Profitability and financial performance of European Union farms: An analysis at both regional and national levels

1 Introduction

The working capital is an important financial indicator having impacts on the profitability [1] of small and medium-sized enterprises and some studies reveal that there is an optimal level for liquidity [2]. These relationships between the working capital and profitability are, in some circumstances, influenced by macroeconomic factors [3], such as internationalisation and globalisation [4].

In contrast, the working capital management has also a relevant impact on the financial performance of the firms, where the policies related to inventories, liquidity, and trade cycle may have their influence [5], as well as the payment and collection periods [6].

The format of the relationship between profitability and the working capital management variables changes from study to study. For example, Lyngstadaas and Berg [7] suggest a quadratic approach, whereas other authors propose linear regressions [8].

Despite the importance of the working capital variables on profitability and financial performance, there are not so many studies for the agricultural sector, few for the European Union context and less using data from the European Farm Accountancy Data Network (FADN). This database publishes data for European farms (disaggregated at the regional, country, and farming type level). This statistical information is collected by the official institutions of each country and is later organised through methodologies which allow one to obtain representative farming indicators for European realities [9].

Considering this framework, it seems pertinent to analyse the context of the working capital dimensions within the European Union agricultural sector, considering data at the farm level. This is particularly important, considering the diversity of realities, across countries and regions, in European farms and is always a difficult task for the policymakers to design adjusted common strategies. In fact, the Common Agricultural Policy (CAP) is frequently criticised for being unadjusted to some specific farming realities. CAP is one of the most famous European Union common policies that was created at the beginning of the European Economic Community (previous designation of the European Union) having two sub-policies, one for the markets and the other for structures [10]. This research may bring new insights to better understand European farming which can be considered to support the policymakers and the farmers in implementing more adjusted approaches which allow for better profitability and performance and a more sustainable development. The sustainability of the European agricultural sector has been a concern over the several CAP reforms, including that from 2013 [11].

In this perspective, the main research questions of this study are:

What are the realities of the net working capital across the European Union member-states and regions and across the several types of farming and economic sizes?

How the working capital variables impact profitability and financial performance?

Considering the financial dimension of the working capital, the idea with these two questions is to first analyse the context of this indicator across the European Union realities and after to assess its impact on the profitability and financial performance. Despite the fact that the CAP instruments were not directly considered in the assessments carried out, considering their impacts on the evolution of the European Union agricultural sector, the findings obtained may add relevant value for the policymakers.

There are not many studies concerning the net working capital for the European Union farming context, less so involving the different agricultural systems, considering the approaches here proposed and including the several frameworks from the diverse member-states. This reveals the novelty of this research and its contribution for several actors, including related institutions. For example, a search on the Web of Science (Core Collection) [12] for the topics “working capital,” agriculture* and “European Union” found only one document for the Spanish context [13].

It will be important, in future research, to further explore these contexts at a regional level, capturing further local and specific characteristics.

2 Literature survey

The financial and accounting concepts, with their respective adjustments, are used and considered around the world in more diverse frameworks, showing their pertinence as fiscal and management instruments [14].

This financial and accounting management is particularly important in the agricultural sector with new needs borne out of current contexts [15], in terms of innovation [16], where intellectual capital has its importance [17].

Agriculture and other rural activities already have great relevance as socioeconomic sectors in some countries [18]. Nonetheless, they appear, often, as sectors with several particularities [19] and financial risks [20], in terms of credit [21]. These contexts call for specific and adjusted strategies [22] around the world [23], including credit requirements [24], credit conditions [25], credit policies [26], and institutional support [27] for smallholders [28]. Here, the cooperatives provide a significant contribution [29] along with other rural organizations [30]. The availability of credit is crucial for the firms of any sector, including the farming sector [31]. In the European Union, the CAP has its influence in these contexts [32].

The conditions such as the credit needs that are provided have implications on the enterprise’s activities [33]. Due to small profit margins, it is important to reduce agricultural costs and here, for example, strategies that provide credit at lower interest rates are needed and are often implemented in several countries [34]. The interest rates have, indeed, a relevant impact on the performance of any sector [35], in any context [36].

