingent on user feedback, the aim is both to update this work to further
improve these measures, as well as use this framework to highlight gaps and identify areas
for future work.
8 Particularly those with significant pollution externalities, such as domestic cars and household gas
boilers.
9 As we bring more assets / services into scope, both the flow of benefits from these assets and the
depletion / depreciation are added to the measure together.
10 We assume that government expenditure already include spend on environmental activity and that
unpaid household goods and services are not internationally traded. There is no trade in environmental
services.
11 In the case of the household satellite account, where the producer is the consumer, the distinction
between consumer surplus (which is excluded from National Accounting frameworks) and producer
surplus (which, as this money is included in the transaction, is included in National Accounting
frameworks) is conceptually a little more difficult to determine.
12 Any ‘single measure’ approach to calculating an economic value of welfare needs to be weighted to
bring contributing factors together into a meaningful common metric. Market prices are the most
objective way to compare, and so aggregate, production of goods and services – and remain so when
creating a singular measure of (production-based) welfare. This only works as a solution when focusing
solely on economic welfare and does not offer a solution of how to compare economic welfare with
environmental and societal measures of well-being. The production of an aggregate measure of overall
well-being, including societal and environmental factors, would necessitate substantially more
subjective intervention, and so, alongside many other authors and statistics producers we consider such
aggregates undesirable, both because their subjective nature could be used to distort debate, but also
because even if subjective weights could be agreed on within one society, they may not apply to another,
making comparisons potentially invalid.
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III. Proposed Methods13
16. To widen the definition of Y in equation 1 to Y* falls into two parts: firstly, expanding
from current standards to capture those dimensions of the productive economy which are
currently omitted, and secondly to bring into scope those flows relating to human and natural
capital which are also out of scope.
17. There are three components omitted from the current definition and methods applied
in the UK to measure Y: ‘uncapitalised’ or omitted intangible assets, quality adjustment of
public service outputs, and the inclusion of output generated in the household for domestic
use using productive capital currently treated as recurrent spending.
18. In relation to uncapitalised intangibles or Intellectual Property Products (IPPs), under
the assumption that this would previously have been accounted for as intermediate
consumption we need to add these in the form of additional output, and resultingly as
additional investment and depreciation in equation 2. Data is drawn from ONS publications
estimating the value of these uncapitalised stocks (e.g. ONS 2021b). As elsewhere, this
assumes definitions for these additional IPPs are mutually exclusive from those already
accounted for in the National Accounts, although in this instance work is currently being
undertaken in ONS to examine the extent to which this is the case.
19. In relation to the value of public services, as summarised in Foxton, Grice, Heys and
Lewis (2019), to understand the value added from public services which are delivered at zero
price, one needs to follow the methods laid out in SNA08 to quality adjust these measures to
take account of the quality of the outcomes achieved, in line with the methods proposed in
Atkinson (2005). The UK does not currently conform to this standard as it aligns to the
European System of Accounts 2010 (ESA10), which deviates from SNA08 in this important
dimension14.
13 Wherever a method is presented in summary terms, full methods and datasources can be found
either in Bucknall, Christie, Heys, and Taylor (2021) or the Quality and Methods documentation
available on the ONS website (ONS 2022b).
14 ESA10 regulates the production of GNI estimates for each EU country, which determine
contributions to the EU budget. The EU wished to observe further method developments to confirm
comparable methods across all countries to ensure consistent application and therefore a ‘fair’
budgetary allocation.
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Figure 1
The effect of quality adjustment on Government, Health, and Education (O, P, and Q)
Output
20. Chained Volume Measure, 1997 = 100
21. This paper uses the ONS’s work to develop quality adjustments on the public services
to produce public service productivity data to implement an adjustment to the non-market
component of sectors O, P and Q15. To do this, we take the average quality adjustment on the
49.1% of public services where quality adjustments exist, (ONS 2023) and extrapolate this
across the whole of the non-market portion (around 80%) of O, P, and Q, using a simplifying
assumption that the whole of government is subject at any time to the same spending
constraints and a consistent requirement for efficiencies and service improvements. To derive
this measure, we uprate the CVM measures of non-market output of the industries associated
with the provision of public services (O, P, and Q) in line with the average quality adjustment
of service areas with calculated quality adjustments.
22. In relation to unpaid household activities, the sum of these is simply drawn from the
household satellite account (ONS 2022d) in current price terms and CVM estimates are
constructed using;
• Direct volume estimates in the case of childcare (where hours are used) and transport
(where distance travelled, adjusted for time taken, is used)
• Services producer price indices are used for laundry (specifically, the “Washing and
(Dry-)Cleaning Services of Textile and Fur Products” SPPI)
• Industry deflators for comparable industries are used for household housing services,
nutrition, and adult care.
• The whole economy implied GVA deflator is used to deflate voluntary activity.
23. In addition to these, we also need to account for the flows resulting from the inclusion
of human and natural capital. Of these, natural capital is the easiest as the value of both natural
capital stocks, and the flows of capital services arising from these are included in the Natural
Capital Accounts (ONS 2022d). The flow of benefits from carbon sequestration in the Natural
Capital Account are used as provided in current price terms but deflated using the GDP
deflator. This deflator is used for the time being as the benefits received from environmental
assets are difficult to compare with other broad categories of products from the market sector
15 Whilst there are other non-market sectors of the economy, such as imputed rentals on owner-
occupied housing, we do not propose any adjustment of these.
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– in theory, the best deflator to use would be one which represents a market-equivalent of the
service the environmental asset provides. Future work would be required to identify these
market equivalents and their relevant deflators, which in some cases may require additional
data collection.
