Systems Approach to the Economic Impact of Technical Performance in the Sheep Sector

This paper investigates the structure and characteristics of the full distribution of sheep farms achieving various levels of financial and technical performance. Analysing data from the Irish panel dataset, the Teagasc National Farm Survey (NFS) shows Irish sheep farms exhibit relatively low level of technical performance and that on-farm technical advances have been stagnant over the past 20 years. NFS data files not previously manipulated for research purposes are used to capture monthly animal data flows for the full sample of NFS sheep farms for the 3 year period 2008 – 2010. Utilising this data we identify and analyse key flock performance indicators including reproduction, mortality rates. These “Livestock Demographic” variables are important indicators for estimating and modelling flock dynamics and production, combining two drivers of flock performance: the biological characteristics of the stock on the farm and the farmers’ flock management practices. Results indicate the potential impacts on farm output and gross margins of improved animal performance which is achievable through specific technology adoptions

Measuring GHG Emissions Across the Agri‐Food Sector Value Chain: The Development of a Bioeconomy Input‐Output Model

Increasing food production to meet rising global demand while minimising negative environmental impacts such as agricultural greenhouse gas (GHG) emissions is one of the greatest challenges facing the agri‐food sector. Sustainable food production relates not only to primary production, but also has wider value chain implications. Aninput‐output (IO) model is a modelling framework which contains information on the flow of goods and services across a value chain at a regional or national economy level. This paper provides a detailed description of the development of a Bioeconomy IO (BIO) model which is disaggregated across the subs‐sectors of the agri‐food valuechain and environmentally extended (EE) to examine environmental outputs, including GHG emissions, We focus on Ireland, where emissions from agriculture comprise 33% of national GHG emissions and where there has been a major expansion and transformation in agriculture supported by national and EU policy. In a substantial Annex to this paper, we describe the modelling assumptions made in developing the BIO model. Breaking up the value chain into components, we find that most value is generated at the processing stage of the value chain, with greaterprocessing value in more sophisticated value chains such as dairy processing. On the other hand, emissions are in general highest in primary production, albeit emissions from purchased animal feed are higher for poultry than for other value chains, given the lower animal based emissions from poultry than from cows or sheep. The level ofdisaggregation also shows that the sub‐sectors are themselves discrete value chains. The analysis highlights that emissions per unit of output are much higher for beef and sheep meat value chains than for pig and poultry. The analysis facilitated by the BIO model also allows for the mapping of emissions along the agri‐food value chain using the adapted IO EE approach. Such analysis is valuable in identifying emissions ‘hot‐spots’ along the value chains and analysing potential avenues for emission efficiencies

MEASURING GHG EMISSIONS ACROSS THE AGRI-FOOD SECTOR VALUE CHAIN: THE DEVELOPMENT OF BIO - A BIO-ECONOMY INPUT-OUTPUT MODEL

peer-reviewedSustainable intensification is one of the greatest challenges facing the agri-food sector which needs to produce more food to meet increasing global demand, while minimising negative environmental impacts such as agricultural greenhouse gas (GHG) emissions. Sustainable intensification relates not just to primary production, but also has wider value chain implications. An input-output model is a modelling framework which contains the flows across a value chain within a country. Input-output (IO) models have been disaggregated to have finer granular detail in relation to agricultural sub-sectoral value chains. National IO models with limited agricultural disaggregation have been developed to look at carbon footprints and within agriculture to look at the carbon footprint of specific value chains. In this paper we adapt an agriculturally disaggregated IO model to analyse the source of emissions in different components of agri-food value chains. We focus on Ireland, where emissions from agriculture comprise nearly 30% of national emissions and where there has been a major expansion and transformation in agriculture since the abolition of milk quota restrictions. In a substantial Annex to this paper, we describe the modelling assumptions made in developing this model. Breaking up the value chain into components, we find that most value is generated at the processing stage of the value chain, with greater processing value in more sophisticated value chains such as dairy processing. On the other hand, emissions are in general highest in primary production, albeit emissions from purchased animal feed being higher for poultry than for other value chains, given the lower direct emissions from poultry than from ruminants or sheep. The analysis highlights that emissions per unit of output are much higher for beef and sheep meat value chains than for pig and poultry meat value chains

What Does Ecological Farming Mean for Farm Labour?

