Download and for the global economy

GRO: modelling the impact of
resources constraints on
growth
Dr. Irene Monasterolo
Global Sustainability Institute,
Cambridge (UK)
The global challenge
• Get the balance right between economic
growth/environmental loading to allow future
generations enjoying comparable well-being in
safe, bio-diverse planet:
• At the global level resources limited yet fundamental for
life are being depleted at a faster pace than the planet
can replace (UNEP, 2011; FAO SOFI 2012; EC 2012)
• Emissions from human activities cause an irreversible loss
of biodiversity (Global Footprint Network’s Biodiversity
Indicators Partnership) and worsen climate change.
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Why this project
1.
2.
3.
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We live in a planet with finite resources
Resources are getting more scarce as
population increases
The resource scarcity issue is causing price
spikes
Price spikes cause political instability
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GRO objectives

Investigate most likely level of GDP (and beyond)
in the short-term given resource constraints:
– What kind of composition of GDP required for
growth/green growth?
– ‘Composition’: sector (e.g. % of GDP in services,
investment, agri), energy & resource intensity
– List of credible disruptive events to affect the situation
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Provide clear information on sustainable scenarios:
– Close time-lag btw short term governments’
agenda/long-term modelling
– Commit governments to targeted sustainability
measures..and follow policy recommendations.
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Filling the knowledge gap

Previous studies (e.g., LtG, Mann, IPCC) on
human interaction with environment and its
(negative) feedback on our activities:
..Waiting for full IPCC 5° Report
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The state of play

Limits to growth 1972: role of human activity on
resources depletion and impact on global growth
– Simulate interaction of 5 global economic
subsystems: population, food production, industrial
production, pollution, consumption non-renewables.
Message: overshoot & collapse in standard run
- Continued growth leads to (i) planetary limits being
exceeded in 21st century (in all 12 resources/pop.
interaction scenarios) (ii) collapse of pop and eco.
systems due to resources overuse and pollution
– Collapse avoidable if combination of main changes in
behaviour, policies, technol. (stabilized world)
– Significant controversy and rejection of its scenarios:
end to growth followed by a long period of relatively
high human welfare.
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Not predictive in details but analysis of interaction of
global eco. Systems (indication of system’s
behavioural tendencies only, Meadows, ‘72)
It introduced Forrester’s new computational SD
modelling approach and quantitative scenarios
analysis into environmental discipline
Since then, increase in data, indicators (ecological
footprint, GHG emissions), models, programmatic
docs and actions (Agenda 21, Kyoto Protocol),
institutions …but low impact on sustainable policies of
influential countries
EU2020 ambitious strategy to provide sustainable
development while tackling climate change… but
discrepancies willingness/actual implementation.
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Anthropocene and its consequences

Alarming LtG results partially confirmed (Turner 2008):
• human-led resource depletion (Mann, 1998, Steffen et al., 2011) &
impact of climate change (more frequent floods, droughts) affect
access to global resources and environment (ecological debt increasing as
“Earth Overshoot Day” occurs earlier every year)
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Multidimensional consequences
– Uncertainty with regards to future economic growth
(capital constraints and productivity challenge,
McKinsey, 2011 )
– Systemic risks in high indebted (and resources
intense, e.g. USA) countries
– High volatility of commodity prices (Grantham 2012,
FAO) due to costly resource extraction and
conversion, D/S imbalances
– High inequality, poverty, famine, vulnerability (WB)
– Resources exploitation & land grabbing (Oxfam)
– Political instability (e.g., Arab spring)
– Quality of life of future generations at risk (WWF).
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Resources nexus: local issues…
Source: FAO, ‘Dimensions of need: An atlas of food and agriculture’, 2012.
• Most resources have both local and global impacts such as soil
degradation and water abstraction and the presence of
phosphorous and potassium which are very local issue with global
consequences through food availability
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And global impacts
Oil
150
Tin
Gas
100
50
Copper
Coal
0
Zinc
Uranium
Indium
Silver
50 years left for tin, zinc and oil
(approximate number of years
left= current global reserves/
current annual consumption
(assuming no growth in demand)
Source: Jones et al., 2013. Data: BP 2012,
Cohen, 2007.
Rockstrom et al (2009) 9 ecological
boundaries which human activity
should not cross (green circles)
- red wedges: current situation, 3
boundaries already crossed
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In a more crowded...
 UN Pop Dept (2013): from 7.2 to 9.6 bn by 2050, most growth in LD
regions (Africa), to double in least developed countries. India to be
largest country passing China (2028), Nigeria to overtake the US.
 Reasons: higher fertility, fast increase in life expectancy at
birth.
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And aged world
810 million people 60y or over (2012), 55% in Asia, 21% in EU.
Over 60 expected to grow to 2bn by 2050 (from 1 out of 9 to 1
out of 5), outnumbering children for the first time.
.. effects on environment and States budgets
(health care, insurance, pension)!
Consequences for the environment
 Planet’s temperature expected to increase by 4-6 degrees
by 2100, with possible loss of Artic summer-ice by 2016
• IPCC’s Fourth Assessment Report (AR4) 2007: CO2 now at 35 000
m metric tons py (projected to rise to 41,000 m metric tons in
2020), CO2 concentration rising at 1.8 ppm (parts per million) py
• World temperature kept increasing and now at 0.8 degrees above
pre-industrial levels
• Oceans to rise 15-20 cm this century, damaging coastal cities
• Change in precipitation patterns will increase droughts and floods.
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Source: Turn Down the Heat (IPCC & WB, 2012)
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..and for the global economy
Grantham (2012) ‘We are experiencing a paradigm shift: after 200
years characterized by declining prices, since 2002 resources prices
started to rise’. See 2007/2008 volatility of food commodity prices…
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Models contribution to policy making
for sustainable prosperity