24. We have only added carbon sequestration from ONS’s Natural Capital Accounts as a
number of flow of services from environmental assets labelled ‘provisioning services’ (e.g.,
fossil fuel production) are already be included in GDP, and other environmental asset services
have short time-series which only begin after 2005. As such, these estimates should be seen
as a component of the contribution of environmental assets to value added – and not as a
proxy for the entirety of environmental asset services.
25. We label Y* Gross Inclusive Income (GII), which can be considered as conceptually
equivalent to GDP with a widened production and asset boundary. In summary, GII is
calculated as:
Gross Inclusive Income (GII)
GDP (minus non-market gross value added in industries O, P, and Q)
Plus: Quality adjusted non-market GVA in industries O, P, and Q
Plus: Household flow of benefits (to be expanded to include household production using
digital services in future work)
Plus: The flow of benefits from carbon sequestration performed by a subset of
environmental assets in the UK.
Plus: Investment in previously uncapitalised Intellectual Property Products (i.e. intangible
capital)
= Gross Inclusive Income (GII)
Capturing depreciation and depletion
26. GII is still a gross measure, failing to capture the impact of depreciation or depletion
of various types of assets. Alongside Y*, we also compute new equivalent values for K* via
equation (2) taking into account uncapitalised productive capital, natural capital and human
capital16.
27. We also develop a new net measure of Y*N, Net Inclusive Income (NII), which can
be considered as broadly equivalent to the existing Net National Disposable Income (NNDI)
variable already produced within the ONS Blue Book (e.g ONS 2022c). NII takes GII and
converts it to a net measure in line with the methodological steps used to convert GDP to
NNDI by taking account of depreciation and depletion through the consumption of capitals,
covering productive capital, including a wider set of IPPs (‘intangible capitals’), household
durables, and environmental assets (effectively δ*). It is also capable of capturing
degradation of natural resources. Importantly we have not included any adjustment for human
‘capital’, as discussed below.
28. Income and transfers from abroad are also taken into account to arrive at NII, derived
from net national income by adding all current transfers in cash or in-kind receivable by
resident institutional units from non-resident units and subtracting all current transfers in cash
or in kind payable by resident institutional units to non-resident units.
Net Inclusive Income (NII)
Gross Inclusive Income (GII)
Plus: Income from abroad
= Gross National Income
Less: Transfers from Abroad
= Gross National Disposable Income
Less: Depreciation of
i) Tangible and intangible productive assets
ii) Durables in the Household sector
16 Derivations of stock estimates, including asset lives etc is contained in Heys, Bucknall, Christie and
Taylor (2021).
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ii) Uncapitalised intangibles
Less: Degradation of Atmosphere due to Carbon Emissions
= Net Inclusive Income (NII)
29. A key feature of this measure is the subtraction of deprecation for all assets involved
in the production of GII. This means that, as well as subtracting depreciation of those assets
already capitalised in GDP, we also subtract depreciation of capitals involved in household
production.
30. The calculation of natural capital degradation is key to the valuation of environmental
assets within production accounts, however, as ONS have not yet produced these estimates,
this paper presents experimental estimates for an area of environmental assets the authors
view as of primary importance – the atmosphere17.
Deflation
31. We compute GII and NII in both current price (CP) and chain volume measure (CVM)
terms. For CVMs we also need to determine how to deflate assets and flows outside the
national accounts to ensure we adequately control for the relative change in real value over
time of different flows of benefit or cost, noting that in some instance direct measures of
volume are available which do not require deflating.
32. This is one of the most complex issues in this study: how best to ensure that prices
have been adjusted into comparable terms which make conceptual sense. In a number of
instances we have derived volume measures in terms of CVM values from available current
price estimates. As such, we made every attempt to utilise deflators from other ONS data
sources (such as producer price indexes), from National Accounts, or have used the GDP
deflator where appropriate local deflators are unavailable. In some cases direct volume
measures are available and have been used where high-quality deflators are not available.
Both GII and NII CVMs have been constructed by chaining together the relevant
components.
IV. Exclusions and areas for future work
33. For speed we have worked with available data. In some instances data is not available,
or the work to align the conceptual frameworks has not been fully undertaken. Some data is
therefore excluded, which we would wish to later incorporate, and we have provided
experimental estimates where international methods agreement has not yet been achieved.
These include the experimental, purpose-built estimates of carbon emission related
atmosphere degradation, the treatment of public service quality adjustments, and the use of
the ONS’s experimental estimates of uncapitalised intangibles. Finally, in the interest of
pragmatism we have identified further conceptual changes which would be required to make
our system fully internally consistent but where we have not been able to make progress.
These include the use of free digital services and platforms, degradation of other
environmental assets, and the full inclusion of human capital.
Improving atmospherics degradation estimates
17 This model only reflects degradation due to carbon emissions. As this excludes greenhouse gases
such as methane, the model could be thought of as a lower bound estimate of atmospheric degradation
– or, more accurately, atmospheric degradation purely accounted for by carbon emissions. The model
also makes no assumption of the proportion of the atmosphere – if any – which would be included
within the UK’s national or domestic boundary, or which economic sector owns the atmosphere.
Instead, degradation of the (global) atmosphere, as included in NII, can be interpreted as a
combination of two phenomenon, both of which have the same effect on the numbers. The first is the
UK ‘consuming’ its own atmospheric environmental asset through the emission of carbon. The
second is the UK importing degradation (akin to importing capital services) of the atmosphere
through the emission of carbon into the non-UK atmosphere. As both of these (consumption of
‘capital’ and importing of ‘capital services’) have the same effect on a ‘net’ measure of production,
the question of which is taking place can be put to one side.
