The effect of scale on the profitability and
capital structure of Dutch dairy farms
Pim Schipper
5673321
August 2014
of Amsterdam. The subject dairy firm is not in line with my study, which mainly discusses large listed companies. I have grown up on a farm and there arises my interest for the dairy sector.
Firm expansion is a major target for dairy firms and is viewed as necessary for
maintaining a profitable firm in the future. Although this is common knowledge in the sector there is not a lot of research that confirms this hypothesis. This article adds value at this point. It is written for farmers, consultants and other persons that are interested in the dairy sector.
This article is realized thanks to a few persons and institutions.
First of all I have to thank my UvA supervisor Jeroen Ligterink. He helped me to choose a subject very specific in the world of my interest, the dairy sector. Thanks to this research I expanded my study with much knowledge over small and medium enterprises and dairy firms, which is not in my normal study.
Second I have to thank Flynth, a Dutch consulting and accounting firm, with 40% of turnover in agriculture and horticulture. They provided the dataset for this study. Jan Breembroek (Director Agro) and Henk van Dijk (Database) have given me the chance to do this specific research and helped me to make good hypotheses.
Besides a very interesting dataset Flynth has given me the opportunity and space to have a look inside their organization. I have to thank them for their working space and the discussions on my article with my colleagues. I need to thank everybody from Flynth in Joure for a great time, especially Jan Kuiper who was my contact person and mentor.
Finally I have to thank my family and friends for reading the article, discussing my insights and helping to make this article readable.
Besides my study I am a professional ice speed skater and last year I opted for the Olympic Games of Sochi. Therefore I am very busy and have never worked full time on my thesis. Thanks everybody that worked with me for always being patient and giving me positive feedback.
2.! Literature review 4!
2.1! Effect of scale on the profitability 4!
2.2! Size and profitability as a determinant of capital structure 10!
2.2.1! Size as a determinant of capital structure 11!
2.2.2! Profitability as a determinant of Capital Structure 12!
2.2.3 ! Research questions for determinants of capital structure 16!
3.! Dataset and research method 17!
3.1! Flynth dataset 17!
3.2! Research method 20!
4.! Results 21!
5.! Conclusions and recommendations 29!
Bibliography 32!
Appendix 1 34!
Appendix 2 34!
1. Introduction
Dairy prices in the Netherlands have never been so high as on this moment (Boerenbussiness.nl, 2013). Unfortunately prices of feed, forage and fuel have increased as well. At the bottom line profits have decreased for farmers instead of increased (Boerenbussiness.nl, 2013). The last three years have shown a stable dairy price, but the increase in costs appears to be permanent. Due new regulations future dairy prices are expected to fluctuate more. Therefore dairy farmers should be prepared for lower dairy prices. Dairy farmers usually invest all their profit. This makes them vulnerable in the case of dairy price
fluctuation. Fluctuations of dairy prices bring attention to better or more financial reserves for farmers (Boerenbussiness.nl, 2013).
To create more financial reserves, firms can invest less, but it is better to create higher profits. Dairy farmers are price takers, they have little influence on the dairy price they receive. As a result, they are focused on lowering the cost price. One way to get a lower cost price is by economies of scale. Zijlstra and Kortstee (2006) describe increased scale as an important, or maybe the most important development for the going concern of a lot of Dutch dairy farmers. The enlarged scale should lead to cost price reductions, increased work efficiency and a better internal organization (Zijlstra & Kortstee, 2006). Through enlarged scale, cost price reduction and work efficiency can help to get higher profits, but what is the optimal scale? Stevens (2013, p. 4-7) describes an optimal scale for large organizations with or without staff. The organization without staff is optimal with a herd of 80-100 cows, while the organization with staff should have a herd of 400-500 cows. Stevens (2013) describes that bigger scale decreases cost per kg milk, but increased income is not inherent. Increased income in the first years after the investment is not assured because although the cost price of dairy drops, there is less income from other activities.
Stevens (2013, p. 44-46) describes that dairy farmers that had the biggest growth between 2007 and 2012 (an average growth of 175%) had higher labor efficiency but didn’t improve their cost efficiencies on the short term (due to
differences in regulations they are expected to improve on the long run) (Stevens 2013, p. 44-46).
Ham, Daatselaar, Prins en Hoop (2003, p.17) describe that after creating two groups of the 25% largest and 25% smallest farms, small firms have a higher cost price of almost 1,5 times the large firms. Meulen at al. (2011, p.58-59 and 64) also describe that the cost price is decreasing in companies with larger volumes. But in the cost price the benefits of increased scale fall at a larger scale, because of scale inefficiencies.
It becomes clear there may be economies of scale found for Dutch dairy farms. This economies of scale can be found in for example a lower cost price. In this article the effect of scale economies is examined using profitability instead of cost price. This is because cost price is partly estimated or calculated,
profitability describes the effect at the bottom line instead of what the expected cost are. In section three this is discussed in further detail.
This article investigates two subjects for Dutch dairy farms.
First this article will investigate what the effect is of scale on the profitability of the Dutch dairy farm. Do companies with a larger scale have a larger profit per kg output?
The second subject is capital structure of Dutch dairy farms. Instead of optimizing through increasing the scale, big improvements can be made in optimizing within the current scale (Stevens 2013, p. 44-46). What are the improvements that can be made to optimize within the current scale?
Hamerlinck and Eyckens (2013) describe that optimal scale depends on: herd size (dairy cattle and young cattle), labor, land and capital. Especially capital is a point of interest in this article. Which capital structure is optimal for dairy farms? Are there differences in capital structure for different categories of scale? On what basis is chosen for the existing capital structure? Is this done on basis of the trade-off or pecking order theory? Or the ratio of debt and capital is not selected, but just created by making use of the maximum amount of debt funding. In this article is investigated what influences the capital structure. Is it
determined by the size of the firm, or does it depend on the profitability of the firm. The variables size and profitability are specifically chosen because it helps to determine the most important variable in the development of the capital structure. If it depends on size, firms probably use debt to finance their growth investments. When it depends on profitability, the trade-off or pecking order theory are probably involved.
The second subject of this article tests how important size and profitability are as a determinant of capital structure. This will be done by the following two research questions: First what is the influence of the size of the firm on the amount of long-term debt per kg dairy delivered? The second research question is what is the effect of profitability and land tenancy on the amount of long-term debt per kg dairy delivered?
This article is important because it adds value on the following two points. First, a lot of Dutch research describes how economies of scale can be utilized in the dairy sector, but little research describes the statistic advantage of a larger scale (further discussed in section 2.1). This research will therefore describe what the cost reduction or profit impact is of this larger scale. Second this article discusses various theories and approaches for optimal capital
structure. Former researches are contradicting each other on the effects of scale and profitability on the capital structure. Small firms have a higher calculated cost of debt than large firms, the paid interest cost of large firms are however higher (Meulen et al. 2011, p. 84). For the relation between profitability and technical efficiency an article that reasons the other way around is discussed. This article describes contradicting results of former studies. Besides empirical results explained by one hypothesis can potentially be explained by another hypothesis (Hadley et al. 2001). Therefore this article clarifies the effects of scale and profitability on capital structure for Dutch dairy farms.
