IMPACT OF HIGH ENERGY COSTS:

RESULTS FROM A GENERAL AND

A PARTIAL EQUILIBRIUM MODEL

Francesco Gracceva

Umberto Ciorba

International Energy Workshop Kyoto, 4-6 July 2005

2

OVERVIEW

Energy price and the economy/energy system

Understanding and simulating the link

A general and a partial equilibrium model

Markal-Macro

Markal-ED

Simulation assumptions

Results

Impact of high energy costs on the economy

Impact of high energy costs on the energy system

Conclusions

3

ENERGY PRICES

AND THE ECONOMY

4

UNDERSTANDING/SIMULATION OF THE LINK ENERGY COST ECONOMY/ENERGY SYSTEM (1)

MACROECONOMIC EFFECTS Direct effects (more spending for

energy costs), depending on: % energy costs on GDP dependence on imported energy ability of the economy to substitute

energy with other inputs …

Adjustment effects, linked to real wage, price and structural rigidities: inflation from increased input costs

and pressure on nominal wages reduced demand and lower

investments risk of unemployment, budget deficit …

Need for a general equilibrium approach

5

UNDERSTANDING/SIMULATION OF THE LINK ENERGY COST ECONOMY/ENERGY SYSTEM (2)

ENERGY SYSTEM EFFECTS Direct effects (energy costs more),

depending on: sensitivity of energy demands to

prices and income ability of the energy system to reduce

energy consumption through: conservation efficiency improvements

ability of the energy system to change the fuel mix

…

Indirect effects: through GDP reduction …

Need for a simulation of the endogenous

impact of prices/income on demand (together

with a detailed description of energy

system)

6

A GENERAL AND A PARTIAL

EQUILIBRIUM (MARKAL) MODEL

7

MARKAL-MACRO

MARKAL MACRO

Labor

Consumption

Energy Costs

Energy

InvestmentCapital

Y

Hydrogenproduction

Industry

Residential/commercial

Electricityproduction

Refineries

Transport

HeatingCoolingPower

Movingetc.

GasolineNatural gasElectricity

CokeHydrogen

Heatetc.

Renewables

Fossil fuels

Nuclear

Usefulenergy

Primary energy

Conversion sectors/processes

Finalenergy

Demandsectors/processes

Coke ovens

Heatproduction

Links the technology model MARKAL with a neoclassical economic growth model, through an aggregate (non linear) production function

Variations of energy demand are due to substitution between energy and other production factors, strongly dependent on ESUB

G.E. model: detailed description of the energy sector plus interactions between energy and the economy

BUT, as a single sector model, it is only able to roughly capture many changes in energy demand resulting from changes in exogenous variables

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MARKAL-ED

An extension of the technology model MARKAL allowing energy service demands to be endogenously affected by its shadow prices and income

The model maximizes net social surplus (based on Equivalence Theorem), a non-linear function linearised by piecewise linear functions

Possible to handle different elasticities for different demand categories

BUT partial equilibrium: no mechanism to simulate macroeconomic feedback effects (even if loss of Net Social Surplus is a proxy of GDP loss)

Hydrogenproduction

Industry

Residential/commercial

Electricityproduction

Refineries

Transport

HeatingCoolingPower

Movingetc.

GasolineNatural gasElectricity

CokeHydrogen

Heatetc.

Renewables

Fossil fuels

Nuclear

Usefulenergy

Primary energy

Conversion sectors/processes

Finalenergy

Demandsectors/processes

Coke ovens

Heatproduction

9

MARKAL, MARKAL-MACRO, MARKAL-ED

Markal

Markal-Macro

As most effects are related to measures taken inside the energy sector, “ignoring the impact of GDP on the energy system is not a very significant error” (Loulou, Lavigne, 1996) Preferable to use: MM to estimate economic effects; models with better simulation of demand sensitivity to prices/income to analyse the impact on the energy sector

Modest impact of GDP on energy demand Larger CO2

reduction in MM,

mainly due to lower DM/GDP

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SIMULATING THE LINK BETWEEN ENERGY COST AND THE ECONOMY/ENERGY SYSTEM: A TWO MODEL APPROACH

