Does it pay to be green?
An empirical case study on the Dutch dairy farming industry
ERASMUS UNIVERSITY ROTTERDAM
Erasmus School of Economics
Department of Applied Economics
Supervisor: Dr. B. Hoogendoorn
Name: Wessel van den Broek
Student Number: 369913wb
Study: International Bachelor and Business Economics
In this research the relationship between sustainability and financial performance and the effect of (farm) size on
this relationship will be investigated. First several theories explaining this relationship will be presented.
Secondly, using data of the Farm Accountancy Data Network, sustainability indicators will be regressed against
financial performance indicators. Following from the regressions, a positive relationship between sustainability
and financial performance is found depending on the financial and sustainability indicator used and a negative
effect of size (increase) on this relationship. Finally, recommendations and limitations of the research will be
given.
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Table of content
1.0 - Introduction ........................................................................................................................ 3
2.0 - Literature & hypotheses ..................................................................................................... 6
2.1 - Sustainability .................................................................................................................. 6
2.2 - Sustainability in the dairy farming sector ...................................................................... 7
2.3 - Corporate social responsibility and financial performance ............................................ 8
2.4 - Sustainability and financial performance in the agricultural sector ............................. 11
2.5 - Hypotheses ................................................................................................................... 12
3.0 - Data .................................................................................................................................. 16
3.1 - Independent variables ................................................................................................... 17
3.2 - Dependent variables ..................................................................................................... 18
3.3 - Control variables .......................................................................................................... 19
3.4 - Variable overview ........................................................................................................ 20
3.5 - Variable descriptives .................................................................................................... 21
4.0 - Methodology .................................................................................................................... 22
4.1 - Financial performance indicators ................................................................................. 22
4.2 - Research methodology ................................................................................................. 22
4.3 - Correlation matrix ........................................................................................................ 26
5.0 - Results .............................................................................................................................. 28
5.1 - Farm net income ........................................................................................................... 29
5.2 - Return on Assets........................................................................................................... 31
5.3 - Return on investment ................................................................................................... 33
6.0 – Discussion ....................................................................................................................... 34
6.1 – Hypothesis 1 ................................................................................................................ 34
6.2 - Hypothesis 2 ................................................................................................................. 35
7.0 – Conclusion ....................................................................................................................... 36
8.0 - Limitations & Recommendations .................................................................................... 38
9.0 - Appendix .......................................................................................................................... 39
10.0 – Bibliography .................................................................................................................. 44
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1.0 - Introduction
Sustainability in agriculture has been a very popular subject since the appearance of the
Brundlandt report (Brundtland Commission, 1987). This report, ordered by the United
Nations, addressed the issue of sustainable development and the growing concern of heavy
deterioration of the human environment and natural resources. Over the past decade,
numerous movements have arisen, addressing the issue of sustainable development: an
inconvenient truth (Gore, 2006), United Nations Environment Program, Greenpeace and
countless NGO’s. This concern is shared by all sectors in the economy. Agriculture is an
essential sector in the economy. Agriculture is the driver behind the production of human
food. At the same time the agricultural sector has a major impact on the environment.
Through production, greenhouse gasses are released and practices as tillage, fertilization and
pesticides will heavily influence environmental sustainability.
Sustainability in agriculture, in fact addresses the problem of sustainable production, i.e.
production which will meet the needs of the current generation without compromising the
ability to address the needs of the future generation. Economic viability, in this case, is a
necessary condition for sustainability in every sector. Economic viability is needed to
maintain the sustainable production, i.e. to maintain profitable while minimizing your impact
on the environment (Baumgartner & Quaas, 2008).
Holland is the second largest exporter of agricultural products. Yearly, Holland exports
roughly 70 billion euros in the agricultural sector, of which 7.7 billion is accounted for by
dairy products, this makes Holland the world’s third largest exporter of dairy products (LEI
Wageningen, 2014). With the recent substantial growth, the farms have become larger in
scale and more intensive in production, this of course poses challenges to the environment
(Holland Trade, 2013). Together with the continuous pressure on farmers’ incomes,
sustainability in agriculture in Holland is a very hotly debated topic. (Calker, Berentsen,
Giesen, & Huirne, 2013).
Over the recent years a large body of literature investigating the relationship between
financial performance (economic viability) and corporate social responsibility (CSR) has
emerged (Aupperle, Carroll, & Hatfield, 1985); (Hart & Ahuja, 1996); (Mahon & Griffin,
2013); (McGuire, Sundgren, & Schneeweis, 1988); (McWilliams & Siegel, 2001); (Orlitzky,
Schmidt, & Rynes, 2003).
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Also a large body of literature has emerged concerning the ‘identification of sustainability in
dairy farming’ (Boogaard, Oosting, & Bock, 2008); (Calker, Berentsen, Boer., Giesen., &
Huirne, 2004); (Calker., Berentsen, Giesen., & Huirne, 2008); (Calker, Berentsen, Giesen, &
Huirne, 2013); (Meul, Nevens, & Reheul, 2009); (Reinhard, 1999); (Thomassen, Dolman, van
Calker, & de Boer, 2009); (van Passel, Nevens, Mathijs, & van Huylenbroeck, 2007).
Yet, none of these researches have investigated the relationship between financial
performance and sustainability in the Dutch dairy farming sector. Over the past years,
environmental protection expenditure by farms in the Dutch agricultural sector has risen from
421 million in 1999 to 700 million in 2011 (OECD, 2015). However no research has shown
the successful effects of these investments on profitability. This rapid growth of
environmental protection expenditure thus has no underlying prove of operational profitable
success.
Summarizing, the Dutch dairy farming sector is a very important sector in our Dutch economy
and exports. Due to recent developments, sustainable agriculture has become a muchdiscussed topic. Dutch environmental-agricultural protection expenditure has risen rapidly.
Economic viability is a necessary condition in sustainability and though environmentalagricultural protection expenditure has risen rapidly over the past years, no underlying prove
has been found that investments in sustainability (i.e. sustainability improvements) lead to
improved economic viability. Consequently this research will investigate the relationship
between financial performance and sustainability in the Dutch dairy farming sector.
This thesis will thus elaborate on the following research question:
“What is the relationship between sustainability and financial performance in the Dutch dairy
farming industry and how is this affected by (farm) size”
First fitting variables have to be identified, combining the results of the above-mentioned
research papers, to rank the Dutch dairy farms on their sustainability. Secondly the Dutch
dairy farms will be assessed on their sustainability with the variables using the data from the
Farm Accounting Data Network (F.A.D.N). The F.A.D.N provides us with extensive
information concerning micro-economic data on agricultural holdings. Information on the
financial performances of the firms will also be gathered using the F.A.D.N. Lastly, the
Dutch dairy farms will be analyzed using Ordinary-Least-squares (OLS).
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In this research, the following results were found: firstly, each sustainability indicators has the
expected positive effect on one of the financial performance indicators. However, this positive
relationship was not univocal for all sustainability and financial performance indicators.
Secondly, a positive relationship between sustainability and financial performance is
concluded and a negative effect of size (increase) is found on this relationship. I.e. the
positive effect of sustainability on financial performance is smaller for larger dairy farms, in
comparison with smaller dairy farms.
In the following sections the research hypotheses and the underlying argumentation will be
established. Following the literature research and hypotheses, the data and methodology will
be addressed. Consequently the results will be presented and conclusions will be drawn.
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2.0 - Literature & hypotheses
In the following sections, the literature on sustainability, sustainability in the dairy farming
sector, financial performance and the relationship between CSR and financial performance (in
the agricultural sector) will be analyzed.
2.1 - Sustainability
Sustainability has a different specific meaning in various science perspectives. In biology, it
stands for the obviation of extinction. In economics, it represents preventing major
disruptions, protecting against instabilities and discontinuities. Concluding: sustainability in
general is concerned with longevity (Costanza & Patten, 1995).
Sustainable development therefore stands for the protection of the environment and creating
social and economic welfare for current and future generations. In common literature,
sustainability is divided in three pillars, namely: environmental, social and economic
(Hansmann, Fritsch, & Fritschknecht, 2012). Environmental is the most common discussed
pillar. This pillar stands for environmental issues (e.g. greenhouse gasses, oil spills, waste
disposal). The social pillar of sustainability stands for the well-being and equal treatment of
people (e.g. social injustice, poverty, human inequality). The last pillar, economic, reflects the
issue of economic viability (Pope, Annandale, & Morrison-Saunders, 2004).