This article first reviews the literature. Previous research is discussed and hypotheses are formed. In section three the design of the Flynth dataset is
described and the research method is explained. In the fourth section the results will be discussed and compared to the outcomes of the literature review. In the last section this article will be concluded.
2. Literature review
In this chapter in the first part the effect of scale on the profitability is
discussed. Then in the second part size and profitability as determinants of the capital structure are discussed.
2.1 Effect of scale on the profitability
First is discussed why scale should influence the profitability of a firm. Then specific studies on the effects of scale within the dairy sector specifically are discussed.
By increasing the company size economies of scale can be achieved. Pindyck and Rubinfeld (2005, p. 237) describe this effect for general companies in the following way: when output increases, the firm’s average cost decreases, at least to a certain point. The decreases in cost arise from: specialization from workers, more effective production organization and more bargaining power in buying inputs.
However, at some point average cost rises when output increases, this is called diseconomies of scale. This can happen for the following reasons: thanks to a busy work floor, workers can’t do their work efficiently, or companies become too large and complex are therefore inefficient, or the benefits of bargaining power are exhausted (Pindyck & Rubinfeld, 2005, p. 237).
In general economies and diseconomies of scale reflect a U-shaped long-run average cost curve. For relatively low output levels there are economies of scale and for relatively high output levels diseconomies of scale (Pindyck & Rubinfeld, 2005, p. 237).
Economic theory describes economies of scale and an optimal scale size, because of the U-shaped average cost curve. But how is this optimal scale size defined within the dairy sector?
In the following scheme the main points of some researches are summarized. Hereafter these points are discussed.
Table 1: Summary of discussed articles regarding scale size for dairy farms Beldman et al. (2006)
Netherlands Farms with a production over 1 million kg have decreased revenues, but a more decreased cost per kg milk. Therefore a higher profitability.
Stigler (1958) Decrease in number of small firms points at small firms
being of suboptimal scale. Meulen et al. (2011)
Netherlands
Scale economies in profitability and cost price. Economies of scale flatten at a production of more than 500.000 kg. Large firms have higher modernity and lower solvency. The economic perspective of large firms is better.
Ham et al. (2003) Netherlands
Cost price calculation for different groups: 25% largest and 25% smallest firms: Small firms have an almost 1,5 time higher cost price than large firms. Labor is the most influential cost driver; it determines two-thirds of the cost price.
Knox Lovel and Mosheim
(2009) United States Estimated variable cost function: Scale economies are larger at all output levels. Thanks to correcting for economic inefficiency and other, no region of decreasing returns to scale.
Loyland and Ringstad
(2001) Norway Production elasticity function: Large unexploited scale economies. Possible to have an optimal scale in a given year. Technical change is scale augmenting
Jaforullah and Whiteman (1999) New Zealand
DEA analysis: 6% inefficiency due to suboptimal scale size. 53% farms below optimal scale, 28% above and 19% at optimal scale.
Meulen et al. (2011) describe that Dutch dairy farms have grown in the last decades. Over the period 1990-2008 average dairy cattle grew from 43 to 75, the average produced quantity of dairy doubled to 600.000 kg per farm and the average area of agricultural land grew from 24 to 45 ha (Meulen et al. 2011, p. 55-56).
A lot of Dutch research points out that scale of dairy farms increases, (like the statistic facts of Meulen et al. (2001)) but doesn’t mention the cost reduction, or profit impact of scale. The growth of dairy farms is only established and research focuses on how to manage these large farms.
The determination of growth of the average firm size can explain an optimal or suboptimal scale. Stigler (1958) describes in his study of economies of scale that the survivor technique seems to adapt well to determine the range of optimum size. Since the number of small dairy farms decreases, it could be stated that small scale doesn’t survive and is not at the optimal scale.
There are researches that do look at the effects of scale on the profitability of Dutch dairy farms. Beldman, Jager, Van Dellen and Zijlstra (2006) describe that there are almost 1000 dairy farms with a production of 1 million kg dairy in the Netherlands. These farms are characterized by higher production per staff and higher production per hectare of land compared to firms with a production smaller than 1 million kg dairy. The total revenues are €0,21 per 100 kg dairy lower, but total costs are €1,20 lower per 100 kg dairy. This means that farms with a big scale have higher profits than average farms (Beldman et al. 2006).
Scale economies can be found in the Netherlands. Later this will be discussed in further detail, but first some international research is discussed. Knox Lovell and Mosheim (2009) studied data drawn from the 2000 Agricultural Resource Management Survey. The aim of the study was to estimate the effect of scale economies without confusing this effect with the effect of economic
inefficiency and other. According to Knox Lovell and Mosheim (2009), the effects of scale and the effects of technical and allocative efficiency are often mixed up.
For their study they estimated a variable cost function, which they use to compare different scales. In this way the effect of “real” economies of scale are measured per scale size. The results of this study point to significant scale economies in U.S. dairy firms. More precise this study concludes that scale economies are larger at all output levels than previously expected. In contrast
to other research the average cost function does not have a region of decreasing returns to scale, no U-shaped, but a L-shaped cost function. This helps explain why the average size of U.S. dairy farms has grown (Knox Lovell & Mosheim, 2009).
In a Norwegian study done by Loyland and Ringstad (2001) four main issues concerning scale economies were explored. For this research a production elasticity function is used. Their findings were first that there are large unexploited scale economies in the Norwegian dairy production. Second that there is an optimal scale of operation in a given year. Third technical change is scale augmenting, because optimal scale increases slightly but significantly. The fourth point of investigation is the gain of exploiting full-scale economies. Their calculations, exploiting these full-scale economies suggest that in 1996 cost could be reduced by 27% and this would imply a reduction in dairy farms of 73% (Loyland & Ringstad, 2001).
Also in New Zealand the scale efficiency in the dairy industry is investigated. In the research of Jaforullah and Whiteman (1999) the relationship between farm size and efficiency is measured using non-parametric data envelopment analysis (DEA). The results indicate an overall technical inefficiency of 17%. From this 17%, 6% of this inefficiency is due to scale inefficiency and 11% due to pure technical inefficiency. This suggests that larger farm sizes would be beneficial for the efficiency. This should be taken with care, because this varies at the individual level, 53% of farms operate below their optimal scale, but 28% operate above their optimal scale. Finally 19% is operating at optimal scale (Jaforullah & Whiteman, 1999).
The international researches in New-Zealand, Norway and the USA, all refer to an average scale which can be enlarged, to create a more optimal scale size. Knox Lovell & Mosheim even describe a L-shaped cost curve and an infinite big scale size as optimal. This is in contrary to the Dutch research of Meulen et al. (2011, p.57). They describe that when profitability is taken in account (ratio of income and expenses) economies of scale can be found in the dairy sector.
These scale benefits however flatten at a production of 500.000 kg dairy. The biggest efficiency gain is at a production level below this volume. Table 2 indicates that profitability is increasing the most between the categories 0-400 and 400-900.
