1. ICON-Institute Public Sector1 Overview of experiences in Slovenia and Hungary Riga, 19-20 July 2007 Transition Facility Statistical Cooperation Programme 2005 LOT 2 – Pesticide Indicators

2. ICON-Institute Public Sector2 General features about agriculture/wheat  Hungary (Eurostat data) → UAA: 4.4 M ha, 70% of total land area 2003 → arable land 80% UAA (3.6M ha), of which 0.95M ha for wheat (20% of UAA) → arable land 80% UAA (3.6M ha), of which 0.95M ha for wheat (20% of UAA)  Slovenia (Eurostat / SI data) → UAA: 0.5 M ha, 25% of total land area → 34% UAA is arable land, of which 35 000 ha for wheat (7% of UAA)

3. ICON-Institute Public Sector3 Involved parties  Hungary → Statistical Office (KSH) Environmental Section → Ministry of Agriculture and Rural Development → Plant Protection Service (Inspectors)  Slovenia → Statistical Office (SORS) → Phitosanitary Administration → Agricultural Institute of SI → Chamber of Agriculture and Forestry of SI (Inspectors)

4. ICON-Institute Public Sector4 Pesticide use  Hungary → 248 registered PPPs for wheat, out of 742 authorised products → 0.2 kg/ha a.s (2003): 56% fungicides, 32.5% herbicides, 11.5% others  Slovenia: → 80 registered PPPs for wheat → 0.6 kg/ha a.s.: 27% fungicides, 72% herbicides, 2% others

5. ICON-Institute Public Sector5 Sampling frame  Hungary →Farm register (from Agricultural Census 2000), partially updated via FSS 2003 and 2005 (15%)  Slovenia → Farm register (from the Census 2000), partially updated via FSS 2005 and 2007

6. ICON-Institute Public Sector6 Sampling error  Hungary → not specified  Slovenia → coefficient of variation: 0.89% for wheat and <1% for the other main agricultural products

7. ICON-Institute Public Sector7 Sample unit  Hungary → farm, survey information is filled in at parcel level but calculations are then made at farm level  Slovenia → parcel but there is possibility to provide data at farm level also if detailed info does not exist

8. ICON-Institute Public Sector8 Sample size  Hungary → 12 000 wheat producers (2 858 enterprises,9 546 private farms) → 200 enterprises and 580 private farms : 780 units selected  Slovenia → 5 000 farms cultivating wheat in the FSS sample → 2 800 family farms plus 100 enterprises selected (20% of area growing wheat)

9. ICON-Institute Public Sector9 Sample stratification  Hungary → 60 strata : 3 size classes for the 20 counties (NUTS2): <5 ha 5-100 ha >100 ha  Slovenia → 4 strata: <50 ha (12% of wheat farms / 40% of wheat area) 50-<100 ha (27% / 30%) 100-250 ha (41% / 25%) >250 ha (20% / 6 %)

10. ICON-Institute Public Sector10 Sample selection  Hungary → 780 units correspond to the maximum number of units given budget constraints (exists also a substitute list)  Slovenia → 2 900 units defined in line with budget constraints Optimisation method rather than pure result of sample

11. ICON-Institute Public Sector11 Survey type  Hungary → 780 surveys carried out by electronic questionnaire : e-mail for the 200 enterprises and 580 interviews by 25 PPP inspectors (with lap-tops) → substitute list used to achieve 100% response → high quality responses (trained inspectors, involved in 2005 survey)  Slovenia: → 200 farms : face-to-face interviews (PAPI) by 40 advisors from the Agricultural Advisory Services (Chamber of Agriculture and Forestry) → good response rate (+/- 100%), high quality

12. ICON-Institute Public Sector12 Survey type (cont.)  Hungary  Slovenia: → 1 350 farms : postal surveys (POST) with instructions → relatively small response rate but good quality responses

13. ICON-Institute Public Sector13 Survey type (cont.)  Hungary  Slovenia: → 1 350 farms interviewed by telephone (CATI) by students → high level of responses but more errors than the other 2 methods

14. ICON-Institute Public Sector14 Survey type (cont.)  Hungary  Slovenia: → no computer- assisted face-to-face interviews → no survey by email

15. ICON-Institute Public Sector15 Survey planning  Hungary → original plan: start in June, delayed to summer → early results in September → processing eased by several checks directly when entering the data (application rate min.- max., treated area, application date etc.)  Slovenia: → start in October → early results by year end → processing eased by several checks directly when entering the data (application rate, farmers contact details etc.)

16. ICON-Institute Public Sector16 Objectives/Future plans  Hungary → nothing concrete foreseen for future → though, exists a demand for such statistics (e.g. risk)  Slovenia: → long-term vision → survey every 2 years (crop rotation) → exists also demand for such statistics (e.g. risk)