Macro-economic health-focussed assessment of
GHG emission reduction strategies in the UK
DRAFT PAPER- PLEASE DO NOT QUOTE OR CITE
Henning Tarp Jensen*
Marcus Keogh-Brown
Richard D Smith
Zaid Chalabi
Mike Davies
Alan Dangour
Phil Edwards
Tara Garnett
Moshe Givoni
Ulla Griffiths
Ian Hamilton
Ian Roberts
Paul Wilkinson
James Woodcock
Andy Haines,
*Corresponding author: Senior Researcher Henning Tarp Jensen, Institute of Food and
Resource Economics, University of Copenhagen, Rolighedsvej 25, DK-1958 Frederiksberg,
Denmark. Email: htj@foi.ku.dk.
Acknowledgements
Funded by the UK Department of Health Policy Research Programme.
1
1 Introduction
High and increasing greenhouse gas (GHG) emissions have remained an urgent priority on the
international political agenda since the first Assessment Report of the Intergovernmental Panel on
Climate Change (IPCC 1990).1 The most recent IPCC report found a high likelihood of a range of
serious impacts at global mean temperature increases above 2°C (IPCC 2007). Climate model
predictions suggest that this scenario is very plausible since future temperature rises will, most likely,
fall within the interval of 2.0-4.5°C over the course of this century (Roe and Baker 2007). Hence,
there is a need for immediate global action. The need for global action is further underlined by recent
evidence suggesting that the current Copenhagen Accord commitments are insufficient to maintain a
medium (50-66%) chance of achieving the 2°C target (den Elzen, Hof and Roelfsema 2011), and that
delayed action until 2030 will be virtually impossible to compensate for in later years (den Elzen et al.
2010).
In response to the call for action, a vast inter-disciplinary literature has emerged on a range of
economically-related aspects of climate change, including the costs of mitigation and adaptation, and
the use of policy instruments such as carbon pricing and accelerated technological innovation (Stern
2007). The UK has committed itself through the adoption of global treaties (the Kyoto protocol) and
unilateral legislation (the 2008 Climate Change Act), to reduce GHG emissions by 80% in 2050
relative to 1990 levels (DECC 2008). Preliminary estimates suggest that UK emissions have been
reduced by around 25% in 2010 (DECC 2011). This is better than the formal 23% reduction target for
the first carbon budget period 2008-2012, but remains well below future targets (and some emissions
have been ‘exported’ as a result of purchasing products from emerging economies such as China). A
number of new UK mitigation initiatives are, therefore, needed in order to achieve the intermediate
50% reduction target in 2030 and the final 80% reduction target in 2050. Even this target may be
conservative in the light of current trends in emissions.
Policies to reduce greenhouse gas emissions may also result in substantial ancillary (co-) benefits to
health, for example as a result of reduced fine particulate air pollution from cuts in coal combustion,
or from increased physical activity as a result of increased active travel (walking and cycling) and
reduced car use in urban centres. The current study uses a single-country Computable General
Equilibrium (CGE) model to assess UK GHG mitigation initiatives, which can help to achieve the
50% UK reduction target in 2030. The study focuses on initiatives with important health benefits, and
concentrates on three sectors: urban transport, home insulation, and food and agriculture. Previous
macroeconomic CGE model studies have focussed on health co-benefits related to reduced air
pollution (Garbaccio, Ho and Jorgenson 2000; Li 2002; Dessus and O’Connor 2003; Bosello, Roson
and Tol 2006; Ciscar et al 2010). The current study follows Haines et al. (2009) and Jack and Kinney
(2010) and applies an extended health co-benefits concept. The extended methodology is important
for capturing the full economic effects and to address the long-standing critique that macroeconomic
cost-benefit analyses may overestimate the net cost of GHG interventions (van den Bergh 2010).
Four previously established UK household-level GHG scenarios with important health benefits are
analysed: (1) a healthy diet scenario (Friel et al. 2009), (2) a household insulation and improved
1
Although a more accurate term would be “greenhouse pollutants”, we will employ the widely used term
“greenhouse gases” to refer to all anthropogenic climate-active atmospheric species including both gases and
aerosols.
2
ventilation control scenario (Wilkinson et al. 2009), (3) a cleaner cars scenario (Woodcock et al.
2009), and (4) an active travel scenario (Woodcock et al. 2009). Standard and breakeven
methodologies are applied to assess the cost-effectiveness of the four scenarios. Previous
macroeconomic assessment studies have been criticized for assuming a trade-off between global
warming initiatives and economic activity (van den Bergh 2010). In contrast, the current study seeks
to assess potentially cost-effective ways of achieving a given reduction in GHG emissions – in this
case the 2030 UK target reduction.
The rest of this article is structured as follows: Section 2 provides background information and
reviews the existing macroeconomic literature on GHG emission reductions and health co-benefits;
Section 3 present our emission reduction scenarios and discusses the measurement of health effects;
Section 4 presents the macroeconomic methodology for our cost-effectiveness analyses; Section 5
presents the main results; and section 6 presents conclusions.
2 Background
We seek to analyse cost-effective ways of achieving a given reduction in UK GHG emissions. The
analytical starting point is that scientific evidence attaches wide probability distributions to global
temperature increases and inter alia to possible changes in human living conditions. Since excessive
temperature increases and associated changes in precipitation and (extreme) weather patterns are
likely to have catastrophic consequences for many areas around the globe, this study acknowledges
that it is imperative to limit GHG emissions to levels which are consistent with the IPCC upper bound
of a long term 2°C temperature increase (within reasonable levels of confidence). The key issue then
becomes how to achieve the given emission targets in a cost-effective way.2
Due to the urgency and multi-facetted nature of global warming, a vast inter-disciplinary literature has
emerged over the last couple of decades (Stern 2007). In view of the global nature of the problem,
macroeconomic impact studies have typically employed national or global Computable General
Equilibrium (CGE) simulation models. Global models have the proper dimensions for measuring, for
example, the impact of international emissions trading schemes (Klepper and Peterson 2005;
Nijkamp, Wang and Kremers 2005; Hagem et al. 2006; Böhringer and Helm 2008) and multilateral
agreements such as the Copenhagen Accord (den Elzen, Hof, Beltran et al. 2011; Lim 2011; Peterson,
Schleich and Duscha 2011). In contrast, detailed single-country models are better equipped to assess
the national impact of domestic emission reduction strategies (Telli, Voyvoda and Yeldan 2008;
Böhringer and Rutherford 2010) and specific interventions such as the introduction of abatement
technologies (Dellink et al. 2004; Grepperud and Rasmussen 2004; Fisher-Vanden and Wing 2008).
Previous CGE model studies of health benefits have focused narrowly on health co-benefits from air
pollution. The multi-country studies have focussed on global temperature-related health effects of
specific global warming scenarios (Bosello, Roson and Tol 2006; Ciscar et al 2010), while the singlecountry studies have typically focussed on health effects of changes in local air pollution due to
demand-constraining carbon tax interventions (Garbaccio, Ho and Jorgenson 2000; Li 2002; Dessus
2
Previous macroeconomic studies have been criticized for assessing the economic value of undertaking GHGrelated interventions (van den Bergh 2010). The main line of criticism seems to be that the imperative of
avoiding extreme climate change cannot be traded off against potential welfare losses from required
investments in mitigation measures. Hence, it has been argued that the key issue is “whether consumption
growth can compensate for environmental degradation caused by global warming” (Neumayer 1999).
3
and O’Connor 2003). This study extends the existing single-country CGE model methodology by
employing an extended health effects concept, and by analysing a set of interventions which includes
both demand-constraining and efficiency-enhancing mitigation elements.
Two of the existing single-country studies characterized health outcomes in terms of disease
symptoms and evaluated them based on willingness-to-pay (WTP) estimates (Garbaccio, Ho and
Jorgenson 2000; Dessus and O’Connor 2003). A different approach was adopted by Li (2002), who
measured the impact of morbidity and mortality effects on (1) labour supplies and (2) health-system
costs, and imposed these shocks on the CGE model and evaluated their overall impact based on an
equivalent variation (EV) welfare measure. The current study relies on a similar but more wellfounded public health methodology. Basic health effects have been measured on the basis of WHOs
Comparative Risk Assessment (CRA) approach (Woodcock et al. 2009; Friel et al. 2009; Wilkinson et
al. 2009). However, while the existing literature focused on health co-benefits related to reduced
emissions of local air pollutants, the current study applies an extended health effects concept
encompassing other sectors (Haines et al. 2009; Jack and Kinney 2010). The extended methodology
includes health externalities associated with (1) direct effects of GHG interventions (for example
reduced fine particulate air pollution as a result of switching to low emission vehicles), and 2) indirect
effects of GHG interventions, (for example increased physical activity associated with a switch in
transport mode from motorized vehicles to walking and cycling).3
The current study also extends the existing CGE model literature on GHG-related health effects, by
explicitly including both demand-constraining and efficiency-enhancing mitigation interventions.
