David Pannell Centre for Environmental Economics and Policy

1. David PannellCentre for Environmental Economics and Policy Value for Money in Environmental Policy and Environmental Economics

3. Problems with the salinity policy • Selection of projects • Delivery mechanisms • Design of projects • Objectives • Internal logic • Focus on outcomes

4. Observations • The problems of the salinity program occur in many other programs and agencies • Cause enormous loss of environmental benefits • Readily avoidable (some trivially easy) • Low awareness

5. Why value for money is important • Limited resources for environmental actions • Salinity program: $1.4 billion • Full mitigation cost: $65 billion • Achieving significant outcomes can be expensive • Gippsland Lakes, Australia • Target 40% reduction in nutrients over 25 years • Budget: PV $30m • Min cost: PV $1000m

6. Why value for money is important • Heterogeneity among potential investments • Values at stake • Threats • Feasibility • Time lags • Adoption/compliance • Project risks • Costs

7. Huge range of benefits and costs • Best 5% = BCR 330 times better than median Source: Fuller et al. (2010). Nature

8. Questions • What is required for public environmental programs to deliver value for money? • What can economists do to increase the chance that investment in environmental economics analysis provides value for money?

9. Value for money from investment in environmental programs

10. 1. Be selective • Target resources to the best investments • Which environmental issues? • In which places? • Which people to involve? • “Best” = expected to provide most valuable environmental benefits

11. 2. Focus on outcomes • Decisions about project priorities, project design, program design, should explicitly consider the environmental outcomes likely to be achieved • Very commonly, programs don’t do so beyond a superficial level • e.g. most agri-environmental programs

12. e.g. Environmental Stewardship program • Entry-level scheme has 200 “priority options” • e.g. permanent grassland with very low inputs • legume- and herb-rich swards • uncropped cultivated areas for ground-nesting birds

13. Outcomes? • Program indicates type of environmental benefits • e.g. dragonflies, newts, toads, bats, dormice, soil erosion • Ideally, allocate funds to actions/places  most valuable environmental outcomes • Would need to account for • How many extra bats? • How much improved water quality? • How much does the community care? • It’s hard, but more effort needed

14. Implication for programs • Focus on actions rather than outcomes means that most funded projects are not great

15. Implication for programs • A suggested strategy: start with outcomes you want and work backwards • Outcome: Reduce frequency of algal blooms in Gippsland Lakes from 1 year in 3 to 1 in 10 by 2025 • Working backwards: What on-ground actions would be required to achieve that target? Where? How much? What policy actions would be required to bring about those on-ground actions? Cost? Value for money?

16. 3. Consider all relevant info • Bio-physical factors • Condition without (current condition, future threats) • Effectiveness of management • Time lags (in threats, in response to actions) • Project risks (technical) • Socio-economic factors • Importance of the environmental values • Adoption/compliance level • Time lag (adoption) • Discount rate • Project risks (social, political, financial)

17. Implications for programs • If you leave some out, project prioritisation can be greatly weakened • Most programs that do prioritise miss several out • values • effect of on-ground actions • adoption/compliance • maintenance costs • time lags

18. 4. Use a sound metric • The most common metric used to rank projects is weighted additive Score = w1.x1 + w2.x2+ w3.x3 + w4.x4 + … Where x1 = environmental threats x2 = project risk x3= adoption x4 = project cost etc.

19. Implications for programs • Very poor rankings • Implies you can compensate for having no adoption by having low technical risk, but you can’t • Where benefits are proportional to a variable, it should be multiplied, not added • To max benefits, must divide by cost, not subtract it • Logic leads to a very different metric • Can make huge difference to environmental benefits ultimately achieved

20. Comparing project rankings • R2 = 0.7% • Cost divided • Favours cheap projects • Of best 16 only 1 is actually best • Loss  50% (5% budget) • Easy to fix

21. 5. Comparing scale/intensity • Typically only one scale/intensity is considered for a project • But value for money can be highly sensitive to scale/intensity