Summary: Ecological farming, such as organic and low‐input farming, is gaining popularity in the public discourse. One question is how this type of farming may impact farm labour from a socio‐economic point of view. The article first discusses how low‐input farming practices (i.e. with lower reliance on inputs derived from fossil fuels) may affect the economic returns to labour, measured as the farm’s revenue per hour of labour input, on data from the Farm Accountancy Data Network (FADN) in 2004‐‐2015 for four European countries. Returns to labour appear to be highest at the two extremes – very low‐input farms and highly intensive farms. Farms in the low‐input end of the spectrum are in the minority, while the overwhelming majority of farms are intensive and have internal economic incentives to intensify further. The article also analyses how working conditions differ between organic and conventional dairy farms in two European countries based on interviews with farmers in 2019. Results show that all dimensions of working conditions are affected by being an organic farm or not, but this is not the only factor. There are many influences on working conditions, such as the production context and workforce composition

What Does Ecological Farming Mean for Farm Labour?

Summary: Ecological farming, such as organic and low‐input farming, is gaining popularity in the public discourse. One question is how this type of farming may impact farm labour from a socio‐economic point of view. The article first discusses how low‐input farming practices (i.e. with lower reliance on inputs derived from fossil fuels) may affect the economic returns to labour, measured as the farm’s revenue per hour of labour input, on data from the Farm Accountancy Data Network (FADN) in 2004‐‐2015 for four European countries. Returns to labour appear to be highest at the two extremes – very low‐input farms and highly intensive farms. Farms in the low‐input end of the spectrum are in the minority, while the overwhelming majority of farms are intensive and have internal economic incentives to intensify further. The article also analyses how working conditions differ between organic and conventional dairy farms in two European countries based on interviews with farmers in 2019. Results show that all dimensions of working conditions are affected by being an organic farm or not, but this is not the only factor. There are many influences on working conditions, such as the production context and workforce composition

Integrated assessment of sheep production systems and the agricultural value chain

This thesis describes the development of an integrated, farm level, bioeconomic systems model of Irish sheep production using nationally representative data from the National Farm Survey (NFS). A systems approach is applied to develop three sub-model components which enable an integrated assessment of the impact of policy reform and farm management practice on the financial, technical and environmental performance of Irish sheep farms. The framework is bioeconomic in that, alongside financial analysis it seeks to capture the biophysical attributes of livestock and crops and the variability in farm environmental conditions that are an inherent feature of agriculture production systems. The framework is subsequently applied to provide input to the Irish Bioeconomy Input-Output model (BIO) in order to simulate the economy wide economic and environmental impact of achieving Food Wise 2025 (FW 2025) National policy objectives in terms of economic output, and greenhouse gas (GHG) emissions. This systems approach, using NFS data, enables the disaggregation of the agriculture sector and the extension of I-O tables to an environmental account of GHG emissions. It is proposed that the linking of micro and macro analysis is necessary for integrated systems assessment in the context of national policy, which straddles both farm level production targets and national macroeconomic targets. A number of economic models of production are specified to analyse the distribution in technical management performance and associated financial performance across the distribution of sheep farms and to examine the farm level effects of a policy reform. In the context of the growing emphasis on production efficiency per unit output, as promoted by recent EU Common Agriculture Policy (CAP) reform, World Trade Organisation (WTO) agreements, and international climate change legislation, Chapter 2 describes the “Animal Nutrition” component of the systems model. This is applied to assess the impact of flock nutrition management practices on financial and technical performance across all sheep farms. Results from a single equation econometric input demand model finds concentrate demand on Irish sheep farms to be elastic and thus sensitive to price changes. A second model specification indicates the presence of spatially heterogeneous effects of lambing date on concentrate demand across regions. Chapter 3 describes the ‘animal demographics’ subcomponent which is applied to estimate the impact of an improved efficiency simulation on farm income. Results indicate the potential impacts on farm output and gross margins for a series of improved animal performance scenarios which are achievable through specific technology adoptions and which are in-line with national policy objections for the sector as set down under Food Harvest 2020 (FH 2020). Chapter 4 describes the ‘environmental component’ of the model by performing a Life Cycle Assessment (LCA) of Irish sheep farms to account for GHG emissions and land occupation. Results provide an estimate of the farm level carbon footprint and land occupation of sheep farms. The distribution in performance witnessed across farms points towards higher technical performance and increased production intensity as a means of mitigating GHG emissions from sheep production systems. This is in line with previous `hypothetical’ or average production systems LCAs for Ireland. Chapter 5 takes data generated from the systems model developed previously and scales results to be representative at the national economy level. This information is used as input to the Bioeconomy Input-Output (BIO) model for Ireland, adapted here to simulate the environmental and economic impacts of meeting FW 2025 growth targets. This is achieved through an extension of the BIO model to include an environmental account of GHG emissions and land occupation. In the context of potentially conflicting economic and environmental policies for Irish Agriculture, a scenario analysis is undertaken which assesses the potential increase in GHG emissions arising from the achievement of agriculture sector expansion plans. This thesis informs the current production literature through an analysis of the full distribution of Irish sheep producers. Detailed farm level production data not previously used in applied economic research provides information here on animal and crop performance, and the technical proficiency and management choices of the range of producers. This new information illuminates the management behaviour of these agents in response to policy and environmental stimulus. This provides a unique contribution to knowledge by establishing a framework under which the economic and environmental impacts of policy and farm management for the full distribution of sheep farms can be assessed. Unlike previous systems models applied to Irish agriculture, which modelled `representative’, average farms or `hypothetical’ farms based on experiment from research farms, this thesis models actual farms. Using NFS data means results are representative of the national population of farms and inference can be made on distribution of performance taking account of site specific environmental and agronomic conditions. Furthermore, results can be scaled to the national level to incorporate an integrated assessment of the impact of policy shocks on economic and environmental outputs across the entire value chain from `cradle to grave’