Demand-constraining interventions lower GHG emissions through reduced demand (and production)
of pollution-intensive goods and services. They are typically implemented through the use of tax
instruments (or outright regulatory constraints). Efficiency-enhancing interventions are characterised
by reducing GHG emissions through the introduction of new efficiency-enhancing technologies or by
increased efficiency of existing technologies. Below, we analyse interventions of both types of
efficiency-enhancing interventions including e.g. the introduction of cleaner cars (emission-saving
technology), and a reduction in urban congestion (which increases the flow of urban traffic, and
thereby lowers emissions from the existing car pool). We demonstrate below how the costeffectiveness of specific GHG policies depends critically on whether they contain (1) efficiencyenhancing mitigation elements, and (2) other positive (health) externalities. This is particularly
important in order to capture the full economic effects and provide proper measures of the costeffectiveness of UK GHG intervention strategies.
3 Data base and simulation model4
3.1 Macroeconomic CGE model
The economy-wide dynamically-recursive Computable General Equilibrium (CGE) model, used in
this study, is based on the ‘IFPRI standard model’ (Löfgren, Lee Harris and Robinson 2002). This is a
well-known and widely applied comparative static, single country, open economy, multi-sector CGE
model, which has recently been used in health and trade-related applications by some of the authors
3
Our focus is on measuring other health co-benefits. Hence, health co-benefits from reduced local air pollution
is only taken into account in one scenario, below (cleaner cars).
4
For details, see Annex A.
4
(Smith, Keogh-Brown et al. 2009; Lock, Smith et al. 2010, Jensen, Robinson and Tarp 2010). The
model accounts for different types of agents including producers/enterprises, private households, the
government sector and the foreign sector.
The CGE model for the UK economy was calibrated on the basis of a 2004 social accounting matrix
(SAM) dataset taken from the GTAP database v7 (Narayanan and Walmsley 2008). The model is a
neo-classical model based on the fundamental principles of profit-maximization among producers and
utility maximization among households. The standard model specification was expanded to account
for household production of transport services and heating services. Furthermore, a set of factor
updating equations was added to turn the static model into a dynamically-recursive UK CGE model.
A standard neo-classical model closure is used in all simulations, implying that flexible prices are
clearing all goods and factor markets and that a flexible real exchange rate is clearing the current
account of the balance of payments. Furthermore, all simulations are based on a revenue-neutral
government budget closure (endogenous household tax rate) which ensures that changes in individual
government revenue components (e.g. due to the introduction of a fat tax or road pricing tax) will not
affect the relative size of the government sector in the economy.
The dynamically-recursive UK CGE model had to be run forward from 2004 (the year of the data set)
to 2010 (the pre-starting year of the simulations). To ensure that the model mirrored the 2010 UK
economy, we targeted key macroeconomic aggregates (nominal and real GDP) over the period 20042010. Furthermore, we created a reasonable 2011-2030 counterfactual growth path by targeting 19902010 historical UK growth rates for nominal GDP (5.1% p.a.) and real GDP (2.1% p.a.). This implies
that the GDP deflator (our numeraire price index) grows at historical UK growth rates (2.9% p.a.) as
well, along our counterfactual growth path.
3.2 Assessment methodology
Two types of assessment methodologies are applied to evaluate the cost-effectiveness of policy
scenarios: (1) a standard methodology, and (2) a breakeven methodology. The standard methodology
is based on standard factor accumulation and therefore compares standard policy simulations to the
counterfactual growth path. In contrast, the breakeven methodology calculates the maximum (timeconstant) non-productive investment costs, which are consistent with an unchanged NPV value of
GDP over the 20 year simulation horizon (2011-2030). More specifically, non-productive investment
replaces productive investment until NPV of GDP is similar to the counterfactual growth path, and the
value of the potential non-productive investment is equal to the breakeven investment cost.
The breakeven methodology is targeted at policy scenarios with an investment element and, in
particular, towards scenarios where there is significant uncertainty about the size of the future
investment intervention. The breakeven methodology is useful, since it provides an accurate measure
of the non-productive investment financing which can be extracted from the UK economy (on a
recurring basis) without reducing future income generation. The breakeven measure is superior to e.g.
the NPV of GDP measure from standard simulations, which does not account for the ripple effects of
reduced productive investment/capital accumulation on future income generation. Due to crowdingout of productive investment and capital accumulation, a £1 increase in current non-productive
investment (and crowding-out of £1 of productive investment) reduces future income generation.
Hence, increased investment financing today will reduce potential investment financing tomorrow.
This mechanism is automatically taken into account in the breakeven methodology. When the purpose
5
is to evaluate a scenario where investment costs are uncertain, the breakeven methodology may
therefore provide a tool for generating key information on breakeven investment costs.5
3.3 Health effects
For each disease, detailed age- and gender-specific calculations of disease burdens, Years of healthy
Life lost due to Disability (YLD) and Years of Life Lost (YLL) were used to calculate implied
changes to UK healthcare costs, UK labour supplies, and UK social security transfers. Gender and
age-specific health effects (YLD/YLL) were determined by the WHO Comparative Risk Assessment
(CRA) approach (see Woodcock et al. 2009; Friel et al. 2009; Wilkinson et al. 2009), and distributed
over the 20 year horizon (see Smith et al. 2012). The resulting dynamic patterns of health effects were
used to derive (1) changes in the effective labour force and (2) changes in social security transfers
including reduced labour market benefits and increased pension payments. Furthermore, changes in
healthcare costs were measured on the basis of changes in disease burden for various health outcomes
and injuries. (See Smith et al. 2012 for details on the methodology, and Table 1, below, for scenariospecific health effects imposed on the CGE model.)
4 Policy scenarios6
The four policy scenarios are presented in the Box below (see Annex B for details). These scenarios
focus on household-level interventions, and include one food and agriculture scenario (‘healthy diet’),
two transport sector scenarios (‘active travel’ and ‘cleaner cars’), and one household energy scenario
(‘home insulation’). The agriculture and energy sector scenarios were designed to achieve UK-wide
50% sector-specific emission reduction targets in 2030, while the two transport scenarios were
designed to achieve a combined urban 60% emission reduction target for England and Wales. It has
previously been argued that the scenarios may bring substantial benefits for both climate protection
and health outcomes (Haines et al. 2009).
The four scenarios include one demand-constraining mitigation scenario (healthy diet), two
efficiency-enhancing mitigation scenarios (home insulation and cleaner cars), and one scenario with
both demand-constraining and efficiency-enhancing mitigation elements (active travel). Efficiencyenhancing elements include increased efficiency in household production of private transportation
(active travel and cleaner cars) and heating services (home insulation), while demand-constraining
mitigation elements include a ‘fat tax’ and a ‘road pricing tax’ to reduce household demand for meat
and dairy products (healthy diet) and private transportation (active travel).
5
The breakeven methodology required the specification of a time-indexed dynamically recursive CGE model,
with endogenous calculation of the NPV of future GDP (2011-2030). This provides an intertemporal constraint
on the model under the breakeven methodology, and allows for calculating the maximum (time-constant)
level of non-productive investment costs which can be financed without reducing NPV of future GDP.
6
For details, see Annex B.
6
Box. Policy Scenarios
Description
Healthy Diet
Reduced meat and dairy
consumption will improve
UK health + lower UK
livestock production and
GHG emissions from
ruminants.
Emission Targets The healthy diet scenario
was designed to achieve a
50% emissions reduction
target for UK agricultural
activities in 2030. The
scenario builds on
efficiency-improvements
which are in the pipeline
(not modelled).
Policy Targets
(Demandconstraining)
30% reduction in household
consumption of meat and
dairy.