MARKAL-ITALY Evolution of energy system up to 2048

Equilibrium quantities and prices of more than 300 flows of energy goods and materials, from more than one thousand technologies

67 energy service demands: Industry: production of energy-intensive

materials Residential: heating, cooling, lighting, warm

water, main electric devices Services: heating, cooling, lighting, other

electric use and motive power Transportation: pass-km and ton-km, three

areas (urban, medium and long distance) Agriculture

Energy system effects

Markal-Macro Italy

Markal-ED Italy(price+income elastic)

Assessment of economic effects

11

SIMULATION

ASSUMPTIONS

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THE REFERENCE SCENARIO

Socio-economic assumptions

GDP (average growth)Population (avg. gr.)

1.8%-0.1%

1.8%-0.1%

2004-2012 2012–2020 2020-2028

1.8%-0.2%

Price of imported fuels

13

OIL PRICE IN REFERENCE AND HIGH PRICE SCENARIOS

Two scenarios:difference about 10$/bbl

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ASSUMPTIONS ABOUT SOME KEY MODEL PARAMETERS

Price elasticities

Industry -0.5

Services -0.4

Residential -0.3

Transp. - passengers -0.4

Transp. - freights -0.2

Income elasticities

Industry 0.8

Services 0.8

Residential 0.6-0.8

Transp. - passengers 1.0

Transp. - freights 0.8-1.2

MARKAL-MACRO: ESUB (elasticity of substitution between capital/labour and energy) = 0.35

GROWV (potential annual GDP growth rates) = 1.8%/yr

MARKAL-ED: Maximum demand reduction/increase = from 20% in 2004 to 50% in 2028

Alternative GDP growth = same GDP growth projected by in MM-High Price

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RESULTS

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HIGH ENERGY PRICES AND THE ECONOMY

The economic impact of high energy price is significant (-0.2-0.3%). Estimates are similar to recent literature (IEA, 2004)

The economic effect of high prices is quite similar according to the two versions of the model: loss of Net Social Surplus in MED is similar to GDP loss in MM

17

HIGH PRICES AND THE ENERGY SYSTEM (1/5): MARKAL-ED vs. MARKAL-MACRO

The impact of high prices on the energy system is quite different: reduction of energy service demands is significantly larger in MM

Introduction of income elasticity in partial equilibrium model increases the reduction of demands only slightly (in medium-term)

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HIGH PRICES AND THE ENERGY SYSTEM (2/5): MARKAL-ED vs. MARKAL-MACRO

The two versions of the model produce quite different reductions In MM, strongly dependent by a key parameter (esub), reduction in almost all sectors

A result produced by different methodology or by different parameters ?

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HIGH PRICES AND THE ENERGY SYSTEM (3/5)

Markal-Macro: Reduction of final consumption

increases with time In medium/long-term reduction

reaches about -2 Mtoe (mainly in industry and residential)

Markal-ED: Reduction of final consumption

in industry follows reduction in service demand

Reduction of final consumption in other sectors follows long-term efficiency improvement

20

HIGH PRICES AND THE ENERGY SYSTEM (4/5)

Change in fuel mix: accelerated substitution between oil and gas (with respect to Reference)

21

HIGH PRICES AND THE ENERGY SYSTEM (5/5)

Markal-Macro: CO2 reduction is strong in industry (demand reduction) electricity sector (change in

fuel mix)

Markal-ED:

CO2 reduction is large mainly in industry, the only sector with significant demand reduction

22

CONCLUSIONS/OPEN ISSUES

GE approach is useful to estimate the impact of energy prices/measures on the economy, but GE models usually simulate only roughly the link between energy cost and energy demand Effects on the energy system overestimated by GE models ?

On the contrary, impact on the energy system is better simulated with more detailed simulation of the sensitivity of energy demands to price/income (Provided that good elasticity estimates are available), partial equilibrium

models are preferable to analyse impact on energy system ? Some results from MM-Italy+MED-Italy:

economic impact of high energy price is significant, and estimates are similar to recent literature

the impact on the energy sector is quite larger in MM than in MED A possible relevant policy implication: even if economic effects are

significant, expected reduction in energy consumption (and emissions) could be overestimated