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Green Accounting

Green Accounting

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Green Accounting

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  1. Green Accounting

  2. EU Policy Context • Lisbon (economic and social) • Gothenburg (environment) • Climate change  • Sustainable transport  • Public health • Resource management • Green accounting links economic and environmental objectives

  3. Overview of Presentation Green (environmental) accounting • Rationale • Elements of Green Accounting: Theoretical & conceptual basis • Empirical progress in different contexts • Conclusions for research and practical applications.

  4. Rationale for conventional accounting • Measurement of economic activity - production = GDP • Often used as indicator of welfare • Two elements of accounts • Changes in Stocks of Capital - Investment • Measurement of production/output – Flows - Consumption

  5. Standard National Accounts (SNA) framework • NNP = C + I – D + X – M Where: NNP = Net National Product C = Consumption I = Investment D = Depreciation X = Exports M = Imports Misleadingly used as measure of welfare: welfare not proportionate to consumption of produced goods

  6. Green accounting – rationale “The effect of mankind’s activity upon the environment has been an important policy issue throughout the last part of the twentieth century…. increasing recognition that continuing economic growth and human welfare are dependent upon the services provided by the environment” Source: The United Nations Handbook of National Accounting - Integrated Environmental and Economic Accounting • Economic – Environmental linkageshave implications for meso- and macro-economic management • Meso/macro-economic management more responsive to environment if environmental indicators exist

  7. Elements of Green Accounting - Outline • Environmental services • Ecosystem life support systems • Landscape • Environmental damages • Pollution flows e.g air & water quality • Defensive (environmental protection) expenditures • e.g. noise reducing windows & IPPC technologies • Resource depletion • Non-renewables; renewables

  8. Empirical progress in Environmental Accounting in different contexts – some evidence

  9. UN initiative on Green Accounting – UNSEEA (1993, 2000, 2003) • System of integrated Environmental and Economic Accounting (SEEA) – complements SNA method for measuring economic activity • Adds environmental information to existing Input-Output economic data • Physical stock and flow tables • Hybrid (physical & monetary) stock and flow tables • Methodological guidance on resource depletion, degradation, defensive expenditures

  10. Physical & monetary stock and flow tables • Often known as NAMEAs (National Accounting Matrix including Environmental Accounts). • Physical flow accounts include four types of flow: • products (produced in the economic sphere and used within it), • natural resources (mineral, energy, biological), • ecosystem inputs (air and water) and • residuals (solid, effluent, emissions). • Each of these accounts is expressed in terms of supply to, and use by, the economy. • i.e. tables represent the flows between the economy and the environment.

  11. An indicator of weak sustainability: genuine savings • Genuine Savings = monetary savings less the depreciation on manmade capital less the depletion of natural capital. (From S = Iv identity) • Value of changes in economy’s overall capital stocks. • Negative genuine saving corresponds to unsustainability, since if depleting capital stock, can receive lower welfare from it in future • Genuine Savings rates low or negative for Sub-Saharan Africa and for Middle East and North Africa. • Assumes all capital is substitutable

  12. Genuine savings for Tunisia, as % of GDP

  13. The Index of Sustainable Economic Welfare (ISEW) • ISEW (Daly and Cobb (1989)) • current welfare should be measured as the current flow of services from all sources, rather than current output of marketed goods • E.g. • value for leisure time to correct for the fact that welfare could increase while NNP decreases if people choose to work less; • higher incomes of urban residents are compensation for externalities connected with urbanisation and congestion,  proportion of income should not be included as welfare

  14. The Index of Sustainable Economic Welfare (ISEW) ISEW = Consumption + Investment + Extra-Market services + Consumer Durables Services + Services of Roads + Public Health & Education – Consumer Durables Expenditure – Private Defensive Expenditure on Health /Education – Advertising – Commuting costs – Pollution costs – cost of loss of ecosystems – resource depletion costs – Long term environmental damage • Applications at national level: UK, Sweden, Netherlands, Italy, Poland, Austria • Applications at local level: Siena (Pulselli et. al. 2006) • Problem – mixes sustainability and welfare issues in single measure

  15. Index of Consumption Corrected for Environmental Damage (ICCED)- EC Greensense project ICCED developed: • to demonstrate how well-being changes over time if sustainability standards imposed and effects of environmental damage are accounted for. • corrects for environmental damage and expenditure incurred under sustainability policies (similarities with local EcoBudget initiatives e.g. Roma)

  16. Sustainability targets analysed under the GREENSENSE project

  17. Greensense: Environmental impacts on welfare (UK)

  18. Greensense:ICCED Measures - UK

  19. Summary of Empirical initiatives • NAMEA: includes environmental issues within standard accounting framework • Genuine savings – sustainability-related decision rule • ISEW – broader interpretation of welfare • ICCED – includes welfare effects of meeting sustainability targets

  20. Conclusions on Green Accounting • Recognition of need to address both current welfare and sustainability issues from macro-perspective • National and international initiatives (e.g. UN SEEA, 2003) are developing improved methodologies • Variety of initiatives reflects lack of consensus on priorities and methods • Local applications of methods can reflect regulatory responsibilities but may be difficult to define sustainability at this scale? • Applications very data-hungry and modelling intensive