Farm Accountancy Data Network Research Articles

FARManalytics – A bio-economic model to optimize the economic value of sustainable soil management on arable farms

Soil quality is an important determinant of agricultural productivity and environmental quality. Despite its importance, few economic models incorporate sustainable soil management. The objective of this study is to develop and illustrate FARManalytics: a bio-economic model to gain quantitative insight in the economic value of sustainable soil management. First, we defined a comprehensive set of chemical, physical and biological soil quality indicators and quantitative rules on how these indicators respond to farmers’ production management over time. Second, we introduce an economic calculation framework that enables accurate calculation of the contribution of different production management decisions towards farm income using Activity-Based-Costing. The set of soil quality indicators and economic calculations serve as the basis for the bio-economic model FARManalytics, which consists of two modules: (1) the PMcalculator, a module that calculates the impact of current production management on soil quality and farm economics and (2) the PMoptimizer, a module that uses Mixed-Integer-Linear-Programming to maximize farm incomewithin predefined soil quality indicator constraints. The decision variables are the crop rotation, cover crops, manure & fertilizer application and crop residue management. We illustrate the added value of the model by applying it to an extensive and intensive farm type, both on clay and sandy soil. These farm types are derived from the Farm Accountancy Data Network (FADN) in the Netherlands. FARManalytics demonstrates that it is possible to increase farm income with up to €940 ha−1 year−1 on clay soil and up to €683 ha−1 year−1 on sandy soil, while meeting all soil quality targets except subsoil compaction vulnerability. The latter was among the most limiting soil quality indicators for the farm types in this study, together with soil organic matter input, wind erosion vulnerability and plant-parasitic nematodes. FARManalytics integrates the impact of production management decisions on soil quality and economics at farm level. Combined with representative farm types, the bio-economic modeling approach of FARManalytics can provide useful information for policy support. FARManalytics can also be tailored to provide decision support for individual farms, based on data that is commonly available on arable farms at low cost.

Agricultural production and biodiversity conservation: A typology of Swiss farmers’ land use patterns

Understanding farmers' land use behaviour is a prerequisite for designing effective policies that aim to protect and enhance biodiversity in agriculture. We develop a typology of Swiss farmers' land use patterns in terms of their agricultural production and biodiversity conservation. We contribute by adopting a comprehensive perspective encompassing not only EFAs (Ecological Focus Areas) but also non-EFAs. Relying on a sample of 2341 Swiss farm observations from the Farm Agri-Environmental and the Farm Accountancy Data Network, we conducted – for each agricultural region (plain, hill and mountain) – a K-means clustering to identify farmland use patterns. We considered four clustering variables, namely agricultural production intensity, the extent of a farm's participation in agri-environmental payment schemes and the impact of farm agricultural practices on the organismal biodiversity of 1) EFAs and 2) non-EFAs. The analysis reveals four distinct farmland use patterns beyond the classical dichotomy of low shares of EFAs and high agricultural production intensity versus high shares of EFAs and low agricultural production intensity. Three of the four land use patterns are similar across all agricultural regions. Our findings show that biodiversity enhancement is possible outside of EFA direct payment programmes. One cluster succeeded in exhibiting both a high agricultural production intensity and a high overall biodiversity score, which highlights that these dimensions are not mutually exclusive. The low or moderate use intensity of mineral fertilisers, pesticides and purchased feedstuffs in combination with a high use efficiency of these inputs seems to be the key to reconciling agricultural production and biodiversity conservation.

Potential impacts of the Common Agricultural Policy's Income Stabilisation Tool on farmers' incomes and crop diversity: A French case study

AbstractThis paper analyses the potential impacts of a hypothetical implementation of the Income Stabilisation Tool (IST) in France for the field crops sector. The IST is a risk management tool available within the 2014–2020 Common Agricultural Policy (CAP) to support farmers facing a severe drop in their incomes. This analysis was conducted using a farm‐level model relying on expected utility theory and based on positive mathematical programming with risk. The model was applied to a sample of 1375 field crop farms in France derived from Farm Accountancy Data Network (FADN) data. Simulation results show that the uptake rate of the tool is relatively low, less than 37% in all scenarios. It is strongly dependent on CAP public support and on how much premium farmers have to pay. Highest uptake rates are observed in farms specialising in Other Field Crops, such as potatoes, pulses and sugar beet, and farms located in regions highly exposed to climatic risks. Previous experience with insurance favours the acceptance of the IST. Model results also show that the IST improves adopters' income and reduces income inequality. However, its impacts on crop diversity, measured by the Shannon index, are negative.

