1. Farm Viability: A Spatial Analysis Paul Kilgarriff, Teagasc, Athenry & N.C.G., Maynooth University Teagasc, Rural Economy and Development Programme (REDP) EAAE conference, Edinburgh, 23 rd October 2015 Co-authors: Prof. Cathal O’Donoghue, Dr Thia Hennessy, Ms. Mary Ryan, Dr. Emma Dillion, Mr. Stuart Green, Dr. Trevor Donnellan, Mr. Brian Moran, Teagasc. Dr Stephen Hynes, Dr. Eoin Grealis, NUI Galway. Dr. Niall Farrell, ESRI, Dr. Karyn Morrissey, University of Liverpool

2. Overview  Introduction  Indicators being used  Environmental  Economic  Social  Review of European Policy  Definition of Viability  Agricultural landscape in Ireland  Maps of Landscape  Results  Conclusions

3. Indicators  Indicators are quantitative measures against which farm sustainability performance can be assessed  The 1987 Brundtland Report “Our Common Future” defined sustainable development as “development which meets the needs of the present without compromising the ability of future generations to meet their own needs.”  We take three indicators from “Measuring Farm Level Sustainability with the Teagasc National Farm Survey” (2013)  One from three of the four groups of indicators: Economic, Environmental, Social and Innovation indicators

4. Sustainability Indicators – NFS (2013) TypeMesureUnit EnvironmentalIPCC estimate/farmTonnes CO2 equivalent/farm EnvironmentalIPCC estimate/kg of outputKg CO2 equivalent/kg output EnvironmentalRisk to water qualityKg N surplus/hectare EnvironmentalNitrogen use efficiency/productKg N surplus/unit product EnvironmentalCO2 equivalent/kg outputKg CO2 equivalent/kg output EconomicIncome per unpaid labour unit€/labour unit EconomicGross Output per hectare€/hectare EconomicMarket based Gross Margin per hectare€/hectare EconomicFarm is economically viable1=viable, 0=not viable EconomicOutput derived from the market% SocialFarm business is not viable - no off farm employmentBinary, 1=Yes, 0=No SocialEducational attainmentCount variable 1-5 SocialFarmer lives aloneBinary, 1=Yes, 0=No SocialFarmer is over 60 years of age and no household member is less than 45Binary, 1=Yes, 0=No SocialWork load of farmerHours worked on the farm

5. Sustainability Indicators – NFS (2013) TypeMesureUnit EnvironmentalIPCC estimate/farmTonnes CO2 equivalent/farm EnvironmentalIPCC estimate/kg of outputKg CO2 equivalent/kg output EnvironmentalRisk to water qualityKg N surplus/hectare EnvironmentalNitrogen use efficiency/productKg N surplus/unit product EnvironmentalCO2 equivalent/kg outputKg CO2 equivalent/kg output EconomicIncome per unpaid labour unit€/labour unit EconomicGross Output per hectare€/hectare EconomicMarket based Gross Margin per hectare€/hectare EconomicFarm is economically viable1=viable, 0=not viable EconomicOutput derived from the market% SocialFarm business is not viable - no off farm employmentBinary, 1=Yes, 0=No SocialEducational attainmentCount variable 1-5 SocialFarmer lives aloneBinary, 1=Yes, 0=No SocialFarmer is over 60 years of age and no household member is less than 45Binary, 1=Yes, 0=No SocialWork load of farmerHours worked on the farm

6. Economic Indicator  Taken from the concept of viability, see:  FRAWLEY, J. P. & COMMINS, P. 1996. The changing structure of Irish farming: trends and prospects, Teagasc Dublin.  HENNESSY, T. 2004. Projecting farm numbers. 2015 Agri- vision report. Irish Department of Agriculture and Food, Dublin, 82-96  Three classifications  Viable - remunerate family labour at the average agricultural wage, together with a return of 5 per cent on non-land assets  Sustainable - not viable, but have off-farm employment  Vulnerable – not viable or sustainable

7. Environmental Indicator  Nitrogen balance / use efficiency  Environmental Protection Agency, Water Framework Directive (EEC 2000)  Measure nitrogen content of rivers and lakes  Agriculture biggest contributor of nitrogen discharge  Directives such as the Nitrates Directive (91/676/EEC) are aimed at reducing pollution to groundwater and surface water as a result of nitrates from agriculture activities  Spreading animal slurry is only allowed during certain periods  Levels of organic nitrogen applied to land also limited  The directive aims to improve farming practices and prevent farmers from over intensive farming

8. Social Indicator  Isolation  Isolated Farmers  Living alone  Social consequences of living alone  Mental Health  Well-being amongst farmers  Generally a high age profile amongst farmers  Lack of a social life

