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........................................................................................................................22.0 - Literature & hypotheses......................................................................................................5

2.1 - Sustainability...................................................................................................................62.2 - Sustainability in the dairy farming sector.......................................................................62.3 - Corporate social responsibility and financial performance............................................82.4 - Sustainability and financial performance in the agricultural sector..............................102.5 - Hypotheses....................................................................................................................11

3.0 - Data...................................................................................................................................153.1 - Independent variables...................................................................................................163.2 - Dependent variables......................................................................................................183.3 - Control variables...........................................................................................................193.4 - Variable overview.........................................................................................................193.5 - Variable descriptives.....................................................................................................20

4.0 - Methodology.....................................................................................................................214.1 - Financial performance indicators..................................................................................214.2 - Research methodology..................................................................................................224.3 - Correlation matrix.........................................................................................................25

5.0 - Results..............................................................................................................................275.1 - Farm net income...........................................................................................................295.2 - Return on Assets...........................................................................................................315.3 - Return on investment....................................................................................................33

6.0 – Discussion........................................................................................................................336.1 – Hypothesis 1.................................................................................................................336.2 - Hypothesis 2..................................................................................................................34

7.0 – Conclusion.......................................................................................................................358.0 - Limitations & Recommendations.....................................................................................379.0 - Appendix..........................................................................................................................3810.0 – Bibliography..................................................................................................................43

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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 much-

discussed topic. Dutch environmental-agricultural protection expenditure has risen rapidly.

Economic viability is a necessary condition in sustainability and though environmental-

agricultural 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 milk-

quota, 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 micro-

economic 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 =

Nitrogen_Surplus

Fertilizers/

Total dairy cows

Sustainability

indicator variable

Scale variable IV

Efficient Energy =

Efficient_Energy

Energy/

Total output

Sustainability

indicator variable

Scale variable IV

Environmental

subsidies =

SubsidiesE

Environmental

subsidies /Net

investment

Sustainability

indicator variable

Scale variable IV

Farm net income per

cow =

FNI_cow

Farm net Income Financial

indicator variable

Scale variable DV

Return on Assets =

Return_Assets

Farm net Income/

Total assets

Financial

indicator variable

Scale variable DV

Return on Investments

=

Return_Investments

Farm net Income/

Net investment

Financial

indicator variable

Scale variable DV

Economic size =

SIZE_LARGE

ESU (>= 100) Size dummy

variable

Dummy variable IV

Rent paid per cow =

Rentpaid_cow

Rent paid/

Total dairy cows

Control variable Scale variable CV

Leverage ratio =

DE_ratio

Total debt/

Total equity

Control variable Scale variable CV

20

3.5 - Variable descriptives

Table 1.1

Variable descriptives – independent variables (IV), dependent variables (DV), control

variables (CV)

Mean Media

n

Min. Max. Standard

deviation

Nitrogen surplus =

Nitrogen_Surplus - IV

80,91 82,33 47,09 116,15 17,09

Efficient Energy =

Efficient_Energy - IV

0,03 0,03 0,02 0,05 0,01

Environmental subsidies =

SubsidiesE - IV

0,13 0,02 -0,06 3,08 0,44

Farm net income per cow =

FNI_cow- DV

628,83 638,36 136,97 1055,46 205,22

Return on Assets =

Return_Assets - DV

0,03 0,03 0,00 0,09 0,02

Return on Investments =

Return_Investments - DV

6,91 1,62 -14,72 176,68 27,11

Rent paid per cow =

Rentpaid_cow - CV

129,77 131,96 49,80 212,63 45,65

Leverage ratio =

DE_ratio - CV

0,35 0,36 0,05 0,64 0,14

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. Accounting-

based 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∗Rentpai dcow+ β2∗D E ratio+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∗Rentpai dcow+β3∗D Eratio+ϵ

Where sustainability represents: nitrogen surplus, (in)efficient energy usage and

environmental subsidies per invested euro.

Model 3: independent variable, size and control variables

23

In this model, the effect of size on the dependent variable is investigated.

Financial performance=β0+β1∗sustainability+β2∗¿¿LARGE++ β3∗Rentpai dcow+β4∗D Eratio+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∗¿¿LARGE+ β3∗interaction term+4∗Rentpai dcow+β5∗D Eratio+ϵ

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

24

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.

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.

Table 2.1

Correlation matrix

25

Sizelarge DE ratio

Rent paid per cow

Environmental Subsidies

Efficient Energy

Nitrogen Surplus

Size large 1 0.69** -.0,25 -0.19 -0,12 -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

When checking for intercorrelations, the following rule of thumb is used: a correlation

=< (-) 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

26

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.

5.0 - ResultsTable 3.1

Farm net Income per cow – Nitrogen Surplus (IV.I)

Model I Model II Model III Model IV

Nitrogen surplus -3,89** (1,61)

-4,22**(1,75)

-4,28**(2,12)

SIZE_LARGE -36,22 -48,03

27

(-36,23) (241,04)

Nitrogen_SizeL 0,16(3,03)

Debt/equity

(control)

367,49**(182,52)

321,71*(175,38)

404,45*(239,11)

400,92(251,82)

Rent paid per cow

(control)

-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

Table 3.2

Farm net Income per cow – Efficient Energy (IV.II)

Model I Model II Model III Model IV

Efficient Energy -2844,08(3037,82)

-114,18(3101,12)

-2698,98(3745,11)

SIZE_LARGE 37,44(69,68)

2,18(174,69)

Energy_SizeL -21,95(5362,51)