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34. Currently being addressed on an international level through the SNA update is the
framework for environmental degradation measurement, and its relation to National
Accounts. This article uses a highly experimental model for estimating atmosphere
degradation related to carbon-emission induced climate change, but this represents a highly
simplified approach – while attempting to follow SEEA guidance where possible – compared
to the integrated set of environmental asset accounts which would be required to fully
understand the economic effects of climate change. As internationally agreed methods are
put in place we would look to substitute these for those put forward as part of this work.
Improving quality adjustments for public services.
35. Quality adjustment of output, particularly that of public service output, remains
challenging in the National Accounts. While quality adjustment of market output can be
achieved indirectly through adjusting prices and deflators, this approach cannot be used for
public service output due to their being provide free at the point of consumption. Hence,
finding conceptually ideal indicators with which to quality adjust the output of this sector
remains challenging and an area always needing further improvement and development.
While this paper uses those adjustments available and expands them to cover all non-market
production of public services, this is no substitute for the rigorous development of new and
improved quality metrics on a service-by-service basis. This process was commissioned by
the Chancellor of the Exchequer in 2023 in a review led by Sir Ian Diamond, the National
Statistician, and the relevant UK Statistics Authority (UKSA) processes have been followed
such that once developed, these metrics can be integrated into UK GDP. This would
effectively align GII and GDP in this respect and this adjustment would therefore drop out
of the GII compilation process at that time to prevent duplication.
Improving Intangibles estimates
36. The ONS already publishes long time series of investment data for these assets, some
of which will be incorporated into the 2025 revision of the SNA. As such methods may need
to be amended to align with agreed international best practice.
Free digital services and platforms
37. Top on the agenda is the impact of free digital services – and free digital platforms in
particular – on the measurement of production of household services in the household
satellite account.
38. The economic welfare of societies can be argued to have been increased partly through
access to free digital platforms (and the content hosted on these platforms) such as those
provided by Facebook, YouTube, Instagram, X/Twitter just to mention a few. Households
use these platforms to engage in activities – such as sending tweets, developing TikTok
dances, or composing pictures on Instagram – which may be thought of as own-account
production within a household, or free-at-the-point-of-use trade in services between
households. The reduction in the number of stamps sold whilst the number of messages has
grown exponentially is a classic example of a movement across the current production
boundary distorting our perception of growth in the economy, widely defined.
39. While the business model underlying these platforms is similar in some respects to
long established industries, such as advertisement funded TV programming, the pace at
which digital services have expanded mean the way in which we account for these services
may impact not just our understanding of the long-run level of economic welfare, but its
growth (or decline) in the short term. Where the value of household production of services
using these free digital services as an input is affected by this, this should be accounted for
in GII and NII.
Degradation of environmental assets other than atmospheric degradation
40. This work currently takes account of a limited number of ecosystem services, due to
the short time series currently available for these assets, and the relatively low values attached
to these, in part driven by the efforts made to align pricing of these assets at market price, or
exchange values, which could exclude some or all of the externalities inherent in these
services. The ONS is at the forefront of the work to develop such measures internationally
and we aspire to add to this element of the model as new data series are produced.
ECE/CES/GE.20/2024/13
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Human Capital
41. Human capital represents the most significant remaining concept omitted from this
analysis at this stage, for two reasons. The first is because it may be necessary to adjust
existing aggregates within the National Accounts, whilst the second is the current method for
calculating the stock is subtly different from that used for other capitals, and this data may
require further developmental work to bring into a consistent form.
Compatibility with existing aggregates
42. If human capital is a capital, it must be created through investment. One therefore
needs to identify the process by which this investment occurs. Clearly education output would
be one source, but also business and household spending on adult education, apprentices, and
non-firm specific training would need to be captured within our estimate of human capital
investment. Under the current framework, firm-specific training18, the benefits of which
accrue to the corporate sector, would be captured in the existing estimates of uncapitalised
intangibles already incorporated into GII and NII.
43. Resolving how the entirety of this educational investment is converted into capital is
a substantive topic in its own right. For example, would primary school spending in year 1
be treated as capital investment in year 1, or as ‘work in progress’ until the child has
completed their school career and joined the labour force? Equally, if human capital is a
capital, what is the rate of return and where would this be observed? When one considers
primary and secondary allocations of income, we require an agreed treatment of
compensation of employees (CoE), mixed income and gross operating surpluses based on
agreed sectoral ownership of the human capital asset, and indeed whether there is a need to
disaggregate CoE into a return to labour and a return to human capital. Importantly, how
would one account for depreciation (e.g., skills eroded through unemployment hysteresis),
depletion (e.g., untimely death whilst still in the labour force), and retirement (e.g., people
leaving the labour market as they reach the end of their career)? If one captures retirement,
how then does one account for human capital deployed in the household for household
production, either during retirement or before? What portion of unpaid childcare should be
classified as investment in human capital? Does one adjust the human capital stock for the
health of the workforce? How does one account for imports (immigration) and exports
(emigration) of human capital?
44. Due to these and further similar issues, this paper excludes human capital. However,
Dunn (2022) provides considerable progress in this space based on UN (2016), and we
consider provides a framework for integrating human capital into this model. Additional
research into flows identifiable in ONS’s existing human capital model, as well as detailed
conceptual considerations around this, is the subject of a forthcoming discussion paper
through the Economic Statistics Centre of Excellence.
