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Animal welfare provision by dairy farmers has implications that go well beyond the individual dairy farm. In this study, we assess dairy farmers' willingness to pay to support a policy aimed at improving calf welfare and link this to altruism. We conceptualise the farmer's decision into private reasons, and motivations to improve animal welfare on their own farm or eliminate bad practices elsewhere. Our data comes from a survey with over 400 Irish dairy farmers that included an experimental component. Specifically, we used a contingent valuation referendum method to elicit farmers' willingness to pay. We measured altruism with a financially incentivised social value orientation scale. Our findings indicate that most farmers are supportive of a policy scheme to improve animal welfare, and altruism is positively associated with higher willingness to pay. Specifically, our findings suggest that altruists are willing to pay €429 per annum, while individualistically minded farmers are willing to pay €220 per annum to support the new initiative. Our findings have important policy implications as we show that the majority of farmers are willing to financially support the implementation of a policy that can help to prevent public bads.

There is a considerable literature about the adoption of organic farming. However, possible abandonment of organic farming has received scant attention. Thus, relatively little is known about the exit decisions of farmers. In addition, most studies are based on a static framework where it is not possible to account for changes in farmer decisions over time. This article attempts to fill this gap in the literature by investigating the determinants that affect both adoption and abandonment of organic drystock farming over time. The use of duration analysis allows for the consideration of cross-sectional and time-varying factors over the study period from 1981 to 2008. Using this dynamic econometric framework revealed a significant time effect on entry and exit decisions. Overall, the results highlight that where no attempt is made to account for exit decisions and time effects, important information about sustainable farmer decisions may not be taken into consideration.

The EU milk quota abolition initiated considerable restructuring in the EU dairy sector. Ireland is one of the countries that experienced significant growth, which has led to changes in farm labour demand. This PhD thesis aims to assess the role of family and hired labour, and automation in enhancing the efficiency of farms in an evolving dairy sector. Based on farm-level panel data sets from 2000 to 2019, and a cross-section supplementary data in 2018, the thesis presents three analyses of farm labour and productivity on Irish dairy farms. The first analysis explores the effect of hired labour on farms' technical efficiency (TE). Using a state-of-the-art stochastic frontier model that controls for endogeneity between inputs and TE, the findings reveal that hired labour positively affects farms' TE, improving dairy production. The findings suggest that the positive effect of hired labour on TE is marginally higher for smaller farms. The second analysis examines the role of automation in the efficiency of Irish dairy farms. A latent class stochastic frontier model is used to jointly estimate TE scores and identify two latent classes of farms utilising different technologies in their production, i.e., smaller, less intensive, and larger, more intensive farms. The results show that automated technologies (i.e., automatic parlour feeders, cluster removers, and scrapers) have heterogeneous effects on farms TE. Specifically, automated cluster removers and scrapers are correlated with higher TE scores in the smaller, less-intensive farms. Automated parlour feeders positively correlate to the TE of the larger-more-intensive farms. The third analysis focuses on estimating the shadow wage of family labour and assesses its role in the demand for hired labour on the farm. A two-step structural production function approach is used to estimate unpaid family labour shadow wage, and a semi-parametric censored dependent variable data model is applied to explore the role of shadow wages on hired labour demand. The findings show that as the size of the farm increase, so does the family labour shadow wage. Moreover, the results indicate positive returns to farmers' formal agricultural education. Finally, findings suggest a substitution and income effect of shadow wages in demand for hired labour— the substitution effect is larger for the demand of casual hired labour. Overall, this thesis provides an improved understanding of farm labour and its link with automation and efficiency as crucial factors for the sustainable development of an evolving dairy sector. 2025-06-19

The objective of this PhD thesis is to assess the role of extension services and technology adoption in enhancing farm sustainability with the goal of informing the debate on how to achieve sustainable intensification. Based on Irish farm-level data, the thesis presents three separate analyses embodied in the technology adoption and extension literature. The first analysis explores the potential of a farm technology, i.e., milk recording, in simultaneously enhancing the economic, environmental, and social dimensions of farm sustainability. Using propensity score matching and robustness checks, the findings reveal that milk recording can lead to economic and social benefits. Conversely, milk recording does not impact farm environmental sustainability. The second analysis examines pathways between extension participation, farm management, and economic and environmental sustainability. Farm management is represented by grassland management and reproductive efficiency. Seemingly unrelated regressions models and treatment-effects bounds are estimated to achieve partial identification. The results show that extension has a positive impact on reproductive efficiency but does not affect grassland management. Improving extension effectiveness on these components of dairy management could result in economic gains, while the effect on environmental sustainability is mixed. The third analysis compares farmer cohorts engaging or not with mixed public-private and private extension services. Differences in farm and farmers’ characteristics are analysed with a mixed logit model, while farm economic and environmental sustainability is compared based on linear regression models. The findings show that farm size, dairy specialisation, and farm management vary across cohorts. Extension is associated with higher economic performance but does not affect environmental sustainability. No significant differences are found between mixed public-private and private extension participants for both sustainability dimensions. 2025-06-15