Are Organic Farms Less Efficient? The Case of Estonian Dairy Farms

The paper investigates the technical efficiency of conventional and organic dairy farms in Estonia in the period 2006‒2015 using Farm Accountancy Data Network. We analyse self-selection into organic farming using the propensity-score-matching approach and explicitly test the hypothesis that organic and conventional farms apply homogeneous technology. We find that organic farms are less efficient. However, the difference in technical efficiency between organic and conventional farms decreases substantially when the technical efficiency assessment incorporates the use of the appropriate technology. The lack of growth of technical efficiency over time indicates that there might be a lack of knowledge in organic milk production that hinders its development. Since technical efficiency increases with farm size, it is important that organic dairy farms increase their scale.

Conversion to organic farming: Does it change the economic and environmental performance of fruit farms?

This paper compares the performance of conventional and organic fruit farms in Spain, using a set of base indicators to assess their economic and environmental performance on a per hectare basis. Composite indicators are also calculated to measure the overall economic and environmental performance of both production systems. Comparisons are made using propensity score matching to minimize the non-randomization biases caused by structural differences between the samples of conventional (n = 552) and organic (n = 127) fruit farms sourced from the Spanish Farm Accountancy Data Network (RECAN). The results based on per hectare metrics point to modest changes in the performance of farms that converted to organic farming. This is mainly because most converted farms were former conventional farms characterized by lower profitability and less intensive input use, consequently minimizing the effects of the conversion process. Nevertheless, the conversion outcomes exhibit a degree of variability depending on the specific type of fruit production. Economic gains are only discernible in the case of nut farms, whereas fruit and tropical fruit farms tend to yield the most favorable results per hectare from an environmental perspective.

Irrigation water economic value and productivity: An econometric estimation for maize grain production in Italy

Climate change, characterized by rising temperatures and limited precipitation, has intensified the demand for irrigation water while simultaneously restricting its availability. This challenge poses significant risks to agricultural and food production, particularly in the Mediterranean regions where, recently, water deficits have led to substantial production losses and quality issues. Water is a critical determinant of crops' economic viability, especially for water-intensive crops, making it essential to estimate its economic relevance, especially in the absence of reliable water market prices. This study has two primary objectives: first, to evaluate the shadow price of irrigation water for maize grain at the farm level, which is defined as the value generated by the marginal unit of water consumed; and second, to analyse its heterogeneity. Leveraging a Farm Accountancy Data Network (FADN) panel of 1625 Italian farms over a decade (2010–2020), an econometric production function approach is employed. Moreover, quantile regressions reveal variations in the shadow price linked to geographical, managerial, and structural farm characteristics. Our findings underscore water’s key role in economically viable maize grain production, significantly enhancing the productivity of other inputs like fertilizers and pesticides. The average shadow price is 0.29 €/m³, with a median of 0.20 €/m³ and water total productivity accounts for one-third of maize’s average gross output. Quantile regressions uncover how factors like geographic location, altitude, farm management, irrigation water source, and farm size influence the distribution of water productivity, reflecting either efficient use or scarcity of this resource. Our estimation provides valuable insights for policymakers by offering accurate shadow price estimates for irrigation water in Italian maize grain production. Furthermore, it enhances our understanding of irrigation water’s role in the economic viability of this crop, while contributing to support evidence-based water management strategies, identifying vulnerable areas and farms and allowing for future methodological developments.

Importance of natural conditions in Poland in the operation of fully organic farms and those with co-existing conventional production

Abstract This study addresses the issue of assessing the functioning of farms in areas with diverse natural farming conditions by evaluating them using the latest version of the Agricultural Production Area Valorization (APAV) index. Analyses were performed on three types of farms: fully organic farms, organic farms with co-existing conventional production, and conventional-production farms. To achieve the research objective, 259 communes were selected depending on the level of their APAV. Assessments were made of their production potential, production organization, production and economic results in communes with average APAVs below, equal to, and higher than the national average (66.6 points) based on data from farms continuously keeping accounts for the Polish farm accountancy data network (FADN) in between 2019–2021. The Shannon-Wiener index (S-W index) was used to measure the degree of diversity of crop species in the farms’ sown crops, and determine what proportion of those were structure-forming plants. This research demonstrates that in order for interest in organic production to develop under current conditions, there must be sufficient financial support for agricultural producers, especially in areas with more difficult farming conditions.