Often two of the three pillars conflict with each other. The first question that naturally arises
is the economic viability of environmental-sustainable improvements (Costanza & Patten,
1995). Often environmental-sustainable improvements require a (monetary) investment. For
an investment to be made, a positive net present value (i.e. economic viability), needs to be
maintained.
Therefore this research will focus on the relationship between the environmental and
economic pillar.
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2.2 - Sustainability in the dairy farming sector
In 1994, 1.7 million cows were kept in the Netherlands. Since the implementation of the milkquota, the absolute amount of cows is decreasing and consequently the cow-land ratio is
increasing. On average the cow-land ratio was around 1.75 with 49 cows on 28 ha in 1994.
(Reinhard, 1999). Other countries in Europe consider 1.7 cows/ha as a highly intensive dairy
holding, following that the Netherlands has a highly intensive dairy farming sector (OECD,
2010). Cow manure and urine consists for 5% out of nitrogen. Even the smallest amounts of
nitrogen affect the environment. Research by Agriculture and Consumer protection (2009) has
shown three harmful effects of cow manure and urine on the environment: through
groundwater, soil and air. Nitrogen that is not taken up by plants, will be metabolized by
micro-organisms to increase soil fertility. However, as this is a slow process, the resulting risk
will be, that nitrogen, which is easy soluble, will run off into surface water or percolate into
groundwater. Another part of the nitrogen will diffuse in the air, through the vitalization of
ammonia. Excessive concentrations of nitrogen will result in the eutrophication of slow
flowing rivers and lakes. High concentrations of nitrogen in water are also considered a health
risk. Besides that, excessive concentrations of nitrogen in the soil will deplete oxygen in the
soil and critically affect soil fertility (Agricultue and Consumer protection, 2013). Research
has shown that roughly 50% of the nitrogen surplus is the Netherlands is created by fertilizers
(European Commission Agriculture, 2005). Furthermore Reinhard’s research on Dutch dairy
farms suggested that nitrogen surplus was the most destructive output factor on the farm’s
environmental sustainability (Reinhard, 1999).
Besides the deteriorating of the environment through the nitrogen surplus, dairy farms also
affect the environment through energy use. The Dutch dairy sector is the second largest user
of energy in agricultural sector (Reinhard, 1999). This is mostly due the industrialization and
the intensification of the dairy farming sector. Most energy in dairy farms is used for heating,
electricity of milking machines and refrigeration of milk. The incineration of fuel will cause
anthropogenic greenhouse gasses to emit and will eventually lead to global warming, which
causes the earth to slowly rise in temperature and result in devastating environmental
consequences, i.e. the greenhouse effect. A report from the Food and Agriculture
Organization has concluded that roughly 18% of the world’s anthropogenic greenhouse gasses
(GHG) is caused by livestock (Steinfeld, 2006). Estimates by the department of animal
science have shown a direct relationship between the use of energy and the growth of CO2
emissions per cow. For this reason the (in)efficient use of energy measured as the energy use
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per cow can be taken as a proxy for GHG emissions. The growth of 13.5 kg CO2/cow (1944)
to the increased 27.8 kg CO2/cow (2007), shows the less sustainable character and increased
carbon footprint of the dairy sector (Capper, Cady, & Bauman, 2014). Reinhard’s research,
has shown the inefficient use of energy to be the second most harmful output on the
environment (Reinhard, 1999).
The Common Agricultural Policy is the agricultural policy of the European Union. This
coordinating institute is responsible for several reforms in the agricultural (and dairy) sector.
Apart from the introduction of the milk quota in 1984, they have also been responsible for the
introduction of subsidies (Zhu & Lansink, 2010). A subsidy in the agricultural sector can have
four impacts: i) changing relative price of input and output, and possibly have an impact on
input usage (Peerlings & Lansink, 2010), ii) through an income effect, change investment
decision and make dairy farmers invest in sustainable projects (Young & Westcott, 2000).
Iii) through an insurance effect on risk mitigation (Hennessy, 1998), and iv) through farm
growth and exit (Ahearn, Yee, & Korb, 2005). The income (or wealth) effect, combined with
the insurance effect is considered to cause change in a farmer’s working motivation, boost
investment in new technologies and allocation of inputs and outputs (Zhu & Lansink, 2010).
In this manner, it will increase technical, economic and environmental efficiency and
eventually profits (Zhu & Lansink, 2010).
Consequently, the three indicators of sustainability that will be used in this research are:
nitrogen surplus, (in)efficient energy use and subsidies per invested euro.
2.3 - Corporate social responsibility and financial performance
Orlitzky, Schmidt and Rynes have performed a meta-analysis on the relationship between
corporate social responsibility and financial performance (Orlitzky, Schmidt, & Rynes, 2003).
Firstly they identify the measurement variables of the dependent variables, financial
performance. Three subdivisions are identified, namely: market-based (investor returns),
accounting-based (accounting returns) or perceptual-based (survey) measurement. It has been
concluded that perceptual-based measurement is too subjective to use in a research because it
is based on subjective opinion. Market based measurement reflect the idea that shareholders
are the firms primary and sole source of influence on management decisions, something that
cannot be assumed in the dairy farming sector, where farms are often managed by a single
manager without shareholders (Reinhard, 1999). For this reason, in contrary to other
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researches, this paper will make use of accounting-based measurement. Accounting-based
measurement, such as return on assets (ROA) and return on equity (ROE), are subject to a
manager’s allocation of funds to specific projects. In this way, this research will reflect
manager’s internal decision and will likely mirror a company’s true willingness to invest in
corporate social responsibility. Also it excludes the external market as influence on business
actions. The paper by Orlitzky, Schmidt and Rynes also identified four possible
measurements for corporate social responsibility, namely: CSR disclosures, CSR reputation
ratings, CSR social audits and managerial CSR principles and values. CSR disclosures consist
of content analysis of corporate disclosures, such as annual reports, letters to shareholders and
10K’s. CSR reputation ratings make use of external ratings, such as Moskowitz’s tripartite
rating or any newspaper’s (mostly Fortune’s) rating on company’s CSR. This measure is
based on the assumption that reputation is a quality indicator of true corporate social
responsibility. CSR audits make use of data such as community service and environmental
programmes to identify CSR. The last CSR measure is established by a company’s inherent
culture. Aupperle for instance, created a forced-choice survey identifying a company’s
(managerial) principles and values. Many of these CSR measurement approaches are very
subjective to external influence. A company’s reputation can depend on many variables,
which can influence their ‘CSR reputation rating’, CSR principles and values in their turn
depend on the willingness of only that single management employee answering the survey.
CSR social audits have been seen to be a bad indicator of CSR; many companies receive
subsidies or are forced by external influences to commit to for instance community service.
An interesting outcome of this meta-analysis by Orlitzky, Schmidt and Rynes on 30 years of
empirical data, on the relationship between CSR and financial performance is it has shown to
be both a positive as a bidirectional relationship. In other words, investing in corporate social
responsibility will be rewarding, though more available funds, will also lead to higher
investment in corporate social responsibility.
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The overall trend in the relationship between CSR and financial performance is positive.
However some papers found different conclusions. The following papers were not included in
the meta-analysis and made use of accounting based measurement.
The paper by McWilliams&Siegel (2001), which suggests that there is an ‘ideal’ level of CSR
investment, for which the ‘demand’ of different stakeholders and shareholders is satisfied and
maximum profits are gained. This ‘ideal’ level can be found by a simple cost-benefit analysis.
Concluding their research that there is no significant relationship between CSR and financial
performance.
Additionally a study by Aupperle, Carrol and Hatfield (1985), making use of accounting
based measurement and CSR principles and values, also suggests no significant relationship
between CSR and financial performance.
A paper by Mahon&Griffin (2013), making use of CSR reputation rating, CSR principles and
values and accounting-based measurement, find no correlation between CSR and financial
performance.
