Mapping a Future Low Carbon Economy
Dirk van Seventer and Rob Davies
MAPS ECONLAB 3:
“PROVIDING ROBUST SOCIO-ECONOMIC INFORMATION OF SCENARIOS & NATIONAL CONTRIBUTIONS”
Cape Town November 5 and 6, 2014
Outline
Motivation
Structural Decomposition Analysis
Introducing new products
Motivation
Bruno asked how we might go about constructing a SAM representing a low energy economy at some date in the future
Our response: you have CGE models which you use to look at policy impacts
run them and generate the future SAM
also – predicting far into the future is inherently impossible
so easy and impossible task
Motivation
But then thought and argued and realisedwhat if CGE model does not arrive at dream future?- where can we do more?
some vision of future useful for gauging progress- multiple targets
process of trying the impossible is instructive
So presenting some incoherent and simplistic thoughtsnot sure if either useful or original
But hope it stimulates some thought
Stylised view of CGE modellingWe all know, but to set the stage
Stylised view of CGE modelling
Post-shock SAM could be produced by static or dynamic model
formal or intuitive model
Just want ‘before’ and ‘after’
Represents a new structure
What drives the changes?
Can use decomposition to think about this
Aggregate emissions decomposition
Kaya identity
Useful for decomposing sources of change in emissions in the past
Also useful thinking about targets and constraints for futureIf - population growth rate is exogenous in medium run- growth rate of income per capita has some lower (desired) bound
then improving energy cleanliness and efficiency provide only room for manoeuvre to reach RBS target
But in a multi-sector/economy wide model there is also possibility of compositional effect
Can change ratios by changing technology AND by changing sectoral structure
Decomposition of CGE results
Structural Decomposition Analysis looks at change of:
Technical change in energy use/intensity (exogenous driver)
Economic growth (exogenous driver)
Shifts in industry composition (endogenous)
Shifts in industry composition may be missing link
Help understand why model may not get “where we want to be”
Could include:- Introduction of new products (currently unknown)
- May require rebalancing end year SAM (entropy method)
Broad Objective of Decomposition Analysis
Decompose change in output into contributions from:
Technical Change- Industry linkages
Change in Final Demand- Change in Levels of Final Demand
- Change in the Mix of Final Demand
- Change in the Distribution of Final Demand
Decompose change in Energy Use
Same as above
Additional: change in Energy Intensity- Can be expanded to other variables (employment, emissions)
Examples
But … also some algebra
-
Some More Algebra
(1)
Let and and substitute into (1)
(2)
Re-arrange
(3)
Average weighting using base year and final year shares
(4)
Technology (Industry Composition)
Change
Final Demand Change
Results of exampleDemo at Speed Dating??
What do the results show?
Further Decomposition of F
(5)
In which & are vectors of expenditure shares
…and and total expenditures (scalars)
Now, follow the same decomposition principles
(6)
Substitute into previous results
eqn (7)FD Level Change
FD Mix Change
FD Mix Change –
New Products
Adding Energy (8)
With &: matrices eng/output ratios on the main diagonal
If : difference in eng/output ratios on the main diagonal
Then: decomposition along same lines:
(9)
Energy Input Effect
Technology Effect FD Effect
Energy Intensity Multipliers
Direct and Indirect
Energy Use Per 1 Unit of
Further Decomposition
possible: FD Mix Change – New
Products
Extensions
Previous examples could be extended to
various types of energy
emissions
Can apply to SAMs
industries, commodities, types of households, types of factors
Needs SAM in constant prices to get proper technical coefficients
Can apply to Hybrid SAMs
Energy (or other) non-monetary units
Monetary units
Can do similar decomposition simultaneously- Energy use
- Output
Lessons from SDA
Shows sources of change in Energy (and emissions)
Not only from growth and improved energy efficiency
But also from structural changeinter-industry linkages
final demand structure
Could be used to summarise major sources of changes from CGE analysis
Might show the ‘gap’ in achieving the RBS ‘dream SAM’
But only deals with existing industries and commodities
What about new industries and products?