Table 2: Key figures for different scale sizes
Source: Meulen et al. 2011, p. 58 (Data Informatienet)
Meulen at al. (2011, p.58-59 and 64) describe that the cost price is decreasing in companies with larger volumes. The biggest cost price decreasing factor of a larger scale is the (calculated) cost of labor. The calculated cost of labor at smaller firms are a lot higher than on large firms, labor input per cow decreases with increased livestock (Meulen et al. 2011, p. 58-59 and 64).
In the next research on cost management in dairy farming, by Ham et al. (2003), the effect of scale is clearly illustrated. Ham et al. (2003) created a group of the 25% with the lowest cost and a group of 25% with the highest cost, the difference of cost price between these groups is € 0,20 per 100 kg dairy. The group of 25% with the lowest cost have a higher dairy production of 2,5 times and produce 40% more dairy per ha. of land than the average of the group with the highest cost (Ham et al. 2003, p.12-13).
Ham et al. (2003, p.17) also created two groups with the 25% smallest and the 25% largest firms (table 3). The difference between large and small firms is approximately comparable to the difference between the groups with high and low cost. However, the group with low cost makes it a little better than the group of large firms (Ham et al. 2003, p.17). The economic situation in the group of small firms is slightly less favorable than the group with a high cost
scale size category (x 1000 kg dairy)
dairy production (x 1000 kg)
profitabillity (%) cost price (euro cents / kg dairy) modernity (%) 0-400 294 74 56 32 400-900 625 89 47 36 900-1.350 1.073 100 42 42 >1.350 1.886 102 39 49
Dairy production, profitabillity, cost price, modernity per firm in 4 categories of different size, year 2008
price. This means that attention to cost is more important than just focus on large scale (Ham et al. 2003, p.17).
Ham et al. (2003, p.53) describe that their group of small firms have a cost price almost 1,5 times the cost price of their group of large firms. (Ham et al. 2003, p.51). Therefore there is more than only firm size that influences the cost price (Ham et al. 2003, p.53). But taken other things in consideration, they conclude that the scale of the firms in terms of delivered quantity of dairy is the most influential factor in the cost price (Ham et al. 2003, p.56).
Table 3:
Source: Ham et al. 2003, p. 54 (data Bedrijven Informatienet LEI)
In the last two researches the cost price is used to determine the difference in cost price for different scale sizes. Ham et al. (2003, p.51) describe that
two-Cost structure, revenues and income in euro per 100 kilograms of milk of 25% of specialized dairy farms with the smallest quantity of milk per farm and 25% with the largest quantity of milk per farm
for the financial years 1993/1994 and 1999/2000 and 2002
1993/1994 1999/2000 2002 1993/1994 1999/2000 2002 Ha feed surface 16,60 20,67 20,96 50,30 52,09 56,23 Dairy production / firm (x 1000 kg) 162 209 216 635 699 762 Dairy production/ ha (kg) 9.747 10.130 10.302 12.642 13.412 13.557 Total Variable 12,09 9,59 10,84 12,01 9,82 11,03 Labor 27,67 24,99 27,72 13,01 12,43 13,53 Total Fixed cost 51,10 50,70 55,22 34,53 34,09 37,27 Revenues other than Dairy 8,91 5,95 5,85 7,77 4,94 4,61 Dairy including levy 34,36 32,04 33,33 35,84 32,82 34,07 Cost price 54,28 54,34 60,21 38,77 38,97 43,69 Extra cost ownership basis 1,64 2,38 2,52 1,06 1,69 1,93 Paid interest 3,22 2,52 2,65 4,70 3,30 3,46 Family income from businesses 11,34 6,34 5,72 9,46 8,11 6,83 Total family income 16,34 11,56 10,67 11,00 9,42 8,31 Disposable income 14,56 9,87 9,31 9,45 7,96 7,19 Savings 1,20 0,79- 1,73- 3,85 2,42 1,60 Reservation capacity 8,26 7,64 6,06 8,97 11,27 11,08 Net cash 4,76 2,25 1,04 4,15 5,36 4,49 Critical selling price 29,60 29,79 32,29 31,69 27,46 29,58 Net operating profit 19,93- 22,31- 26,88- 2,93- 6,14- 9,62-Labor income 7,75 2,68 0,84 10,08 6,29 3,91 Debt 43,77 62,68 67,64 65,07 79,15 89,88 Repayment rate debt 5,1 9,7 10,7 7,6
Modernity (%) sustainable 43,5 39,9 50,6 42,9 means of production
thirds differences in cost price are determined by cost of labor. Labor cost however is the cost driver which directly paid share is only 5% (Ham et al. 2003, p.51). Unfortunately, labor cost of farmers is hard to measure, because they generally have no hour’s registration of their own working hours and their wage payment is indirectly through company profit. Therefore this labor cost is usually a calculated cost. To overcome this calculated uncertainty in this article a dataset is used without this calculated cost. This will be discussed in further detail in section 3.
In this paragraph the effect of scale on dairy farms is discussed. These
economies of scale can be found in for example cost price. Because revenue/kg is almost fixed, this directly influences profit. It is expected that a larger scale size gives greater profit. Therefore the first hypothesis of this article is: companies with a larger scale have greater profit per kg output.
2.2 Size and profitability as a determinant of capital structure
This section investigates the drivers of capital structure decisions. It discusses the theoretical effects of scale size and profitability on the capital structure of Dutch dairy firms. First, the relation and effects of scale size on capital structure is discussed in section 2.2.1. Second the relation and effects of profitability on capital structure is discussed in section 2.2. Finally in section 2.2.3 the research questions for these two relations are defined.
Before the theoretical effect of scale and profitability on capital structure will be discussed, first the current capital structure of Dutch dairy firms is
discussed. The assets side of a dairy firm consists of livestock, stables, land, machinery and equipment, stocks, working capital, etcetera. The liabilities side consists of long-term debt, short-term debt, equity (personal net wealth), loans,
creditors and other payables. In the Flynth dataset1 there is no statement of
private equity worth mentioning. On average the capital structure for firms in the Flynth dataset is divided in following way: 52% is funded with equity (personal net wealth), 39% is funded with long-term debt, 4% is funded with short-term debt (the complete table can be found in Appendix 1).
2.2.1 Size as a determinant of capital structure
Theoretically firms with an optimal scale are more efficiently deployed and profitable, than firms with a suboptimal scale. Therefore these firms are better able to pay off liabilities and debt. Meulen et al. (2011) describe that the (calculated) capital cost per kg dairy is higher in small firms. This means that capital cost (calculated) for small firms are higher than large firms. One explanation for this is that smaller companies have lower dairy output per hectare (The production factor land is the most expensive, low production per hectare ensures a higher capital cost). At these smaller firms land and other assets are likely less efficiently deployed. In contrast the paid interest per kg dairy are a lot higher per kg dairy for large firms. This is due to differences in funding (Meulen et al. 2011, p. 58-59).
Different ways of funding between large and small firms provide for
differences in observed capital costs and expected capital costs. Meulen et al. (2011) describe that large firms have a significant lower solvency, less equity relative to total assets. This is mainly determined by recent investments in expansion; milk quota, land, or extension of buildings (Small firms have a large portion of their loan repaid). Large firms have a debt per kg dairy of € 1,60 while small firms have a debt per kg dairy of less than € 1,- (Meulen et al. 2011, p. 60).