In any case, some authors defend an optimal level of resources, with impacts on liabilities and leverage [37], to achieve the targeted profitability. Inadequate levels of resources have impacts on the farmers’ income [38] and in rural development [39], where the diversification of activities is a priority [40], in alternative or complementing agricultural incomes [41]. Tourism may bring about crucial contributions here [42], from a perspective of economic diversification in rural regions. The level of efficiency of the resources that are used in the agricultural sector depends, often, on the farm’s size [43] and the economic results on the options taken by the farmers [44]. The farmers’ decisions are influenced by their managerial skills [45]. The levels of liberalisation/protectionism have their impacts here, too [46], as well as, the farmers’ interrelationships with the local agricultural markets [47]. The land tenure is another dimension causing impact on the farms’ dynamics [48] as well as specific sociocultural conditions [49].

The main objective of this research is to highlight the dimensions of the working capital concept as a financial instrument which may be considered to support farms management [50]. In the literature, as a financial concept, the working capital appears as the difference between the current assets and the current liabilities and represents the liquidity [51] with impacts on the micro and macroeconomic performance [52]. In some cases, it is calculated as a ratio and known as current ratio [53]. The current assets have, in fact, a determinant role in the sector for agricultural management [54].

However, sometimes, working capital is represented in the literature as having other meanings such as costs of inputs associated with seeds, fertilizers, hired labours, and energy requirements [22], in general, known as variable inputs [55]. It is considered, also, as the money that operators use to buy products and pay marketing costs [56], or productive capital [57], or stock of productive capital [13], or specific costs plus overheads [58].

The specificities of the agricultural markets lead often to a dependency on only one buyer with implications on the dimensions of the account receivables and this impacts the farm’s financial sustainability [59], consequently the profitability [60] and financial performance [61]. The inventories and the account receivables dimensions have, indeed, real impacts on several firms’ indicators, specifically on liquidity [62] which depends on the working capital management policies [63]. Between the working capital management variables, the current ratio is, often, preferred in audit reports [64].

The account payable, market share, and gross margins are other critical success factors [65]. Imbalanced and shortage of working capital are real weaknesses in the agricultural sector [66]. These particularities gain specific importance when the scientific literature highlights the greater importance of the farm and sector characteristics relative to macroeconomic dimensions [67].

3 Materials and methods

To address the research questions proposed and achieve the main objectives of this study, data from the European Union FADN were considered which was assessed through data analysis (to address the first question about “What are the realities of the net working capital across the European Union member-states and regions and across the several types of farming and economic sizes?”) and by spatial autocorrelation methodologies and panel data regressions, for the period 2004–2018 (to answer the second question “How the working capital variables impact profitability and financial performance?”). For the data analysis, because the statistical information was assessed on average, a shorter period (2016–2018) was considered that allows to capture cyclical effects of the agricultural productions and avoid influences from older farming characteristics.

The European Union FADN database is an interesting platform that provides statistical information at the farm level for several farming indicators. This micro statistical information is collected in several member-states and is fundamental to support policymakers and associated institutions in the design of measures and instruments for the European framework. The statistical information obtained from the farmers of each country is worked through a special weighting system to obtain results for representative farms. This means that for each region/country that is considered by the database, data for the respective representative farm (one farm for each region/country) are published. For example, in 2018 the FADN (European Union – 28) considered a sample of 80,000 to <90,000 farms that represented 4,033,544 farms [9].

The spatial autocorrelation analysis is an interesting approach, because it allows for the assessment of possibilities of spreading effects between neighbouring countries or regions. This is particularly important in the processes of policy implementation. There is spatial autocorrelation when the variables in one country are correlated with the same variables in the neighbouring countries [68,69]. For spatial autocorrelation assessment, the Moran’s I statistic was considered. For the global spatial autocorrelation, the Moran’s I range from −1 (negative spatial autocorrelation) to 1 (positive autocorrelation) is expected [70,71]. For the estimations, Prais–Winsten regression, correlated panels corrected standard errors (PCSEs), methodology was considered to deal with cross-sectional dependence, heteroscedasticity, and autocorrelation [72–75]. In fact, the several diagnostic statistical tests reveal that the data have problems concerning spatial autocorrelation, serial correlation, heteroscedasticity, and cross- sectional dependence. To avoid biased results, and to handle these statistical infractions, several methodologies previously described were considered.