Policy Targets
(Efficiencyimprovements)
Economic
Instruments
(Tax)
Economic
Instruments
(Other)
Assessment
Methodology
lllnesses/Injuries
included in
health impact
assessment
Fat Tax
Active Travel
A switch from car travel to
active travel (walking and
biking) in urban areas will
improve UK health + lower
UK fossil fuel-based
transport and associated
GHG emissions.
The active travel scenario
was designed to achieve a
38% reduction in GHG
emissions from the
transport sector (with the
cleaner cars scenario, this
was designed to achieve a
combined 60% emissions
reduction target in urban
areas in England and Wales
in 2030.)
41% reduction in urban
fossil-fuel based private
transport. Implemented as
15.6% UK-wide reduction in
private transport.
16% urban fuel-efficiency
improvement for general
(private and commercial)
traffic. Implemented as 6%
UK-wide fuel-efficiency
improvement for general
traffic.
Home Energy
Improved insulation and
ventilation of the housing
stock will improve in-door
climate and thereby UK
health + improve efficiency
of fossil-fuel based heating
and thereby lower GHG
emissions.
The home energy scenario
was designed to achieve a
50% emissions reduction
target for UK dwellings in
2030
Cleaner Cars
A switch to more a more
fuel-efficient car stock will
improve UK health
Dynamic growth path of
efficiency-gains in
household heating derived
from household energy
model
38% fuel-efficiency
improvement for private
traffic
The cleaner cars scenario
was designed to achieve an
additional 35% reduction in
GHG emissions from the
transport sector (with the
active travel scenario, this
achieves a combined 60%
emissions reduction target
in urban areas in England
and Wales in 2030).
Road Pricing Tax
Investment in household
insulation and ventilation,
measured by unit
investment costs (per unit
of efficiency gain)
Standard
Standard
Standard and Breakeven
Breakeven
Improved diets with
reduced intakes of
saturated fats and
cholesterol leads to
reduced disease burdens of
ischaemic heart disease and
stroke.
Increased physical activity
leads to reduced disease
burdens of diabetes,
Alzheimers disease,
hypertensive heart disease,
ischaemic heart disease,
cerebrovascular disease,
breast cancer, colorectoral
cancer, and depression.
Increased walking and
biking also leads to
increased traffic-related
injuries: Short- and longterm intracranial injuries,
and spinal cord injuries.
Improved home insulation
ensures reasonable in-door
temperatures and reduced
concentrations of externally
produced particulate
pollutants, leading to
reduced disease burdens of
cardiovascular disease,
depression,
cardiopulmonary disease
and lung cancers. Improved
insulation also leads to
health harms in the form of
lung cancers (due to higher
in-door radon
concentrations), asthma
(due to mould growth), and
cerebrovascular disease and
ischaemic heart disease
(due to increased in-door
concentrations of
environmental tobacco
smoke).
A new car pool with lowercarbon-emission motor
vehicles reduces local air
pollution in urban centres
and thereby lowers disease
burdens and, in some case,
premature deaths due to
trachea, bronchus and lung
cancers, lower and upper
respiratory infections,
hypertensive heart disease,
ischaemic heart disease,
cerebrovascular disease,
inflammatory heart
diseases, chronic
obstructive pulmonary
disease, asthma and other
respiratory diseases.
Note: See Annex for more details on the scenario specifications.
7
As discussed in Section 3, the four scenarios will be assessed with two assessment methodologies: (1)
a standard methodology and (2) a breakeven methodology. The ‘standard’ assessment methodology
requires well-defined economic instruments to achieve stated policy targets. Three of our four policy
scenarios are associated with well-defined economic instruments, including a fat tax (healthy diet), a
road pricing tax (active travel), and an insulation and ventilation investment scheme (home
insulation). These scenarios will therefore be assessed using the ‘standard’ methodology. The home
insulation scenario will also be assessed using the breakeven methodology, since there is some
uncertainty surrounding the scale of efficiency improvements and required investment outlays (which
are derived from the home energy model).7 The final cleaner cars scenario is not associated with a
specific policy instrument. However, a key element in this strategy is likely to be investment in new
fuel-efficient cars. The cleaner cars scenario will therefore (together with the home insulation
scenario) be evaluated using the ‘breakeven’ methodology.
There is a general tendency for tax instruments to be applied to achieve demand-reductions (fat tax
and road pricing tax) while investment instruments are used to achieve efficiency-improvements via
introduction of new technology (insulation investment and fuel-efficient car investment). It should be
noted, however, that the road pricing tax (in the active travel scenario) serves the double purpose of
reducing transport demand and reducing urban congestion – and that reduced urban congestion leads
to an efficiency-improvement of an existing technology (improved fuel-efficiency of existing car
stock). The road pricing tax is therefore a special instrument which has both demand-reducing and
efficiency-enhancing effects on GHG emissions and economic outcomes.
The temporal implementation of the four scenarios differs between (1) instantaneous implementation
and (2) gradual implementation. The home insulation and cleaner cars scenarios are implemented
gradually since efficiency-enhancing interventions require large (and time-consuming) investment
programmes. In contrast, the healthy diet and active travel scenarios are implemented instantaneously.
These scenarios are based on demand-constraining tax interventions which may be implemented
without much delay. Instantaneous implementation therefore seems like a reasonable first
approximation for these scenarios.8
The measurement of health co-benefits also differs between the four scenarios. Two approaches with
distinct health focus may be distinguished, including focus on (1) direct health benefits from reduced
local air pollution (cleaner cars), and (2) indirect health effects from e.g. improved diets (healthy diet),
increased physical activity (active travel) and better in-door climate (home insulation). A list of the
specific health effects included in the scenarios, both benefits and harms, are presented in Box 1.
7
The housing energy model (DECC 2011) provide measures of energy consumption which exceeds national
accounts numbers obtained from the Office of National Accounts (ONS). It was therefore decided to compute
a dynamic growth path of relative efficiency improvements from the housing energy model (relative reduction
in energy use consistent with an unchanged consumption of heating services) and impose it on the CGE model.
Similarly, it was decided to compute a dynamic growth path of unit investment costs (per unit of efficiency
improvement). This essentially allowed us to scale investment costs in proportion to efficiency gains. Since the
necessary investment costs required to support the derived energy efficiency gains are uncertain, it was
decided to apply both the standard methodology as well as the breakeven methodology to the home
insulation scenario.
8
Note that the active travel scenario also requires investment in infrastructure for pedestrians and cyclists (the
costs of which are assumed to be counteracted by reduced road maintenance costs), so the assumption of
instantaneous implementation is not fully valid. Similar concerns arise for the healthy diet scenario, indicating
that the latter scenarios should be viewed as stylized scenarios. In contrast, the home insulation scenario is
based on a detailed dynamic household insulation model (DECC 2011), indicating that the temporal dimension
of this scenario is more realistically described.
8
The three scenarios with a focus on indirect health effects (healthy diet, active travel, and home
insulation) are also the scenarios with well-defined economic instruments. The standard assessments
of these scenarios are therefore comparable except for one distinction: The home insulation scenario
is implemented gradually over the 20 year period, while the healthy diet and active travel scenarios
are implemented instantaneously. As for the breakeven assessment of the home insulation and cleaner
cars scenarios, they are both implemented gradually but differ in their focus on indirect health effects
of improved insulation and ventilation and direct health effects of reduced local air pollution. Neither
the standard nor the breakeven assessments are therefore fully comparable across scenarios.
5 Results
Two sets of simulation analyses are presented: The standard simulations in section 5.1 analyses the
three scenarios with a focus on indirect health effects (healthy diet, active travel, and home
insulation), while the breakeven simulations in section 5.2 analyses the two investment-based
efficiency-enhancing mitigation scenarios (cleaner cars and home insulation).9 Health-related shock
values for each of the four policy scenarios are given in Table 1. The health shocks are imposed on
the CGE model, and the discussion of results, below, therefore refers to the UK-wide economic
impacts of these health co-benefits. Three types of health effects are analysed including (1) UK
healthcare savings, (2) UK social security transfers, and (3) health effects on the UK labour force.
Table 1. Health-related Shocks (mn £; NPV value in 2010 prices)
Individual
Scenarios
Combined
Scenario
III.
Home
Insulation
I.
Healthy Diet
2,533
II.
Active Travel
13,526
IIA.