Despite more debt per kg of milk, large firms are expected to be more
efficiently deployed and have lower calculated capital cost per kg dairy. Their debt / kg and paid interest cost however are higher. The difference between calculated capital cost and paid interest cost is determined by the relative
1 Flynth, a Dutch consulting and accounting firm, with 40% of turnover in
agriculture and horticulture, the dataset contains fiscal numbers from the financial statements for the year 2012, this is further discussed in section 3
amount of equity (personal net wealth) used for the firm. Small firms have higher solvency and therefore use relatively more equity. In the calculated capital cost price, the cost of equity (personal net wealth) is included, in the paid interest cost price this not. Therefore despite the higher paid debt costs, it can be stated that larger firms have a better economic perspective for the future, than small firms (Meulen et al. 2011, p. 84).
Summarizing previous research describes that the calculated cost of capital are higher for small firms than large firms. However in practice shows that debt is greater per kg in large companies than small companies.
2.2.2 Profitability as a determinant of Capital Structure
In the latter part the relation between scale size and the cost of capital is discussed. Now the relation between profitability and capital structure is
discussed. Profitability can influence the capital structure, because profit can be used for new investments, share repurchases or to pay off liabilities. But on the other side a tax shield created by debt may be advantageous to profitable firms. There are several prevailing theories on the composition of the optimal capital structure. Of these theories, first the trade-off theory and pecking order theory are discussed. Then agency costs and other perspectives are discussed.
How should firms finance their operations and what factors should influence these choices? Frank and Goyal (2008) describe the contest between two perspectives on corporate debt. First the trade-off theory, which states that firms balance their tax shield from debt against the deadweight costs of bankruptcy. The second perspective is called the pecking order theory which states that firms look first at retained earnings, then debt and finally in extreme circumstances to equity for financing. These theories have the following key characteristics. First the trade-off theory is characterized by target adjustments. Deviations from the leverage target are gradually eliminated. The pecking order theory is characterized by strict ordering of the use of funds (Frank and Goyal, 2008).
In the previous paragraph the trade-off theory and pecking order theory are described. Now these theories are applied more specifically for dairy farms. Appendix 2 shows net profit for average dairy farms from the Flynth dataset for the years 2002-2013. Interest costs clearly depreciate net profit with 30-50%. This means that the tax-shield of debt is effectively. With this data however cannot be said that the firms make target adjustments on their amount of debt.
Dairy farms are highly funded with net personal wealth (52%, see appendix 1). This is consistent with the pecking order theory. The second most important source of finance is debt (long-term debt 39%, short-term debt 4%). Finally, shareholders other than the manager/major shareholder are rare in the dairy firm sector. In the Flynth dataset this financial statement is not worth mentioning (Appendix 1). Therefore, share issue or private equity (bringing external ownership into the company) is exceptional in the dairy sector. The described characteristics are consistent with the pecking theory. First
investments are funded using net personal wealth, second debt is used as funding method and finally (exceptional) external equity or private equity is used as funding method. There are arguments for the adoption of both the trade-off theory and the pecking order theory. Further research needs to investigate this more carefully before any conclusions can be drawn. In the latter paragraph the characteristics of the trade-off and pecking order theory are discussed for the dairy sector. An attempt was made to indicate that the capital structure is best explained by the trade-off theory or pecking order theory. In the next paragraph the relation between profitability and capital structure is described by several different theories. The relation is somewhat similar, but the chosen variables are a little different. Instead of profitability, technical efficiency is used. And instead of capital structure, debt/assets ratios are used. But most important profitability or technical efficiency is explained by debt/assets ratios. The depending variables are now the explanatory
relationships found, where the causality runs from profitability to capital structure.
Hadley, Shankar, Thirtle and Coelli (2001) describe three different articles with in total five different hypotheses to describe the relation between technical efficiency and debt/assets. From this five theories, the first three hypotheses fall under the heading of agency theory. All these five theories are first described; their contradicting results are discussed afterwards.
-Agency costs/ Asymmetric information (Nasr, Ellinger and Barry, 1998) Asymmetric information creates monitoring costs by lender. Monitoring involves costs and these costs are passed on to the borrowers. Therefore higher indebted farms are higher cost farmers, and therefore less technical efficient. -Free Cash flow (Nasr, Ellinger and Barry, 1998) Large asset holdings and excess cash flows encourage managerial laxness. Therefore more debt and higher financial exposure leads to higher efficiency.
-Credit Evaluation (Nasr, Ellinger and Barry, 1998) Only low cost and high efficient firms are evaluated positively to receive new loans. Therefore the causality runs from efficiency to higher debt and this relation is positive. -Embodied Capital (Chavas and Aliber, 1993) Technical change is with great cost. This is typically financed with debt and therefore firms with higher debt profiles appear to be leading the technical change. This implies a positive relationship between debt/assets and technical efficiency.
Adjustment (Paul, Johnston and Frengley, 2000) In a New Zealand survey the impact of a regulatory reform is studied. The transition from a subsidized system to a less sheltered system forces farmers to be more efficient. The research points out that less indebted farmers are better able to adjust and therefore are more efficient.
There are two hypotheses that describe a negative relation between debt/assets and technical efficiencies. The first hypothesis “Agency cost / Asymmetric
information” is rejected by Nasr, Ellinger and Barry (1993). The second negative hypothesis is the “Adjustment” hypothesis.
In contrary to the negative relation described by the latter two hypotheses, the “Free Cash flow”, “Credit Evaluation” and “Embodied Capital” hypotheses describe a positive relation. The results are therefore not unanimous.
Another interesting given is that there is no conflict of interest between owner and manager, since this is the same person in the dairy sector. Therefore the free cash flow problem should be smaller. However tight budgets thanks to heavy debt funding may help to have a more efficient production.
The last five hypotheses are inconclusive, but all describe a positive or negative relation between profitability and capital structure. Hadley et al. (2001)
underlines this and describes that production measures are significantly affected by financing issues. However the following points arise: - empirical results contradict each other
- empirical results explained by one hypothesis can potentially be explained by another hypothesis
The research of Hadley et al. (2001) differs from the latter hypotheses, because it analyses the influence of different individual variables on technical
efficiency. This article explains that an increase in debt ratios, farmer age, or location in a less favored area lead to a decrease of technical efficiency. In contrast increase of the herd size and the size of land tenancy provide greater technical efficiency (Hadley et al. 2001).
In the last research of Hadley et al. (2001) the influence of multiple variables on technical efficiency are tested. This article has the same study design for this research question as the research of Hadley et al. (2001) with another dataset. However, there are quite a few deviations from the original. The explanatory and dependent variables are vice versa and from the original variables only technical efficiency, debt ratios and land tenancy are used. In addition, no use is made of technical efficiency and debt ratios, but respectively
profitability and the amount of debt per kg of milk. This research differs from the original in the case of the depending and explanatory variables. It is a conscious choice to approach this relation with many old conflicting
conclusions from a different angle. The research is therefore less comparable, but new insights may be found.
In summary, the following is discussed in section 2.2.2: In total 6 theories on the relationship between debt/assets and technical efficiency are described. Of these theories
- 2 theories describe a negative relation, - 3 theories describe a positive relation - 1 theory is rejected.
