The document discusses $14.6 trillion that has been spent globally on economic recovery from the COVID-19 pandemic. It notes that $11.1 trillion was spent on rescue measures, $1.9 trillion on recovery spending, and $341 billion of unclear spending. It then discusses categorizing spending policies and assessing their impacts on the environment, social outcomes, and economic activity. The document proposes modeling the potential impacts of recovery spending using data from a Global Recovery Observatory that is tracking over 5,000 spending policies across 89 countries.

1. 1
How good is green?
OECD Technical Workshop | 14th of April 2021
brian.ocallaghan@smithschool.ox.ac.uk | @brian_ocall
Incentivising green recovery and modelling
spending impacts on the environment and on
economic activity

2. $14,600,000,000,000
in 2020
Note: excludes currently unclear funds from the European Commission. Including these funds, the total approaches $17tn.
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

3. What makes up the $14.6tn?
$11.1tn
Note: all figures exclude currently unclear funds from the European Commission. Including these funds, total spending
approaches $17tn.
Rescue
spending
Recovery
spending
Unclear
spending
Total green
recovery
spending
$1.9tn
$1.6tn
$341bn
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

4. The environment
Long-term growth
Social inclusion
Economic recovery
Public health
If you are going to spend, make it green
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

5. The environment
Long-term growth
Social inclusion
Economic recovery
Public health
If you are going to spend, make it green
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall
GHGs
Biodiversity
Material use +
circular economy
Air pollution

6. What is the Observatory?
The Global Recovery Observatory
Quick description
World map
• Brings transparency to govt spending,
pressures more responsible env. action, & gives
practical policy examples from around the world
• Tracking fiscal spending in 89 countries
• >5,000 policies recorded & assessed using our
original green fiscal policy taxonomy
o 40 policy archetypes & 150 sub-archetypes (see appendix)
o Assessed for short- and long-term GHG, air pollution, natural
capital, social inequality, rural livelihoods, quality of life, and
economic impact
Indicative Observatory output
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

7. Methodology: (1) Tracking policies
Who? 50 largest countries + PAGE countries + LAC countries = 89 total
Which policies? All COVID-related fiscal spending/tax (unlike others, we record at the policy level)
What characteristics? name, description, value, date, sources
Progress to date? 5,000+ policies
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

8. Copyright
©
2019
by
Boston
Consulting
Group.
All
rights
reserved.
Temporary
liquidity
measures
D Liquidity support for not for profit organisations
A Liquidity support for subnational public entities
B Liquidity support for large businesses
C Liquidity support for start-ups and SMEs
E Temporary waiver of interest payments for
businesses
Rescue Measures (archetypes)
Temporary
life
and
livelihood
measures
F Direct provision of basic needs
G Targeted welfare cash transfers
H Job continuation support
I Temporary waiver of interest payments for
individuals
J Healthcare services support
L Income tax cuts
Temporary
tax
&
payment
relief
measures
K Emergency services (disaster management)
support
M VAT and other goods and services tax cuts
N Business tax cuts
O Business tax deferrals
Q Other tax cuts and deferrals
P Reduced prices for centrally-controlled
products and services
Incentive
measures
Investment
measures
R Targeted recovery cash transfers
S Tourism and leisure industry incentives
U Electronic appliance and efficiency incentives
T Electric vehicle incentives
V Green market creation
W Other incentive measures
Recovery Measures (archetypes)
Z Healthcare investment (non-infrastructure)
𝛽 Communications infrastructure investment
X Worker retraining and job creation
Y Education investment (non-infrastructure)
𝛼 Social and cultural investment (non-infrastructure)
𝛾 Traditional transport infrastructure investment
𝛿 Clean transport infrastructure investment
𝜂 Clean energy infrastructure investment
𝜀 Traditional energy infrastructure investment
𝜃 Local (project-based) infrastructure investment
𝜆 Buildings upgrades and energy efficiency
infrastructure investment
𝜎 Armed forces investment
𝜓 Clean research and development investment
𝜇 Natural infrastructure and green spaces investment
𝜋 Other large-scale infrastructure investments
𝜏 Disaster preparedness & capacity building investment
𝜑 General research and development investment
Methodology: (2) Categorising policies
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

