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Economic Joint Venture Model Progress Summary

A summary of progress on the Economic Joint Venture model by Graeme Doole and Alvaro Romera. The project evaluates the impacts of setting water quality objectives, with a focus on credibility and partnerships. It includes stages, aims, and results from catchment modeling to economic implications. The model assesses diverse biophysical resources and land types in the Waikato region to estimate economic implications of water quality targets.

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Economic Joint Venture Model Progress Summary

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  1. Economic Joint Venture model: summary of progress Graeme Doole Alvaro Romera Technical Leaders Group DairyNZ (presenting)

  2. Economic Joint Venture

  3. Waikato Economic Joint Venture Project • Commissioned a series of studies to evaluate potential impacts of setting water quality objectives and limits. • Key partners were Central Government, DairyNZ, WRC, and WRA. Focus on credibilityof process and assumptions. Background • Considered environmental, economic, social, and cultural costs and benefits across all direct market values (e.g. agriculture) and non-market values (e.g. recreation) of fresh water. Assessing ‘impacts’ • Support policy making by Central Government, Regional Council, and community. • Develop methods to support the Healthy Rivers Plan Change. • Build genuine partnerships. Purpose

  4. Work streams within Joint Venture • Non-market values • Cultural values • Farm modelling • Catchment modelling (hydrological) • Catchment modelling (economic) Understand both benefits and cost of improved water quality

  5. Aims of EJV modelling work Primary aim: • Provide a model to allow potential economic implications of targets to be estimated Secondary aims: • Establish early collaboration • Provide foundation for extension, if required Generate scenarios only to test model.

  6. Economic Joint Venture: Stage 1 • Focus on UW catchment • Completed Sep 2013 • Public release Aug 2014 • Multiple work streams • Economic modelling • Central Gov. focus • Evaluate NOF approach

  7. Economic Joint Venture: Stage 2 • Entire catchment focus • Develop economic model • Broad data collection • Focus on N and P • Scenarios to test model

  8. Model

  9. Distribution of land type Catchment consists of zones based on biophysical resources and land types Cost curves Farm-level information relates cost of mitigation and resultant change in pollutant(s) in each land type Identify profit and production implications of different limits on pollutant(s) Economic modelling

  10. Biophysical resources • Land use diversity • Farm diversity • Climate • Soils • Intensity • Subcatchments • Hydrological network

  11. Land use in Waikato (~1.1 m ha) N: 2.5 kg/ha P: 0.4 kg/ha N: 34.0 kg/ha P: 1.3 kg/ha N: 3.0 kg/ha P: 0.3 kg/ha N: 66.0 kg/ha P: 1.2 kg/ha N: 11.0 kg/ha P: 0.8 kg/ha

  12. Representative enterprises 26 Dairy platforms 10 Dairy support blocks 4 Sheep & beef types 3 Horticulture farms 66 Forestry types 20 Point sources

  13. Example: costs for UW dairy farms • Farm information is important • Profit vs N relationships • Diversity within industries • Diversity across industries

  14. Model output Goal to achieve targets at least cost on-farm Land management • Intensity • Mitigation • Land use Implications for production Implications for profit

  15. Reasons for adopting this framework • Approach is broadly used (policy and publication) • Integrates many sides of the conversation • Deal with multiple contaminants • Provides key outputs (e.g. cost, production) • Part of the puzzle (e.g. SIA, CGE)

  16. Illustrative scenarios • Reductions in N load at catchment level: • 10% • 20% • 30% • Land use change not in main scenario • Key outputs: • Cost • Production • Mitigations

  17. Illustrative results

  18. Impact of N targets on production • Limits of 10, 20, & 30% • Across whole catchment • Dairy does most • Lamb and beef robust • Point sources used for 30% limit (50% red.) • What can we attain with no land-use change?

  19. Impact of N targets on dairy mitigation • Production decline observed • Stand-off used increasingly • Reductions in production intensity • Stocking rate • Supplement • N fertiliser

  20. Story changes with land-use change Without land-use change • Increased flexibility impacts production • Large movement out of sheep and beef • Large increase in timber production • Social impact • Lack of cost-effective on-farm mitigations for nitrogen With land-use change

  21. Impact of N targets on profit Cost in dollar terms • High cost in Upper Waikato and Waipa • Mitigation ranges from 26%-34% for 30% limit • Point source cost is $37m for 30% limit • Effect of site-specific targets? Cost in % terms

  22. Caveats • Assume perfect information • Assume no frictions • Assume current profit relativities persist • Omission of policy mechanism to achieve targets • Omission of technology change • Omission of change in land value • Omission of flow-on costs to region

  23. Existing limitations of model • Limited representation of P mitigations • No inclusion of E. coli • No inclusion of sediment • No inclusion of hydrology in Phase 2 model

  24. Questions?

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