This research question somewhat resembles the article of Hadley et al. (2001). The effect of profitability and land tenancy on debt per kg dairy is tested. 2.2.3 Research questions for determinants of capital structure
In this section first in 2.2.1 the relation between size and capital structure is discussed. Here the theory and practice on the capital cost contradict one another. Therefore this relation between firm size and capital structure is investigated. Second in 2.2.2 the relation between profitability and capital structure is discussed. There are a lot of different theories on this subject and they also have different empirical relations (sometimes even contradicting). Therefore as exemplified by Hadley et al. (2001) the effect of profitability and land tenancy on the capital structure is tested.
To answer the question, what is the influence on the capital structure? The capital structure should be defined in terms of a measurable quantity. Here is chosen for the amount of long-term debt per kg dairy delivered, because in this way firms are comparable.
In summary, this section provides the following research questions. First what is the influence of the size of the firm on the amount of long-term debt per kg dairy delivered? The second research question is what is the effect of
3. Dataset and research method
In the first part of this section the Flynth dataset is described and some key figures are shown to give an overview of the data. In the second part the research method is explained and the estimated models per hypothesis are presented.
3.1 Flynth dataset
In this part first the dataset is described, then summary statistics are displayed in table 4 and finally the chosen variables for this article are described.
Flynth, a Dutch consulting and accounting firm, with 40% of turnover in agriculture and horticulture provide the dataset for this study. 20% of Dutch agricultural companies throughout the Netherlands are clients of Flynth. Therefore, the dataset provides a good picture of the average business in the Netherlands. This dataset uses the financial report of 1521 dairy farms in the Netherlands.
The data for this report are also the data for the fiscal report. An advantage of this fiscal data is that it only makes use of actual costs. There are no estimated costs, for example for the number of working hours. In contrary to former researches this research doesn’t use data of a cost price. Instead of cost price, this article uses earnings data. This takes away the uncertainty in cost price of the (partly) estimated cost of labor.
Table 4: Summary statistics
Source: Flynth dataset 2012
The chosen variables for this article are the following:
-Gross Surplus (X0)
Gross Surplus is an important variable to determine profit. It is defined as net profit, but before the payment of interest, taxes, depreciations and
amortizations. In this specific agricultural case it is also before tenancy and milk-quota costs.
The Flynth dataset consist of fiscal data, therefore net profit is always as low as possible using investments, carry back, carry forward, increased depreciations, etc. to pay a minimum or no taxes. But since (fiscal) net profit is always as low
Summary'statistics'from'sample
Variable Average Standard/
Deviation Minimal/Value Maximal/Value
Net$profit$(€) 44.896 50.841 5321.365 418.212 Gross$surplus$(€) 150.619 86.053 25.260 1.159.606 Gross$surplus/100$kg$(€)** 20 4 8 33 FPCM$per$farm$(kg)* 790.863 401.387 265.022 6.120.312 FPCM$per$ha$(kg)* 17.088 5.120 7.495 50.081 FPCM$per$cow$(kg)* 8.704 996 5.219 11.468 Herd$size$dairy$cows 91 47 28 877 Total$Land$Areal$(ha) 48 23 12 460 Total$Assets$(€) 1.971.992 1.414.967 201.033 13.406.589 Total$Equity$(€) 1.059.953 1.117.114 51.055.269 10.219.082 Debt$(€) 831.954 709.379 0 7.690.500 Debt$/$100$kg$(€)** 105 58 0 413 Debt$ratio 0,48 0,31 0,00 3,27 Equity$ratio 0,47 0,33 51,81 1,03 Tenancy$ratio$(%) 30 26 0 100 Modernity$(%) 48 32 number$of$farms 1521 *$FPCM$is$Fat$Protein$Corrected$Milk,$quantity$of$milk$corrected$for$fat$and$protein. **$quantity$is$defined$as$kg$milk$delivered$to$dairy$factory,$not$FPCM
as possible net profit would not reflect the financial position of the company. In order to avoid this skewed picture the gross surplus is used instead of net profit to compare firms. Gross surplus has another advantage, it is EBITDA, but also before agricultural tenancy, and milk-quota costs. In this way, firms with different forms of finance for land and property (tenancy) can be well compared.
-Gross Surplus / kg FPCM (X1) This variable represents the gross surplus per
kg FPCM milk. In this way small and large firms can be compared.
-Fat Protein Corrected Milk (FPCM) (X2) represents the quantity of milk
corrected for fat and protein. Because not every farmer has the same fat and protein in milk, this is corrected, so that the quantity of milk is converted to 4.00% fat and 3.30% protein. The FPCM is calculated according to the following formula:
FPCM = (0.337 + 0.116 x% fat + 0.06 x% protein) x kilograms of milk (Remmelink, van Dooren, van Middelkoop, Ouweltjes, and Wemmenhove, 2013, p. 6_9).
-Dummies scale size in quantity of FPCM
(DL) This dummy states 1 if the current farm has a production that belongs to
the 25% smallest farms in the dataset (production of less than 533.100 kg FPCM) (later defined as small firms).
(DH) This dummy states 1 if the current farm has a production that belongs to
the 25% largest farms in the dataset (production of more than 955.772 kg FPCM) (later defined as large firms).
The relation of the output size in kg dairy (X2) and the depending variables
gives a non-significant result. Therefore, as chosen by Ham et al. (2003) dummies for the 25 percent largest and smallest companies are used.
-Land tenancy ratio (X3) presents the ratio of rented/tenanted land to total feed
-Modernity (X4) is a measure of the replacement of fixed assets such as
buildings and machinery. A low or declining modernity indicates that the company is aging. Modernity is calculated by dividing the book value of buildings and machinery at end of year through the purchase price.
-Debt (X5) represents the amount of long term liabilities. This includes
mortgages and long-term (family) loans.
-Debt/ kg FPCM (X6) represents the amount of debt per kg FPCM.
3.2 Research method
The introduction (section 1) describes two subjects and three research questions for this article. First do companies with a large scale have a larger profit / kg output? Second how important are size and profitability as determinants of capital structure.
This article investigates these two questions with three hypotheses. These hypotheses are now described one by one.
The first hypothesis is: Companies with a greater scale have a greater profit per kg output.
This hypothesis is tested with the following model: X1 = β0 + β1 DL + β2 DH + β3 X3 + β4 X4
In this hypothesis X1 Gross Surplus / 100 kg FPCM is declared by the dummies
for a large and small firm size (DL; DH), but also by the variables tenancy ratio
(X3) and modernity ratio (X4). Tenancy ratio is included to test the effect of this
different funding method (funding of land or property using tenancy). Higher modernity due to new investments can have a positive relation with Gross Surplus. The higher interest cost of investments in new buildings is not included in Gross Surplus. But the lower maintenance cost for these new buildings are advantageous to the gross surplus.
The second hypothesis states that the scale of the firm affects the amount of debt per kg.
X6 = β0 + β1 DL + β2 DH + β3 X3 + β4 X4
In this hypothesis X6 Debt / 100 kg is declared by the dummies for a large and
small firm size (DL; DH), but also by the variables tenancy ratio (X3) and
modernity ratio (X4). Tenancy is a different funding method for the land or
property in use. Higher tenancy ratio leads to lower debt/kg FPCM, because there is less financed with debt. Modernity is added because it can be used to explain heavy debt funding due to investments in new buildings.