4 Net working capital by the European Union agricultural regions, types of farming, and farm economic size

The data analysed in this section were obtained from the European Union Farm Accountancy Data Network [9], including the shapefiles considered in Figure 1. The data available in the FADN were obtained through a special weighting system, with each agricultural region being represented by a representative farm. Figure 1 is obtained through the QGIS software [76]. Figure 1 shows that, on average over the period 2016–2018, the top10 European agricultural regions with higher working capital are the following: Lombardia (Italy), Piemonte (Italy), Veneto (Italy), Thüringen (Germany), Champagne-Ardenne (France), Trentino (Italy), Netherlands, Friuli-Venezia Giulia (Italy), Liguria (Italy), and Denmark. The majority of the top10 regions are from Northern Italy, showing the relevance of working capital for the respective farms. In turn, for the Central and Eastern European countries (which adhered to the European Union in 2004), in Greece and Portugal, the levels of net working capital are the lowest. These findings highlight the importance of CAP measures that are even more adjusted to the regional particularities inside the European Union, allowing for a deeper involvement of local stakeholders in the design of policy instruments and making the CAP less common and more specific.

Figure 1

Distribution of the net working capital (euros) across the former 28 European Union agricultural regions, on average over the period 2016–2018. Source of the original shapefile: [9].

When the data are considered at a national level (one representative farm for each country), Table 1 presents the Netherlands and Denmark as being the two countries with higher average net working capital. This means that the most dynamic farms are, also, those with higher working capital. In addition, beyond the Netherlands and Denmark, the European countries with net working capital above the European Union average are the following: Italy, Belgium, Czech Republic, Sweden, Ireland, France, Spain, United Kingdom, Austria, Luxembourg, and Finland. This framework confirms the context previously described at the regional level. In fact, Portugal, Greece, some regions from Germany, and the Central and Eastern European Countries are the European member-states with lower average net working capital. Inversely, the farms which still have structural problems, such as those from Southern Europe (Portugal), manage their different resources with less working capital. In these frameworks, there are historical explanations, but also others that are related to endogenous specificities [10].

In terms of types of farming, the farms specialised in livestock production have, in general, higher average working capital than farms specialised in crop activities. Among livestock production, cattle, sheep, and goat farms are those with a lower working capital. In turn, among the crop activities, wine farms are those with greater working capital and olive farms are those with lower values for this financial indicator (Table 2). The particularities of each farming type influence the dynamics of their respective productions and the resource requirements, including working capital [77].

Table 3, with data for the representative farms considering together countries and farming types, confirms the higher values for the net working capital in countries such as Italy, Denmark, and the Netherlands and in farms specialised in granivores and milk. This explains that amongst the top40 European countries and types of farming for the average working capital appear the following combinations: Italy-Specialist granivores, Italy-Specialist milk, Denmark-Specialist granivores, Lithuania-Specialist granivores, the Netherlands-Mixed crops, Italy-Specialist cattle, Belgium-Mixed livestock, and Czechia-Specialist granivores. This context highlights, for example, the levels of liquidity in farms specialised in granivores, including in countries such as Lithuania, which when considered for the totality of farming production appears below the European average.

Farm size matters for the levels of net working capital is revealed in Table 4. In fact, the farms with greater economic size have higher levels of liquidity. This is also highlighted in Table 5.

The values for the net working capital range between 6,198 euros for the economic size 2,000 to <8,000 euros and 543,096 euros for the economic size ≥500,000 euros. The greater increases in the average working capital were from the first to the second class of economic size and from the penultimate to the last, showing that the greater changes, in terms of liquidity, are verified in the extremes. In other words, the smaller farms significantly increase their working capital when they grow, as well as, bigger farms (Table 4).