Finally a paper by McGuire, Sundgren and Schneeweis (1988), making use of both
accounting, as well as market-based measurement and CSR reputation rating, suggests several
interesting outcomes. Firstly, CSR is more correlated with prior financial performance than
current financial performance and secondly accounting-based measurement is more accurate
that market-based measurement.
However, all these ‘contradicting’ papers have in common that they make use of subjective
CSR measurement approaches (CSR reputation, CSR principles and values) and do not have a
sample over a longer period of time. For this reason, this paper will make use of a sample
over a long time period and objective data from FADN, using CSR disclosures and CSR
audits. By analyzing the use of fertilizer and the usage of energy, the CSR disclosure method
is used, due to the fact that for the FADN firms this data is publically available and
objectively measured by the FADN committee. CSR social audits is used when analyzing
environmental subsidies, as CSR social audits is the proxy for being sustainable innovative
when analyzing the participation in environmental programmes or (environmental) subsidies.
To prevent the measurement of the wrong variable, CSR social audits is used as opposed to
CSR disclosures. Because of the risk of companies investing in sustainable practices for the
convenient subsidy policies (mere financial benefit) rather than the willingness to be
sustainable, objective data of the CSR disclosure is used. Also based on the research by
McGuire, Sundgren and Scheeweis, the choice of accounting-based measurement is validated.
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2.4 - Sustainability and financial performance in the agricultural sector
Several studies have been conducted using similar sustainability indicators as in this research.
Firstly, a study conducted by Lockeretz, Shearer, Kohl (1978), investigated the relationship
between energy efficiency and crop production costs for agricultural holdings in the Midwest
of America. Agricultural holdings were separated as organic and conventional holdings.
Organic holdings conserved soil productivity by planning, allowing the soil ‘to rest’ and
optimally reducing energy use. Results indicate that though the crop yield of organic farms
was lower, their operational costs (energy usage) were significantly smaller (40% of
conventional farms) by the same cash equivalent (Reganold, 1990).
Secondly, a study by Klein (2001) has been done using the sustainability indicator nitrogen
surplus, building on previous research which suggested that restricted grazing can lead to a
50% reduction in nitrogen surplus. This research created a model for an economic cost-benefit
analysis based on data of an average New Zealand dairy farm using conventional grazing and
a dairy farm using restricted grazing. Their results indicate that for an average New Zealand
dairy farm, restricted grazing will be economically viable on the long term.
Another study by Neil Schaller (1993) suggests that the manner the profits are calculated is
not representative for the reality. Many benefits to the farmer and society as well as costs
incurred in non-sustainable agriculture are not included. Research by Feath et al. (1991)
confirms this conclusion. In this research the economic costs of soil erosion and groundwater
contamination are included in several farmers’ profit calculations and negative profits are
found. Also a study was conducted on financial performance and sustainability in Dutch
agriculture, namely the sugar beet growers, by Koeijer, Wossink, Struik and Renkema (2002).
They identified technical efficiency optimally when reducing environmental-damaging-inputs
as fertilizers and pesticides. A combination between technical and environmental efficiency
creates sustainable efficiency. Consequently, a model is created where technical efficiency
and environmental efficiency is analyzed. Results suggest that there is a positive relationship
between sustainable efficiency and technical efficiency (sustainable efficiency).
In this section literature involving the relationship between sustainability and financial
performance in the agricultural sector is analyzed. Due to the fact that these researches use
similar sustainability indicators and one study even the identical geographical scope, the
usage of this research’s sustainability indicators, is reinforced.
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2.5 - Hypotheses
Following the analysis of literature, this research has established the research question:
“What is the relationship between sustainability and financial performance in the Dutch dairy
farming industry and how is this affected by (farm) size”
Firstly, this research identified the conflicting pillars of sustainability and identified the
research scope. This paper will focus on financial performance and environmental
sustainability, environmental sustainability will be named ‘sustainability’ and economic
sustainability (economic viability) will be named ‘financial performance’.
Secondly, sustainability in the dairy farming sector is identified. Here three sustainability
indicators were found, namely: nitrogen surplus, (in)efficient energy use and environmental
subsidies per invested euro.
Thirdly, the relationship between these sustainability indicators and financial performance is
analyzed. This paper found a significant body of literature suggesting a positive relationship
between CSR and financial performance.
Lastly, the relationship between sustainability and financial performance in the agricultural
sector is analyzed. In the body of literature again a positive relationship is suggested. Almost
no literature on the relationship between sustainability and financial performance in the Dutch
dairy farming sector is available. Therefore an assumption is drawn, based on the relationship
between CSR and financial performance and sustainability and financial performance (in the
agricultural sector and making use of the same sustainability indicators). Hence this paper can
conclude a presumption of the presence of a positive relationship between sustainability and
financial performance in the Dutch dairy farming sector.
Using the three sustainability factors: nitrogen surplus, (in)efficient use of energy and
subsidies per invested euro against accounting-based financial performance measurement,
will lead to the following hypothesis:
Ha: Sustainability indicators are positively related to financial performance in the Dutch
dairy farming sector
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Research by Orlitzky (2001) on the relationship between firm size, environmental and
financial performance, suggests that due the fact a positive relationship between firm size and
environmental performance/financial performance exists, firm size positively influences the
relationship between environmental and financial performance and function as a moderating
variable. Following Orlitzky’s argumentation, theories and theoretical argumentation, as
discussed in the next section, provide argumentation for a positive relationship between farm
size and CSR investments (environmental performance). In the last section the theoretical
argumentation for the relationship between financial performance and firm size is given.
Small and Medium-sized Enterprises (SME’s) form 90% of the of the world’s firm-population
and employ over 50% of the employees in the private sector (United Nations, 2002). Several
researches conclude that SME’s contribute a lesser amount to CSR as in comparison with
large corporates (Graafland, Ven, & Stoffele, 2003); (Heene & Lepoutre, 2006); (Perrini,
2006); (Russo, Tencati, & Perrini, 2007); (Udayasankar, 2008). Another research suggests
that SME’s, at the same time are overlooked upon by policy makers, academics, the media
and civil society. The existing frameworks, tools and academic reports tend to focus on large
corporates (Fox, 2005). There are several possible theories that may explain the claim that
SME’s invest less of their resources to CSR.
The first probable explanation for such a difference is the organizational theory perspective
(Weber, 1905). The two variables that affect a firm’s sustainable character are: firm visibility
and resource access. Larger firms are mostly better known to the public than small firms. For
this reason they attract the attention of the public, resulting in a larger variety and greater
number of stakeholders. Consequently corporates become an ‘easy target’ for NGO’s and
environmentalists. (Hart & Sharma, 2004). Also large firms have proven to have more human
and financial capital, relative to small firms. With larger funds and more reason to invest in
sustainability (because of firm visibility), larger firms will probably pay more attention to
CSR (Hart & Sharma, 2004).
The second probable theory explanation that supports the claim that SME’s invest less in
CSR, is suggested by Pfeffer and Salancik’s (1978) power explanation, also named the
resource dependence theory. This theory suggests that all organizational institutions are
dependent on their external environment (i.e. stakeholders) for its resource needs. A firm
needs resources to survive and resources are often in the hands of other organizations, which
makes a firm dependent. The more a firm is dependent on critical resources hold by
stakeholders, the more a firm is willing to alter her response based on stakeholders.
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The third possible explanation for such a difference between SME’s and large firms, is based
on the McMahon and Harvey’s moral intensity construction. Their research identified the
three dimensions of moral intensity as an important factor of CSR contribution. (McMahon &
Harvey, 2006). Firstly they have identified the magnitude of consequences; this refers to the
probability that their action will have a certain level of effect, in a given time. Secondly, they
have identified proximity as an important factor. This dimension refers to the fact that a firm
could have a social, psychological or physical closeness with the victim of the action. The
third dimension is recognized as social consensus, which refers to the social agreement that
the action is good or evil (Lepoutre & Heene, 2006).