The last hypothesis describes that the profitability per kg and land tenancy affects the amount of debt per kg.
X6 = β0 + β1 X1 + β2 X3
In this hypothesis the effect of an increase in profitability (Gross surplus per
100 kg, X1) and land tenancy (X3) is tested on the amount of debt finance (debt
per 100 kg, X6).
Here the relationship between Gross surplus per 100 kg and debt / 100 kg is tested. The variable land tenancy is included to take away the bias of a different funding method for land.
Hypotheses are tested with Ordinary Least Squares (OLS) as research method. Multiple regressions are performed to test the relation of multiple independent variables on the explained variable.
4. Results
The analysis of the data will be carried out as follows:
First the dataset is categorized in five groups with dairy farms divided by quantity of milk delivered (this method is similar to the research of Meulen et al. (2011)). These groups are compared on indicators like gross-surplus per kg milk delivered, debt per kg milk, financial reservation capacity, repayment
obligation, investments and modernity. This gives a good picture of the distribution of the data and the characteristics of different scale sizes.
Then the dataset is split up in two groups, the largest and smallest 50 percent,
in terms of delivered quantity dairy. These groups will be compared on sample averages and a t-test will be performed to determine if they are significantly different. In the latter part becomes clear that there are differences between a large and a small-scale size.
In table 5 a few differences can be detected. For instance the Gross surplus / 100 kg seems to be higher for large firms; the same can be said for margin.
group&1 group&2 group&3 group&4 group&5
Number&of&firms 304 304 304 304 305
FPCM&/&firm&(kg)* &&&&&&&&&404.428 &&&&&&&&&568.725 &&&&&&&&&710.758 &&&&&&&&&897.004 &&&&&&&1.371.491
Total&feed&areal&(ha) 29,5 37,9 44,2 52,9 73,2
FPCM&per&ha&(kg/ha)* &&&&&&&&&&&14.432 &&&&&&&&&&&15.983 &&&&&&&&&&&16.972 &&&&&&&&&&&18.028 &&&&&&&&&&&20.017 FPCM&per&dairy&cow&(kg)* &&&&&&&&&&&&&8.135 &&&&&&&&&&&&&8.567 &&&&&&&&&&&&&8.763 &&&&&&&&&&&&&8.979 &&&&&&&&&&&&&9.077 Gross&surplus €&&&&&&&&&73.360 €&&&&&&&&106.524 €&&&&&&&&132.047 €&&&&&&&&172.375 €&&&&&&&&268.399 Gross&surplus&per&100&kg&dairy** €&&&&&&&&&&&19,42 €&&&&&&&&&&&20,09 €&&&&&&&&&&&19,79 €&&&&&&&&&&&20,45 €&&&&&&&&&&&20,73 Debt €&&&&&&&&320.465 €&&&&&&&&535.052 €&&&&&&&&739.519 €&&&&&&&&917.471 €&&&&&1.644.590 Debt&per&100&kg&dairy** €&&&&&&&&&&&82,34 €&&&&&&&&&100,36 €&&&&&&&&&110,57 €&&&&&&&&&108,41 €&&&&&&&&&125,18
Tenancy&ratio 28% 29% 31% 32% 29%
Modernity&ratio 41% 46% 50% 51% 52%
Total&Assets €&&&&&1.092.282 €&&&&&1.427.194 €&&&&&1.798.944 €&&&&&2.176.899 €&&&&&3.360.074 Equity*** €&&&&&&&&731.095 €&&&&&&&&844.189 €&&&&&&&&996.205 €&&&&&1.170.661 €&&&&&1.555.986
Solvability 57% 51% 45% 46% 42% €&/&100&kg&dairy** Total&revenues 41,01 41,33 41,04 40,96 40,69 Direct&cost 15,09 15,04 15,20 14,85 14,95 Margin&Dairy&cattle 25,91 26,30 25,84 26,10 25,73 Additional&income&and&other 6,13 5,81 5,04 4,95 4,57 Margin&farm 32,04 32,11 30,88 31,06 30,31 Total&indirect&cost 20,42 20,86 20,66 20,73 20,78 Operating&profit 11,63 11,25 10,22 10,33 9,53 After&tax&interest 3,56 4,24 4,23 4,01 4,39 Net&profit 8,06 7,02 5,99 6,32 5,14 Critical&dairy&price 34,70 35,28 35,26 34,10 33,46 Dairy&revenues 36,72 36,98 36,94 36,88 36,63 Margin 2,02 1,70 1,67 2,78 3,17 Available&for& privat/repayments/reservations 11,79 11,45 11,34 11,72 11,63 *&FPCM&is&quantity&of&Fat&Protein&Corrected&Milk **&dairy&is&in&this&table&defined&as&quantity&of&milk&delivered&to&dairy&factory ***&probably&private&equity&of&owner/manager
Table 5: Dataset divided in 5 groups of different quantity
Modernity seems to be increasing for larger firms, just like debt / 100 kg. In table 6 these differences are displayed in two groups and tested with a t-test. Table 6: Dataset divided in groups of smallest and largest 50%
Source: Flynth dataset 2012
Table 6 shows that gross surplus / 100 kg is significantly higher for large firms than small firms. The same can be said for the higher modernity of large firms and the margin / 100kg. The solvability and critical dairy price are significantly lower for large firms. In contrary to what is expected in this paper net profit / 100 kg is significantly lower for large firms. But this can be explained by the difference between fiscal profit and real profit. Therefore in the next regression analyses is chosen for gross surplus / 100 kg instead of net profit.
