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Input Requirement Estimations

Input Requirement Estimations. Estimating Input Requirements using FADN Data Stephan Pfaffenzeller, NUI, Galway. Objective. To Estimate Intput Requirement Coefficients for Each CAPRI Activity for insertion into the CAPRI database. Data. FADN DATA from 1990-1999 AT - Austria - 2451 farms

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Input Requirement Estimations

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  1. Input Requirement Estimations Estimating Input Requirements using FADN DataStephan Pfaffenzeller, NUI, Galway

  2. Objective • To Estimate Intput Requirement Coefficients for Each CAPRI Activity for insertion into the CAPRI database.

  3. Data • FADN DATA from1990-1999 • AT - Austria - 2451 farms • BL - Belgium, 2601 farms • DE - Germany, 15110 farms --> price data from ‘91-’99 • DK - Denmark, 6625 farms • EL - Greece, 11877 farms --> price data from ‘95-’99 • FI - Finland, 1324 farms • IR - Ireland, 3409 farms --> no price data prior to 1995

  4. Data • FADN DATA from1990-1999 • IT - Italy, 57264 farms • PT - Portugal, 6379 farms • SE - Sweden, 1191 farms • UK - United Kingdom, 6668 farms • ES - Spain, 22609 farms • NL - Netherlands • FR - France

  5. Variables • I: CAPRI INPUTS • L: CAPRI LEVELS (hect./head) • Y: CAPRI YIELDS (tonnes p/h etc.) • O: CAPRI OUTPUTS (tonnes, litres etc.) • 11 Input Variables • 53 Level Variables and 53 Output/Yield Variables in Full Model

  6. Model (for Any One Input) Basic specification • i is the farm i.d., t the year, L are Relevant Level Values

  7. Model (for Any One Input) Alternative specification I • i is the farm i.d., t the year, L are Relevant Level Values and O are Output Values

  8. Model (for Any One Input) Alternative specification II • i is the farm i.d., t the year, L are Relevant Level Values and Y are Yield Values

  9. Choice of Estimator • SUR eliminated (not feasible – problems last summer with SUR estimation) • Choice between OLS, FE and RE for each model • Preliminary Tests revealed FE was far superior: decided to be consistent

  10. Results • Generally good (pending final evaluation of specifications) • Problems with Negative coefficient estimates in some cases • Fitted values need to be reconciled with EAA

  11. Negative Coefficients • These problems are mainly with the OTHER categories of activities/inputs (OFRU, OCRO, OANI etc.). • The chosen solution is to use the average coefficient from the relevant activity category (e.g. the Fruit Average if OFRU is negative)

  12. Selected Results

  13. Level Coefficient Estimates bL estimates for selected Crop activity levels:

  14. Level Coefficient Estimates bL estimates for selected animal activity levels:

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