Cleaner Cars
51
15
16,073
-618.7
10.2
628.8
-789.9
101.2
891.1
-27.8
1.7
29.5
-71.5
17.5
89.0
-1,480.0
128.9
1,608.9
3,151.9
42,203
159,121
14,315.6
78,738
217,662
78.7
2,383
7,630
86.0
9,845
21,979
17,553.5
130,787
398,762
YLD (accumulated years)2
- Working age change
- Labour force change
- Dependents change
10,346
3,924
2,862
6,422
94,098
40,171
28,793
53,926
1,790.6
660.0
478.3
1,130.6
8,725
6,887
4,909
1,839
113,169
50,982
36,564
62,187
YLL (accumulated years)2
- Working age change
- Labour force change
- Dependents change
159,121
54,006
39,341
105,115
217,662
69,294
49,946
148,368
7,629.8
2,621.5
1,904.8
5,008.3
21,979
6,846
4,936
15,133
398,762
130,146
94,223
268,616
Total Public Budget Net Savings
Social Security Net Savings1
- Social Security Savings (labour force)
- Social Security Costs (dependents)
Healthcare Savings1
Total Labour Force Change
Total Population Change
(I + II + III)
NB: 1 Net Present Value over 2011-2030 (million £ in 2010 prices); 2 Accumulated years over 2011-2030 without discounting
5.1 Standard Simulations
Aggregate health co-benefits and macroeconomic effects are presented in Table 2, price and tax
changes are presented in Table 3, and sector impacts on domestic production are presented in figure 1.
9
The home energy scenario is analysed using both methodologies.
9
Table 2. Macroeconomic Effects and Health Co-benefits (NPV in 2010 prices)
Individual
Scenarios
I.
Healthy Diet
Macro
effects
ΔGDP (2011-2030)1
ΔGDP decomposition - marginal effects
- Demand-constrained mitigation
II.
Active Travel
-96,085
-10,007
-100,437
-49,044
- Efficiency-enhancing mitigation
Combined
Scenario
III.
Home
Insulation
-24,580
- Investment costs
24,408
63,529
-49,431
-49,431
4,429
15,902
469
20,800
-96,008
5,875
-24,554
-115,609
- ΔGDP per capita (2015)2
-77.1
-19.0
2.0
-95.9
- ΔGDP per capita (2020)2
-78.4
-14.8
-20.3
-114.4
- ΔGDP per capita (2030)2
-68.3
4.9
-46.4
-109.9
ΔGDP Total (marginal effects)
Per Capita GDP
Health
Co-benefits
-131,990
-150,507
39,016
- Health co-benefits
(I + II + III)
ΔGDP (2011-2030)1
4,429
15,902
469
20,800
(2015)2
-1.64
0.32
0.07
-1.25
- ΔGDP per capita (2020)2
-0.28
5.78
0.00
5.50
- ΔGDP per capita (2030)2
2.60
21.45
-0.43
23.62
- ΔGDP per capita
NB: 1 Net Present Value over 2011-2030 (mio. £ in 2010 prices); 2 Net Present Value of value in 2015, 2020, and 2030 (£ per capita in 2010 prices)
Table 3. Prices and Tax Rates
Individual
Scenarios
I.
Healthy Diet
II.
Active Travel
Combined
Scenario
III.
Home
Insulation
(I + II + III)
Price indices (2030)1
- Real Exchange Rate
-0.55%
0.22%
0.22%
-0.12%
- Consumer Price Index
- Investment Price Index
0.58%
0.00%
0.31%
0.00%
-0.04%
0.00%
0.85%
0.00%
Agricultural Terms-of-Trade (2030)1
- Market Prices
- Producer Prices
- Value Added Prices
-0.28%
0.39%
-0.53%
-0.15%
0.03%
-0.04%
0.14%
0.02%
-0.06%
-0.30%
0.44%
-0.64%
Factor Returns (2030)1
- Land
- Unskilled wages
- Skilled wages
- Capital Return
-4.55%
-1.49%
-1.04%
-1.28%
-0.32%
-1.05%
-0.71%
-0.58%
-0.25%
-0.15%
-0.20%
0.41%
-5.16%
-2.69%
-1.95%
-1.47%
0.00%
0.01%
0.01%
0.33%
0.00%
0.02%
0.02%
0.31%
0.00%
0.00%
0.00%
-0.70%
0.00%
0.03%
0.03%
-0.05%
0.04%
26.1%
28.9%
-1.19%
Factor Stocks (2030)1
- Land
- Unskilled labour
- Skilled labour
- Capital
Tax Rates (2030)2
- Fat Tax (%-point change)
- Road Tax (%-point change)
- Household Tax (%-point change)
25.9%
-0.64%
NB: 1 Percentage changes in 2030; 2 Percentage point changes in 2030.
10
29.1%
-0.58%
Domestic Production
(Percent change)
5.0%
0.0%
0.0%
0.0%
-5.0%
-10.0%
-15.0%
2020
2030
-15.0%
2011
2020
2030
Domestic Production
(Percent change)
-20.0%
5.0%
-20.0%
11
-5.0%
-10.0%
Home Energy (Percent)
0.0%
-5.0%
-10.0%
-15.0%
-20.0%
Crops
Livestock
Forestry and…
Fossil Extraction
Oth Extraction
Meat and Dairy
Oth Processed…
Fossil Fuel
Transport…
Oth…
Energy
Construction
Trade
Land Transport
Non-land…
Government…
Other Services
Healthy Diet Scenario (Percent)
Crops
Livestock
Forestry and Fishery
Fossil Extraction
Oth Extraction
Meat and Dairy
Oth Processed Food
Fossil Fuel
Transport Equipmnt
Oth Manufacturing
Energy
Construction
Trade
Land Transport
Non-land Transport
Government Service
Other Services
-10.0%
2011
Domestic Production
(Percent change)
5.0%
Crops
Livestock
Forestry and…
Fossil Extraction
Oth Extraction
Meat and Dairy
Oth Processed…
Fossil Fuel
Transport…
Oth…
Energy
Construction
Trade
Land Transport
Non-land…
Government…
Other Services
-5.0%
Crops
Livestock
Forestry and…
Fossil Extraction
Oth Extraction
Meat and Dairy
Oth Processed…
Fossil Fuel
Transport…
Oth…
Energy
Construction
Trade
Land Transport
Non-land…
Government…
Other Services
Domestic Production
(Percent change)
Figure 1. Domestic Production
Active Travel (Percent)
2011
2020
2030
-15.0%
-20.0%
Combined Scenario (Percent)
5.0%
2011
2020
2030
Health effects
The health shocks in Table 1 indicate that the three GHG scenarios, combined, may reduce healthcare
costs by as much as £17.6bn over the 20 year period (2011-2030). At the same time, social security
costs increases by £1.5bn, leaving a net public sector gain of £16.1bn. The positive health effects also
increase the labour force by 130,000 person-years or 6,500 workers per year. Table 2 shows that these
health shocks raise overall GDP by £20.8bn. In comparison, the overall macroeconomic cost of
implementing the three scenarios is estimated at £132.0bn (Table 2). Hence, health co-benefits, alone,
may lower the macroeconomic net costs of implementation by around 14%. This demonstrates the
importance of accounting for health-related externalities, when assessing the cost-effectiveness of
GHG interventions.
Looking at the individual scenarios, health effects are particularly important for the active travel
scenario. Increased physical activity associated with increased walking and cycling, leads to
significant reductions in disease burdens for diabetes, Alzheimer’s disease and ischaemic heart
disease with other notable contributions from cerebrovascular disease, breast cancer and depression.
The potential healthcare savings amounts to an appreciable £14.3bn. Since the £0.8bn net increase in
social security transfers is relatively small (increased pensions slightly outweighs reduced benefit
payments to working age people), the scenario reduces the overall public deficit by a total of £13.5bn
over 2011-30 (Table 1). The increased physical activity also raises the effective labour force by
almost 80,000 person-years or nearly 4,000 workers per year, and, in combination with the £14.3bn
deficit reduction, leads to a £15.9bn increase in GDP over 2011-30. This macroeconomic health cobenefit is big enough to cover more than 60% of the net macroeconomic cost of the active travel
scenario (net cost= efficiency loss from increased road pricing tax (29.1%) ÷ efficiency gains from
reduced urban congestion/improved fuel efficiency of existing car stock (6%)). This demonstrates that
health externalities may, in some cases, be large enough to cover the entire macroeconomic net cost of
implementing specific GHG interventions.
