Peak Oil through the lens of a general equilibrium assessment

1. Peak Oil through the lens of a general equilibrium assessment Waisman H, Rozenberg J, Sassi O et Hourcade J-C (2012). “Peak Oil profiles through the lens of a general equilibrium assessment”, Energy Policy 48:744-753.

2. Motivation • Peak Oil = impending stagnation and decline of world oil production • Determinants of Peak Oil : what drives the occurrence of Peak Oil? • Date of Peak Oil : a signal for the urgency of changes in energy uses • Economic consequences : sudden shocks and long-term effects

3. Motivation Two largely disconnected strands of literature • Geological-based analyses of Peak Oil • Hubbert-like approach = bell-shaped production curves at the field level • Extrapolation at a global level is questionable (heterogeneous oil reserves and producers’ rationale) • Economic dimensions of oil markets • Short-term effects of oil disruption • econometric analyses after first oil shock • no explicit accounting of resource depletion • Long-term effects of exhaustible resources exploitation • production profile under perfect foresight (Hotelling) • scarce representation of peaks

4. Objectives Representing the macroeconomic dimensions of long-term oil markets • Endogenizing the interplay between determinants of long-term oil markets under inertia and imperfect anticipations • Oil supply, Liquid Fuels demand, Alternatives to oil • Representing the impact of the economy on oil markets • Consumer behavior driving oil demand in function of price signals • Investment decisions in production capacities of oil and alternatives in function of profitability prospects and capital availability • Capturing the feedback effects of oil markets on macroeconomy • Energy trade (energy security for oil-importers, exportation revenues) • Technical and structural change ( oil-dependency, industrialization) • Aggregate effects on economic activity and welfare

5. Approach (1) A CGE approach embarking lessons from economic assessments of oil shocks mark-up pricing instead of competitive markets to capture a set of market imperfections partial utilization rate of capital due to the complementarity between energy and capital services putty-clay description of capital (with fixed energy intensity for old vintages) capturing the effects of inertias in the renewal of productive capital frictions in reallocating capital and labor across heterogeneous sectors (in terms of sensitivity to oil prices) causing differentiated levels of idle production capacities and unemployment.

6. Approach (2) A hybrid bottom-up/top-down approach sectoral modules embarking expert-based information on the direction and magnitude of technical change, including the determinants of oil markets a dialogue between technical/behavioral determinants and macroeconomic interactions A representation of « second-best »economies missing, imperfect or distorted markets noncompetitive behaviors technical and institutional inertias asymmetry or incompleteness of information

7. The IMACLIM-R model Static Equilibrium (t) under constraints Dynamic sub-modules (reduced forms of BU models) Static Equilibrium (t+1) under updated constraints ... Technical and structural parameters (i-o coefficients, population, productivity) Electricity Residential Transport Oil Supply Industry Economic signals (prices, quantities, Investments) Agricolture Energy Transport • Hybridmatrixes in values, energy and « physical » content (Mtoe, pkm) • Secure the consistency of the engineering based and economic analyses • Explicit accounting of inertias on equipement stocks • Technical asymptotes, basic needs • Solowiangrowthengine in the long run but transitorydisequilibrium • Unemployment, excesscapacities • Investmentsunderimperfectforesight (informed by sectoralmodels) • Trade and capital flowsunderexogenousassumption about debts

8. Modeling oil supply geological dimension • In each region, 7 categories of conventional + 5 categories of non-conventional reserves • size of the reservoir Q∞,i (ultimate reserves, including past production) • threshold selling price pi(0)above which production is profitable (proxy for costs of exploration/exploitation and accessibility) • Maximum rate of increase of production capacity for each category, given geological constraints bi: steepness of the bell-shape profile (default value: b=0.061) t0,i : expected date of the maximum for oil category i, given past production

9. Modeling oil supply producers’ decisions • All regions except Middle-East = “Fatal producers” • maximum deployment for profitable categories (poil> pi(0)) • investment stopped for non-profitable categories (poil < pi(0)) • Middle-East = “Swing producers” • Fill the gap between demand and other suppliers • World price depends on the utilization rate of production capacities • ME deployment of production capacities in function of their price objective • Total production capacity= sum over all categories and regions Production Capacity of oilcategory i Cap(t,i)+Δcapmax(t,i) Cap(t,i) time t t+1