Computational issues
45. UN (2016) lays out a model for the calculation of human capital stocks in line with
the ground-breaking work of Jorgenson and Fraumeni (1989). This delivers a clear picture of
the expected return to human capital acquisition recognising that human capital qualifications
can serve two purposes; the acquisition of new skills, and acting as a gateway permitting
access to further qualifications which will further enhance skills, increasing earning power,
and themselves potentially permitting access to further qualifications. Let us take a simple
three time period model (shown by t), where in period 1 people can receive education at level
A with probability p(A), and in period 2, undergo education at level B with probability p(B)
if and only if they have achieved education level A. Wages relate to training undergone
(shown by sub-scripts – 0 representing not having achieved educational level A or B) where
w0 < wA < wB, w0 is always received whether working or in education, and δ is a time discount
factor.
18 Defined as training which does not result in a transferable wage supplement – that is if the worker
moves employer the new employer would not add a wage supplement in response to holding these
qualifications.
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The UN (2016) model calculates the human capital (KH) stock of an average individual at
time 0 as the discounted sum of future earnings.
KH
0 = w01 + δ1 [(1-p(A)).w02 + p(A).wA2] + δ2 [(1-(p(A)).w03 + (p(A)-p(B)).wA3 + p(B)).wB3]
46. The challenge with this approach in a National Accounts context is that the capital
investment in future time periods (education B in period 2) is reflected in the stock in period
1. This is akin to arguing that if one took the example of a building to which significant
extension work was undertaken in future time periods, then this future investment should be
incorporated into the capital value of that building today. Core national accounts principles
are to reflect the value of the building today, in line with its current market valuation, and
recognise future investment in maintenance or new capital acquisition in future time periods.
In this light, it is not hard to see why human capital estimates for the UK at £24tn exceed the
complete value of productive capitals contained in the National Accounts (£11tn) to such an
extent (see ONS (2022a) and figure 6 below). National accounts consistent human capital
data, with a clear bridging table to the existing data, is clearly the next required step to show
the value of current investment without further investment, whilst existing published data
show the full potential value of such investments including commensurate future investment.
Initial exploratory work suggests the difference in stock values terms is likely to be in the
region of 15%.
47. Finally, there are two potential expansions to this model, relating to a) externalities
and b) distribution.
Accounting Prices
48. As can be observed in the results section below, the benefits arising from
environmental assets are dramatically low compared to other benefit streams. This is due to
several factors, including;
49. This work has not split out from market, public sector, and non-profit GVA the portion
which could be attributed to ecosystem services (i.e. provisioning services).
50. Due to the limited time spans available for time series, we have not yet incorporated
the full suite of non-provisioning ecosystem services produced by ONS, to maintain
comparability of our estimates across time
51. But as well as these practical factors, there is one important theoretical factor which
may lead to these estimates being lower than expected – following SEEA, the estimates are
based on exchange prices (i.e. market equivalent prices). Considering the externalities
associated with natural capitals and their corresponding ecosystem services, this could omit
a substantial portion of the economic importance of these capitals. The work recommended
by Dasgupta (2021) to make more use of accounting prices, prices which do not reflect
exchange values but instead try to internalise the cost of externalities, is clearly key to
presenting a more realistic picture of these data.
Distributional Analyses
52. By thinking about this work in ‘income’ terms, the key question arises of ‘whose’
income and what do they consume from this income? Once this question is addressed, there
is the further issue of sourcing relevant deflators for different groups. Drawing on Aitkin and
Weale (2018a & 2018b), the question of ‘whose income this is’ can be expanded into several
more particular questions, such as how to allocate non-household income to households, and
which deflator is considered optimal, particularly for services delivered in the household or
from the environment.
53. Net Inclusive Income (NII) denotes the most complete plutocratic (as Aitken and
Weale would describe it) aggregate measure of welfare possible using currently available
data, as it reflects the average of all households not the average household19. Extending this
framework is possible to develop a metric we would label Adjusted Inclusive Income (AII).
19 A simple example is if a billionaire in a country of 60 million people purchased a £60m superyacht
(if this was considered a consumption item), then the average individual would consume £1 of
superyacht.
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This is a ‘democratic’ measure which would attempt to adjust NII to take income distribution
into account (Aitken and Weale 2018a), delivering the growth rates of different percentiles
of the economy. The following figure is a diagrammatic representation of a potential end-
state.
Figure 2
The range of inclusive income metrics
54. Within this framework, Well-being would be measured by pluralistic indicator
frameworks incorporating a wider range of quality-of-life factors which are harder to
conceptualise as flows on consumption / proxied by income. Such frameworks would include
the full range of factors that influences what we value in living, reaching beyond its material
side. Well-being includes intangible aspects that cannot be traded in a market. This paper
again does not attempt to deliver this component of the spectrum, in the main because existing
‘dashboards’, such as the UN’s Sustainable Development Goals (United Nations (2015)) are
clearly superior in terms of their spread and depth. The authors propose that NII or preferably
AII could naturally fit into such a ‘dashboard’ and provide a powerful context for the other
measures.
V. Results
55. A proof of concept, a pilot model was compiled using the methods above to produce
GII (Gross Inclusive Income) and NII (Net Inclusive Income) in previous working papers
which was translated into a full statistical publication in 2022 and 2023 by the Office for
National Statistics (ONS (2023). Whilst data can be sourced for some variables for long time
periods, the period for which all the key data are available is 2005-2019. Full tables are
available in Annex A.
56. Figure 3 presents the relative scale of the adjustments incorporated to derived GII and
then NII in current prices20 for 2019, with positive contributions shown as green and negative
as red. The inclusion of household production is by far the biggest adjustment – adding
£1.54tn in 2019. For context, this is around three times bigger than the size of the non-market
elements of the economy currently contained within GDP and is nearly equivalent in scale of
all market-based production. That is to say that the UK is in a position whereby the value of
production within the household is only marginally less than the value of output produced in
20 The quality adjustment of public services has no effect on current price data, as the quality
adjustment only applied to volume measures.