Concerning the first dimension, magnitude of consequences, research has suggested that small
firms consider their destruction or enhancement to the external environment as negligible
(Hitches, 2005). This conclusion is based on the visibility theory by Bowen (2000). Visibility
can depend on two manners, visibility of the organization or the issue. Following the
discussion of the first visibility in the previous section, this research will now focus on the
latter. Where unethical behavior in marketing issues is very visible to stakeholders, financial
issues are not as comprehensively audited in SME’s as in comparison to large firms. Thus the
issue visibility – the extent to which an issue is noticeable by constituents in or outside the
firm – will be low in SME’s. SME’s also differ in the second principle proximity. SME’s
attach high value to their immediate stakeholders, such as employees, customers and suppliers
rather than the ‘external domain’, such as community or the environment (Lepoutre & Heene,
2006). Based on the last dimension of social consensus: empirical research has suggested that
large and small firms share the same thought on social consensus (Bucar, 2003).
Summarizing, both the organizational theory, power explanation theory as well as the
dimensions of moral intensity provide explanation for the claim that SME’s contribute less to
CSR as in comparison with corporates. Besides that, Fox’s research suggests that SME’s are
also not provided with the correct framework and tools.
In the following section the relationship between financial performance and firm size will be
analyzed. The first theory used for the explanation of the positive relationship between firm
size and financial performance is based on the economies of scale theory by Adam Smith
(1776). This theory suggests that costs per product is reduced when production increases.
Other researchers, like Alfred Marshall (1890), have provided further argumentation for this
theory. Marshall suggests that cost reductions are achieved, due to lower input costs,
specialized inputs and organizational/learning inputs. Lower input costs represents the fact
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that inputs can be bought in bulk, through which a firm can lower her average input costs per
product, by volume discounts. Specialized inputs represents the fact that a firm can use her
specialized machinery and labor in greater efficiency. Organizational/learning inputs
represents the fact that the labor force and firm’s management will be more skilled (learning
curve effect).
A second theory, that provides argumentation for the positive relationship between firm size
and financial performance, is based on research by Mueller (1969), Stanford (1980) and
Williamson (1975). These researches suggest that due the fact that larger firms have increased
promotional opportunities, as previously-discussed: higher visibility, this results in the
attraction and retention of better employees. This skilled workforce will, through
organizational/learning inputs (economies of scale), lead to lower costs per product and higher
quality (Orlitzky, Schmidt, & Rynes, 2003).
The third theory, by Baumol (1959), suggests that there exists a positive relationship between
firm size and financial performance due to the existence of capital barriers. Large firms have
all the options small firms have, including other investment possibilities demanding large
amounts of capital, resulting in ‘monopoly profits’. Research by Hall and Weiss (1967), have
proven this theory to be correct.
Following from the previous sections, firm size both positively influences CSR investments
and financial performance and functions as a moderating variable in their relationship.
Consequently, this lead to the following hypothesis:
H2a: The positive relationship between sustainability and financial performance will be
enhanced by increasing the size of the firm
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3.0 - Data
The data that will be used comes from the Farm Accounting Data Network (F.A.D.N).
Derived from surveys, the FADN is the only institution that provides extensive microeconomic data from agricultural holdings. FADN is frequently used to analyze impacts of
Common Agricultural Policy. In FADN, an overview of agricultural-important variables in
European countries can be identified, as can be seen in the Appendix table 1. The FADN is
stratified random sample. In the sample, the stratification is based on: farm size, age of
farmer, region and type of farm. The FADN covers 99% of milk production and no systematic
errors due to non-response are found (Reinhard S. , 1999). Following that the FADN is a
highly representative dataset for the use of analyzing dairy farms.
Micro-economic data is gathered by the FADN committee, surveying agricultural holdings.
To qualify as ‘agricultural holding’ for the purpose of FADN data, the holding has to satisfy
the following conditions: a) the holding must have a characteristic type of farming (i.e. milk,
horticulture, field crops), b) the farmer needs to be willing to keep track of farm accounts
(agricultural data) and accountancy data and be willing to share them, c) the conditions of
production on the holding and its location be regarded as normal as in comparison with the
market.
This paper uses data on farms specialized in dairy farms over a period of 1989-2009. Farms
are selected on country and type of farming, which in this research will be the Netherlands
and dairy farming.
The dataset consist of 52 specialized dairy farms, mixed in economic size. The variables that
will be used from the dataset are: farm net income (SE420), production good-milk (TF8), total
assets (SE436), net investments (SE521), Energy (SE345), total output (SE131), dairy cows
(SE085), fertilizers (SE295), net worth (SE501) and environmental subsidies (SE621).
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3.1 - Independent variables
The following variables were created using SPSS to identify sustainability:
Sustainability indicators
Three indicators will be used for the identification and measurement of sustainability in dairy
farms:
Firstly, nitrogen surplus, which is defined as the amount of fertilizer usage (value: euro) per
dairy cow.
Fertilizers/dairy cows = Nitrogen_Surplus
Nitrogen is the most harmful substance produced by dairy farms for the environment
(Reinhard, 1999). It harms the environment through the urine of cows and through fertilizers.
As the amount in the urine of cows (and the production of urine) is roughly constant, dairy
farms’ nitrogen surplus is only affected by fertilizer use (Kebreab & Dijkstra, 2002). Larger
dairy farms, with more dairy cows, use more fertilizer products. To correct for this
assumption, nitrogen surplus is calculated by dividing fertilizers by dairy cows, creating the
‘efficient use of fertilizers’. Concluding that a lower value of nitrogen surplus indicates a
more sustainable farm.
Secondly, efficient energy, which is defined as the energy usage per output.
Energy/total output = Efficient_Energy
Energy in the FADN dataset is measured as the use of motor fuels and lubricants, heating
fuels and electricity. The emission of carbon dioxide (CO2) is the second most harmful
manner dairy farms affect the environment (Reinhard, 1999). Total output is calculated as
follows: +change in stock of products +change in valuation livestock –purchases of livestock
+various non-exceptional products (Farm Accountancy Data Network, 2015). In fact, this is
simply the total value of the output. By dividing energy by total output, the (in)efficient level
of energy per output is created.
Thirdly, environmental subsidies, which is defined as the environmental subsidy per invested
euro.
Environmental subsidies/net investment = SubsidiesE
17
The last indicator of sustainability in the dairy farms is environmental subsidies per invested
euro. Both subsidies, as well as net investment are calculated over a time span of one year. By
dividing the total amount of subsidies dairy farms receive by the total investment a proxy for
the ‘willingness to be innovative and green’ of dairy farms is created. Assuming that dairy
farms that receive more environmental subsidies invest more in sustainable improvements.
Besides these continuous variables, one categorical variable is used being economic size
(SE005). Economic size is measured in ESU: European Size Unit. ESU is a unit used to
measure standard gross margin (SGM). SGM is calculated per unit area of crops and per head
of livestock, making use of standardized (geographical) SGM coefficients for different types
of crops or livestock. The outcome of the SGM is representative for the average level of profit
that can be expected from the crops or livestock. SGM is a predefined number of expected
value per hectare or livestock, set out for different agricultural sectors. As agreed upon in the
EU, 1200 SGM (EUR) equals 1 ESU. SGM is used, so it will not intercorrelate with our
financial performance indicators, such as farm net income. (Eurostat, 2013). A dummy
variable of economic size, for large dairy farms will be created, to investigate the effect of
farm size on the relationship between sustainability and financial performance. As set out by
the FADN, a large dairy farms has an ESU of at least 100.
3.2 - Dependent variables
The financial performance measures used in the research are farm net income, return on assets
and return on investment.
Firstly, farm net income, which is defined as farm net income per cow.
Farm net income/dairy cows = FNI_cow
The overall absolute net income of a dairy farm is used as an indicator of the financial health
of the company. The farm net income is divided by the total amount of dairy cows to create a
relative variable, in correspondence with the other dependent variables.
“FADN: remuneration to fixed factors of the farm (work, land and capital) and remuneration
to the entrepreneur’s risk (loss/profit) in an accounting year.” – In this case it is used as a
proxy for net profit.
18
Secondly, return on assets, which is defined as the farm net income divided by total assets.
Return on assets: Farm net income/total assets = Return_Assets
The return on assets is another indicator used for the financial health of the company.
Thirdly, return on investment, which is defined as farm net income divided by net investment.
Return on investment: farm net income/net investment = Return_Invesment
The last indicator of financial health is return on investment.