Policies to reduce GHG emissions from agriculture, their implications for agricultural activity levels and land use decisions in Ireland

To prevent the most damaging effects of climate change, the Intergovernmental Panel on Climate Change (IPCC) have identified the need to limit the rise in the global average temperature to 1.5°C above pre-industrial levels. In support of the goal of climate change mitigation, Ireland’s Climate Action Plan has set a goal of reducing overall greenhouse gas emissions by 2030 and setting us on a path to reach net-zero emissions by 2050. As part of the plan the agriculture sector has been set of 25% reduction target relative to 2018. This paper utilises the CAPRI model to evaluate the effect of a hypothetical €100 carbon tax on non-CO2 emissions for agricultural. Results revealed that under a €100 carbon tax, overall GHG emissions would decrease in large part due to a decrease in beef meat activities, which is along with the dairy sector the dominant source of methane emissions in Irish agriculture. Average agricultural income would be projected to increase due to less profitable production exiting under carbon tax and price. A significant increase in the area of set aside and fallow land is also observed, which leads to a reduction in agricultural land and can be used for an increase in afforestation

Systems Approach to the Economic Impact of Technical Performance in the Sheep Sector

This paper investigates the structure and characteristics of the full distribution of sheep farms achieving various levels of financial and technical performance. Analysing data from the Irish panel dataset, the Teagasc National Farm Survey (NFS) shows Irish sheep farms exhibit relatively low level of technical performance and that on-farm technical advances have been stagnant over the past 20 years. NFS data files not previously manipulated for research purposes are used to capture monthly animal data flows for the full sample of NFS sheep farms for the 3 year period 2008 – 2010. Utilising this data we identify and analyse key flock performance indicators including reproduction, mortality rates. These “Livestock Demographic” variables are important indicators for estimating and modelling flock dynamics and production, combining two drivers of flock performance: the biological characteristics of the stock on the farm and the farmers’ flock management practices. Results indicate the potential impacts on farm output and gross margins of improved animal performance which is achievable through specific technology adoptions

Economic factors affecting concentrate usage on Irish sheep farms

While comprehensive farm level models for the dairy, beef and cereal sectors have previously been developed, to date, relatively little research has been conducted on the economics of the sheep sector at farm level. Nationally representative farm level data from Teagasc’s National Farm Survey (NFS) is used to develop a model examining the economic factors of concentrate usage on Irish sheep farms informed by the current body of literature on pastoral based production systems research. Results from a 2 step random effects panel regression of a demand function for concentrate use with log linear functional form support the established production literature. The demand for concentrates on Irish sheep farms was found to be elastic and thus sensitive to price changes. Farm labour input, fertiliser application, subscription to an extension and research provider and date of lambing were found to be significantly associated with concentrate demand on sheep enterprises. Results from a second model specification indicate the presence of spatially heterogeneous effects of lambing on concentrate demand across regions