ECE/CES/GE.20/2024/13
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the market. Whilst we do not have historic data to compare to, this may represent a significant
turning point in UK society and merits further investigation.
57. The size of other contributions added to GDP to derive GII (investment in additional
IPPs, £103bn, and carbon sequestration, -£1.33bn) are substantially smaller, or even
negative21. As we will observe elsewhere, the impact of environmental services, as measured
under SEEA as broadly equivalent to market prices, may exclude significant externalities and
merit consideration, as proposed in Dasgupta (2021), towards measuring value in accounting
prices.
Figure 3
Progression through Spectrum from Market GVA to Net Inclusive Income
UK, £trillions, Current Prices, 2019
58. Note: Different measures are shown in grey, and green and red bars represent
components added to progress from measures on the left to measures on the right. Quality
Adjustment of Public Services has no impact on current price data, but are included for
completeness.
59. Turning to the contributions subtracted from GII to move to NII, we see less of a
dominance of any one component. That said, depreciation of capitals already included in
National Accounts still accounts for just over half the contributions at this stage (-£333bn).
In contrast with its effect on GII, the effect of accounting for household production on moving
to net figures is much more subdued, amounting to just -£79.1bn. Finally, the effect of
carbon-emission related degradation of the atmosphere is relatively small, at -£14.5bn. We
re-emphasise that this measure is intended as a proof-of-concept.
60. As with standard GDP data, comparisons of growth over time are best undertaken
using Chained Volume Measures (CVM) – which control for changes in prices – as shown
in the following figure, which compares NII with GDP, market-sector GVA and NNDI. The
general trajectory of NII over time is correlated with that of GDP but demonstrates weaker
overall growth through the period (20.5% compared to 22.1%). Comparing to Blue Book
NNDI also shows similar overall trends, excepting 2008-9: Blue Book NNDI falls by 6.1%
21 In the case of carbon sequestration this is negative because natural resources in the UK which
should absorb carbon, such as peatland, is so damaged it is currently emitting / releasing carbon rather
than capturing it.
ECE/CES/GE.20/2024/13
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between 2007 and 2009 while NII only fell by 2.8%. However, NII does not always show
stronger growth than GDP, with 2012 telling a quite different story: whilst market GVA grew
at 3.4% and GDP grew at 1.5%, NNDI grew by 0.1% and NII grew by 0.5%. Compared to
GDP, this is driven by negative contributions in that year from capital depreciation (from
national accounts capitals), household production, and income and transfer from abroad.
Figure 4
A comparison of market GVA, standard GDP and Net National Disposable Income, as
published by the ONS in Blue Book 2022, with Gross and Net Inclusive Income
UK, 2005 = 100, Chained Volume Measures
61. Figure 5 explains these differences by decomposing cumulative growth in CVM GII
and NII since 2005. Whilst market GVA is a relatively large component with substantial
volatility – such as the 2008-09 recession and subsequent recovery, other components of NII
mitigate these movements. When market sector GVA pushed GII growth downwards by 2.9
percentage points in 2009, household production partially offset this through a 0.4pp upwards
contribution. Interestingly, household production generally demonstrates a stronger counter-
cyclical dynamic (i.e. growth in household production is negatively correlated with growth
in market GVA) than non-market GVA currently included in GDP.
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Figure 5
Contributions to growth in CVM GII and NII since 2005
UK, % and percentage points
Notes: “IPPs” refers to a subset of assets called Intellectual Property Products, otherwise
known as “intangible capital”.
62. Certain stories dominate: while the market economy is the largest contributor to
growth in GII (and so NII), household production makes a substantial contribution in second.
While (CVM) market GVA grew by 25.6% between 2005 and 2019, household production
grew by 17.9%. Additionally, an interesting narrative which comes out of this data is that,
despite carbon emissions falling over the period, carbon-related climate degradation
increased (albeit mildly) so climate degradation contributed negatively to NII. This can be
attributed to the global temperatures increasing over time, such that the marginal growth in
the damage per unit of carbon emitted outweighed the effect of carbon emissions falling, or
put another way, the price of the damage incurred grew faster than UK output of emissions
fell.
63. Finally, annual growth figures are summarised in Figure 6 for all measures.
Differences between the growth rates mostly below 2 percentage points, with a few outliers;
2008-09 for example, reflecting the market-led economic downturn in those years.
Nevertheless, an overall effect can clearly be seen: while broad trends are similar, NII and
GII growth were less volatile than NNDI and GDP. This indicates that market-centred
ECE/CES/GE.20/2024/13
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indicators like GDP may overstate the importance of short-term factors on economic welfare,
and broader measures like NII may better focus on longer term trends.
Figure 6
Comparison of annual growth for economic welfare measures
UK, % change on same time previous year, Chained Volume Measure (CVM)
64. These analyses demonstrate the power of these new aggregates in assessing
expansions of the production and asset boundaries in order to better measure welfare – and
evaluating how these expansions can change our understanding of events like the 2008-09
recession.
VI. Conclusions
65. This paper claims only a relatively narrow contribution to the international statistical
community’s broader work on Beyond GDP – it does not deal with distributional issues, or
comprehensively tackle the inter-linkages between the Stiglitz’s three pillars of the Economy,
Environment, and Society. It brings together many pieces of work which have previously
been treated in isolation and adds value by combining them within a framework consistent
with those already in place for National Accounts, but it is not a substitute for the UN’s
Sustainable Development Goals, or other multi-dimensional analyses of wider wellbeing,
where the components of these are harder to conceptualise in proxy income terms.
66. This paper nevertheless presents new indicators of welfare using national accounts
methods applied to a wider range of assets, goods, and services, using data which is available
today. Even using this limited evidence, several key insights are available which touch on a
variety of key current debates.