3.3 - Control variables
Independent control variables are added to the model, to check for possible spurious
relationships. Spurious relationships are relationships that do not originate from a causal
effect on each other but their relationship to other variables. The following control variables
are added to the model:
Rent paid per cow: rent paid for farm land and buildings / dairy cows
Rent paid per cow = Rentpaid_cow
Previous research has proven farm rent to be one of the farmers’ largest costs (Eller, 2014).
Higher fixed costs in the firm could lead to less or later (CSR) investments (McDonald &
Siegel, 1982). Due to the variation of rent in the Netherlands, this research controls for rent
paid. Concluding, this research controls for one of the highest fixed costs, which could vary in
the Netherlands and could diminish investment in sustainability.
Leverage ratio: debt / equity
Leverage ratio = DE_ratio
Based on outcome of FADN advanced results research, equity is based on the percentage
share of net worth out of total capital (Economydoctor, 2010). The leverage ratio essentially
tells something about the financial health of a company. Highly leveraged firms can have
strong farm net income, return on assets or return on equity, however can also be in great
jeopardy of default (Investopedia, 2015). As in this research investigates economic viability
of sustainability, this research controls for highly leveraged firms, by including the leverage
ratio as a control variable (Hart & Ahuja, 1996).
19
3.4 - Variable overview
Table 1.0
Variable overview – independent variables (IV), dependent variables (DV), control variables (CV)
Variable
Variable formula
Type of variable
Scale/Categorical IV/DV/CV
Nitrogen surplus =
Fertilizers/
Sustainability
Scale variable
IV
Nitrogen_Surplus
Total dairy cows
indicator variable
Efficient Energy =
Energy/
Sustainability
Scale variable
IV
Efficient_Energy
Total output
indicator variable
Scale variable
IV
Scale variable
DV
Scale variable
DV
Scale variable
DV
Dummy variable
IV
Control variable
Scale variable
CV
Control variable
Scale variable
CV
Environmental subsidies Environmental
Sustainability
=
subsidies /Net
indicator variable
SubsidiesE
investment
Farm net income per
Farm net Income
cow =
Financial
indicator variable
FNI_cow
Return on Assets =
Farm net Income/
Financial
Return_Assets
Total assets
indicator variable
Return on Investments = Farm net Income/
Financial
Return_Investments
Net investment
indicator variable
Economic size =
ESU (>= 100)
Size dummy
SIZE_LARGE
variable
Rent paid per cow =
Rent paid/
Rentpaid_cow
Total dairy cows
Leverage ratio =
Total debt/
DE_ratio
Total equity
20
3.5 - Variable descriptives
Table 1.1
Variable descriptives – independent variables (IV), dependent variables (DV), control
variables (CV)
Mean
Median Min.
Max.
Standard
deviation
Nitrogen surplus =
80,91
82,33
47,09
116,15
17,09
0,03
0,03
0,02
0,05
0,01
0,13
0,02
-0,06
3,08
0,44
628,83
638,36
136,97
1055,46
205,22
0,03
0,03
0,00
0,09
0,02
6,91
1,62
-14,72
176,68
27,11
129,77
131,96
49,80
212,63
45,65
0,35
0,36
0,05
0,64
0,14
Nitrogen_Surplus - IV
Efficient Energy =
Efficient_Energy - IV
Environmental subsidies =
SubsidiesE - IV
Farm net income per cow =
FNI_cow- DV
Return on Assets =
Return_Assets - DV
Return on Investments =
Return_Investments - DV
Rent paid per cow =
Rentpaid_cow - CV
Leverage ratio =
DE_ratio - CV
21
4.0 - Methodology
4.1 - Financial performance indicators
One could find financial performance based on accounting-based, market-based performance
or perceptual based measures. Orlitzky, Schmidt and Rhynes (2003) have concluded
perceptual based to be too subjective and market-based to be an unrealistic reflection of the
truth. When following the market-based measurement, one might conclude that all eventual
profits are a subsequent consequence of stakeholder decision making and external market
environment. Adding, that the FADN does not provide information on ‘outstanding shares’ or
‘prices’, a possible market-based performance measure is therefore not possible. Accountingbased measurement reflects a firm internal efficiency. Managers allocate funds to different
projects aiming for optimal (sustainable) profit creation. Here the internal decision/policy
process will directly influence profits, instead of a reaction to the external market
environment. Also due to the fact that sustainability variables are mostly highly endogenous
with respect to the market value (sustainable companies receive positive attention), the use of
accounting-based performance measures are more in place. The most commonly used
accounting-based performance measures in similar researches (Artiach, Lee, Nelson, &
Walker, 2009); (Aupperle, Carroll, & Hatfield, 1985); (McWilliams & Siegel, 2001);
(Murphy, 2002); (Sneirson, 2008); (Orlitzky, Schmidt, & Rynes, 2003), will also be used here
are: farm net income, return on assets and return on equity. To capture the relationship
between sustainability and financial performance as extensive as possible, all three variables
will be used.
4.2 - Research methodology
As mentioned in the previous sections this research will make use of the ordinary least
squares method to investigate the relationship between sustainability and financial
performance indicators. Each of the sustainability indicators will be individually regressed
against each of the financial performance indicators. Following that we have 3 regressions per
financial performance indicator, namely: nitrogen surplus, (in)efficient energy usage and
environmental subsidies per invested dollar. Control variables are added to the model to
control for rent variation in the Netherlands and highly leveraged dairy farms. Also a dummy
22
variable will be created for large dairy farms, to investigate the effect of farm size on the
relationship between sustainability and financial performance. In the following section the
several models that were used in this research will be explained.
Model 1: control variables
To begin with the control variables are entered in the regression models. In model 1 this
research checks for the effects of the control variables on the dependent variables. Here, the
regression is controlled for a variation of rent paid per cow and highly leveraged firms.
𝐹𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 = 𝛽0 + 𝛽1 ∗ 𝑅𝑒𝑛𝑡𝑝𝑎𝑖𝑑𝑐𝑜𝑤 + 𝛽2 ∗ 𝐷𝐸𝑟𝑎𝑡𝑖𝑜 + 𝜖
Where financial performance represents: farm net income, return on assets or return on
investment.
Model 2: Independent and control variable(s)
In the second model, the independent (sustainability indicator) variable will be entered. Due
to the fact that control variables are also entered in the model, one could see if the effect of
the independent variables holds, when controlled for other covariates. A significant
coefficient proves an existing relationship between the sustainability indicator and dependent
(financial) variable.
𝐹𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒
= 𝛽0 + 𝛽1 ∗ 𝑠𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑖𝑙𝑖𝑡𝑦 + 𝛽2 ∗ 𝑅𝑒𝑛𝑡𝑝𝑎𝑖𝑑𝑐𝑜𝑤 + 𝛽3 ∗ 𝐷𝐸𝑟𝑎𝑡𝑖𝑜 + 𝜖
Where sustainability represents: nitrogen surplus, (in)efficient energy usage and
environmental subsidies per invested euro.
23
Model 3: independent variable, size and control variables
In this model, the effect of size on the dependent variable is investigated.
𝐹𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒
= 𝛽0 + 𝛽1 ∗ 𝑠𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑖𝑙𝑖𝑡𝑦 + 𝛽2 ∗ 𝑆𝐼𝑍𝐸_𝐿𝐴𝑅𝐺𝐸 + + 𝛽3 ∗ 𝑅𝑒𝑛𝑡𝑝𝑎𝑖𝑑𝑐𝑜𝑤
+ 𝛽4 ∗ 𝐷𝐸𝑟𝑎𝑡𝑖𝑜 + 𝜖
Where size = {𝐿𝐴𝑅𝐺𝐸 = 1|𝑆𝑀𝐴𝐿𝐿 = 0}. The coefficient of SIZE_LARGE will both
indicate whether a significant relationship exists as the effect of size increase on this effect.
By making a dummy variable, taking the value 1 for large dairy farms, the coefficient
represents the effect of large dairy farms as in comparison with small dairy farms.
Model 4: independent variable, size, interaction effect and control variables
In this model an interaction term between the size dummy and the independent variables will
be included. One could include an interaction term between variables when the effect of one
independent variable may possibly depend on another independent variable, i.e. an interaction
effect that changes the independent variable’s specific effect (main effect). The interaction for
each independent variable and the size dummy category is created. The interaction effect
compares the sustainability effect on financial performance of large as in comparison to small
dairy farms, to investigate the effect of economic size class on the relationship between
sustainability and financial performance.