Health effects are less important for the two remaining healthy diet and home insulation scenarios.
The most significant health effect is associated with the introduction of healthy diets. Reduced
saturated fat intake may significantly lower the disease burden of ischaemic heart disease. This should
lower healthcare costs by around £3.2bn and reduce the public deficit by £2.5bn over the 20 year
period (Table 1). The reduced disease burden also raises the labour force by 42,000 person-years or
2,100 workers per year. These health-system shocks amount to respectively 10% (public deficit
reduction) and 50% (labour force increase) of health benefits in the active travel scenario. This shows
that individual GHG scenarios may have widely different impacts on individual types of health
effects. The relatively large labour force shock means that health effects lead to a macroeconomic
£4.4bn increase in GDP for the healthy diet scenario.
The home insulation scenario has relatively small overall health effects and this leads to a £0.5bn
GDP gain. Nevertheless, it should be noted that the current estimates of health co-benefits were based
on conservative estimates. This applies in particular to common mental disorder (depression)
attributable to alleviation of winter indoor cold, which was assumed to apply for only the first season
following the introduction of home insulation interventions. Furthermore, the gradual roll-out of the
insulation and ventilation programme over 2011-2030 means that the maximum health co-benefits
will not be achieved until 2030 and beyond.
Apart from the economic impact of health effects, it may also be observed that there are wide
differences in the relative contributions of morbidity (YLDs) and mortality (YLLs) effects across
12
scenarios. These alternative welfare indicators show that morbidity-effects are particularly important
for the active travel scenario (>40% of total DALYs = YLDs + YLLs), while mortality-effects are
particularly important for the healthy diet scenario (>90% of total DALYs). These differences are due
to differences in targeted diseases among the GHG scenarios. Hence, the active travel scenario (with a
focus on increased physical activity) affects chronic diseases such as diabetes, Alzheimer’s disease,
and depression, while the healthy diet scenario (with a focus on reduced intakes of saturated fat and
cholesterol) mainly affects diseases for which periods of disability may be relatively short lived (e.g. a
myocardial infarction in the case of ischaemic heart disease). In general, the relatively large number
of disability-adjusted life years (DALYs) saved in the healthy diet (and home insulation) scenarios
shows, that macroeconomic indicators such as GDP cannot stand alone when evaluating the welfare
consequences of health externalities and the cost-effectiveness of GHG interventions with important
health effects. A more general holistic evaluation approach is needed in this case.
The need for a more holistic approach is further underlined by the impact of health effects on on GDP
per capita (Table 2) which is (1) negative in the short and medium term for the healthy diet scenario,
(2) negative in the long term for the home insulation scenario, and (3) positive for the active travel
scenario. These results are not surprising since they reflect the substantial increase in survival which
is projected to occur in the scenarios. Hence, the highly welfare improving survival of large groups of
old-age people turns into a welfare reduction measured by GDP per capita (since it increases the
denominator in GDP per capita calculation).
Macroeconomic Effects
Having detailed the positive economic effects in isolation, we consider the combined health and
wider-macroeconomic effects of our three scenarios. Table 2 shows that the healthy diet scenario will
be the most costly to implement (in the absence of substitution effects whereby reductions in animal
products may be counterbalanced to some degree by increased consumption of fruit and vegetables).
The scenario uses demand-constrained mitigation without any efficiency-enhancing elements, and the
high cost was therefore to be expected. A 25.9% fat tax is required to achieve the 30% reduction in
consumption of meat and dairy products (Table 3). The net cost of the healthy diet scenario is £96.1bn
over the 20 year period, while the economic cost of the demand-constrained mitigation alone exceeds
£100bn. In comparison, the home insulation scenario (with efficiency-enhancing elements) will cost
the UK economy £24.6bn in welfare losses while the active travel scenario (with both demandconstrained and efficiency-enhancing mitigation elements), surprisingly, is the least costly GHG
scenario with an aggregate welfare loss of £10.0bn.
The results exemplify that demand-constrained mitigation may be very costly to implement, while
mitigation scenarios with efficiency-enhancing elements are less costly and may even prove beneficial
to the economy over the very long term (beyond our time horizon). In this context, it should, however,
be noted that health co-benefits are more closely associated with demand-constraining interventions.
Accounting for these (and other) types of co-benefits may therefore disproportionately reduce the cost
of demand-constraining interventions (as well as providing significant welfare improvements through
saved DALYs). Nevertheless, the results do suggest that (required) demand-constraining scenarios are
likely to be relatively costly compared to scenarios with efficiency-enhancing elements.
In view of the substantial tax distortions and welfare improving increasing survival of the population,
it is not surprising that the healthy diet scenario leads to substantial GDP per capita losses. Our model
predicts that losses amount to: £77.1, £78.4 and £68.3 in the short, medium and long terms (Table 2).
The implementation of a 25.9% fat tax under the assumption of a cost-neutral government budget
13
closure yields a 0.64% decline in household tax (Table 3). This partly compensates households for
increasing food costs. Nevertheless, real household incomes are significantly reduced, since the fat tax
distortions reduce factor returns across the board. In particular, factor returns to land decrease by
4.6% over the 20 year period reflecting income loses due to ineffective reallocation of land towards
other productive uses. Domestic production in processed meat and dairy industries are reduced by
>17% and lay-offs spills over into livestock and other processed food sectors, manufacturing and
trade as shown in Figure 1. At the same time, less closely related sectors such as extraction industries,
increase production. This ‘leakage’ of carbon emissions emphasizes the need for economy-wide
strategies to reduce GHG emissions.
The large fat tax creates distortions without introducing any efficiency improvements in the economy.
Health co-benefits provide a positive economic contribution of £4.4bn, but this is not sufficient to
significantly dampen the economic losses of this demand-constrained mitigation intervention.
Nevertheless, changing the speed of introduction and taking into account possible substitution effects
(whereby an increase in fruit and vegetable consumption could occur as animal product consumption
declines) could substantially offset the potential adverse effects on the economy. Another strategy to
increase the income of the agricultural sector is through production of lignocellulosic biofuels which
have the advantage of not competing with land for food production unlike some other biofuels.
The active travel scenario requires a road pricing tax which raises private transport costs by 29.1%
(Table 3). This demand-constrained mitigation creates inefficiencies and distortions which are similar
to the healthy diet scenario. The associated welfare loss amounts to £49bn (Table 2). However, the
efficiency-enhancing element of this scenario, i.e. improved fuel efficiency from reduced congestion
and idling, also brings a £39bn gain. This suggests that the non-health aspects of this scenario
(assuming cost-neutral investment in walking and biking infrastructure) yield an approximate loss of
£10bn. However, the interaction of reduced traffic volumes and improved fuel efficiency introduces a
non-linearity, suggesting that non-health welfare losses are around £26bn. The £16bn health cobenefits are therefore ‘only’ able to finance around 60% of the net (non-health) welfare losses. (The
importance of health co-benefits is illustrated in Figure 2.) Furthermore, the results show that health
co-benefits and efficiency-improvements together cover around 80% of gross welfare losses. (The
contribution of efficiency-improvements and health co-benefits is illustrated in Figure 3.) These
results illustrate that efficiency-improvements (for existing technologies) and health co-benefits can
significantly reduce costs associated with demand-reducing mitigation interventions.
Due to the revenue-neutral budget closure, the road pricing tax reduces household tax rates by 0.58%.
This partly compensates households for increasing transport costs. Nevertheless, tax distortions
reduce factor returns and lowers household income levels over the long term. The negative factor
returns, are reflected in declining GDP per capita over the short and medium terms (-£19.0 and -£14.8
respectively). However, GDP per capita becomes positive in the long term (£4.9) due to rising and
accelerating health benefits (from reduced disease burdens of several chronic diseases). The
accumulation of healthcare savings in terms of both new and recurrent cases averted grows over time,
and this leads to increased capital accumulation and increased household income levels in the long
term.