Farming of Medicinal and Aromatic Plants in Italy: Structural Features and Economic Results

In recent years, the primary sector in Italy and elsewhere has been profoundly affected by climate change and a deep economic crisis, mainly linked to stagnating prices and rising production costs. Because of this situation, we are witnessing renewed interest in alternative agricultural productions, which are characterized by their resilience and sustainability, including medicinal and aromatic plants (MAPs). This sector is characterized by a certain heterogeneity due to the great variety of species and their wide range of uses. Although these characteristics contribute to the sector’s economic success, they also hinder its study due to commodity complexity and limited data availability. At the farm level, the situation is complicated by the fact that MAP cultivation is often embedded in complex cropping systems, and more rarely, is practiced exclusively or predominantly. In light of these considerations, we concentrated solely on the agricultural phase of the supply chain, using data available in the Farm Accountancy Data Network. We aimed to examine the main structural characteristics and economic outcomes of Italian farms that grow MAP, as well as the profitability of some of the species. To ensure accurate species classification, only MAPs exclusively designated for botanical use in the Italian National List were considered. The analysis of farm economic performance indicators (gross output, variable costs, gross margins, etc.) focused mainly on the species most represented in the sample: saffron, rosemary, lavender, oregano, and sage. The results indicate that the total gross output and gross margin show the best performance in the case of saffron (66,200 and 57,600 EUR/ha, respectively) and rosemary (27,500 and 22,000 EUR/ha, respectively). However, for saffron, the biggest cost concerns propagation (purchase of bulbs), amounting to 50% of the variable costs, whereas fertilization ones are particularly high for sage and rosemary.

Determinants of Financial Security of European Union Farms—A Factor Analysis Model Approach

The objective of this study was to assess the level of financial security of farms and identify its determinants based on factor analysis. The data used in this research were obtained from the European FADN (Farm Accountancy Data Network). Factor analysis (FA) was employed to reduce the number of variables that potentially determine the financial security of farms. The results indicate that the surveyed entities maintained financial security between 2014 and 2021. This study suggests that it is necessary to examine these factors separately for farms engaged in crop farming and animal production. The results obtained for all farms were less satisfactory than those that took into account the specifics of agricultural production. This study addresses a gap in the literature by including highly correlated variables in the analysis of the determinants of financial security. Factor analysis is used to reduce the number of variables without losing important information. Firstly, seventeen variables related to the financial security of all farms were assigned to six factors. These were income and self-financing of operations; area and subsidies; long-term investments and financial decisions consequences; economic size, taxes, and non-breeding livestocks; investment activity; and inputs, stock, short-term loans, and labor. Then, the determinants of the financial security of farms were examined, taking into account the specialization of activities. For crop-producing farms, six factors were identified, including three that were identical to those for all farms: income and self-financing of operations; long-term investment and financial decisions consequences; and investment activity. In addition, the following items were specified: area, subsidies, non-breeding livestocks, and taxes; economic size, inputs, and labor; and stock and short-term loans. The correlated variables in the case of livestock production combined into factors in a different way. In this case, four factors were distinguished: economic size, non-breeding livestocks, income, and self-financing of operations; operational activities of animal production; long-term investment and financial decisions consequences; and investment activity. Financial security is a complex matter that can be affected by a range of factors related to agricultural activities.

Non-monetary motivations of the EU agri-environmental policy adoption. A causal forest approach

This paper investigates the non-monetary motivations of farmers' adoption of agri-environmental policies. Unlike the monetary (income) motivations, non-monetary drivers can not be directly observed but can be identified from observational data within appropriate quasi-experimental designs. A theoretical justification of farmers' choices is first formulated and a consequent natural experiment setting is derived. The latter admits heterogeneous, i.e. Individual, Treatment Effects (ITE) that, in turn, can be interpreted in terms of more targeted and tailored policy expenditure. A Causal Forest (CF) approach is adopted to estimate these ITEs for both the treated and not treated units. The approach is applied to two balanced panel samples of Italian Farm Accountancy Data Network (FADN) farms observed over the 2008–2018 period and concerns agri-environmental policies delivered through the Common Agricultural Policy (CAP). Results show how heterogeneous the farmers’ response and the associated non-monetary motivations can be, thus indicating room for a more efficient policy design.