67. Firstly, our perspective of the way the UK produces goods and services has to reflect
the impact of unpaid household production of goods and services, specifically whether the
large and growing share of GII which we observe is evidence of a fundamental change in the
way we relate to production as a society.
68. Second, and inherent in the first, is the question of the relationship between paid and
unpaid work, both following the 2007-9 Financial crisis and the Covid-19 pandemic. What
factors caused labour to become dislocated from paid activity at these times, and here in
particular the question of distribution is important: if this unpaid work is retired people on
good pensions delivering unpaid childcare through enjoying days out with their
ECE/CES/GE.20/2024/13
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grandchildren this is dramatically different from a lone parent providing the same childcare
because they cannot afford to work and pay childcare fees. The relationship between financial
and non-financial wealth and the decision to opt out (either fully or in part) of the labour
market and deliver unpaid output is one we consider worthy of further investigation.
69. In the immediate term, the relative growth of unpaid work and its distribution have
experienced a major shock, through Covid-19. During the pandemic, roughly a quarter of the
UK workforce were furloughed and had more time for training, self-development, or to
undertake unpaid activity in the home, shifting a volume of consumer services from the
market economy back to the household economy. For example, time use data taken between
28 March and 26 April 2020 indicates that time spent on paid work was below 2014-15 levels,
but time spent on gardening and DIY increased during lockdown (ONS 2020b). GDP fell
over this period, but GII and NII would allow us to analyse the effect of the wider basket of
contributors to economic welfare through the shock, such as reduced pollution from fewer
car journeys. While this would not fully capture the effect of the lockdown on wider well-
being – for example, the effects of a possible increase in domestic violence (ONS 2020a) or
reduced socialising due to social distancing – being able to judge the extent to which
economic activity ‘shifted’ outside the traditional production boundary and the extent to
which economic activity as a whole actually declined would be a useful advancement of our
understanding of the pandemic.
70. Fourth, the dramatic extent of growth outside the production boundary necessarily
compels us to think again about productivity and the puzzle of the UK’s low growth since
2008. Whilst traditional analyses have focussed on investment and flatlining TFP growth, it
needs to be questioned whether we should be considering this growth of output as a key
factor. For example, could it be the case that business innovation and investment may be
delivering growth outside the traditional measures of the market sector? An obvious example
is investment in projects to reduce carbon emissions and other pollutants. A business could
easily invest significant sums to do this, without delivering any increase in output, with the
benefits being observed only through enhanced ecosystems delivering improved flows of
services to households. Stopping polluting a public beach improves that beach’s amenity
value but is not visible in GDP as currently scoped22. Secondly, as mentioned above, free
goods and services have dramatically changed the production technology for unpaid
activities. Instead of writing one or two letters a week and posting these via the mail, today’s
digital correspondent sends dozens of written communications a day, via platforms such as
email, LinkedIn, Facebook, WhatsApp and Twitter/X to name but a few. That exponential
growth in unpaid output, from one or two communications to maybe hundreds is just one
example of how free technologies may have created vast productivity growth, just not within
GDP, which will only value these platforms in terms of the cost of production.
71. Fifth, this work presents a significant challenge to natural capital measurement. The
SEEA uses, as mentioned, market prices or imputes the equivalent to exchange values. Whilst
these will internalise some current externalities, the threat is this may continue to under-value
these assets and hence place relative less importance onto them than justified. In part this is
because of notable methodological challenges around how to value cliff-edges in marginal
pricing models. This suggests further thought needs to be urgently given to the feasibility of
using accounting prices rather than market prices, recognising the challenges both
methodological and practical. Finally, the impact of human capital, when applied into the
framework could be very significant, but is heavily dependent on continued methodological
work. Where the current international methods appear to not fully align with national
accounting norms means more work is required, and this may change our understanding of
the relative value of human capital in the UK.
72. These are all key questions: the nature of the UK economy, the nature of apparent
economic inactivity, the relative importance of the environment, the productivity puzzle and
22 It may be visible in a market price if the beach has charged access and more can be charged to
access a ‘clean’ beach. One of the challenges with accounting prices is not necessarily adding the
externalities costs to the polluters price, but working out if there are second-order effects where the
externality may, to some degree already be included in a different price. Public service provision of
health services may be the key example of this.
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the importance of human capital, and all are cast in a new and better informed way by
presenting data together to allow policy-makers to observe in a simple way the trade-offs
between the economic, social and environmental domains. Following sustained investment
since the Bean Review (2016) the UK’s Office for National Statistics, commenced
publication of these data in 2022 and will be updating as well as improving upon them over
time. Although these data will be improved further in future years, the ability to apply proven
methods and techniques across a wider landscape opens the door for economists to build
upon, rather than rebuilding, GDP without further delay. Rather than long debates about how
and whether to change GDP, this model allows consumer choice, and provides users a means
to place the data they have previously used into a wider context at low additional cost to the
taxpayer now the foundational investments by ONS have already been delivered. Whilst there
is always more to do to perfect methods and data, we have enough data to aide users now,
without compromising the quality of market-based metrics essential for macro-economic
policy making.
