Economics of farmer early retirement policy

We estimate the structural effects, costs and potential efficiency gains that might arise from the introduction of an Early Retirement Scheme for farmers in Northern Ireland using data from the Farm Business Survey and a separate survey of 350 farmers aged between 50 and 65. Modelling results suggest that farm scale is a significant determinant of profit per hectare but that operator age is not. The economic gains from releasing land through a Scheme were conditional on transfers bringing about significant farm expansion and changes in land use. When these conditions were satisfied pensions payments of only about one-third the statutory maximum could be justified. Survey responses indicated that participation in the Scheme would bring forward farmers' retirement age by an average of four years. Moreover, 'deadweight' payments would equate to about 23 per cent of potential total expenditure. Overall, the economic case for the introduction of an Early Retirement Scheme to Northern Ireland is judged to be weak

AD|ARC (Administrative Data | Agricultural Research Collection): Linking individual, household and farm business data for agricultural research – Challenges of linking agricultural datasets with individual-level records

Objectives To create an anonymised research-ready data resource of farm households in the UK to generate evidence to support policy development, implementation and evaluation; improve understanding of farm family socio-economic characteristics; and assist stakeholders interested in understanding the health and well-being, resilience and prosperity and spatial properties of farming communities. Methods The ADARC research-ready data resource is being created in each nation of the UK. Each core dataset links agricultural datasets with individual- and household-level population data from the Census 2011. The farm business data is drawn from a number of sources (the Inter Departmental Business Register, EU Farm Structure Survey 2010 and Rural Payments data), which presented many data preparation challenges when linking to the Census of Population. Each core dataset will be linked to the health and education data available for that nation. Where possible, the ADARC datasets have been harmonised to allow federated querying across the UK. Results The ADARC core datasets are complete in Wales and near completion in England and Scotland. Work is also well advanced in Northern Ireland. To the best of our knowledge, these are the first datasets linking agricultural data to individual- and household-level data at a population level. We will report the challenges experienced in linking farm business data with data at the household and individual level. This will include a description of the data preparation steps, the challenges encountered and solutions utilised at each stage of building this complex dataset from numerous, very different ‘parent’ datasets. The structure and content of the core datasets will be presented as well as the potential benefits to researchers investigating the individual, household and community dimensions of agricultural research. Conclusion Agriculture is currently facing a range of challenges with little known about the impact on farmers and farming households. ADARC introduces a new, powerful and versatile resource that will help inform debate and potentially lead to better outcomes on a range of issues relevant to farmers and farming communities

Unpacking Total Factor Productivity on Dairy Farms using Empirical Evidence

Publication history: Accepted - 31 January 2022; Published online - 4 February 2022This study examines the farm-level factors that influence differences in total factor productivity (TFP) on dairy farms. To this end, a fixed-effects regression approach is applied to panel data for dairy farms obtained from the Farm Accountancy Data Network for Northern Ireland over the period of 2005 to 2016. The findings are largely consistent with existing empirical evidence, showing that herd size, milk yield, stocking density, and share of hired labour have a positive and statistically significant impact on TFP, while labour input per cow, purchased feed input per cow, and share of direct payments in total farm output have a negative and statistically significant impact. The more complex relationships, namely age, education, and investment, have been unpacked using interaction terms and nonlinear approximation. The impact of age is negative, and the drag on productivity grows as age increases. Capital investment and education both have a positive impact on farm-level TFP, as well as on their interaction. Policy recommendations on strategies and best practices to help dairy farms tackle productivity constraints are suggestedThis research was undertaken as part of the Northern Ireland Department of Agriculture, Environment and Rural Affairs Evidence and Innovation Programme [E&I 17/2/04—Productivity growth in the Dairy sector in Northern Ireland: Trends and drivers]

The economic impact of BSE: a regional perspective

A regional input-output model, detailing agriculture and its ancillary sectors, is used to quantify the effects of a BSE-induced reduction in final demand for beef on the economy of Northern Ireland, a region with heavy dependence on beef exports. The long-run regional output, income and employment effects are estimated assuming no market stabilization measures and taking account of substitution effects in final demand. Predicted net losses in regional income are 0.5% of regional GDP with job losses of up to 0.6% of regional employment. About 77% of the income losses and 87% of the job losses are in the beef sector, primarily beef production. Compensating gains due to demand substitution effects occur mainly in meat processing sectors, other than beef, and are relatively small. Adverse intra-regional distributional effects are likely due to the concentration of beef production in the more disadvantaged areas. The importance of appropriate policy responses is highlighted.