Bigger farms have higher working capital in countries such as (Table 5): Italy (2,324,913 euros), Lithuania (1,118,991 euros), Czech Republic (1,026,720 euros), Hungary, Romania, Spain, Ireland, Poland, and Bulgaria. This framework highlights the relevance of the average net working capital for bigger farms in these countries, and that significant parts of these are countries from Central and Eastern Europe. Germany and Luxembourg are amongst the European member-states where bigger farms have lower liquidity, 191,886 and 149,205 euros, respectively.

5 Results for spatial autocorrelation analysis

The results displayed in Table 6 were obtained with the GeoDa software [78,79] and were relative to the global (in this study, for the totality of the European countries) autocorrelation assessed through the Moran’s I values. These statistics may assume values between −1 and 1, where 0 means no spatial autocorrelation, negative values signify that the values of a variable in a country (in this study) is correlated negatively with the values of that variable in neighbouring countries, and positive results mean that the values of each variable are correlated positively between a country and its neighbours.

Beyond the problems of statistical significance, Table 6 highlights that the spatial autocorrelation is, in general, positive (with the exception for the current liabilities-to-total assets ratio) for profitability, financial performance, and working capital management variables (liquidity ratio, current assets-to-total assets ratio, and leverage ratio), however, for low values (below 0.5). The higher results were found for profitability, financial performance, and leverage ratio.

This weak spatial autocorrelation found for the global Morans’ I was obtained, also, for the local spatial autocorrelation (in this study, considering each country individually). The absence of a strong spatial autocorrelation for these variables means that European farms are not correlated in financial dimensions, signifying that each country has its specific working capital policy that is not influenced and does not influence the neighbouring member-states.

6 Results from panel data regressions

Tables 7 and 8 provide results obtained through the Stata software [73–75] and following Torres-Reyna [80] procedures for panel data. Torres-Reyna presents a useful explanation to interpret the results obtained for panel data with the Stata software. In these tables, the Prais-Winsten regression, correlated PCSEs) approach was considered to deal with cross-sectional dependence (Pesaran’s test of cross-sectional independence), heteroscedasticity (Modified Wald test for groupwise heteroscedasticity), and autocorrelation in panel data (Wooldridge test for autocorrelation). The statistical significance of the Pesaran’s test of cross-sectional independence, modified Wald test for groupwise heteroscedasticity, and Wooldridge test for autocorrelation signify, respectively, the presence in the data of problems relative to cross-sectional dependence, heteroscedasticity, and autocorrelation. The variance inflation factor (VIF) test reveals the absence of multicollinearity. The variables and models considered in this section, with the profitability and financial performance, as dependent variables, and liquidity ratio, current assets-to-total assets ratio, current liabilities-to-total assets ratio and leverage ratio, as independent variables, were selected and calculated following authors such as Azam and Haider [5] and Vuković et al. [1].

Profitability is positively explained by the current assets-to-total assets ratio (0.148 as marginal effect), current liabilities-to-total assets ratio (0.187 as marginal effect), and negatively by the leverage ratio (−0.131 as marginal effect). The liquidity ratio has no impact on the profitability of European farms, showing that the total current assets/short-term loans ratio is irrelevant for the profitability of these farms (Table 7). In turn, it is more relevant for the profitability of the relationships between the short-term loans with the total assets than with the current assets.

Similar patterns were found for financial performance (Table 8), nonetheless the marginal impacts from current assets-to-total assets ratio and current liabilities-to-total assets ratio are greater, showing that the current accountancy indicators (assets and liabilities) have more marginal impacts on the farms’ performance explanation rather than for the profitability analysis.

In any case, the results shown in Tables 7 and 8 highlights the importance to well-manage the current assets and the leverage, considering their, respective, positive and negative impacts on the European farms’ profitability and performance. On the other hand, investments in total assets require more current assets and liabilities to improve profitability and financial performance. In addition, increases in the total liabilities impact negatively on the returns on assets and on equity. These contexts call for policies with measures that support and promote the investments, but also the associated dimensions (better current assets and liabilities and better conditions to increase the total liabilities).