𝐹𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒
= 𝛽0 + 𝛽1 ∗ 𝑠𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑖𝑙𝑖𝑡𝑦 + 𝛽2 ∗ 𝑆𝐼𝑍𝐸_𝐿𝐴𝑅𝐺𝐸 + 𝛽3 ∗ 𝑖𝑛𝑡𝑒𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑡𝑒𝑟𝑚
+ 4 ∗ 𝑅𝑒𝑛𝑡𝑝𝑎𝑖𝑑𝑐𝑜𝑤 + 𝛽5 ∗ 𝐷𝐸𝑟𝑎𝑡𝑖𝑜 + 𝜖
24
Subsequently 3 dependent variables versus 3 independent variables (9 tables) will be
regressed. The different variables will be regressed using Ordinary Least Squares (OLS).
Concluding each table holds 4 models, namely:

Model I: control variables

Model II: independent variable including control variables

Model III: independent variable including the size dummy and control variables

Model IV: independent variable including control variables, size dummy and the
interaction effect
The variables will be entered in the models on forced entry. Variables will be entered in the
model through forced entry to be sure to include all variables. As is justified in the literature
framework, all the variables have an expected explanatory influence on the dependent
variable, based on other researches. Also the independent variables are not entered in the
same tables to prevent intercorrelation between the independent variables. Consequently, each
table holds his own combination of dependent, independent and interaction variables.
25
4.3 - Correlation matrix
Also the correlation matrix for the all variables is checked, to check for possible
intercorrelation and complications in the several models.
When checking for intercorrelations, the following rule of thumb is used: a correlation
Table 2.1
Correlation matrix
Size large
Size
large
1
Rent paid Environmental Efficient
DE ratio per cow Subsidies
Energy
0.69**
-.0,25
-0.19
-0,12
Nitrogen
Surplus
-0,15
DE ratio
0.69**
1
-0.31**
-0.14
-0.28**
0.08
Rent paid per
cow
-0,25
-0.31**
1
0.26
0.59**
-0.53**
Environmental
Subsidies
-0.19
-0.14
0.26
1
0.12
0.04
Efficient Energy
-0.12
-0.28**
0.59**
0.12
1
-0.63**
Nitrogen Surplus
-0.15
0.08
-0.53**
0.035
-0.63**
1
**= Correlation is significant at 5% significance level
26
=< (-) 0.6 is considered as acceptable and can be used in the regression (Field, 2007).
If the correlation matrix is checked, the following conclusions can be drawn:

None of the independent variables intercorrelates with the control variables or size.

The control variables do no intercorrelate.

Size large intercorrelates with DE ratio.
The positive intercorrelation between size large and DE ratio will most likely cause the
coefficient of both to be higher and there thus will be an overestimation. As no conclusions
will be drawn from the coefficient (magnitude) of size large (only the significance effect is
investigated), size large and DE ratio can remain in the models.
27
5.0 - Results
Table 3.1
Farm net Income per cow – Nitrogen Surplus (IV.I)
Model I
Nitrogen surplus
Model II
Model III
Model IV
-3,89**
(1,61)
-4,22**
(1,75)
-4,28**
(2,12)
-36,22
(-36,23)
-48,03
(241,04)
SIZE_LARGE
0,16
(3,03)
Nitrogen_SizeL
367,49**
(182,52)
321,71*
(175,38)
404,45*
(239,11)
400,92
(251,82)
-1,85**
(0,56)
-2,67**
(0,63)
-2,76**
(0,66)
-2,76**
(0,67)
Adjusted R2
0,27
0,33
0,32
0,31
N
52
52
52
52
Debt/equity
(control)
Rent paid per cow
(control)
**=significant at 5% significant level
*= significant at 10% significant level
Table 3.2
Farm net Income per cow – Efficient Energy (IV.II)
Model I
Efficient Energy
Model II
Model III
Model IV
-2844,08
(3037,82)
-114,18
(3101,12)
-2698,98
(3745,11)
37,44
(69,68)
2,18
(174,69)
SIZE_LARGE
-21,95
(5362,51)
Energy_SizeL
367,49**
(182,52)
345,58*
(184,23)
253,98
(251,99)
253,88
(253,87)
-1,85**
(0,56)
-1,51**
(0,67)
-1,46**
(0,68)
-1,46**
(0,69)
Adjusted R2
0,27
0,27
0,26
0,24
N
52
52
52
52
Debt/equity
(control)
Rent paid per cow
(control)
**=significant at 5% significant level
*= significant at 10% significant level
28
Table 3.3
Farm net Income per cow – Environmental Subsidies (IV.III)
Model I
Environmental
subsidies
Model II
Model III
Model IV
-11,06
(56,97)
-8,402
(57,97)
-10,28
(57,43)
24,78
(70,05)
105,09
(90,24)
SIZE_LARGE
-3616,17
(2597,90)
SubsidiesE_SizeL
Debt/equity (control)
367,49**
(182,52)
365,33**
(184,63)
306,60
(249,55)
283,20
(247,71)
Rent paid per cow
(control)
-1,85**
(0,56)
-1,83**
(0,58)
-1,82**
(0,58)
-1,67**
(0,59)
Adjusted R2
0,27
0,26
0,24
0,26
N
52
52
52
52
**=significant at 5% significant level
*= significant at 10% significant level
5.1 - Farm net income
For this research’s first independent variable, this research finds that nitrogen surplus, in table
3.1, has a significant negative effect on farm net income of -3,89. When size is added to the
model, the variable coefficient significantly changes to -4,22. For the second and third
independent variable, efficient energy and environmental subsidies, no significant effects are
found (table 3.2 and 3.3). The significant control variables’ effect, leverage ratio and rent per
cow, are respectively stable around 345 and -1,95.
29
Table 4.1
Return on Assets – Nitrogen surplus (IV.I)
Model I
Nitrogen surplus
Model II
Model III
Model IV
0,00*
(0,00)
0,00
(0,00)
(-1,67*10^-5)
(0,00)
-0,1**
(0,01)
-0,04**
(0,02)
SIZE_LARGE
0,00*
(0,00)
Nitrogen_SizeL
Debt/equity
(control)
0,03**
(0,01)
0,03**
(0,01)
0,06**
(0,02)
0,05**
(0,02)
Rent paid per cow
(control)
0,00**
(0,00)
0,00**
(0,00)
0,00**
(0,00)
0,00**
(0,00)
Adjusted R2
0,58
0,60
0,63
0,64
N
52
52
52
52
**=significant at 5% significant level
*= significant at 10% significant level
Table 4.2
Return on Assets – Efficient Energy (IV.II)
Model I
Efficient Energy
Model II
Model III
Model IV
-0,95**
(0,17)
-0,89**
(0,17)
-0,67**
(0,20)
-0,01**
(0,00)
0,01
(0,01)
SIZE_LARGE
-0,58**
(0,28)
Energy_SizeL
Debt/equity
(control)
0,03**
(0,01)
0,02*
(0,01)
0,04**
(0,01)
0,04**
(0,01)
Rent paid per cow
(control)
0,00**
(0,00)
0,00**
(0,00)
0,00**
(0,00)
0,00**
(0,00)
Adjusted R2
0,58
0,73
0,76
0,77
N
52
52
52
52
**=significant at 5% significant level
*= significant at 10% significant level
30
Table 4.3
Return on Assets – Environmental Subsidies (IV.III)
Model I
Environmental
subsidies
Model II
Model III
Model IV
0,01
(0,00)
0,01
(0,00)
0,01
(0,00)
-0,01**
(0,00)
0,00
(0,01)
SIZE_LARGE
-0,54**
(0,16)
SubsidiesE_SizeL
Debt/equity (control)
0,03**
(0,01)
0,02**
(0,01)
0,06**
(0,02)
0,05**
(0,02)
Rent paid per cow
(control)
0,00**
(0,00)
0,00**
(0,00)
0,00**
(0,00)
0,00**
(0,00)
Adjusted R2
0,58
0,58
0,62
0,69
N
52
52
52
52
**=significant at 5% significant level
*= significant at 10% significant level
5.2 - Return on Assets
To begin with, the first regression, in table 4.1, proves that nitrogen surplus has no significant
effect on return on assets. Size is negatively correlated with return on assets. When the
interaction term is added to the model, a significant non-existing relationship with return on
assets is found. Efficient energy, in table 4.2, has a negative significant effect of -0,95 on
return on assets. There exists a negative relationship between size and return on assets. When
including the interaction term again a negative relationship is found, with magnitude -0,58.