Debt/equity

(control)

367,49**(182,52)

345,58*(184,23)

253,98(251,99)

253,88(253,87)

Rent paid per cow

(control)

-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

**=significant at 5% significant level *= significant at 10% significant level**=significant at 5% significant level *= significant at 10% significant level

**=significant at 5% significant level *= significant at 10% significant levelTable 3.3

Farm net Income per cow – Environmental Subsidies (IV.III)

Model I Model II Model III Model IV

Environmental subsidies

-11,06(56,97)

-8,402(57,97)

-10,28(57,43)

28

SIZE_LARGE 24,78(70,05)

105,09(90,24)

SubsidiesE_SizeL -3616,17(2597,90)

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

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 4.1Return on Assets – Nitrogen surplus (IV.I)

Model I Model II Model III Model IV

Nitrogen surplus 0,00*(0,00)

0,00(0,00)

(-1,67*10^-5)(0,00)

SIZE_LARGE -0,1**(0,01)

-0,04**(0,02)

Nitrogen_SizeL 0,00*(0,00)

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)

30

Table 4.2Return on Assets – Efficient Energy (IV.II)

Model I Model II Model III Model IV

Efficient Energy -0,95**(0,17)

-0,89**(0,17)

-0,67**(0,20)

SIZE_LARGE -0,01**(0,00)

0,01(0,01)

Energy_SizeL -0,58**(0,28)

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

Table 4.3Return on Assets – Environmental Subsidies (IV.III)

Model I Model II Model III Model IV

Environmental subsidies

0,01(0,00)

0,01(0,00)

0,01(0,00)

SIZE_LARGE -0,01**(0,00)

0,00(0,01)

SubsidiesE_SizeL -0,54**(0,16)

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)

Table 4.1Return on Assets – Nitrogen surplus (IV.I)

Model I Model II Model III Model IV

Nitrogen surplus 0,00*(0,00)

0,00(0,00)

(-1,67*10^-5)(0,00)

SIZE_LARGE -0,1**(0,01)

-0,04**(0,02)

Nitrogen_SizeL 0,00*(0,00)

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)

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 4.3Return on Assets – Environmental Subsidies (IV.III)

Model I Model II Model III Model IV

Environmental subsidies

0,01(0,00)

0,01(0,00)

0,01(0,00)

SIZE_LARGE -0,01**(0,00)

0,00(0,01)

SubsidiesE_SizeL -0,54**(0,16)

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)

Table 5.1Return on Investment – Nitrogen Surplus (IV.I)

Model I Model II Model III Model IV

Nitrogen Surplus 0,33(0,27)

0,24(0,29)

0,37(0,35)

SIZE_LARGE -9,60(11,51)

15,50(39,16)

Nitrogen_SizeL -0,33(0,50)

Debt/equity (control)

-3,94(28,74)

-0,07(28,75)

21,86(39,03)

29,38(40,82)

32

Table 5.1Return on Investment – Nitrogen Surplus (IV.I)

Model I Model II Model III Model IV

Nitrogen Surplus 0,33(0,27)

0,24(0,29)

0,37(0,35)

SIZE_LARGE -9,60(11,51)

15,50(39,16)

Nitrogen_SizeL -0,33(0,50)

Debt/equity (control)

-3,94(28,74)

-0,07(28,75)

21,86(39,03)

29,38(40,82)

Table 5.2Return on Investment – Efficient Energy (IV.II)

Model I Model II Model III Model IV

Efficient Energy -480,17(477,71)

-395,52(483,28)

-549,00(582,20)

SIZE_LARGE -11,74(10,86)

-23,71(27,16)

Energy_SizeL 401,41(833,64)

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

Table 5.3Return on Investment – Environmental Subsidies (IV.III)

Model I Model II Model III Model IV

Environmental Subsidies

54,25**(4,25)

53,74**(4,58)

53,78**(4,61)

SIZE_LARGE -4,76(5,52)

-6,71(7,25)

SubsidiesE_SizeL 87,78(208,80)

Debt/equity (control) -3,94(28,74)

6,62(14,66)

17,88(19,70)

18,46(19,91)

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.

6.0 – Discussion

6.1 – Hypothesis 1

33

Table 5.3Return on Investment – Environmental Subsidies (IV.III)

Model I Model II Model III Model IV

Environmental Subsidies

54,25**(4,25)

53,74**(4,58)

53,78**(4,61)

SIZE_LARGE -4,76(5,52)

-6,71(7,25)

SubsidiesE_SizeL 87,78(208,80)

Debt/equity (control) -3,94(28,74)

6,62(14,66)

17,88(19,70)

18,46(19,91)

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.

6.2 - Hypothesis 2

34

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.

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.

35

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.

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”

36

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.

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

37

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.

9.0 - Appendix

Table 1 – FADN variables

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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

33 SE115 Yield of maize

34 SE120 Stocking density

35 SE125 Milk yield

36 SE131 Total output

39

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

70 SE281 Total specific costs

71 SE284 Specific crop costs / ha

72 SE285 Seeds and plants

73 SE290 Seeds and plants home-grown

40

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

107 SE446 Land, permanent crops & quotas

108 SE450 Buildings

109 SE455 Machinery

110 SE460 Breeding livestock

41

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

144 SE631 Single Farm payment

145 SE632 Single Area payment

146 SE640 Additional aid

147 SE650 Support_Art68

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148 TF8 Production (field crops, horticulture, other permanent crops, milk , other grazing

lifestoch, granivores mixed)

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