22. Diminishing marginal benefits • Width of riparian buffer strips in Germany (Sieber et al. 2010, Land Use Policy) • 3m wide: 61% reduction in pesticides in river • 30m wide: 94% reduction • 50m wide: 96% reduction • Technical vs psychological

23. Increasing marginal costs BCR: 3.2 1.1 0.3 0.04

24. 6. Select good policy mechanism • Salinity policy: spent most of its money on extension • Promoted practices that were not adoptable on the required scale • Needed a simple tool to help people think through the choice of mechanism • Public: Private Benefits Framework

25. Definitions • “Private benefits & costs” relate to the landholder making the decisions (internal) • “Public benefits & costs”: all others (external) • neighbours, downstream water users, city dwellers interested in biodiversity

26. Perennials Farm B Perennials Farm A Current practice Forestry in water catchment Possible projects Each dot is a set of land-use changes on specific pieces of land = a project. • Which tool? • Incentives • Extension • Regulation • New technology • No action

27. Simple rulesfor allocating mechanisms to projects 1. No positive incentives for land-use change unless public net benefits of change are positive. 2. No positive incentives if landholders would adopt land-use changes without those incentives. 3. No positive incentives if overall costs outweigh overall benefits.

28. Simple public-private benefits framework Win/Small loss Win/Large loss Win/Win Small loss/Win Loss/Loss Large loss/Win Pannell (2008) Land Economics

29. 7. Other • Review proposed projects for accuracy, logic • Monitoring, learning, adaptation (uncertainty) • Training and support for decision makers • Incentives for environmental managers to pursue outcomes • Remove incentives that conflict with that

30. What vs How? Both • Be selective (what) • Outcomes (what and how) • All info (what) • Metric (what) • Scale (how) • Mechanism (how) • Logic (how)

31. Value for money from investment in environmental economics

32. Observations • Huge potential • Largely unrealised • We could do better • Apply economic principles to thinking about which economics research to do • Getting it across better

33. 1. Optimising portfolio of EE • Many information products to choose from: • non-market values • market values • human behaviour (e.g. adoption of new practices) • risk, uncertainty • environmental production functions • discount rates • time lags • costs curves • transaction costs • policy mechanism choice • mechanism design • metric design

34. Policy agencies as consumers • Optimal portfolio determined by • We should not concentrate on production of too few information products. • Produce enough of each product for an optimal consumption bundle.

35. Do we comply with that? • Some info products relatively well-supplied • non-market values • discount rates • Others much less so • costs vs scale • transaction costs • environmental production functions (effectiveness of management) • human behavioural responses to policy • metric design

36. 2. Optimise depth/sophistication • Fertilizer: maximum profit  maximum yield • Information: max net benefit maximum detail or sophistication (diminishing marginal benefits)

37. Approximate information might be optimal for decision making (depending on context) • Also more timely, less challenging

38. 3. Recognise users’ limitations • Most are not economists • Easily psyched out by economics • Another reason for simple information • Need help to see how to use economics information in their decisions – it’s not obvious • Training and support • Cultural change

39. INFFERInvestment Framework for Environmental Resources

40. INFFER • Addresses the identified common weaknesses • Outcome-oriented (works backwards) • Includes all key bio-physical and socio-economic variables • Theoretically sound metric to rank projects • Includes Public: Private Benefits Framework • Asks “consistency check” questions to get the logic right • Can cope with expert judgement or high-quality scientific information • Simplifications – usable by non-economists • Structured, documented, supported, training

41. River reach • Intact native veg • Cultural heritage • Woodland birds Asset types • Wetland • Listed on register • Last of its type • Fauna species • Flagship • Critically endangered • Native vegetation • Concentration of threatened species • Near pristine condition • Important location

44. Before INFFER After INFFER

45. Regional application

46. International application

47. Final comments • It’s possible to embed economics thinking in environmental organisations/agencies • Many challenges • Culture, timeliness, transaction costs, communications, aversion to the results, attitudes to economics • Enormous opportunities to deliver greater environmental outcomes – worth the effort • Keen to support a UK pilot of INFFER

48. inffer.org pannelldiscussions.net