Environmental subsidies, in table 4.3, has no significant relationship with return on assets,
however the interaction effect between environmental subsidies and size is found to be a
significant negative effect of -0,54. The size variable has a negative coefficient of -0,01 for all
three independent variables. The significant control variables’ effect, leverage ratio and rent
per cow, are respectively stable around 0,04 and 0,00.
31
Table 5.1
Return on Investment – Nitrogen Surplus (IV.I)
Model I
Nitrogen Surplus
Model II
Model III
Model IV
0,33
(0,27)
0,24
(0,29)
0,37
(0,35)
-9,60
(11,51)
15,50
(39,16)
SIZE_LARGE
-0,33
(0,50)
Nitrogen_SizeL
Debt/equity
(control)
-3,94
(28,74)
-0,07
(28,75)
21,86
(39,03)
29,38
(40,82)
Rent paid per cow
(control)
0,01
(0,01)
0,07
(0,10)
0,05
(0,11)
0,06
(0,11)
Adjusted R2
-0,04
-0,03
-0,04
-0,05
N
52
52
52
52
**=significant at 5% significant level
*= significant at 10% significant level
Table 5.2
Return on Investment – Efficient Energy (IV.II)
Model I
Efficient Energy
Model II
Model III
Model IV
-480,17
(477,71)
-395,52
(483,28)
-549,00
(582,20)
-11,74
(10,86)
-23,71
(27,16)
SIZE_LARGE
401,41
(833,64)
Energy_SizeL
Debt/equity
(control)
-3,94
(28,74)
-7,64
(28,97)
21,06
(39,27)
23,00
(39,80)
Rent paid per cow
(control)
0,01
(0,01)
0,01
(0,11)
0,05
(0,11)
0,06
(0,11)
Adjusted R2
-0,04
-0,04
-0,04
-0,05
N
52
52
52
52
**=significant at 5% significant level
*= significant at 10% significant level
32
Table 5.3
Return on Investment – Environmental Subsidies (IV.III)
Model I
Environmental
Subsidies
Model II
Model III
Model IV
54,25**
(4,25)
53,74**
(4,58)
53,78**
(4,61)
-4,76
(5,52)
-6,71
(7,25)
SIZE_LARGE
87,78
(208,80)
SubsidiesE_SizeL
Debt/equity (control)
-3,94
(28,74)
6,62
(14,66)
17,88
(19,70)
18,46
(19,91)
Rent paid per cow
(control)
0,01
(0,01)
-0,12**
(0,05)
-0,12**
(0,05)
-0,13**
(0,05)
Adjusted R2
-0,04
0,73
0,73
0,72
N
52
52
52
52
**=significant at 5% significant level
*= significant at 10% significant level
5.3 - Return on investment
Due to the fact that a negative adjusted R2 is found for the first two independent variables,
these models will not be used. A negative adjusted R2 can be caused by over-parameterization
and effects can be interpreted as not significant (Fidell & Tabachnik, 2007). The third model,
in table 5.3, using environmental subsidies, has a large positive adjusted R2 and a significant
positive effect on return on investment. In this model the significant control variables’ effect,
rent paid per cow, is stable around -0,11. From table 5.3 a positive effect of 54,25 on
environmental subsidies on return on investment can be concluded.
33
6.0 – Discussion
6.1 – Hypothesis 1
To answer the first hypothesis, this research makes use of the significant effects from model
II. A negative significant effect between farm net income and nitrogen surplus is found; an
increase in nitrogen surplus (diminishment of sustainability) will result in a decrease of farm
net income (financial performance indicator). Farm net income ranges from 136,97 to
1055,46. An increase of nitrogen surplus of 1 euro (fertilizer per cow), will result in a
decrease of farm net income of -3,89. A nitrogen surplus increase will thus almost quadruple
its effect on farm net income. Concluding from the second dependent variable, return on
assets, a significant non-existing relationship between nitrogen surplus and return on assets is
found. However, between return on assets and efficient energy a negative significant
relationship is found; an increase in the usage of energy per output (diminishment of
sustainability) results in a decrease of return on assets (financial performance indicator).
When revisiting the variable descriptives, table 1.1, we find a range of (0,00|0,09) for return
on assets and a (0,02|0,05) for (in)efficient energy use. A negative coefficient of -0,95,
represents a -0,95 decrease of return on assets when increasing the inefficient energy use by 1
euro per cow; this is an immense diminishment of return on assets.
Finally, for return on investment, a significant positive relationship between environmental
subsidies and return on investment is found. An increase in environmental subsidies, used as a
proxy for innovative sustainability, will result in an increase in return on investment (financial
performance indicator). An increase of 1 euro environmental subsidy per invested dollar,
results in a 54,25 increase in return on investment. Taking into account the range of return on
investment, from table 1.1, (−14,72|176,68), again a very large effect of environmental
subsidies per invested euro can be concluded.
Using these significant relationships this paper can partly confirm hypothesis 1, where a
sustainability increase (environmental subsidies increase or
nitrogen surplus/efficient energy decrease) leads to increased financial performance. This
research can only partly confirm the hypothesis due the fact that only some combinations of
financial performance and sustainability indicators are significant.
34
6.2 - Hypothesis 2
To answer hypothesis 2, this research will use the significant results of model III and IV. For
the first dependent variable, farm net income, this research finds no significant relationship
for the size variable and/or the interaction term. For the second dependent variable, return on
assets, a negative significant size coefficient is found for each sustainability indicator. This
could imply that larger dairy firms have worsened return on assets, as in comparison to
smaller firms. When investigating the interaction term in for the sustainability indicators, a
significant non-existing relationship between the interaction term of nitrogen surplus and size
with return on assets is found. Also a significant negative interaction effect of environmental
subsidies and efficient energy with size and return on assets is found. For the third dependent
variable, return on investment, no significant relationship between size and the interaction
term with return on investment is found. As concluded in the previous section, an
environmental subsidy increase indicates a sustainability improvement and a financial
performance increase. The negative interaction effect of environmental subsidies indicates
that, for larger dairy farms a sustainability improvement (environmental subsidies increase)
will likely lead to a lower increased financial performance, compared to small companies. In
the previous section also a negative relationship for efficient energy is found, i.e. an increase
in energy usage per cow (sustainability diminishment) will likely result in a decreased
financial performance. The negative interaction term between efficient energy and size
indicates that, for large dairy farms, a sustainability improvement (efficient energy decrease)
leads to a lower increased financial performance, as in comparison to small dairy farms.
Concluding that these results do not confirm hypothesis 2.
35
7.0 – Conclusion
This research investigates the much-discussed relationship between sustainability and
financial performance and the influence of size of the farm, in the Dutch dairy farming sector.
To investigate the relationship this research uses three dependent accounting-based variables
(financial performance indicators): farm net income, return on assets and return on investment
and three independent variables: nitrogen surplus, (in)efficient energy usage and
environmental subsidies per invested euro. Also there will be controlled for highly leveraged
farms and rent variation in the Netherlands.
This research concluded that a sustainability improvement leads to an increased financial
performance, however greatly depending on the financial indicator used in the research. Also
it concluded that by increasing the firm size, the positive relationship between sustainability
and financial performance will not be enhanced, but rather decreased the (positive) effect of
sustainability on financial performance.
An extensive body of literature has preceded this research to answer the question whether
corporate social responsibility leads to increased financial performance. Making use of the
most reliable data and statistical methodology this research answers this question, using an
empirical case study of Dutch dairy farms over the years 1989-2009. This research provides
farms in the Dutch dairy market the underlying argumentation when ‘investing’ in corporate
social responsibility. It provides managers with the underlying prove of economic viability
when making such an investment. Also it provides insights in the magnitude of the financial
performance increases, where can be concluded that especially increasing efficient energy
usage will have major positive consequences on financial performance. This research also
concludes that the positive effect of sustainability improvements on financial performance,
will not be enhanced by increasing farms size. To clarify that this does not mean that large
companies do not experience a positive relationship between sustainability and financial
performance, rather this research concludes that the financial increase of large companies is
lower as compared to smaller companies. This poses the following interpretation of this
research: small companies especially benefit from investing in corporate social responsibility.