Several projects at the EU (FP 6th and 7th) developed
models which tried to understand limits to sources of
capital (natural, human) and what this means for
society, e.g.:
–
–
–
–
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Planetary Boundaries by Stockholm Institute;
One Planet Living by WWF & EUREAPA (I-O),
Stern’s PAGE 2002,
OECD’s ENV-LINKAGES (GEM+SAM)
DSGE
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Unconventient modelling limits
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These models present several limits which
prevent the application to reach our research
goals:
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not transparent about the reasons of impacts
do not model physical limitations, sectorial
model on long time scales
strong equilibrium assumptions
do not directly tell a story through their
scenarios
– too complex to be used as initial decisionmaking tool.
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A new model army
Development and application
of SD and ABM:
System Dynamics:
Deterministic representation of
the world
Long tradition of complex
system thinking application to
sustainability (1972 LtG, MIT)
Agent Based Models:
Shaping micro heterogeneity which
interacts with macro
‘New wave’ from ‘90s thanks to
data and computational power
First applied to biology
(agents=turtles)
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Building a better model

Innovativeness: ABM integration into SD
– more info for more modelling transparency (process and
output interpretation)
– Higher consistency and correctness of results through
control over of methodological steps (double statistical
internal validation systems)

Short-term focus (next 5 y.):
– What if scenarios during a government term
– Better understanding of results and dissemination to
create the basis for higher public commitment towards
sustainability

Move from empirical evidence: multidimensional
dataset (1995-2010):
– Analysis of historical countries behaviour
– Geographic detail (country/regional/global)
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GRO outputs
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New global database of national demand, supply and flow
figures relevant to global natural resources (in)security.
Global 'debt map' for natural resources availability,
specifying for each UN country (212) current supply of
resources that can be found within its borders compared to
current consumption.
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A world-scale SD model to investigate current interaction
between resources/global economy.
An ABM to investigate possible future economic growth
pathways
– Accounting for list of disprutive events, ie. Wild cards

Case study country/regional analyses selected for
specific resources relevance (e.g., socio-economic and
environmental).
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Database
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Multidimensional dataset at global level (212 UN countries)
Time series: from 1995 onwards
6 main groups of commodities – i.e., food, water, land,
fuel, minerals, air) including social (socio-economic,
demographic, social cohesion), financial (markets and
prices), agri-enviornment (env.loading, footprints,
emissions)
Vars. gathered from official sources (internationally
validated) comparable, consistent, and yearly updated.
To be completed by December 2013.
Statistical analysis (using exploratory econometric methods
and multivariate statistics) to understand correlations
between resources and global economic system.
Model for disclosing resource-price dynamics to be
complete by December 2013.
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Global debt map
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Calculated as countries’ reserves of specific natural
resources (food, water, land, fuel, minerals) divided by
their annual consumption
Maps to geographically visualise
 number of ‘years left’ until a resource is fully depleted
by each country based only on their own national
reserves
 the quantity of a renewable source consumed each year
GDM input for SD to describe resourceseco/pol systems behaviour, accounting
for market imperfections.
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Oil debt map
Oil Proved Reserves (Mil. Barrels) 1995-2010 (52 c.): Recoverable reserves in reservoirs
under existing economic and operating conditions
Oil Consumption (t. million barrels) 1995-2010 (72 c.): Includes inland demand,
internat.aviation, marine bunkers, oil products for refining process, fuel ethanol biodiesel.
Calculation: Reserves /consumption = years left
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Analysis
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Mainland Europe under much oil stress – Canada,
Middle East and Vietnam as the potential traders
of their oil supplies (inc. Brazil, Kazakhstan,
Australia, Norway)
Africa not as dependent and lacks resources
Can see the development of the BRIC nations
Lack of data for Africa, Iceland, Central Americas
Next steps: get per capita figures, and fill in
countries gaps
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From World 3...

