1. Fødevareøkonomisk Institut EU dairy policy analysis: Exploring the importance of quota rent estimates By Research Fellow Chantal Pohl Nielsen

2. Fødevareøkonomisk Institut Why dairy ? Why quota rents ? Dairy remains one of the most protected sectors in the EU – Price support, intervention purchases, production quotas, import tariffs, TRQs, domestic consumption and export subsidies The EU is a dominant player on world dairy markets – 36% of production – 27% of exports – 14% of imports 2003 CAP reform fine-tunes the dairy policy – Fast-tracking certain price cuts, limiting intervention purchases, decoupling compensatory payments – Production quotas prolonged until 2014/15

3. Fødevareøkonomisk Institut Objective To discuss the level of milk quota rents in the EU – What are the correct estimates for the individual EU member countries? – What are the underlying assumptions re. e.g. farmers’ expectations? To illustrate the impact of using different initial quota rents when analysing EU dairy policy reform using CGE models and to stress the importance of recognising EU heterogeneity To emphasise the need for further data work

4. Fødevareøkonomisk Institut Binding production quotas generate rents

5. Fødevareøkonomisk Institut Binding production quotas generate rents – but how large?

6. Fødevareøkonomisk Institut Problem of unobservable marginal cost curves Determining the size of quota rents amounts to determining whether a country is capable of competing (unsupported) on world markets Analytical, we’re trying to determine the position of a country’s supply curve in an unregulated market, i.e. unobservable. Approaches taken in the literature: Direct: Estimates of marginal costs using farm accounts Indirect: Quota prices (rent or lease) supplemented by assumptions about the annual value of quota - Which real interest rate ? Length of depreciation time ? Farmers’ expectations re. future compensation ?  All important assumptions – with implications for the evaluation of the effects of dairy policy reform

7. Fødevareøkonomisk Institut The Danish case…

8. Fødevareøkonomisk Institut The Danish quota value, % of producer price Depreciation time, years Real interest rate, pct. Value of Danish Quota, % of producer price

9. Fødevareøkonomisk Institut Value of Danish Quota, % of producer price Depreciation time, years Real interest rate, pct. Guyomard (2002) Jansson (2002)Jensen og Frandsen (2003) The Danish quota value, % of producer price

10. Fødevareøkonomisk Institut Different estimates 1. Guyomard et al. (2002): Use EC Farm Accountancy Data Network (FADN) to estimate marg. costs but not entirely clear how. Quota rents: 15-49%. DK: 42% 2. Jansson (2002): Depreciation time: 8 years, real interest rate: 6% == > quota rent = 22% of milk price 3. Jensen & Frandsen (2003): Depreciation: infinite, real interest: 4% == > quota rent = 5% of milk price Depreciation time reflects farmers’ expectations High quota rents: No compensation for policy changes Low quota rents: Compensation for future policy change

11. Fødevareøkonomisk Institut Substantial EU-15 differences...

12. Fødevareøkonomisk Institut Quota rents, EU-15, 2001 Source: Jensen & Frandsen (2003) % of producer price

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14. Illustrative simulations To illustrate the impact of using different initial quota rents when analysing EU dairy policy reform using CGE models To stress the importance of recognising EU heterogeneity Starting point is standard GTAP model and database (v 6.2) Four different adjusted databases o “Small” (Jensen and Frandsen) and “large” (Guyomard) quota rents o EU-15 as a single region and EU-15 disaggregated Simulation eliminates EU dairy export subsidies

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18. Effects on third countries Exports increase substantially USA: 20-24% Canada: 27-19% Australia: 22-25% New Zealand: 11-12% Using large or small initial quota rents -> differences in results between 0.5 and 1 %-points

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21. Preliminary findings Initial quota rent estimates/assumptions influence results Magnitude of change in production, exports and welfare Both at EU aggregate level and for individual countries Influence on 3 rd country results is less significant Ranking of initial quota rents is important for results Important to discuss relative competitiveness among EU-15

22. Fødevareøkonomisk Institut Future work National quota rent estimates (reliable marginal cost estimates and/or milk quota prices) Relative competitiveness of EU15 (primary and processing) => Survey initiated among agri-economic researchers in the EU Disaggregate GTAP dairy sector into categories such as butter, cheese, SMP, WMP, and other dairy products => Possibilities of collaboration with Trinity College, Dublin Integration of full set of dairy policy instruments in models Include rest of CAP in model, incl. EU budget and interregional transfers, accession of new member states, etc. Baseline / update databases (dairy sector competitiveness depends on changes in factor markets, technology, policy, etc.)