14
Figure 2. Health benefits and net (non-health) welfare costs
(billion £)
120,000
100,000
80,000
Health benefits
60,000
Net scenario costs
40,000
20,000
0
Healthy Diet Active Travel
Home
Energy
Figure 3. Health and Efficiency benefits and gross welfare costs
(billion £)
120,000
100,000
80,000
Health benefits
60,000
Efficiency benefits
40,000
Net scenario costs
20,000
0
Healthy Diet Active Travel
Home
Energy
The active travel intervention naturally reduces domestic production of transport equipment and fossil
fuels (Figure 1). As a result, there is a knock-on effect causing a decline in the fossil fuel extraction
sector. Re-allocation of consumer demand away from private transportation means that private
consumers increase spending elsewhere. This leads to increased production and leakage of GHG
emissions to those other sectors. It should also be highlighted that this intervention would be likely to
yield an increase for the cycle industry (a transmission mechanism which has not been explicitly
included in the model).
The home insulation scenario requires significant reallocation of investment to the construction sector.
This introduces distortions in the economy and crowds out investment which could be used
productively in other sectors. By itself, crowding-out of productive investment leads to a £49bn GDP
loss over 20 years (Table 2). However, home insulation efficiency gains (£24.4bn) and health benefits
(£500mn) contribute positively, and thereby allows for around 50% self-financing of the 2011-30
15
programme (Figure 3). The self-financing rate is expected to be even higher, if account is taken of
health effects and efficiency gains beyond 2030 after the programme of investment has ceased. This
again demonstrates how efficiency-enhancing mitigation elements (through introduction of new
technologies) are crucial for GHG interventions to be cost-effective.
The GDP per capita effects of the home insulation scenario are initially positive (£2.0) as relatively
cheap investment in the initial phases yields proportionally high gains in efficiency. In addition the
mental health impacts of this scenario brings immediate gains to those affected, reducing healthcare
savings and increasing productive labour supply (but by relatively small amounts). In the medium and
long terms, GDP per capita effects, however, become negative (-£20.3 and -£46.4 respectively). The
positive short term effects of a policy to, initially, reap low-hanging fruits therefore raises the question
of what level of investment should be considered optimum.10
The combined GHG scenario amalgamates the economic effects to produce an aggregate UK
economy-wide cost of £132bn. Dominating this income loss are the inefficiencies and distortion
effects of the demand-constraining mitigation interventions and investment costs, which together
constitute a £200bn cost to society (Table 1). Clearly, the £100bn GDP loss from demand-constrained
mitigation in the healthy diet scenario plays a significant part (but, again, this welfare loss could
possibly be reduced through e.g. changes in consumers’ attitudes towards fruit and vegetables). The
£63bn efficiency-enhancement effects, to some extent, counter these negative impacts. Similarly, the
health co-benefits contribute welfare gains of £20.8bn and so play an important part in further
lowering the macroeconomic cost of implementation of these scenarios. Overall the GDP per capita
effects are negative and fairly consistent over time (-£96, -£114 and -£110 in the short, medium and
long terms), which is not surprising since GHG interventions are expected to be costly and since the
health-related (and welfare-enhancing) population expansion necessarily lowers the denominator of
GDP per capita. Again, it should be highlighted that proper evaluation of GHG policies with
significant health effects requires a holistic evaluation approach.
Table 4. Breakeven Calculations (million £; NPV in 2010 prices)
Individual Scenarios
III. Housing
IIA. Cleaner Cars Insulation
Potential Investment Costs1
ΔPotential Investment decomposition - marginal effects
Efficiency-enhancing mitigation (productivity gain)
Health co-benefits
Combined Scenario
(IIA + III)
142,155
26,143
168,453
141,999
25,651
167,810
158
493
650
NB: 1 Net Present Value over 2011-2030 (million £ in 2010 prices)
5.2 Breakeven Simulations
The breakeven simulations of the cleaner cars and home insulation scenarios indicates that health cobenefits and, especially, productivity gains allows for substantial self-financing for these efficiencyenhancing mitigation initiatives. Table 4 shows that the home insulation scenario remains costeffective as long as investment costs are kept below £26bn, while the similar figure for the cleaner
10
Please note that the issue of choosing the optimal level of insulation and ventilation investment is separate
from the issue discussed above (and the motivation for the breakeven methodology) about uncertainty
surrounding insulation and ventilation investment costs of achieving a given energy efficiency improvement.
16
cars scenario is £142bn. The results also indicate that health co-benefits accounts for £150-£500
million or less than one per cent of gross benefits, indicating that these scenarios mainly provides
economic gains from efficiency improvements.
Home insulation and ventilation investment costs will, as demonstrated in the previous section, most
likely exceed benefits and thereby be cost-ineffective. However, since all investment costs are
incurred during the programme period 2011-2030, while health and (energy) efficiency gains will
persist for the lifetime of the housing improvements, longer term gains are likely to be greater. This is
all the more so since the adoption of conservative health estimates for the programme period means
that longer term health co-benefits are likely to be significantly greater. Hence, with possible
breakeven costs of £26bn alone over the 20 year programme period, the UK home insulation and
ventilation programme may well be cost-effective over the very long term.
The cleaner cars scenario is even more likely to be cost-effective. A UK network for electric cars is
yet to be developed and hybrid cars remain comparatively costly. Furthermore, while relatively small
and efficient fossil fuel-based vehicles are currently less costly to acquire and maintain for the average
car buyer, traffic jumps may be seen in connection with adoption of efficient transportation modes.
Nevertheless, the implementation of the cleaner cars scenario may well be attained through a general
change in attitudes towards hybrid and smaller fossil fuel-based vehicles at little additional or possibly
even at lower (investment and maintenance) costs to car owners. This is all the more likely as the
hybrid car technology is likely to become cheaper and more accessible for the average car buyer over
time. With an overall (additional) breakeven investment cost estimated at £142bn over the initial 20
year period, the UK cleaner cars scenario is therefore very likely to be cost-effective.
6 Conclusion
The UK has committed itself through the adoption of the 2008 Climate Change Act, to reduce GHG
emissions by 80% in 2050 from a 1990 baseline. Preliminary estimates suggest that UK emissions
have been reduced by around 25% in 2010. Nevertheless, a number of new mitigation initiatives are
needed in order to achieve the intermediate 50% reduction target in 2030 and the final 80% reduction
target in 2050. This study constructed a single-country Computable General Equilibrium (CGE)
model to assess UK GHG initiatives, which can help to achieve the 50% reduction target in 2030.
Focus is on initiatives with important health benefits.
We analysed three scenarios (healthy diet, active travel, and home insulation) with a standard
methodology for impact assessment based on an extended methodology for measuring health effects,
and found that health benefits significantly contributes to lowering society’s costs of implementation.
Net macroeconomic costs were reduced by 14% for three scenarios combined. Furthermore, health
co-benefits covered 60% of net society costs for the active travel scenario. This shows that health
externalities may, in some instances, be sufficiently important to decide whether specific GHG
scenarios are cost-effective or not.
We showed that demand-constraining mitigation interventions may be very costly to implement,
while mitigation scenarios with efficiency-enhancing elements are less costly and may even prove
beneficial to the economy over the very long term (beyond our time horizon). The high cost of
demand-constraining interventions was exemplified by the healthy diet scenario (with a focus on
economic instruments: fat tax). However, we noted that induced changes in consumer preferences
17
may significantly lower society costs of implementation. We also noted that health co-benefits and
efficiency gains for existing technologies are relatively closely associated with demand-constraining
interventions, and that accounting for these benefits may significantly reduce the cost of demandconstraining interventions. The active travel scenario provides an example, where high efficiency
gains and health co-benefits lowers the gross cost of demand-constraining transport interventions
(with a focus on economic instruments: road tax) by 80%.
While demand-constraining interventions, based on economic tax-instruments, may be accompanied
by significant efficiency gains and health co-benefits, the results also show that cost-effectiveness
typically requires efficiency-improvements based on the introduction of new technologies. This was
evident from the home insulation scenario where energy efficiency gains from improved insulation
and ventilation lowered gross society costs by 50%. Moreover, the cleaner cars scenario (assessed by
the breakeven methodology) indicated that efficiency-improvements from a switch to a smaller and
more fuel-efficient car stock would carry a significant breakeven investment cost of >£140bn during
2011-2030.