10. Modelling oil demand • Liquid fuels’ demand (residential, industry, transport) • Utility and profit maximization under constraints • Short-term : inertia in the renewal of equipments and LBD • Long-term : consumption styles (preferences), technical potentials (technology availability, asymptotes), location patterns • Alternatives to oil • Biofuels • Competition over oil-based fuels: supply curves increasing with oil price • Asymptotes on BF production at a given year (competition of land uses) • Evolve in time to represent technical progress • Coal-To-Liquid • backstop technology with capacity constraints • enter the market at high oil price • production limited by the cumul of past investments

11. Results Two counterfactual scenarios of the world economy over 2010-2050 on production capacity expansion • Market Flooding scenario • ME expands production capacities to maintain oil price at 2009 level • Intense demand in the short-term • Technical change towards oil-intensive patterns in the long term • Limited Deployment scenario • ME restricts capacity expansion to let short-term prices rise • Moderation of oil demand • Technical change towards oil-free patterns in the long term

12. ResultsPeak Oil profiles • Level • Date • Post-PO decrease Close dates but verydifferent time profiles!

13. ResultsWorld oil prices • Controlled by OPEC in the short-term • Sudden rise at the Peak Oil date • Continuous increase in long term due to constraints on CTL

14. ResultsTime profile of oil revenues • Short-term revenues controlled by price targets • Bubble of long-term profits triggered by price increase after PO Room for Short-term vs. Long-termtradeoff!

15. ResultsTradeoff for oil producers MF scenario profitable for oil producers at discount rates lower than 6%

16. Results Impacts on oil-importers (OECD) Close average growth but different time profiles

17. ResultsA sensitivity analysis on oil determinants • Amount of reserves • Low bound: 1.6Trillion bbl conventional+ 0.8Trillion bbl non-conventional • High bound: 2.3Trillion bbl conventional+ 1.2 Trillion bbl non-conventional • Inertia on non-conventional production • Low inertia: b=0.04 vs. high inertia: b=0.07

18. Conclusion • A model to frame the debate on Peak Oil and long-term oil markets • representing the interplay between geological and macroeconomic dimensions of long-term oil markets • endogenizing the date of Peak Oil from market interactions between oil supply, liquid fuels’ demand and alternatives to oil • analyzing the effects of alternative pricing strategies and various assumptions on reserves and non conventional production • assessing the indirect macroeconomic effects of Peak Oil on long-term economic growth trajectories

19. Conclusion • Some important messages • Oil pricing trajectories hardly affect the date of Peak Oil … but have important consequences on its macroeconomic effects (oil revenues, economic activity in oil importing countries) • strong variations of Peak Oil and related macroeconomic effects according to assumptions on oil reserves • Middle-East producers may prefer moderate short-term prices if they are able to bias technical change under imperfect foresight • High short-term oil prices may be beneficial in oil importing countries as a hedging strategy against long-term oil scarcity

20. Thank you for your attention! waisman@centre-cired.fr http://www.centre-cired.fr http://www.imaclim.centre-cired.fr/ 34th IAEE International Conference Stockholm - 19/23June 2011

21. Approach (1) • A CGE approach embarking lessons from economic assessments of oil shocks • mark-up pricing instead of competitive markets to capture a set of market imperfections • partial utilization rate of capital due to the complementarity between energy and capital services • putty-clay description of capital (with fixed energy intensity for old vintages) capturing the effects of inertias in the renewal of productive capital • frictions in reallocating capital and labor across heterogeneous sectors (in terms of sensitivity to oil prices) causing differentiated levels of idle production capacities and unemployment.

22. Approach (2) • A hybrid bottom-up/top-down approach • sectoral modules embarking expert-based information on the direction and magnitude of technical change, including the determinants of oil markets • a dialogue between technical/behavioral determinants and macroeconomic interactions • A representation of « second-best »economies • missing, imperfect or distorted markets • noncompetitive behaviors • technical and institutional inertias • asymmetry or incompleteness of information