Dataset÷d&in&2&groups 0250% 502100%
Number&of&firms &&&&&&&&&&&&&&&&& 760 &&&&&&&&&&&&&&&&& 761 FPCM1&/&firm&(kg) &&&&&&&&&&&& 523.624 &&&&&&&&& 1.058.667 **
Total&feed&areal&(ha) &&&&&&&&&&&&&&&&&&& 35 &&&&&&&&&&&&&&&&&&& 60 ** FPCM1&per&ha&(kg) &&&&&&&&&&&&& 15.492 &&&&&&&&&&&&& 18.692 **
FPCM1&per&dairy&cow&(kg) &&&&&&&&&&&&&&& 8.423 &&&&&&&&&&&&&&& 8.986 **
** Gross&surplus €&&&&&&&&&&&& 96.441 €&&&&&&&&&& 204.935 ** Gross&surplus&per&100&kg&dairy2 €&&&&&&&&&&&&& 19,70 €&&&&&&&&&&&&& 20,50 **
**
Debt €&&&&&&&&&& 477.145 €&&&&&&&&1.186.726 **
Debt&per&100&kg&dairy2 €&&&&&&&&&&&&& 94,51 €&&&&&&&&&&&& 116,14 **
Tenancy&ratio 29% 31%
Modernity&ratio&% 44% 52% **
Total&Assets €&&&&&&&&&1.359.893 €&&&&&&&&&2.586.505 **
Equity3 €&&&&&&&&&&&836.634 €&&&&&&&&&1.285.558 **
Solvability 52% 44% **
€&/&100&kg&dairy2
Total&revenues &&&&&&&&&&&&&&&&&&& 41 &&&&&&&&&&&&&&&&&&& 41 * Direct&cost &&&&&&&&&&&&&&&&&&& 15 &&&&&&&&&&&&&&&&&&& 15 Margin&Dairy&cattle &&&&&&&&&&&&&&&&&&& 26 &&&&&&&&&&&&&&&&&&& 26 Additional&income&and&other &&&&&&&&&&&&&&&&&&&& 6 &&&&&&&&&&&&&&&&&&&& 5 ** Margin&farm &&&&&&&&&&&&&&&&&&& 32 &&&&&&&&&&&&&&&&&&& 31 ** Total&indirect&cost &&&&&&&&&&&&&&&&&&& 21 &&&&&&&&&&&&&&&&&&& 21 Operating&profit &&&&&&&&&&&&&&&&&&& 11 &&&&&&&&&&&&&&&&&&& 10 ** After&tax&interest &&&&&&&&&&&&&&&&&&&& 4 &&&&&&&&&&&&&&&&&&&& 4 * Net&profit &&&&&&&&&&&&&&&&&&&& 7 &&&&&&&&&&&&&&&&&&&& 6 ** Critical&dairy&price &&&&&&&&&&&&&&&&&&& 35 &&&&&&&&&&&&&&&&&&& 34 ** Dairy&revenues&/&100&kg &&&&&&&&&&&&&&&&&&& 37 &&&&&&&&&&&&&&&&&&& 37 * Margin &&&&&&&&&&&&&&&&&&&& 2 &&&&&&&&&&&&&&&&&&&& 3 ** Available&for&privat/repayments/reservations &&&&&&&&&&&&&&&&&&& 12 &&&&&&&&&&&&&&&&&&& 12
1&&FPCM&is&quantity&of&Fat&Protein&Corrected&Milk
2&&dairy&is&in&this&table&defined&as&quantity&of&milk&delivered&to&dairy&factory 3&&probably&private&equity&of&owner/manager
*&&&&only&one&sided&significant&α=0,05 **&&two&sided&significant&α=0,01
In the latter part the difference between large and small firms are presented for individual variables. But what is the influence of the variables when they are tested in a multiple regression using OLS?
From the regression results must be taken into account, the following estimation problems: first the correlation matrix in Appendix 3 shows that correlations between different variables are sometimes higher than 0.4 (apart from diagonal elements), this may indicate multicollinearity in the estimates.
Second the R2 of the different regressions are not high (well beyond 0,10). This
lack of predictive value of the model may indicate the absence of some explanatory variables.
In the next part the results are presented for the hypotheses and their
regressions which where explained in chapter 3. The results are explained and discussed per hypotheses.
The first hypothesis is: Companies with a greater scale have a greater profit per kg output.
Table 7: OLS Regression on Gross Surplus / 100 kg
The table presents the regression on Gross Surplus / 100 kg FPCM.
Regression outputs 1 to 4 present the effect of different models, with model 4 as the most extensive model. Standard errors are in parentheses, ***, ** and * denote statistical significance at the 1, 5 and 10% level, respectively.
Variable (1) (2) (3) (4) Intercept 20,0685 *** 20,0762 *** 19,9335 *** 19,9469 *** (0,15) (0,21) (0,19) (0,25) Small firms DL -0,4696 * -0,4624 * -0,4601 * -0,4534 * (0,25) (0,25) (0,25) (0,25) Large firms DH 0,5715 ** 0,5789 ** 0,5708 ** 0,5779 ** (0,25) (0,25) (0,25) (0,25) Tenancy ratio X3 0,0045 0,0043 (0,004) (0,004) Modernity ratio X4 -0,0003 -0,0003 (-0,003) (-0,003) R2 0,008 0,008 0,009 0,009 # observations 1520 1520 1520 1520
In the regression presented above in table 7, the following relations become
clear: first firms with a production of lower than 533.100 kg FPCM (DL=1)
(small firms) are expected to have a lower Gross surplus / 100 kg of € 0,45.
Second firms with a production of more than 955.772 kg FPCM (DH=1) (large
firms) are expected to have a higher Gross surplus / 100 kg of € 0,58. Finally the relation between the variables Tenancy and Modernity are not significant different from zero.
Small firms have a lower Gross surplus / 100 kg and large firms a higher surplus. This is in line with the described literature in section 2.1. Ham et al. describe that small firms have a cost price 1.5 times higher than large firms. The differences found in gross surplus in table 7 are less large, but significantly different from zero. Meulen et al. (2011) describe that scale economies flatten at a production of more than 500.000 kg. The found higher Gross surplus / 100 kg of € 0,58 for large firms contradicts this. It seems that the described U-shaped cost function is less strong and that scale diseconomies are less
important than described. This is inline with the research of Knox Lovell & Mosheim.
Since there are some regression problems, the results should be treated with caution. Multicollinearity and missing variables are indicated; therefore the causality of the results may not be used. The results may only be used to describe the positive or negative relation.
It can be concluded that large firms have a greater gross surplus per kg than small firms. This gross surplus per kg also has a multiplier effect. Large firms produce more kg dairy and as long as they are profitable, they make more profit due their large production. When large firms make more gross surplus than small firms, this extra gross surplus should also be multiplied by this larger quantity.
Table 8: OLS Regression on Debt / 100 kg
The second hypothesis states that the scale of the firm affects the amount of debt per kg.
X6 = β0 + β1 DL + β2 DH + β3 X3 + β4 X4 (regression (2) table 8)
This first two and last regressions present the effect of scale on the amount of debt / 100 kg. Here the following relations become clear (regression 2): first
firms with a production of lower than 533.100 kg FPCM (DL=1) (small firms)
are expected to have a lower amount of debt / 100 kg of € 20,55. Second firms
with a production of more than 955.772 kg FPCM (DH=1) (large firms) are
expected to have a higher amount of debt / 100 kg of € 17,69. Third the relation between the variable Tenancy and debt per kg is that firms with a Tenancy percentage of 1% more have a decreased amount of debt / 100 kg of € 0,26. Finally the relation between the variable Modernity and debt / 100 kg is not significant different from zero.
Also here there are some regression problems, the results should be treated with caution. Multicollinearity and missing variables are indicated; therefore
This table presents the regressions on Debt / 100 kg
Regression outputs 1 and 2 estimate the effect of scale on the capital structure Outputs 3 and 4 estimate the effect of profitability on the capital structure.
Output 5 is the most extensive model. Here the effect of scale and profitability are both measured. Standard errors are in parentheses.