Overall, we find that efficiency-enhancing elements (based on new technologies) are likely to be
crucial for the cost-effectiveness of GHG interventions. Nevertheless, efficiency-enhancing elements
(based on existing technologies) and health co-benefits has the potential to significantly lower the
costs of demand-constraining GHG interventions. Furthermore, demand-constraining interventions
may, in some cases, be associated with strongly welfare increasing improvements in health outcomes
(longevity and life quality) – welfare improvements which tend to have a negative economic impact
through increased dependency ratios. A more holistic and all-inclusive approach to impact assessment
(accounting for health co-benefits and going beyond economic outcomes) may therefore make
demand-constraining interventions, if not cost-effective, relatively attractive
It should also be noted that we find evidence of significant health co-benefits, in spite of our relatively
conservative assumptions of our approach. First, we only account for health effects during our 20 year
time horizon (2011-2030). However, health co-benefits may continue to increase beyond the 20 year
time horizon due to long lag periods between the implementation of the policy and the health effects
such as Alzheimers disease and cancer. Underestimation of health effects is likely to be especially
pronounced in the home insulation scenario, where realistic phasing-in of the investment programme
occurs over a 20 year period. Health effects associated with interventions during the final years of the
programme therefore contribute little (or nothing) towards the health co-benefits. We may also have
underestimated some of the individual health co-benefits. For example, we conservatively assumed
that depression was only reduced for one year by improved home insulation and warmer homes.
Overall, it may be concluded that the political feasibility of specific GHG initiatives is likely to rest
critically on whether they include efficiency-enhancing mitigation elements (of new and/or existing
technologies) and important health co-benefits.
18
Annex A: SAM/CGE methodology and health effects
A.1 Macroeconomic CGE model
The economy-wide dynamically-recursive Computable General Equilibrium (CGE) model, used in
this study, was based on the ‘IFPRI standard model’ (Löfgren, Lee Harris and Robinson 2002). This is
a well-known and widely applied comparative static, single country, open economy, multi-sector CGE
model, which has recently been used in health and trade-related applications by some of the authors
(Smith, Keogh-Brown et al. 2009; Lock, Smith et al. 2010, Jensen, Robinson and Tarp 2010). The
model accounts for different types of agents including producers/enterprises, private households, the
government sector and the foreign sector.
The model is a neo-classical model based on the fundamental principles of profit-maximization
among producers and utility maximization among households. Production is specified as a Constant
Elasticity of Substitution (CES) function of aggregate intermediate input demand (individual
commodity input demands are determined by a Leontief specification) and aggregate factor input
demand (individual factor input demands are determined by a CES specification). Trade between
domestic and foreign agents is specified as a function of relative prices (determined by the real
exchange rate), based on an Armington CES specification on the import side and a Constant Elasticity
of Transformation (CET) specification on the export side. The standard model specification was,
furthermore, expanded to account for household production of transport services and heating services.
Household production was in each case determined by a Leontief specification.11,12 Based on this setup, the fuel efficiency (cleaner cars/active travel) and heating efficiency (home energy) improvements
were modelled as changes to the Leontief input parameters for respectively fossil fuel and private
energy input use.
A standard neo-classical model closure is used in all simulations, implying that flexible prices are
clearing all goods and factor markets and that a flexible real exchange rate is clearing the current
account of the balance of payments. In addition, the counterfactual projections are based on a
balanced macro closure (fixed government demand-to-absorption ratio) which ensures a (relatively)
unchanged composition of absorption (private and government consumption vs. investment) over the
projection period. Furthermore, all simulations are based on a revenue-neutral government budget
closure (endogenous household tax rate) which ensures that changes in individual government
revenue components (e.g. due to the introduction of a fat tax or road pricing scheme) will not affect
the relative size of the government sector in the economy.
A.2 Macroeconomic data base and CGE model calibration
The CGE model for the UK economy was calibrated on the basis of a 2004 social accounting matrix
(SAM) dataset taken from the GTAP database v7 (Narayanan and Walmsley 2008). The basic dataset
11
Since production of private transportation and heating services does not constitute a standard industrial
production sector, it was necessary to specify separate household production sectors for each of these private
services. A Leontief production function was chosen based on the assumption of proportional input use.
Furthermore, profit-maximization was invoked based on the standard separability assumption for household
production and consumption decisions, and a standard equilibrium condition was implemented as part of the
general equilibrium framework.
12
A more sophisticated specification of household production of transport services have previously been
applied within a CGE model, to study how taxation of work journeys (akin to our road pricing scheme) may
affect labour supply decisions (Berg 2007). This type of specification was outside the scope the current paper.
19
was aggregated to 17 production activities and 17 retail commodities covering both agricultural,
industry and service sectors (including health). A further five retail commodities were created
specifically to allow for analysing abatement technologies in household production of heating services
and transport services. These five commodities included two heating-related commodities (“heating
services” and “private energy” inputs), and three transport-related commodities (“private transport
services” as well as “private fuel” and “other private transport” inputs). Value breakdowns were based
on the UK Office for National Statistics Family Spending Survey 2004-5.
A.3 Assessment methodology
Two types of assessment methodologies are applied to evaluate the cost-effectiveness of policy
scenarios: (1) a standard methodology, and (2) a breakeven methodology. The standard methodology
is based on standard factor accumulation and standard calculation of macroeconomic aggregates such
as GDP. This methodology will be used to assess the three main scenarios (I), (II), and (III). In
contrast, the breakeven methodology calculates the maximum non-productive investment costs, which
are consistent with an unchanged NPV value of GDP over the 20 year simulation horizon (20112030). The methodology is targeted at policy scenarios with an investment element (where actual
investment costs are eliminated, and potential investment financing is calculated). The breakeven
methodology is therefore only applied to assess the cleaner cars (IIa) and home energy (III) scenarios.
The breakeven methodology is especially useful for our purposes, since it allows us to highlight the
beneficial effects of efficiency-enhancing mitigation elements and health externalities. An
understanding of the accumulation of factor stocks is central to understanding the economic impact of
GHG emission reduction strategies. GHG strategies have direct consequences for annual spending on
investment and capital accumulation. E.g. efficiency-enhancing abatement technologies may increase
productivity and thereby raise value creation and investment, while non-productive investment in
housing may lead to crowding-out and lower investment.
Reduced capital accumulation leads, ceteris paribus, to reduced future value creation and welfare.
This mechanism has been used by many economists to argue that GHG emission reduction strategies
may entail a trade-off between GHG emission reductions and (future) welfare gains. This argument
does not, however, take account of (1) the possibility of employing efficiency-enhancing abatement
technologies (which may reduce GHG emissions at no cost or even increase productivity and welfare)
and (2) the possibility that beneficial (health) externalities may reduce the economic costs of policy
implementation.
A.4 Health effects
For each disease, detailed age- and gender-specific calculations of disease burdens, including Years of
healthy Life lost due to Disability (YLD) and Years of Life Lost (YLL) were used to calculate implied
changes to UK healthcare costs, UK labour supplies, and UK social security transfers. Gender and
age-specific health effects were determined by the WHO comparative risk assessment approach
(Woodcock et al. 2009; Friel et al. 2009; Wilkinson et al. 2009), and distributed over the 20 year
horizon (Smith et al. 2012). The resulting dynamic patterns of health effects, including YLDs and
YLLs, were used to derive (1) changes in the effective labour force (based on reduced YLD and YLL
for the working age population corrected for gender-specific labour market participation rates), and
(2) changes in social security transfers including reduced labour market benefits (based on reduced
YLD for the working age population) and increased pension payments (based on reduced YLL for the
old-age population). Furthermore, changes in healthcare costs were measured on the basis of
20
disease/injury incidence numbers. Details of the methodology for calculating these healthcare costs
are provided in Jarrett et al. (2012).13,14
For each illness (with the exception of road traffic injuries) a disease-specific sigmoid curve was used
to determine the lag time between the implementation of an intervention and the health benefits (or
harms). In the cleaner cars and home energy scenarios, interventions occur gradually over a 20 year
period. For these scenarios, the time-lagged health effects and healthcare savings were further
staggered to account for the gradual implementation of the interventions. Health harms from increased
road traffic injuries (attributable to the increased number of pedestrians/cyclists under the intervention
scenarios) were assumed to occur linearly.
13
The reduction in YLDs had not been estimated for several illnesses in the healthy diet (Friel et al 2009) and
home energy (Wilkinson et. al. 2009) scenarios. Nevertheless, it was decided to include the reduction in YLDs
for diseases for which a reduction in YLLs had been calculated. This was achieved by using ratios of YLLs to
YLDs for Europe from the WHO Global Burden of Disease.