4 key elements to
understand constraints &
behaviour of world system:
– feedback loops (pos. And
neg)
– Resources depleted by
eco.systems (land)
– Delays in info
transmission (eg
transmission of pollution
on life exp.)
– World eco system as
complete system of
subsystems (no sectorial)
Characteristics
- 8 variables
(demographics, fertility,
industrial output, nonrenew. resources, life exp.,
agri.productivity, pollution,
service output)
- Aggregate variables
(pop=tot.pop,
ind.output=avg.)
- No spatial/socio-economic
disaggregation
- Causal links=loops, made
mathematically to reflect
mutual vars. influence
Complex to design policy mitigation solutions.
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World 3: demographics
- Total population per class of age is function of initial value of
reproductive_lifetime, population_equilibrium_time, total_fertility, which adds
to the effect of the other variables which contribute to dynamics of the system.
- Population is the most important variable because it is used in the other
classes to determine/define other key values of variables which are relevant for
a full understanding of the system.
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..to World 4
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SD (‘World4’) to analyse interconnections btw natural
resources (water, food, land, fuel, minerals), countries
and growth
Current links btw resources parameterised in new SD
model (World4)
Links to include:
– substitution (e.g.,liquefying coal as an oil substitute),
– feedback loops (prices, water availability for food production)
– time delay loops (investment into infrastructure providing future
resilience).
– Tipping points
– Rebound effect (eroding goals)
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These parameters derived from global database
Future projections derived from most discussed
international model outputs (e.g.,IPCC).
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Updating World 3
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Exploit new information available (resource prices, climate
change
and planetary boundaries)
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New influential variables added (e.g., prices, oceans
acidification, sea level and temperature, precipitations and
their disruptive effects, emissions by sectors, eco. Footprint)
Prices and food fundamental:
– Prices endogenous in SD (because short term analysis), to
become exogenous in ABM (to inform agents’ behaviour)
– Food central for global political instability&sustainable living
being closely related to demographic, economic growth,
inequality, resources management& fuel prices.
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Comparing W3/W4:
– Run statistical analysis on both groups of initial variables, eplaining
differences as regards (i) correlation results, (ii) PCA (identification and
meaning).
– Graphical visualization: comparison of the two SD diagrams.
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ABM for sustainability analysis
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Proper method to model socio-economic-ecological systems
and simulate policy scenarios (Building better models)
To explore country behaviour characteristics:
– Comprehensive picture of relation btw agents’ properties,
behaviour in resource use, GDP level, composition
– Able to shape single defined agents which interact within a
dynamic environment, given assumptions
Allows to analyse micro&macro levels at the same time (and
mutual influence) in the same environment
Impact of policy introduced in year 1 visible at year 5 (govt.
term):
– Change in country/region/global GDP level and
composition
– Change in main resources use (trade off and resource
substitution effects)
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ABM Strenghts
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Display and describe emergent collective behaviour:
– ‘Wild cards’ (e.g., extreme weather events or resource
shocks) scenarios modelled to explore key stress
variables that could lead to political instability.
Use of generative approach (emerging prop., bottom-up)
Possible to shape heterogeneous and hierarchical agents
Analyse non-linear interactions at micro-level to results in
macro level patterns
Explore world’s resiliency to a set of credible circumstances,
e.g., under BAU, global economy may be stable but there
may be a number of connected events which could
destabilise regions or even global economic activity.
Able to test these connections (internal validation)
Interdisciplinary approach into modelling
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ABM weaknesses
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Time-consumin initial data-gathering phase
Complex modelling and simulation phase
– Computationally intense thus need for powerful processors,
and time...
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..but time well spent! Informative scenarios
provided
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ABM Characteristics
ABMs include the following elements (Bravo et al.
2012):
– an environment, i.e., a set of objects the
agents can interact with;
– a set of agents who interact with each other;
– a set of relationships linking objects and/or
agents;
– a set of operators that allow the interaction
between the agents and the objects.
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Agents’ behaviour assumptions
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Agents: 212 UN countries
Countries wish to maximise GDP growth given resource
availability, productive structure, specialization
Agents behave in a social network (geo, trade, pol.)
Countries decide whether to consume their own
resources or to import
If they import, they look for the closest country to
which they are linked
When all their neighbours are red, they look for the
closest green/yellow country
Model stops when the world is red
SD informs (historical behaviour) what agents can trade
change in relative prices) and consumption implications
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Social network
Agents embedded in a social network (each country
linked to its neighbours)
 Agents randomly positioned in a 3D world
 Links randomly created according to the “proximity”
of the countries
2 indexes to better define countries relationship:
1.
Trade index, e.g. WTO membership, multi &
bilateral trade agreements, cross-country
investments, actual trade
2.
Political/cultural index, i.e. what drives political
fragility given resource constraints (e.g. religion,
political ideology, corruption, language)
Each index will correspond to a type of link and will be
assigned to a different colour.
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Pilot ABM overview 1
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Software -> NetLogo
197 countries (agents)
1 resource -> Oil
Size -> Population
Colour -> Years-left:
– Green > 20
– Yellow > 5 and < 20
– Red < 5
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Building the social network
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Population:
– Birth rates
– Death rates
– Randomness (up to 0.5%)
Oil:
– New discoveries (up to 2% of all oil stock)
– Consumption
– feedback from population growth
– up to 5% randomness
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Preliminary results 1
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1000 Runs
Oil stocks get depleted in 36 years on average
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THANK YOU FOR THE ATTENTION!
GSI Team, Cambridge
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