Importance and determinants of cooperation between fruit farms and the institutional environment

The development of farms requires support from the institutional environment of agriculture. Institutions help introduce innovations and adapt their functioning to the requirements of the European Union. The aim of the research was to determine the factors affecting the cooperation of orchard farms with the institutional environment and the economic effects of this cooperation. The article's novelty answers two questions: what factors on the farm affect cooperation with the institutional environment, and whether such cooperation affects the economic results of orchard farms? The study covered 45 farms from the Małopolska and Pogórze Region in Poland, specializing in cultivating fruit trees and shrubs, which in 2018 kept accounts under the Farm Accountancy Data Network (FADN). The descriptive method, chi-square test, and Spearman's rank correlation coefficient were used in the data analysis. An original relationship index was used to assess fruit producers' cooperation with agricultural organizations. A backward stepwise multiple regression model was used to identify the factors influencing its level. The research showed a statistically significant relationship between the relationship index with the organization and utilized agriculture area, total workload, the value of subsidies to operating activities, direct costs, and the farmer's age. The regression model shows that the value of subsidies to operating activities explains 28.09% of the variability of the relationship index (Ri). Based on the analysis, it can be concluded that the cooperation of fruit producers with the institutional environment positively impacts orchard farms' economic and financial results.

Subsidies and the income inequality in the Hungarian wine sector

The paper investigates the impact of different sources of income on wine farm total income inequality in Hungary using Farm Accountancy Data Network data for the period 2013-2019. The decomposition of the Gini coefficient is applied to focus on the impact of the Common Agricultural Policy (CAP) shift from market to government budgetary support on wine farm total income inequality. Off-farm income has a rather stable impact on wine farm total income inequality. CAP Pillar 1 subsidies have remained more important than CAP Pillar 2 subsidies, both in the structure of wine farm total income and in the reduction of wine farm total income inequality. The most striking finding is regarding a shift in wine farm market income from a negative (losses) to a positive (profit) value and its increasing role in wine farm total income inequalities. The 20% of the largest wine farms created from almost 90% to less than 80% of wine farm total incomes between 2013 and 2019, but during the same period their participation in CAP subsidy payments was reduced much more from more than 80% to around 60%. Subsidies from Pillars 1 and 2 were reduced, and wine market income increased wine farm total income inequality, while it remained constant for off-farm income. The wine farm market income has driven wine farm total income inequalities. This might strengthen because of the ongoing market selection process with the exit of less efficient and loss-making wine farms and the increasing role of surviving profitable wine farms. This market selection process can be related to managerial, entrepreneurial, and innovation activities based on the differentiation and segmentation of wine farm products and their market incomes.

Curbing methane emissions from Italian cattle farms. An agroeconomic modelling simulation of alternative policy tools

Methane (CH4) emissions from cattle farms have been prioritised on the EU agenda, as shown by recent legislative initiatives. This study employs a supply-side agroeconomic model that mimics the behaviour of heterogeneous individual farms to simulate the application of alternative economic policy instruments to curb CH4 emissions from Italian cattle farms, as identified by the 2020 Farm Accountancy Data Network survey. Simulations consider increasing levels of a tax on each tonne of CH4 emitted or of a subsidy paid for each tonne of CH4 curbed with respect to the baseline. Individual marginal abatement costs are also derived. Besides, to consider possible technological options to curb emissions, a mitigation strategy is simulated, with different levels of costs and benefits to appraise the potential impacts on the sector.Relevant reductions in operating income are foreseen, the most substantial in farm types and size classes characterised by lower levels of carbon productivity. The introduction of the mitigation strategy shows that the outcome in terms of mitigation potential, without undermining production level, highly depends on the implementation costs, but can also vary widely due to heterogeneous farms’ economic performances. Policy implications are also derived.