***, ** and * denote statistical significance at the 1, 5 and 10% level, respectively.
Variable (1) (2) (3) (4) (5) Intercept 106,041 *** 112,831 *** 86,1543 *** 92,4752 *** 99,0545 *** (2,05) (3,42) (7,500) (7,607) (7,882) Small firms DL -20,157*** -20,547 *** -20,234 *** (3,55) (3,53) (3,53) Large firms DH 17,48 *** 17,69 *** 17,2888 *** (3,55) (3,53) (3,53) 0,9579 *** 1,0045 *** 0,6906 * (0,366) (0,364) (0,356) Tenancy ratio X3 -0,259 *** -0,2437 *** -0,262 *** (0,06) (0,058) (0,06) Modernity ratio X4 0,019 0,0196 (0,04) (0,04) R2 0,053 0,066 0,004 0,016 0,068 # observations 1521 1520 1521 1520 1520 Gross0Surplus0/01000 kg0FPCM
the causality of the results may not be used. The results may only be used to describe the positive or negative relation.
It becomes clear that larger firms are funded with more debt than small firms. This is in line with the research of Meulen et al. (2001), which describes that large firms in practice have more debt per kg dairy.
This is in contrast to theory, which describes that large firms are more
efficiently deployed and have lower capital cost per kg dairy. And vice versa, small firms are less efficiently deployed and have higher capital cost. This difference can be explained by the difference in relative amount of equity (personal net wealth) for the firm. Small firms have higher solvency (equity relative to total assets) and therefore use more equity. The cost of this equity (personal net wealth) is not included in the database or in the regression made here.
More research is necessary to investigate the real difference in capital cost for dairy farmers. But it is hard to overcome the difficulties of estimating the cost of personal net wealth of farmers. For this article it can be concluded that debt / kg dairy increases when firms are larger.
The last hypothesis indicates that the profitability per kg and land tenancy affects the amount of debt per kg.
X6 = β0 + β1 X1 + β2 X3
This last hypothesis is tested in table 8 in regressions (3), (4) and (5). The fourth regression presents the effect of profitability and land tenancy on the amount of debt per 100 kg. Here the following relation becomes clear: Every euro improvement in Gross surplus / 100 kg is related to an increase of the debt / 100 kg by € 1,00. Every percent of extra land tenancy is related to a decrease of debt / 100 kg by € 0,24.
The effect of land tenancy cannot be compared to the discussed researches, because it describes the effect on a different depending variable. However it is
logical that when there is much tenanted land, the amount of debt will be lower relative to firms with the same land areal, with lower tenancy percentages. Although the results should be treated with care and only the found relation may be used, it is visible that the effect of Gross Surplus / kg FPCM is highly volatile between the regressions (3), (4) and (5). This also indicates some important variables are missing.
The found relations on the effect of gross surplus / 100 kg in table 8 are in line with 3 of the 6 described theories in section 2.2.2. Despite the fact, that the examination of Hadley et al. (2001), was the most extensive. It is contradicting the negative relationship described by this research.
It must be said that the former researches had their explanatory and depending variables vice versa, but a negative or a positive relationship is a big difference. The positive relationship between gross surplus and debt / 100 kg probably is described best by the hypothesis of “Credit evaluation” (section 2.2.2). In this hypothesis the causality also runs from efficiency (profitability) to higher debt. From the other two positive hypotheses, first the “free cash flow hypothesis” is less strong because the conflict between owner and manager is smaller here. This manager and owner is the same person in dairy firms. Finally the last positive hypothesis “Embodied capital theory” is somewhat similar to the “credit evaluation theory”. Only good evaluated firms receive new loans to invest or to finance technical change. The causality from the “embodied capital theory” however runs the other way, and is thereby closing less well with the found results.
The found relation is best described by the hypothesis of “Credit evaluation”. But when the effect of higher gross surplus and more or less tenancy is tested the numbers show the following:
The found positive relationship between gross surplus and debt / 100 kg is described best by the hypothesis of “Credit evaluation”. This conclusion however must be interpreted with care. Former research was inconclusive and
even contradicting; besides the effect on debt / 100 kg of an increase of decrease of gross surplus / 100 kg is very small. Therefore more research on this subject is necessary before strong conclusions and recommendations are made.
5. Conclusions and recommendations
In this section this article will be concluded. The main points of the described results are summarized and recommendations are made. First the results of three different hypotheses are discussed one by one. Second recommendations are made and finally these recommendations are translated to daily practice. First have companies with a greater scale a greater profit per kg?
This article concludes that large farms are relative more profitable than small
farms. Small firms (DL) are expected to have a lower Gross surplus / 100 kg. In
contrast large firms (DH) are expected to have a higher Gross surplus / 100 kg.
These results are consistent with the described literature, however here the higher profit is proven on Gross surplus instead of cost price.
Second what is the effect of scale on the amount of debt per 100 kg?
This article concludes that large firms are funded with more debt than small
firms. Small firms (DL) are expected to have a lower amount of debt / 100 kg.
Large firms (DH) are expected to have a higher amount of debt / 100. This is in
line with the practical results of the research of Meulen et al. (2001). It is however in contrast with theory that describes that small firms are less
efficiently deployed and have higher capital cost per kg dairy. For this article it can be concluded that debt / kg dairy increases when firms are larger.
Third what is the effect of profitability per kg and land tenancy on the amount of debt / 100 kg? Higher gross surplus / kg is related to an increase of debt / 100 kg dairy. An extra percent of land tenancy is related to a decrease of debt /
100 kg. The found relation between gross surplus and debt can best be described by the “Credit evaluation hypothesis”. Only low cost and high efficient firms are evaluated positively to receive new loans.
Recommendations
Large firms have a significantly higher Gross surplus per kg than normal firms or small firms. This however doesn’t mean that this extra gross surplus is a result of expansion of the business activities. But it is a simple statistical conclusion that large firms have higher gross surplus per kg. This extra gross surplus per kg also has a multiplier effect. Because large firms produce more kg dairy, every cent higher gross surplus per kg should be multiplied by this large production. Other matters disregarded it can be concluded that large companies make more gross surplus per kg and above all more gross surplus on total farm level.
In evaluating farm performance large firms should be evaluated with these increased gross surplus. When these larger firms do not make bigger gross surplus, then management is wrong or there should be a demonstrable reason for this.
Large firms are expected to be more efficiently deployed nevertheless debt / kg is higher for large firms. More research is necessary to investigate the real difference in capital cost for dairy farmers. But it is hard to overcome the difficulties of estimating the cost of equity (personal net wealth) of farmers. The found relation however can be used to evaluate firm performance. It can be concluded that large firms that do not have a large debt / 100 kg have relative advantage over their colleagues.
The found relation between profitability and debt / 100 kg should be interpreted cautiously. The discussed literature was inconclusive with a described negative and positive relation. More research on this subject is necessary. Therefore there are no recommendations on basis of the found relationship.
The use of the recommendations
The research of Ham et al. (2003, p. 53-56) states that the scale of the firm cannot fully explain the differences in cost price between the 25% highest and lowest cost. It is however the most influential factor in the cost price. Ham et al. (2003, p. 17) also points out that attention to cost is more important than just focus on large scale. Therefore the results of this article should be used to create stricter targets for dairy firms with different scales on the subjects: gross surplus and debt.
Although large firms have a significantly higher gross surplus per kg this is not a direct effect of expansion to this larger scale. Therefore it cannot be said that investing in growth increases gross surplus.
However when there is an investment opportunity for business expansion than the firm should take this investment when the net present value is positive, or just break even. This is because larger companies have a greater long-term gross surplus than small firms and therefore will make more profit in the long run.