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Annex A
GII and NII Datasets
Table F1
Current Price Spectrum Estimates and Contributions
Market
GVA
Non-market
GVA
Taxes
minus
subsidies GDP
Intangible
Investment
Quality
Adjusted
Public
Services
Household
production
Carbon
Sequestration
Gross
Inclusive
Income
Capital
depreciation:
National
Accounts
Capital
depreciation:
Intangible
Investment
Capital
depreciation:
Household
Capital
Climate
degradation
Income &
Transfers
from abroad
Net
Inclusive
Income
1997 631,841 230,601 91,510 953,952 48,709 - - 123,199 - 4,937 - 6,814
1998 662,863 237,753 98,710 999,326 52,684 - - 1,314 - 127,653 - 5,273 1,835
1999 687,055 250,032 107,063 1,044,150 56,607 - - 1,385 - 135,278 - 5,722 - 11,626
2000 726,530 261,376 113,237 1,101,143 61,658 - - 1,373 - 143,789 - 6,523 - 7,148
2001 752,093 278,212 115,018 1,145,323 64,016 - - 1,318 - 153,461 - 7,522 - 762
2002 781,004 291,229 119,282 1,191,515 66,379 - - 1,238 - 161,878 - 7,828 4,380
2003 824,487 309,746 125,442 1,259,675 69,035 - - 1,237 - 170,746 - 8,760 3,595
2004 861,775 328,421 133,224 1,323,420 72,008 - - 1,165 - 177,483 - 9,348 - 164
2005 912,809 347,991 138,843 1,399,643 75,307 - 684,877 - 1,149 2,158,677 - 187,530 - 68,932 - 62,451 - 10,028 1,710 1,831,446
2006 962,522 364,204 146,111 1,472,837 78,114 - 710,686 - 1,102 2,260,535 - 199,136 - 72,150 - 63,782 - 10,666 - 18,366 1,896,435
2007 1,013,865 377,448 154,479 1,545,792 82,952 - 761,523 - 1,059 2,389,208 - 210,672 - 75,485 - 65,378 - 11,401 - 27,858 1,998,414
2008 1,051,497 391,663 151,577 1,594,737 82,293 - 822,438 - 1,010 2,498,458 - 225,870 - 79,919 - 62,989 - 11,937 - 34,899 2,082,845
2009 1,010,393 402,865 138,624 1,551,882 80,997 - 890,020 - 1,009 2,521,889 - 235,710 - 83,507 - 61,595 - 11,479 - 28,492 2,101,107
2010 1,040,692 412,139 159,550 1,612,381 80,045 - 917,950 - 1,004 2,609,372 - 236,805 - 86,091 - 62,119 - 12,912 - 19,561 2,191,884
2011 1,070,943 415,001 178,267 1,664,211 77,416 - 982,992 - 956 2,723,663 - 243,877 - 86,456 - 62,570 - 12,733 - 14,136 2,303,892
2012 1,107,224 423,912 182,105 1,713,241 78,390 - 1,021,507 - 993 2,812,145 - 252,270 - 85,699 - 63,888 - 13,984 - 37,102 2,359,202
2013 1,161,386 429,369 191,541 1,782,296 81,434 - 1,092,304 - 1,050 2,954,984 - 259,619 - 84,858 - 65,408 - 14,408 - 57,689 2,473,002
2014 1,217,581 443,471 201,775 1,862,827 83,314 - 1,144,063 - 1,019 3,089,185 - 268,199 - 84,752 - 66,989 - 13,829 - 57,559 2,597,856
2015 1,257,522 455,907 207,569 1,920,998 88,461 - 1,213,031 - 1,112 3,221,378 - 277,744 - 83,643 - 69,457 - 13,379 - 65,988 2,711,167
2016 1,308,415 473,700 217,346 1,999,461 91,678 - 1,242,874 - 1,078 3,332,935 - 290,604 - 84,714 - 71,109 - 13,226 - 70,973 2,802,308
2017 1,374,338 485,948 224,722 2,085,008 97,248 - 1,335,697 - 1,048 3,516,905 - 306,716 - 86,618 - 72,332 - 13,537 - 45,324 2,992,377
2018 1,420,672 504,763 231,975 2,157,410 102,726 - 1,437,117 - 1,198 3,696,056 - 319,006 - 89,107 - 75,572 - 14,128 - 55,247 3,142,997
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2019 1,473,430 526,727 238,191 2,238,348 102,563 - 1,543,104 - 1,329 3,882,686 - 332,595 - 92,242 - 79,090 - 14,480 - 27,535 3,336,744
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Table F2
Chained Volume Spectrum Measures and Contributions (£2019)
Market
GVA
Non-
market
GVA
Taxes
minus
subsidies GDP
Intangible
Investment
Quality
Adjusted
Public
Services
Household
production
Carbon
Sequestra
tion
Gross
Inclusive
Income
Capital
depreciation:
National
Accounts
Capital
depreciation:
Intangible
Investment
Capital
depreciation:
Household
Capital
Climate
degradation
Income &
Transfers
from abroad
Net
Inclusive
Income
1997 904,686 405,845 167,436 1,471,263 69,001
-
24,369
-
186,838
-
3,199
-
10,509
1998 940,048 409,977 172,999 1,517,715 73,531 23,485
1,997
192,680
3,470 2,787
1999 972,464 419,655 175,939 1,563,460 78,390 23,290
2,073
200,032
3,823 17,408
2000 1,025,507 422,025 182,246 1,627,447 86,245 22,273
2,028
208,460
4,416 10,564
2001 1,046,135 431,933 187,101 1,662,558 87,229 23,163
1,913
217,344
5,183 1,106