14
Detailed healthcare savings were measured for the active travel scenario (Jarrett et al. 2012). Healthcare
savings were, subsequently, calculated for the remaining scenarios by applying the active travel healthcare
savings per patient to incidence estimates for the same common diseases.
21
Annex B: Policy Scenarios
B.1 The healthy diet scenario (Scenario I)
Greenhouse gasses are produced throughout the food-system supply chain, including agricultural
farming, food distribution, consumption, and waste disposal (Friel et al 2009). The agriculture sector
is responsible for 10-12 % of global greenhouse gas emissions (and an additional 6-17% if land use
change is included), and livestock-related activities accounts for 80% of agricultural emissions (FAO
2006). Furthermore, increasing demand for meat is expected to raise livestock production in 2030 by
85% above the level in 2000 (World Bank 2008). These numbers indicate that livestock activities are
– and will remain – a key contributor to anthropogenic GHG emissions for the foreseeable future.
The healthy diet scenario was designed to achieve the sector-specific 50% emissions reduction target
for UK agricultural activities in 2030 (Friel et al. 2009). The emissions reduction scenario was
developed as a two-pronged strategy: (1) introduction of new abatement technologies, and (2)
reduction in livestock activities. Based on estimates of technological change, already in the pipeline, it
was estimated that the 50% overall reduction target could only be achieved by an additional 30%
reduction target for livestock production, which for the purposes of illustration was assumed to result
in a commensurate reduction in consumption (Friel et al. 2009). In this paper, we focus on the health
co-benefits of reduced meat and dairy consumption. We therefore decided to target a 30% reduction
in demand (rather than output). This was achieved through the introduction of a tax instrument – a socalled ‘fat tax’ – on livestock-related meat and dairy products.15 Health co-benefits stem primarily
from improved diets with reduced intakes of saturated fats and cholesterol, which leads to reduced
disease burdens of ischaemic heart disease and stroke.16
B.2 The active travel (Scenario II) and cleaner cars (Scenario IIa) scenarios
The transport sector accounts for more than a quarter of global anthropogenic GHG emissions.
Furthermore, fossil fuels account for 95% of global transport fuel demand, and current trends suggest
that emissions from this source will increase by 80% during 2007-2030 (Ribeiro et al. 2007). Within
the transport sector, road traffic accounts for three-quarters of global emissions. Road traffic is
therefore another key contributor to anthropogenic GHG emissions, which needs to be addressed
within an overall UK GHG emission reduction strategy.
The active travel and cleaner cars scenarios were originally designed to achieve a combined 60%
emissions reduction target for the Greater London area in 2030 (Woodcock et al. 2009). By itself, the
active travel scenario was designed to achieve a 38% reduction in GHG emissions through a switch
from fossil fuel combustion vehicles to alternative active travel modes including walking and biking.
The cleaner cars scenario was, subsequently, developed to achieve an additional 35% reduction in
GHG emissions, through a switch to more fuel-efficient lower-carbon-emission vehicles, and thereby
reach a combined 60% reduction in GHG emissions. In the policy simulations below, the active travel
15
The decision to specify the policy shock as a 30% reduction in demand rather than production is due to our
focus on health effects (which are consistent with a 30% demand reduction for processed meat and dairy
products – see Friel et al. 2009). As discussed below, the 30% demand reduction is only accompanied by a 17%
reduction in the production of meat and dairy products. Hence, this scenario specification may not fully
achieve the GHG emission reduction targets which it was designed to achieve, due to trade-related ‘leakages’.
16
The healthy diet scenario focuses narrowly on measuring the economic impact of indirect health effects.
Hence, the scenario does not account for direct health effects of e.g. reduced local air pollution (which are
considered to be of minor importance).
22
and cleaner cars scenarios will be analysed separately. Furthermore, the simulations (and associated
health effects) are expanded to cover all major urban centres throughout England and Wales (active
travel) and the entire UK (cleaner cars). 17
The cleaner cars scenario is based, solely, on a (UK-wide) 38% fuel efficiency improvement. In
contrast, the active travel scenario includes both demand-constraining and efficiency-enhancing
mitigation elements: (1) a 41% reduction in urban traffic volumes, which translates into a 15.6% UKwide reduction in traffic volumes. In the policy simulations, this target reduction will be achieved
through the introduction of a tax instrument – a ‘road pricing’ tax – on private transport services; and
(2) an accompanying reduction in urban congestion, which improves fuel efficiency by 16% for urban
car journeys or 6% on a UK-wide basis.18
In the cleaner cars scenario the focus is on replacing the current car pool in urban areas with lowercarbon-emission motor vehicles. Important health effects therefore arise from reduced local air
pollution in urban centres.19 In the active travel scenario the switch to active travel modes such as
walking and biking leads to increased physical activity, and this has a number of health co-benefits
including reduced disease burdens of diabetes, Alzheimers disease, ischaemic heart disease,
cerebrovascular disease, depression, etc. However, increased walking and biking also leads to
increased numbers of traffic-related injuries which are nevertheless greatly outweighed by the health
co-benefits.
B.3 The home insulation scenario (Scenario III)
Residential and commercial buildings account for 8% of global anthropogenic GHG emissions. In
spite of limited growth in emissions, analyses indicate that buildings have the highest potential
(among the major sectors of emissions) for mitigation in 2030 (5.3-6.7 GtCO2-eq/year) (IPCC 2007).
Within the UK, dwellings account for around 30% of total UK energy consumption, while space
heating accounts for around 60% of energy consumption in UK dwellings (DTI 2008). Furthermore,
space heating is estimated to account for more than half of total CO2 emissions by UK dwellings
(DCLG 2006). Improving the heating and insulation of dwellings is therefore another important
policy to implement within an overall UK GHG emission reduction strategy.
The ‘home insulation’ scenario was designed with the aim to achieve the sector-specific 50%
emissions reduction target for dwellings in 2030 (Wilkinson et al. 2009). The scenario took as point of
departure that emissions from dwellings had already been reduced by 9% in 2010 relative to 1990
levels. The target reduction to be achieved was therefore 41% during 2010-2030. The scenario was
developed as a four-pronged strategy: (1) fabric improvements (insulation), (2) improved ventilation
control, (3) fuel switching (fossil fuel combustion to electricity), and (4) occupant behaviour (in-door
temperatures controlled at 18˚C or above). Due to uncertainty regarding fuel switching, this
17
The temporal implementation of the active travel scenario is assumed to occur instantaneously, while the
transition to a more environmentally-friendly car stock (cleaner cars) is assumed to occur gradually (efficiencygains are implemented linearly over time horizon, reaching 38% in 2030).
18
The urban congestion impact was not part of the original scenario design (Woodcock et al. 2009). The active
travel scenario (combined with the cleaner cars scenario) is therefore likely to bring GHG emission reductions
in excess of the targets which it was designed to achieve.
19
While the other scenarios (including active travel) focus narrowly on measuring the importance of indirect
health effects, the cleaner cars scenario is the only scenario where the direct health impact of reduced local air
pollution is accounted for. As discussed below, the economic impact of reduced local air pollution turns out to
be relatively limited.
23
component was not counted towards GHG emission reductions (but it was retained for the calculation
of health effects).
The policy simulations below are based on input data from an environmental home energy model
employed by the Department of Energy and Climate Change (DECC 2011). The scenario is based on
a 20 year investment programme for home insulation and ventilation, and therefore involves a
gradually increasing dynamic 2011-2030 growth path for productivity gains in household production
of heating services, supported by a dynamic sequence of unit insulation investment costs. In this way,
investment in improved insulation and ventilation is used as a policy instrument to reduce GHG
emissions and enhance the production efficiency of private heating services in UK dwellings.
Health co-benefits stem from several sources. Insulation of dwellings ensures reasonable in-door
temperatures and reduced concentrations of externally produced particulate pollutants, leading to
health benefits in the form of reduced disease burdens of cardiovascular disease and depression
(temperature) and of cardiopulmonary disease and lung cancers (PM2.5). At the same time, insulation
of dwellings also leads to health harms due to higher in-door radon concentrations (which causes lung
cancers), increased mould growth (which exacerbates asthma), and increased in-door concentrations
of environmental tobacco smoke (a risk factor for cerebrovascular disease and ischaemic heart
disease). The latter health effects can be countered by mechanical ventilation with heat recovery
(MVHH) and this was assumed to occur in the 20 % of homes that were the most tightly sealed.
24
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