9. European Policy  Common Agriculture Policy (CAP) - moving away from a primary focus on supporting agricultural production to have increased support for restructuring and diversification  Agenda 2000 - supporting the provision of environmental and social services and encouraging diversification of activities both on and off-farm  Luxembourg Agreement in 2003 - decoupling of income supports to be unrelated to production  As previously mentioned the Water Framework Directive and Nitrates Directive

10. Data Required  The distribution of agricultural activity and its economic impact  The relative contribution of farming and non-farming incomes within farm households and across other households  The environmental characteristics of agricultural activity (nitrogen use)  The distribution of demographic characteristics

11. Data  Farm data comes from the National Farm Survey (NFS), NUTS 3 level  Household Budget Survey (HBS), the Living in Ireland Survey (LII) and the Survey of Income and Living Conditions (SILC) contain the distribution of incomes, labour market and demographic characteristics, but again are only representative at the national level and with limited agricultural data  Census of Population Small Area Statistics contains spatially disaggregated data at the ED level  Nitrogen data at the river catchment level  Challenge bringing all data to the same geographic scale

12. Spatial Microsimulation  Creates spatially disaggregated micro data not previously available  Simulated Model of the Irish Local Economy (SMILE) model output used  Matches Census data with survey data using overlapping variables  We develop two separate models; one for farms and one for households  Link the National Farm Survey to the Census of Agriculture (SMILIONS)  Link micro household income data (the Living in Ireland Survey) with the Census of Population (SMILE)

13. Dataset  We have a dataset at the farm level with socioeconomic and demographic data linked to those farms at the ED level (3,440 EDs)  Measure of nitrogen, was at river catchment scale matched to EDs  SAPS 2011 at ED scale  Farm viability measure at farm level (simulated data)  Farm survey data from the NFS (1,200 representative farms)  All of these data sources are merged  The result socioeconomic and demographic data linked to farm level data – matched by NFS team, anonymised

14. Farming Landscape  There is significant spatial heterogeneity in Ireland  Better land in the South and East and the poorer land in the North and West  The most profitable sub-sectors within agriculture tend to be dairy and to some extent tillage farming which are predominantly concentrated in the South and East  The lower margin beef and sheep sectors are to a large extent located in the Midlands, North and West of the country  However in addition to the spatial heterogeneity in farm income sources, there is also significant heterogeneity in employment, types of employment and access to labour markets  The drystock sector (sheep and beef) tend to be more likely to have off-farm employment, whilst access to employment is likely to be higher in the south and east  It is important to understand this spatial heterogeneity to pattern target policy interventions.

15. Source: Modelling Farm Viability (2013)

20. Source: Rural Sustainability in Ireland: A Simulation Analysis (2012)

21. EPA Poor Water Quality Points Source: Rural Sustainability in Ireland: A Simulation Analysis (2012)

24. Results  Created deciles of measures  Viable Farms  Sustainable Farms  Vulnerable Farms  Organic Nitrogen per Hectare  Areas classified according to demographic, farm level, environmental and economic variables

25. Classification of areas - Viability  Areas with a high proportion of viable farms have a higher unemployment rate and lower employment rate  Lower levels of tertiary education  A higher population density  A lower old age deprivation rate but higher child deprivation rate  A higher stocking rate (livestock units per hectare)  Higher organic nitrogen usage per hectare  Higher river quality  Higher levels of equivalised disposable income

26. Classification of areas - Sustainability  Areas with a high proportion of sustainable farms have a higher unemployment rate and lower employment rate  Lower levels of tertiary education  A lower population density  A higher old age deprivation rate but lower child deprivation rate  A lower stocking rate (livestock units per hectare)  Lower organic nitrogen usage per hectare  Higher river quality  Lower levels of equivalised disposable income

27. Classification of areas - Vulnerability  Areas with a high proportion of sustainable farms have a higher unemployment rate and lower employment rate  Lower levels of tertiary education  A lower population density  A higher old age deprivation rate but lower child deprivation rate  A lower stocking rate (livestock units per hectare)  Lower organic nitrogen usage per hectare  Higher river quality  Lower levels of equivalised disposable income

28. Classification of areas – Organic Nitrogen  Areas with a high proportion of sustainable farms have a higher unemployment rate and lower employment rate  Lower levels of tertiary education  A lower population density  A lower old age deprivation rate but lower child deprivation rate  A higher stocking rate (livestock units per hectare), much higher  Lower river quality  Higher levels of viable farms  Higher levels of equivalised disposable income

29. Conclusions  Disaggregating to the farm level allows us to add a spatial element to inform not only national policy but local policy  Farm viability classification system allows for more focused analysis  Obvious differences in the areas in which the various farm types are located  Not only farm level differences but demographic, economic and environmental  Possibility to examine other local specific factors and whether there are clear contrasts