2002 1,068,237 431,813 194,352 1,691,998 88,793 21,458
1,759
226,169
5,511 6,220
2003 1,105,073 441,551 200,390 1,744,840 90,283 20,131
1,713
234,662
6,325 4,980
2004 1,130,121 449,997 208,221 1,785,756 91,822 18,723
1,572
241,741
6,927 221
2005 1,172,850 452,892 209,128 1,833,406 94,470 15,774 1,310,296 1,506 3,221,530 248,549 91,666 51,539 7,652 2,240 2,839,782
2006 1,203,792 458,950 211,336 1,873,015 95,754 13,083 1,317,411 1,402 3,276,506 255,313 90,845 52,549 8,384 23,356 2,856,262
2007 1,249,469 455,995 216,540 1,921,029 101,091 11,954 1,311,936 1,315 3,334,558 263,012 91,057 53,556 9,178 34,620 2,890,583
2008 1,250,942 455,217 212,408 1,918,064 98,206 10,527 1,354,440 1,215 3,363,949 270,911 92,321 54,319 9,919 41,975 2,899,135
2009 1,175,797 453,099 202,640 1,831,550 91,589 8,447 1,369,625 1,191 3,274,159 276,469 92,548 54,994 9,723 33,627 2,808,489
2010 1,214,106 457,308 204,165 1,876,058 90,548 7,526 1,381,185 1,169 3,332,711 281,882 92,372 55,914 11,092 22,760 2,871,584
2011 1,233,261 457,440 205,038 1,896,087 86,901 5,897 1,413,981 1,089 3,380,406 286,888 91,311 56,866 11,179 16,106 2,922,267
2012 1,255,362 463,993 203,874 1,923,551 87,420 5,116 1,433,880 1,114 3,428,930 290,924 89,472 57,894 12,460 41,656 2,937,984
2013 1,286,304 463,042 209,197 1,958,557 88,221 4,271 1,457,715 1,154 3,489,264 293,678 87,519 59,566 13,112 63,394 2,971,642
2014 1,334,928 471,297 215,150 2,021,225 89,946 3,012 1,438,019 1,105 3,542,339 297,692 86,358 61,182 12,750 62,453 3,022,115
2015 1,362,923 482,706 224,003 2,069,595 94,913 2,161 1,457,662 1,198 3,617,441 303,653 85,707 63,399 12,416 71,092 3,081,136
2016 1,393,865 493,767 226,792 2,114,406 96,943 1,736 1,472,509 1,139 3,680,643 310,914 86,590 66,574 12,512 75,053 3,128,323
2017 1,430,701 504,336 231,113 2,166,073 100,862 1,320 1,514,081 1,088 3,777,939 318,976 88,084 70,280 13,036 47,086 3,241,120
2018 1,449,855 516,415 236,775 2,203,005 105,163 448 1,531,011 1,224 3,837,333 326,547 89,959 74,696 13,831 56,415 3,275,581
2019 1,473,430 526,727 238,191 2,238,348 102,563 - 1,543,104 1,329 3,882,686 332,595 92,242 79,090 14,480 27,535 3,336,744
E
C
E
/C
E
S/G
E
.20/2024/13
23
Table F3
Contributions to Cumulative Growth in CVM Net Inclusive Income Since 2005 (percentage points)
Market GVA
Non-market
GVA
Taxes minus
subsidies
Investment in
additional IPPs
Quality
Adjusted
Public
Services
Household
production
Carbon
Sequestration
Capital
depreciation:
National
Accounts
Capital
depreciation:
Additional
IPPs
Capital
depreciation:
Household
Capital
Climate
degradation
Income &
Transfers
from abroad
Net
Inclusive
Income
2005 0 0 0 0 0 0 0 0 0 0 0 0 0
2006 1.31 0.25 0.08 0.06 0.09 0.2 0 -0.28 0.03 -0.07 -0.05 -1.07 0.58
2007 3.25 0.13 0.27 0.29 0.14 0.05 0.01 -0.6 0.02 -0.13 -0.11 -1.54 1.79
2008 3.31 0.1 0.12 0.17 0.19 1.3 0.01 -0.92 -0.03 -0.18 -0.15 -1.84 2.09
2009 0.22 0.01 -0.22 -0.11 0.27 1.76 0.01 -1.15 -0.04 -0.22 -0.14 -1.5 -1.1
2010 1.77 0.18 -0.17 -0.15 0.31 2.11 0.01 -1.36 -0.03 -0.27 -0.22 -1.06 1.12
2011 2.52 0.19 -0.14 -0.3 0.37 3.11 0.02 -1.56 0.01 -0.31 -0.22 -0.8 2.9
2012 3.38 0.45 -0.19 -0.27 0.4 3.73 0.02 -1.71 0.09 -0.37 -0.29 -1.8 3.46
2013 4.58 0.42 0.02 -0.25 0.44 4.48 0.01 -1.82 0.17 -0.45 -0.32 -2.65 4.64
2014 6.44 0.74 0.25 -0.18 0.48 3.85 0.02 -1.97 0.22 -0.52 -0.3 -2.62 6.42
2015 7.48 1.18 0.59 0.01 0.51 4.49 0.01 -2.19 0.25 -0.62 -0.29 -2.94 8.5
2016 8.62 1.6 0.7 0.09 0.53 4.99 0.02 -2.45 0.21 -0.76 -0.29 -3.09 10.16
2017 9.98 2 0.86 0.23 0.55 6.37 0.02 -2.75 0.16 -0.92 -0.31 -2.05 14.13
2018 10.69 2.44 1.07 0.39 0.57 6.94 0.01 -3.03 0.09 -1.09 -0.35 -2.39 15.35
2019 11.53 2.81 1.12 0.29 0.59 7.35 0.01 -3.24 0 -1.25 -0.37 -1.35 17.5
ECE/CES/GE.20/2019/5
24
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- Group of Experts on National Accounts
- Twenty-third session
- GDP and Welfare: Empirical Estimates of a spectrum of opportunity
- Prepared by Office for National Statistics, United Kingdom0F
- I. Introduction
- II. The measurement challenge
- III. Proposed Methods12F
- IV. Exclusions and areas for future work
- V. Results
- VI. Conclusions
- Bibliography