9. Copyright
©
2019
by
Boston
Consulting
Group.
All
rights
reserved.
Temporary
liquidity
measures
D Liquidity support for not for profit organisations
A Liquidity support for subnational public entities
B Liquidity support for large businesses
C Liquidity support for start-ups and SMEs
E Temporary waiver of interest payments for
businesses
Rescue Measures (archetypes)
Temporary
life
and
livelihood
measures
F Direct provision of basic needs
G Targeted welfare cash transfers
H Job continuation support
I Temporary waiver of interest payments for
individuals
J Healthcare services support
L Income tax cuts
Temporary
tax
&
payment
relief
measures
K Emergency services (disaster management)
support
M VAT and other goods and services tax cuts
N Business tax cuts
O Business tax deferrals
Q Other tax cuts and deferrals
P Reduced prices for centrally-controlled
products and services
Incentive
measures
Investment
measures
R Targeted recovery cash transfers
S Tourism and leisure industry incentives
U Electronic appliance and efficiency incentives
T Electric vehicle incentives
V Green market creation
W Other incentive measures
Recovery Measures (archetypes)
Z Healthcare investment (non-infrastructure)
𝛽 Communications infrastructure investment
X Worker retraining and job creation
Y Education investment (non-infrastructure)
𝛼 Social and cultural investment (non-infrastructure)
𝛾 Traditional transport infrastructure investment
𝛿 Clean transport infrastructure investment
𝜂 Clean energy infrastructure investment
𝜀 Traditional energy infrastructure investment
𝜃 Local (project-based) infrastructure investment
𝜆 Buildings upgrades and energy efficiency
infrastructure investment
𝜎 Armed forces investment
𝜓 Clean research and development investment
𝜇 Natural infrastructure and green spaces investment
𝜋 Other large-scale infrastructure investments
𝜏 Disaster preparedness & capacity building investment
𝜑 General research and development investment
Methodology: (2) Categorising policies
𝜂1
New or refurbished renewable
energy generation facilities
𝜂2
New or refurbished nuclear
energy generation facilities
𝜂3
New biofuel and other
renewable fuel infrastructure
𝜂4
Upgraded (or new) transmission
infrastructure
𝜂5
Upgraded (or new) distribution
infrastructure including smart
grids
𝜂6 Hydrogen infrastructure
𝜂7
Battery and storage
infrastructure
𝜂8
Carbon capture and
storage/utilisation
𝜂9
Other initiatives to clean
existing dirty energy assets
Clean energy: sub-archetypes
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

10. Copyright
©
2019
by
Boston
Consulting
Group.
All
rights
reserved.
Methodology: (3) Assessing impact
We assess all 150 sub-archetypes for impact on 9 dimensions based on literature, lead
economist surveys, and an ongoing peer review.
environmental impact
• greenhouse gas emissions
• Short term (i.e., construction)
• Long term (i.e., operation)
• air pollution
• natural capital
social impact
• wealth inequality
• quality of life
• rural livelihood
economic impact
• economic multiplier
• speed of policy
implementation
We use a 5-point Likert scale for GHGs and a 3-point scale for all other impacts.
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall
All scoring in our
100-pg peer-
reviewed
methodology
document

11. Green recovery
spending
(% of total recovery
spending)
Recovery spending
(%GDP, logarithmic scale)
Low green
spending
=
missed
opportunities
>
Note for figure: Many countries are clustered at 0% green recovery spending, from left to right on the fig: South Africa, Thailand, Malaysia, Egypt,
Saudi Arabia, Argentina, Portugal, Nigeria, Peru, Iraq, Mexico, Mexico, Argentina, the Netherlands, and the Philippines. Countries with less than
0.1% recovery spending as %GDP do not feature.
brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall

12. 226 dirty policies recorded to date
Country Policy Reference
(sub-archetype)
Policy Name Total Value, USD
(billions)
Argentina B3 Road companies compensation funding 0.01
Australia 𝜀3 Gas-fired recovery 0.04
Bahamas B5 Support for key SOEs 0.05
Canada 𝜀3 Oil and gas tax relief 0.06
China 𝜀3 Pinliang coal mine investment 0.48
Mexico P2 Oil price control 3.22
India 𝜀3 Rebates on coal extraction ?
Indonesia B3 Jet fuel discounts for airports 0.02
Nicaragua 𝜀1 Legislative approval of Natural Gas power-plant ?
Norway 𝛾2 Additional allocation for maintenance + renewal of transport infra 0.11
Norway O1 Fuel industry liquidity support 0.07
Pakistan 𝜀4 Reduction in price of vehicle fuels 0.46
Poland 𝜀3 Establishment of a strategic hard coal reserve 0.03
Russia B3 Support to car-makers 0.32
South Africa O1 Deferred carbon tax 0.14
South Africa B5 Bailout of coal-fired power utility provider 1.78
South Korea B3 Auto-industry financial support 1.80
Turkey P2 Postponement of electricity + natural gas consumption fees ?

13. brian.ocallaghan@smithschool.ox.ac.uk
https://twitter.com/Brian_OCall
Opportunities for modelling potential impact
given limited policy details & broad uncertainty
Input
5,000 policy items (40,000 input data points) across 89 countries, timeseries with Likert impact
assessments across 9 enviro/social/econ dimensions
Collaborating on Modelling
Impact of recovery on GHG emissions
$ invested per sub-archetype per country from
Observatory (2nd scenario with more ambitious policy)
+
GHG impact per $ of spending per sub-archetype per
country (could consider scenarios based on
greenness of inputs/implementation standards)
(similar opportunity for air pollution)
Impact of recovery on economy
(1) Economic multipliers w/ VAR (Bartini et al. 2021)
and apply to $ of tracked spending in Observatory
(2) Immediate term: static input/output using $ of
spending per sub-archetype in Observatory (e.g.,
Vivid Economics)
(3) Jobs?? Short-term, long-term. Use $ of spending
per sub-archetype
(4) Long-term competitive advantage (e.g., H2 race).
Requires paired analysis of policy / private finance