Estimating Nitrous Oxide (N2O) emissions from managed soils at higher spatial resolution in the Republic of Ireland

This paper aims to define a high spatial resolution model for estimating nitrous oxide (N2O) emissions from agricultural soils in Ireland. In 2020, N2O emissions from the management of agricultural soils represented 10% of the total national agricultural Greenhouse Gas (GHG) emissions. The high spatial resolution model employed here takes account of environmental factors that influence N2O emissions at a more disaggregated spatial scale than the Intergovernmental Panel on Climate Change (IPCC) national inventory-reporting framework. Activity data from the EU Farm Accountancy Data Network (for Ireland) is used in conjunction with biophysical and climatic data in a geographic information system (GIS) framework to estimate N2O emissions at a sub-national level. Results indicate that N2O emissions are 5% lower by applying this high spatial resolution modelling approach at the farm level compared to the baseline model (Tier 2). Nevertheless, 25% of the farms in the sample analysed had an overestimation in their N2O emissions of 20%, and another 25% of the farm sample had an average underestimation in their N2O emissions by 19%, a consequence of the variation of environmental factors among farms. Using a data panel regression, results confirm that the environmental factors examined are statistically significant within the model proposed, and with a simulation, we assessed the switching of 20% of CAN fertiliser for protected urea. According to the high spatial model, this mitigation measure can reduce N2O emissions from inorganic fertilisers by up to 15%. However, the reduction is conditioned by local factors and environmental conditions.

The use of purified wastewater for irrigation: Possible strategies in the Capitanata area (Apulia, Italy)

The reuse of purified wastewater can supplement water availability for irrigation and limit withdrawals from groundwater which contribute to deteriorating its quality in many Italian coastal agricultural areas. The regulatory framework defined by EC Reg. 741/2020 specifies the legal and technical conditions, which from 2023 allow this use to be promoted in Italy. However, Italian agriculture is also differentiated in the ways in which farms obtain water for irrigation, and it is advisable to direct the treated wastewater towards the types that will then effectively reduce the use of groundwater. Our study seeks to identify these typologies by examining irrigation conditions in an important agricultural area of Southern Italy. Some districts of this territory are reached by collective irrigation networks of a Consortium that supply all the irrigation water; other areas are connected to those networks, but its supplies are lacking, and the farms also draw on underground aquifers; other areas are not reached by the collective network and groundwater is the only irrigation resource available. An econometric estimate of the irrigation demand in these areas defines whether the relationship between irrigation demand for groundwater and consortium is complementary or substitutive. This outlines the possible responses to the increase in consortium supplies with the introduction of treated wastewater, identifying the farm types to which those additional water resources can be allocated to reduce withdrawals from aquifers. A Seemingly Unrelated Regression Equations system of two irrigation water demand functions, from Consortium and from farm wells, is estimated with data from the National Information System for the Management of Water Resources in Agriculture (SIGRIAN) and the Farm Accountancy Data Network (FADN). The unitary costs of using each of these two sources are amongst the technical and economic regressors. The results indicate that in the farm type that uses both water sources, consortium and groundwater, there is a substitution relationship between these two sources. Also, the irrigation of these farms is the most responsive to current trends in the profitability of the various groups of crops, with the possibility of a further growth in the groundwater use. Supporting irrigation with treated wastewater on these farms would not induce rebound effects that increase the groundwater use: a greater irrigation supply of purified and conventional water at lower costs would instead reduce the use this water source.

Economic and Environmental Sustainability Trade-Off Analysis in Sheep Farming Using the Farm Accountancy Data Network Database

Agriculture and livestock farming significantly contribute to the success of all United Nations Sustainable Development Goals of Agenda 2030 and are pivotal in the sustainability transition of the European agri-food sector. However, those sectors have been criticized for generating negative environmental externalities. In this context, adopting indicators able to evaluate agriculture and sheep farming sustainability is essential for fostering sustainable development in the primary sector and defining appropriate policies to support it. Such indicators are crucial for understanding if European Union policies striving to realize win–win opportunities based on synergy between farms’ environmental and economic dimensions are realistic. This paper focuses on this wave of interest and has two aims. First, it intends to investigate the existence of synergies or trade-offs between those dimensions using a trade-off analysis. To this end, a significant set of economic and environmental farm indicators was selected, and two composite indicators were created. Second, it aims to investigate the relationship between those two indicators and some pivotal structural and socio-demographic variables. This study was carried out on 219 Sardinian sheep farms included in the Italian Farm Accountancy Data Network. The findings showed a low synergy between the economic and environmental spheres, a relationship between economic indicators and farmers’ ages and organic production variables, and no relationships between the environmental dimension and the analyzed variables.

Conventional versus organic olive farming: which has a better economic performance?