New Industries and Products
“Dream SAM” will have new industries/products
Inherently unknowable
But maybe we can think about the characteristics they need to have to help ‘fill the gap’
Relevant characteristics:energy intensity
cost structure
linkages
Old New FD Total
Old A C
New D B
VA
Total
Impact of new industries will depend on:
B – cost structures, energy use and linkages within the new cluster
C – retarding effect of the old on the new
D – progressive impact of the new on the old
Our initial thinking before constructing numerical model
A Stylised Example
A : cluster of old industries
B : cluster of new industries
C : backward linkages from new to old
D : forward linkages from new to old
Took our previous 3x3 IO Table
Added new industriescannot do that without changing size of economy, so halved old economy and put in roughly similar sized new cluster
Constructing a toy model proved difficult, but some lessons
Constructing a numerical example
Old 1 Old 2 Old 3 New 1 New 2 New 3 F XOld 1 10 20 25 - - - 45 100Old 2 15 5 30 - - - 30 80Old 3 30 40 5 - - - 25 100New 1 - - - - - - 0 0New 2 - - - - - - 0 0New 3 - - - - - - 0 0V 45 15 40 0 0 0 0 100X 100 80 100 0 0 0 100
New industries use some of Old 3 “Dirty Energy”
Problem: where do the supplies from old to new come from?growth in output of old?
switch from final demand of old?
switch from intermediate supplies to old?
Adding backward linkages from new to old
Constructing a numerical example
Old 1 Old 2 Old 3 New 1 New 2 New 3 F XOld 1 5.00 10.00 12.50 - - - 22.50 50.00 Old 2 7.50 2.50 15.00 - - - 15.00 40.00 Old 3 15.00 20.00 2.50 0.60 1.00 0.15 12.50 51.75 New 1 - - - 6.00 7.50 12.50 25.00 51.00 New 2 - - - 12.00 5.50 10.00 17.50 45.00 New 3 - - - 5.40 9.00 1.35 13.00 28.75 V 22.50 7.50 21.75 27.00 22.00 4.75 105.50 X 50.00 40.00 51.75 51.00 45.00 28.75 105.50
Old industries replace some dirty energy with clean New 3
Reduces energy use in economy
Completed filling in linkages between ‘non-energy’ old and new
Adding forward linkages from new to old
Constructing a numerical example
Old 1 Old 2 Old 3 New 1 New 2 New 3 F XOld 1 5.00 10.00 12.50 - - - 22.50 50.00 Old 2 7.50 2.50 15.00 - - - 15.00 40.00 Old 3 13.50 18.00 2.25 0.60 1.00 0.15 12.50 48.00 New 1 - - - 6.00 7.50 12.50 25.00 51.00 New 2 - - - 12.00 5.50 10.00 17.50 45.00 New 3 1.50 2.00 0.25 5.40 9.00 1.35 13.00 32.50 V 22.50 7.50 18.00 27.00 22.00 8.50 105.50 X 50.00 40.00 48.00 51.00 45.00 32.50 105.50
When we have a dirty cluster and a clean cluster, the total energy use depends on the total energy produced by each. The linkages do not matter
But the impact of an increase in final demand does depend on the linkage structure including linkages between non-energy sectors, because of multipliers.
Could do a multiplier decomposition (not SDA) for ‘within’ and ‘between’ cluster effects
General lessons from constructing numerical example
Concluding Thoughts
Building a dream SAM that accurately captures a low energy future is inherently impossible
Nonetheless might be a useful exercise‘Balancing constraint’ of SAM constrains our guesses
Put different pieces of an imagined future into a consistent whole
If we do build a dream SAM, might provoke thoughts about the policy levers needed to get there
More insights might come from more realistic SAM – without the simplistic balancing mechanisms in our toy model
will need some statistical balancing procedure
But remember models are simplifications to help us understand issues, so dream SAM could be simple
not trying to describe the future, but to think about it
End
Play it again, SAM
Introducing New Products
Why?: to get closer to “where we want to be”
Unconstrained problem
What do we know? Products must be:
More energy efficient
Sufficiently high value added generation
But do not have policy levers in models
That control introduction of new products
See example
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