From a governmental perspective this means that small firms should be easier to incentivize
when convincing to invest in corporate social responsibility, as opposed to larger firms.
36
Finally, the research question will be revisited:
“What is the relationship between sustainability and financial performance in the Dutch dairy
farming industry and how will this be affected by (farm) size”
Using this research, one could answer the research question as follows: there exists a
positively correlated relationship between sustainability and financial performance, where
sustainability improvements have a positive relationship with increased financial
performance, on which (farm) size has a negative effect, where the positive effect of
sustainability on financial performance, will not be enhanced by increasing farm size.
37
8.0 - Limitations & Recommendations
In this section the limitations of this research will be discussed. The first limitation is the
medium-small sample size. A larger sample size is always preferable, however due to the
many variables in the models, an even larger sample size will most likely lead to variable
coefficients closer to the truth. Secondly, due to the fact that the F.A.D.N does not provide us
with information concerning the external market in which the dairy farms are operating, this
research could not make use of market-based financial performance measures. However when
considering the completeness of the research this could be valuable and possibly lead to
different conclusions. Thirdly, to create a most accurate result, the data covers a time span of
20 years. During these years reforms in the dairy farming market continuously change, such
as: income and rural (keeping agricultural land viable) policy changes, this could have a
significant effect on the results. Finally, this research uses environmental subsidies per
invested euro as a proxy for the willingness to be sustainable innovative. The use of a proxy is
always a risk, as in this case one does not know if environmental subsidies are deliberate
sustainability improvements of the dairy farm or motivated by mere financial benefits gained
due to the subsidy.
A first recommendation to future research is to take market-based financial performance
measures into account, next to the accounting-based performance measures. From the size and
sustainability indicator interaction term, environmental subsidies and efficient energy found a
negative relationship, when comparing large to small dairy farms. Based on the literature
framework, a positive relationship was expected and hypothesis 2 was rejected. A
recommendation to future research would be to re-investigate hypothesis 2, for instance in
other sectors of the economy. Lastly, this research, for some sustainability indicators, finds a
significant relationship with one financial performance indicator and an insignificant
relationship for another financial performance indicator. A final recommendation for future
research would be to investigate which financial performance indicator best reflects the
sustainability-financial performance relationship. As it is very likely that the ‘contradiction’
discussed in the literature framework is caused by the different financial performance
indicators used. Also every financial performance indicator holds different information and it
depends on the party to convince or relationship to prove on which financial performance
indicator best reflects the goal of the research.
38
9.0 - Appendix
Table 1 – FADN variables
name
description
1
SYS02 Farms represented
2
SYS03 Sample farms
3
SE005 Economic size
4
SE010 Total labour input
5
SE011 Labour input
6
SE015 Unpaid labour input
7
SE020 Paid labour input
8
SE021 Paid labour Input
9
SE025 Total Utilised Agricultural Area
10
SE030 Rented U.A.A.
11
SE016 Unpaid labour input
12
SE035 Cereals
13
SE041 Other field crops
14
SE042 Energy crops
15
SE046 Vegetables and flowers
16
SE050 Vineyards
17
SE054 Permanent crops
18
SE060 Olive groves
19
SE055 Orchards
20
SE065 Other permanent crops
21
SE071 Forage crops
22
SE072 Agricultural fallows
23
SE073 Set aside
24
SE074 Total agricultural area out of production
25
SE075 Woodland area
26
SE080 Total livestock units
27
SE085 Dairy cows
28
SE090 Other cattle
29
SE095 Sheep and goats
30
SE100 Pigs
31
SE105 Poultry
32
SE110 Yield of wheat
39
33
SE115 Yield of maize
34
SE120 Stocking density
35
SE125 Milk yield
36
SE131 Total output
37
SE132 Total output / Total input
38
SE135 Total output crops & crop production
39
SE136 Total crops output / ha
40
SE140 Cereals
41
SE145 Protein crops
42
SE146 Energy crops
43
SE150 Potatoes
44
SE155 Sugar beet
45
SE160 Oil-seed crops
46
SE165 Industrial crops
47
SE170 Vegetables & flowers
48
SE175 Fruit
49
SE180 Citrus fruit
50
SE185 Wine and grapes
51
SE190 Olives & olive oil
52
SE195 Forage crops
53
SE200 Other crop output
54
SE206 Total output livestock & livestock products
55
SE207 Total livestock output / LU
56
SE211 Change in value of livestock
57
SE216 Cows' milk & milk products
58
SE220 Beef and veal
59
SE225 Pigmeat
60
SE230 Sheep and goats
61
SE235 Poultrymeat
62
SE240 Eggs
63
SE245 Ewes' and goats' milk
64
SE251 Other livestock & products
65
SE256 Other output
66
SE260 Farmhouse consumption
67
SE265 Farm use
68
SE270 Total Inputs
69
SE275 Total intermediate consumption
40
70
SE281 Total specific costs
71
SE284 Specific crop costs / ha
72
SE285 Seeds and plants
73
SE290 Seeds and plants home-grown
74
SE295 Fertilizers
75
SE300 Crop protection
76
SE305 Other crop specific costs
77
SE309 Specific livestock output / LU
78
SE310 Feed for grazing livestock
79
SE315 Feed for grazing livestock home-grown
80
SE320 Feed for pigs & poultry
81
SE325 Feed for pigs&poultry home-grown
82
SE330 Other livestock specific costs
83
SE331 Forestry specific costs
84
SE336 Total farming overheads
85
SE340 Machinery & building current costs
86
SE345 Energy
87
SE350 Contract work
88
SE356 Other direct inputs
89
SE360 Depreciation
90
SE365 Total external factors
91
SE370 Wages paid
92
SE375 Rent paid
93
SE380 Interest paid
94
SE390 Taxes
95
SE395 VAT balance excluding on investments
96
SE405 Balance subsidies & taxes on investments
97
SE406 Subsidies on investments
98
SE407 Payments to dairy outgoers
99
SE408 VAT on investments
100
SE410 Gross Farm Income
101
SE415 Farm Net Value Added
102
SE420 Farm Net Income
103
SE425 Farm Net Value Added / AWU
104
SE430 Farm Net Income / FWU
105
SE436 Total assets
106
SE441 Total fixed assets
41
107
SE446 Land, permanent crops & quotas
108
SE450 Buildings
109
SE455 Machinery
110
SE460 Breeding livestock
111
SE465 Total current assets
112
SE470 Non-breeding livestock
113
SE475 Stock of agricultural products
114
SE480 Other circulating capital
115
SE485 Total liabilities
116
SE490 Long & medium-term loans
117
SE495 Short-term loans
118
SE501 Net worth
119
SE506 Change in net worth
120
SE510 Average farm capital
121
SE516 Gross Investment
122
SE521 Net Investment
123
SE526 Cash Flow (1)
124
SE530 Cash Flow (2)
125
SE532 Cash flow / farm total capital
126
SE600 Balance current subsidies & taxes
127
SE605 Total subsidies - excluding on investments
128
SE610 Total subsidies on crops
129
SE612 Set aside premiums
130
SE613 Other crops subsidies
131
SE615 Total subsidies on livestock
132
SE616 Subsidies dairying
133
SE617 Subsidies other cattle
134
SE618 Subsidies sheep & goats
135
SE619 Other livestock subsidies
136
SE621 Environmental subsidies
137
SE622 LFA subsidies
138
SE624 Total support for rural development
139
SE623 Other rural development payments
140
SE699 Other subsidies
141
SE625 Subsidies on intermediate consumption
142
SE626 Subsidies on external factors
143
SE630 Decoupled payments
42
144
SE631 Single Farm payment
145
SE632 Single Area payment
146
SE640 Additional aid
147
SE650 Support_Art68
148
TF8
Production (field crops, horticulture, other permanent crops, milk, other grazing
lifestoch, granivores mixed)
43
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46