The European Green Deal sets a target of at least 25% of the total EU agricultural land under organic farming by 2030. In the case of the Spanish olive sector, organic olive farming accounts for barely 10% of the national agricultural area dedicated to this crop. Within this context, this study compares the economic performance of Spanish conventional and organic olive farms in terms of productivity, profitability, viability, resilience, and independence. To do so, microdata provided by the Spanish Farm Accountancy Data Network have been used, and matching methods have been applied to conduct an unbiased comparative analysis of matched conventional and organic farms. Results show statistically significant differences in productivity, with conventional olive groves being more productive. However, CAP subsidies are shown to be an effective instrument for promoting the conversion to organic farming in olive groves since they cancel out the differences in profitability between these two production systems. There is also evidence of the greater resilience of organic farms. These results could contribute to a more efficient design of instruments promoting the ecological transition of agriculture in line with the aforementioned policy objective.

Assessment of environmental performance on farms using FADN: a case study of the Region of Mazowsze and Podlasie

Agri-environmental Schemes are the main agricultural policy instrument currently available in the European Union to help improve the relationship between agriculture and the environment. The conducted research included the assessment of AES (Agri-environmental Schemes) implementation in the Region of Mazowsze and Podlasie, Poland. This Region is characterized by worse natural, organizational, and production conditions than in other Regions in Poland. Out of the 292 analyzed farms, 146 formed the research sample, while another 146 constituted the control sample. In 2010 and 2014, all analyzed farms kept entries in accounting books under FADN (Farm Accountancy Data Network). All farms were classified according to TF8 as fieldcrops, milk, and mixed. For each type of farm, a research and control sample were distinguished. The research sample included farms that participated in the AES, whereas the control sample comprised farms that did not join the program. For each farm from the research sample, the most similar farm was selected in the control group, taking into account its type and location. The conducted study confirmed that the implementation of the AES has a positive effect on the environment, as it results in lower use of synthetic fertilizers, crop protection products, and GHG (greenhouse gas) emissions per ha. However, the research showed that the costs of reduction of GHG emissions are very high. In 2014, the cost of a decrease of 1 Mg CO2 eq amounted to 1,302 PLN on fieldcrop farms, 611 PLN on milk farms, and 1,112 PLN on mixed farms. This is important information for policy makers, as it indicates that, while planning subsequent pro-environmental programs, it is crucial to perform a cost-benefit analysis and an ex ante assessment of the costs of planned activities in relation to the expected environmental effects.

Counterfactual evaluation of two Austrian agri‐environmental schemes in 2014–2018

AbstractThis article investigates the causal effect of farm participation in two Austrian agri‐environmental schemes (AES), Immergrün (ground cover) and Zwischenfrucht (catch cropping), on fertilizer and plant protection expenditures in the 2014 programming period. Combining European Farm Accountancy Data Network data with information on scheme participation from administrative control data offers identifying farm participation in specific schemes targeted at reducing input intensity. Given the overall small sample, we maximized the utilizable sample size by combining difference‐in‐difference and kernel matching with automated bandwidth selection. To address the remaining post‐matching covariate imbalances, we used double machine learning (DML) techniques for a guided selection of potential confounding covariates. Our results suggest that, given the available sample, we cannot substantiate moderate effects of AES participation, and that guided covariate selection by DML offers no gain over non‐guided covariate selection for the small sample. Our results underline the need to increase the number of farms and the duration in available farm panels to substantiate future counterfactual‐based evaluations of policy.

Financial Ratio Analysis as an Advisory Tool for Sustainable Pig Farm Management in Greece

This paper aims to provide pig farmers with the necessary information to guide strategic decisions through the development of a tool that allows them to calculate and control their production costs. A financial ratio analysis can be used as a starting point when assessing and improving a farm’s economic sustainability. The objective of the present article is to (1) provide insight into the financial ratios commonly used for pig farm assessments and (2) how they may be applied through an advisory tool to assess farm economic sustainability. Moreover, in this study, different financial ratios were examined to uncover trade-offs and synergies between them. Using the Farm Accountancy Data Network (FADN), we analyzed Spearman correlations between financial ratios. The correlation between these sets of indicators suggested that they could be used to estimate dairy farm economic sustainability. Our results showed that pig farms face a financial situation that can be improved. Pig farmers can benefit from this tool in multiple ways, by gaining an understanding of the costs and revenues leading to investment decisions, managing the risks, planning for potential growth, and having greater access to funding opportunities.