7 Discussion

With this research, the intention was to analyse the context of the working capital dimensions in European Union farms, considering data from the Farm Accountancy Data Network, over the period 2004–2018, disaggregated at country and agricultural regional levels, as well as disaggregated for the type of farming and farm’s economic size. These data were also worked through panel data regressions.

The literature review highlighted the particularities of the agricultural sector and the pertinence of adjusted policies to deal with these specificities. In fact, the particularities of the farming sector have implications in profitability [60] and financial performance [61]. These findings show that financial sustainability must also be a concern in the design of public policies for agriculture. These agricultural policies are particularly important in supporting farmers during financial difficulties, namely smallholders having greater difficulties to assess the financial markets. In general, the farmers found constraints in access to the amounts of credit needed and in the payment of the interest rates applied in the financial markets [34]. On the other hand, the scientific literature shows that working capital management practices have an effective impact on the profitability and financial performance, showing that the working capital dimensions should be adequately managed, namely current assets [54]. There are relevant insights that highlight the importance of the financial variables for the evolution of the European Union agricultural sector and, in this way, findings with added value for the policymakers.

In general, the data analysis for the average net working capital reveals that Central and Eastern European countries (that adhered to the EU in 2004) have lower levels of liquidity relative to the European average, showing the specificities of each European Union context, including from within these countries [10]. In addition, Italy is where a great part of the agricultural regions have, on average, higher levels of net working capital. Italy is a particular context inside the European Union which has specific accountancy conditions [59,81]. In turn, the livestock productions have, in general, greater working capital and the same happens with bigger farms (farms with higher economic size), showing the influence of the farm characteristics on these contexts. These findings show the importance of a CAP with instruments more adjusted to each reality, supporting, namely, those with more financial difficulties.

The panel data regressions show that the profitability (return on assets) and financial performance (return on equity) in European farms are, mainly, explained positively by the current assets on total assets ratio and current liabilities-to-total assets ratio and negatively by the leverage ratio. The debt financing is, indeed, a problem for any company, including for farms and related activities [59]. This framework highlights the importance of the working capital management for the farms’ dynamics and the impacts of the medium and long-term liabilities. In these cases, the interest rates also have their implications [36]. These results may be relevant contributions for the credit conditions and respective costs to be better addressed in future CAP reforms.

8 Conclusions, practical implications, policy recommendations, and suggestions for future research

For European Union farms, the relationships of the current assets and the liabilities (current and total) to the total assets have an impact on the profitability and financial performance unlike the relationships between the current assets and the current liabilities. In practice, the current assets and liabilities improve the profitability and performance when related to the total assets. On the other hand, the weight of the total liabilities on the total assets has a negative marginal effect, highlighting the negative impacts from the medium and long-term liabilities on the profitability and financial performance, where interest rates have great implications. These findings reveal the importance of easy credit access by European Union farmers and at low costs. In addition, it seems that the investment, and the consequent increase in fixed assets, has impacts on the financial farming conditions, justifying the financial support created by the European Union, but showing, also, that these instruments deserve further attention in future adjustments.

In particular, in the context of CAP, it could be important to design policy instruments to better deal with the profitability and financial performance frameworks, specifically creating conditions that reduce the medium and long-term liabilities and/or decrease the credit access costs. In addition, it is suggested that the policymakers create measures, in the context of the European Union policies which stimulate the weight of the current assets inside the total assets, with better institutional support, more diversification in credit supply and lower interest rates.

In future studies, it could be interesting to assess if the levels of net working capital found for the European Union farming context, namely, the higher values, are a consequence of thought management, or are occasional consequences. If these values are a consequence of a well-organised management, it could be interesting to identify the main explanatory factors. It could also be important to analyse the relationships between the working capital management and the levels of investment in European farms, namely, by assessing the impacts arising from the increase in fixed assets in medium and long-term liabilities and respective costs.