title: Microsimulation modelling of agricultural and spatial economics: Income, investment, and farmer behavior
Creators: name: Haydarov, Dilovar
Publisher: name: University of Galway
Year: 2024
Subjects: subject: Arts Social sciences and Celtic Studies
subject: Geography
subject: Agricultural economics
subject: Farmer behavior
subject: Income
subject: Investment

description: This thesis delves into the impact of natural capital attributes, such as soil quality, continentality, and environmental factors like rainfall and temperature, on the farm market gross margin. These factors vary geographically, affecting farm productivity and expenses differently based on location. To tackle this spatial diversity in natural capital, a model integrating physical, human, and natural capital within a geospatial microsimulation framework is utilized. By analyzing agricultural administrative and National Farm Survey data, the model captures agronomic disparities stemming from natural capital conditions in Ireland. The inclusion of natural capital drivers leads to notable adjustments in simulated agricultural incomes nationwide, with market gross margin per hectare rising in the South and South-East but declining in the Midlands and parts of the North. The main reason for spatial heterogeneity could be that the South and part of the South-East have relatively better natural capital, including improved soil quality compared to the North and part of the Midlands. Recognizing the heterogeneity in natural capital unveils increased income variability, particularly among districts, highlighting the substantial influence of natural capital on farm income and stressing the importance of considering localized environmental and agronomic factors. It was found that there is greater variation in income within districts compared to the variation in income between areas when natural capital is taken into account. Furthermore, while previous researches have focused on individual aspects of adopting practices for optimizing natural resource use to support sustainable agricultural intensification, there is a lack of comprehensive literature examining how various factors such as farm demographics, behavioral drivers, cost-benefit analyses, and agronomic needs for implementing nutrient management practices may differ based on farms' environmental contexts. A part of this thesis aims to explore the correlation between recognizing the need for liming and intending to lime, investigating potential drivers behind this relationship in the context of Ireland. Drawing on data sources like national farm surveys and spatial datasets of Irish farms and soils, the research employs statistical matching techniques alongside regression analyses. Results indicate a strong likelihood that farmers recognizing the need to lime due to low soil pH also intend to lime. Factors such as perceived behavioral controls, subjective norms, perceived resources, education levels, and age categories play significant roles in influencing farmers' intentions regarding lime application. This study sheds light on the complex interplay of behavioral factors impacting farmers' decisions on lime management practices within specific environmental settings. Additionally, financial management is essential for agricultural sustainability amidst economic uncertainties. This work of the thesis introduces a spatially enhanced tool designed to improve farm financial planning for less financially active farmers by leveraging a spatial microsimulation approach based on the SMILE model. Also, utilizing data from Teagasc's National Farm Survey spanning 2001-2014, this tool offers detailed benchmarking information at the townland level to enhance financial planning effectiveness compared to regional or national data. By simplifying financial data input processes and providing tailored insights at a local level, this tool aims to encourage greater engagement in economic planning among small-scale farmers. Finally, in pursuit of economically sustainable farms, managing various factors affecting output and costs is crucial. This study investigates the impact of investment changes on farm output and costs in Ireland using Deep Neural Networks with data from pastoral-based livestock systems surveys spanning 1996-2018. Results show that increasing investments by 10% leads to varying effects on gross output across different deciles of Irish farmers, emphasizing the importance of strategic investment decisions for agricultural productivity and cost management.