Measuring Energy Linkages with the Hypothetical Extraction Method: An application to Spain

1. Measuring Energy Linkages with the Hypothetical Extraction Method: An application to Spain Ana-Isabel Guerra Ferran Sancho Universitat Autònoma de Barcelona (Spain)

2. Key points of this Analysis • Goal: Stressing empirically the relevance of Energy Linkages for the effectiveness of energy efficiency policies • Relevant in the actual context: Energy Efficiency policies one of the main concerns of the EU Energy Policy • Methodology: within the Input-Output framework “Key sectors analysis” using the Hypothetical Extraction Method. (HEM thereafter) • Novel Contribution to the existing literature: We have Generalised the HEM to measure Sectors’ “keyness” in terms of stronger Energy Linkages for Energy Efficiency policies. • Data: SIOC-2004 for Spain and “Satellite” Environmental

3. I.I. Introduction: Why Energy Efficiency Policies are so relevant? • First Goal: Reduce negative externalities: Energy efficiency improvements seek reducing the link between Energy use, Economic activity and Environmental degradation. • Derived Positive Effects: Income effects: Efficiency improvements increase productivity and thus, favors economic growth. Trade Balance: Production is less costly Increases competiveness Less Energy inputs are needed Energy imports decreases • Derived Negative Effects: Potential Energy Savings might be totally or partially lost due to the decline in the actual price of Energy (Rebound effects, Khazzoom (1980))

4. I.II. Introduction: What determines Energy Efficiency Policy effectiveness? • Specific Characteristics of the sector receiving the energy efficiency policy inflow: • Degree of energy intensiveness:Transport, Manufacturing, Energy and Construction sectors. • However this energy intensiveness provides incomplete information for those economies in which there are markets’ interdependencies Tighter sectors’ interdependencies generate stronger economy-wide impacts and this is pertinent for economic policy effectiveness. (Hirschman, 1958) Then, Sectors’ role in the existing network of market interactions should be measured: Identification of “key sectors”

5. I.III. Introduction: How to identify “key sectors”? • Input-output framework the most appropriate for this task: Sectors’ keyness identified using the information contained in the Leontief inverse because it reflects direct and indirect sectors’ linkages: forward and backwardlinkages • Two approaches: Classical Multiplier Method: Sectors’ keyness is measured through out the effect of hypothetical positive demand shocks over output levels, i.e. output gains. Hypothetical Extraction Method: Sectors’ keyness is measured through out the negative effect of an hypothetical cessation of external sectors’ activities, i.e. output losses

6. II.I. Our Approach: the HEM and energy efficiency policy effectiveness • Goal (recalling): Identifying “key sectors” for a higher effectiveness in the design of energy efficiency policies. • Among the two methodologies ( the Classical method and the HEM), the HEM appears to be the most appropriate tool in this case. • Why? the HEM can be seen as an extreme case of energy efficiency policies, this is in fact the advantage of a linear model: “efficiency improvements are so high that energy external linkages completely disappeared”.

7. II.II. Our Approach: About the HEM • It is assumed that there are two blocks in the economy, E, -E. • On Analysing the “keyness” of these blocks, A-E,E =AE,-E=0 Then: • For a constant f, compute the difference between (2) and (3), thus, evaluate changes in output levels.

8. II.III. Our Approach: Data and Methodology • Data: SIOC-2004 for Spain and “Satellite” Environmental Accounts • The economy is partitioned into two large production blocks: Energy sectors and Non-Energy sectors • When using the HEM two types of extractions are applied: • Sequential Extraction of Energy sectors and quantified sectors’ output losses (Energy and Non-Energy) • Sequential Extraction of Non-Energy sectors and quantified Energy sectors’ output losses

9. III.I. Methodology: First type of Extraction • When energy sectors are sequentially extracted: • Sectors’ Higher Output losses indicates higher energy efficiency sensitivity. • This information is helpful to identify the origin of the ‘perverse’ effects of energy efficiency gains: -Channels trough out the decline of the effective price of energy is transmitted generating “Rebound Effects” -Higher sensitivity in terms of quantities can be interpreted as a higher sensitivity in terms of energy input costs. However depending on elasticity of substitution values.

10. III.II. Methodology: Second type of Extraction • When Non-Energy sectors are sequentially extracted: • Higher Output losses in Energy Sectors indicates a larger amount of energy inputs to fulfill they external market relationships (direct and indirect). • This measure turns out to be a more complete approximation to sectors’ energy intensity than the conventional energy input-output ratio. • Input-output ratio only controls for the direct energy input requirements

11. IV.I. Results: First type of Extraction

12. IV.I. Results: First type of Extraction

13. IV.II. Results: Second type of Extraction

14. IV.II. Results: Second type of Extraction

15. Conclusions: • This analysis has performed a double simulation exercise using an adaptation of the HEM applied to energy and non-energy blocks with Spanish data: • First type of extraction: Production and Distribution of Electricity turns to be a “key sector” for energy efficiency policies and for the possible “Rebound effects”. • Second type of extraction: Should the indirect consumption of energy be controlled for, Commercial and Transport activities together with the Manufacturing industries turn out to be the more energy intensive. • This novel reformulation of the HEM provides useful information for maximising economy-wide impacts of energy efficiency policies is concerned.

16. Thanks for your attention