The intensive farming systems of developed countries, such as United Kingdom seek to maximize yield through what is usually described by agricultural economists as Best Management Practice (BMP), which involves the most efficient use of all inputs, including fertilizers, herbicides, seed varieties, and precision agricultural techniques (Goulding et al, 2008). (BMP) Fertilizers have been central to this approach, which has resulted in a tremendous increase in productivity over that last 40 years. For example, the efficient use of improved fertilizers, combined with new varieties of wheat and the successful use of crop protection chemicals, has increased grain yields from 3 tons per hectare to approximately 10 to 11 tons per hectare today (Goulding et al, 2008). Moreover the current market economic incentives facing many farmers are likely to encourage excess fertilizer application (Scott, 2005). It is generally recognized that if eventually the adoption of market prices for most agricultural goods without any subsidies became a reality, in order to be competitive with the lower production costs of developing countries in South America, Asia, Eastern Europe and the Former Soviet Union, the pressure to intensify even the most UNITED KINGDOM intensive production systems will as well become reality despite the negative consequences on the environment (Goulding et al, 2008).
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The purpose of this study is to examine the socio-economic determinants of intensity of fertiliser application in non-organic cropland farms in England using a panel data model (panel data). The quantitative and behavioural studies in agriculture are frequently based on the notion that the family business is managed by a “single decision-maker” – the person who exerts the financial and managerial control over the farm unit (Morris and Evans, 2004). This perspective derives from neoclassical economies and implies that decisions for the business are taken by a single entrepreneur (War and Lowe, 1994). However this study differs from much previous research into the estimation and clarification of the technical drivers responsible for fertilizer application by including variables that relate to both farmer characteristics and farm economic aspects. It will be followed an argument commonly accept in the literature that farmers tend to over-apply fertilizer from an agronomic perspective (i.e., more than warranted to attain a given yield target) essentially given the uncertainty about environmental growing conditions (Sheriff, 1995; Scott, 2005). (apply mainly N). Nonetheless the author will have in mind that the fertilizer inputs into agricultural systems in the UNITED KINGDOM occur mainly via Nitrogen (Velthof et al., 1998) with the general objective to reduce the probability of poor yields and moreover increase the variance in profit. However, given the emergent apprehension with the impact of agriculture on environment and society, there has been a growing need to develop a more comprehensive definition of agriculture productivity (Pretty, 1998; Defra, 2002).
Although government policies will not be addressed or recommended specifically, the author hopes to open a new channel for discussion. As Annan (2005) argues it is imperative to aim at a reasonable balance between the level of technical detail and the availability of meaningful data describing future development of new and improved categories of abatement options. Consequently contributing to reach the 10per cent inorganic fertilizer reduction by 2020 with consequent reductions in N2O emissions (Entec, 2004), and moreover contribute to UNITED KINGDOM reach the overall national target of 80per cent GHG reduction by 2050(ADAS, 2009).(reduce emissions)
Agriculture and fertilizer
Agriculture is one of the most successful sectors in terms of productivity growth, has outpaced the rapid growth in demand for its output for the past decades (Shaink el al, 2002). (agri success). This trend has provided hefty social benefits, such as increased the accessibility of agricultural goods usually at a lower price, provision of jobs and therefore rural sustainability, energy and also positive environmental effects, such as aesthetic value, carbon sequestration by soils and trees, and other additional benefits that are linked with good husbandry such as maintenance of natural habitats and countryside landscape (Shaink et al,2002; Scott, 2005) (social benefits / positive extern). However, is largely referenced in literature that the increased use of chemicals either fertilisers or pesticides in agriculture intensive systems is associated with hidden costs due to environmental pollution – in soil, water and atmosphere -, consequently has amplified the negative social effects on the natural environment (eg. Shaink et al,2002; Scott,2005 ) (pollution1). This argument is supported by an analysis of the externalities from UNITED KINGDOM agriculture made by Hartridge and Pearce (2001), finding that negative externalities amount to at least £1 billion, and positive externalities offset approximately half of these negative effects (negative/positive external).
Farmers and fertilizer application
The main question rises once more, what are the fertilizer application determinants? For a typical farm manager, output is what matters most to the business survival and prosperity. Consequently, farmers apply fertilisers since they represent personal benefits in the form of improved outputs and incomes, however plants absorb fertilisers just up to their needs only, therefore surplus fertiliser over and above the needs of plants can cause harmful side effects (Scott, 2005) either on the farm profit or in the environment. (more/less fert plant). A given agricultural input bundle might result in wide diverse output levels according to the level at which random factors operate (Gallacher, 2001) (input output). Rounsevell and Reay (2009) clarify the previous argument stating that land use and therefore fertilizer application changes are driven primarily by farmer decisions, which are affected by the economic environment (output and input prices), soil features, crop and livestock yields, timeliness of field operations, availability of investment capital, subsidies as well as the socio-cultural attributes of individual farmersThe first driver is clearly an agronomic argument, since agronomists agree that crop nutrient uptake is higher in years with good growing conditions (Babcock, 1992), therefore if a farmer applies the optimal amount of fertilizer for mean growing conditions, and in a particular year those conditions are better than expected, there will be too little fertilizer and decrease in production. On other hand if weather conditions are not conducive, there will be too much fertilizer (Sheriff, 2005), thus a risk-neutral farmer applies fertilizer at a higher rate as long as the expected gain in profit from the increased yield is higher than the expected loss in profit from wasted fertilizer.
Another hypothesis is proposed by Rajsic and Weersink (2008). They argue that while there may be agreement on the functional form of crop response to fertilizer, there will be differences in the optimal rate between locations. Numerous studies have reported that the maximum economic nitrogen rate varies spatially and that the degree of variability can be substantial (Carr et al., 1991). As a consequence there is a need to analyze the spatial variations in order to state the yield potential of the field and/or region, the underlying assumption is that yield potential is directly linked to the productivity of nitrogen, so fields with higher estimated output receive higher rates of fertilizer (Rajsic and Weersink 2008). Dai et al (1993), however, found that nitrogen and soil quality are complements, and soil quality uncertainty and nitrogen availability are linked which will increase nitrogen demand and consequently nitrogen input. Additionally Rajsic (2008), Sheriff (2005) and also Dai el al (1993) argue that one of the main causes for over-fertilisation might be related to the uncertainty about weather and soil characteristics that can lead both risk-averse and risk-neutral farmers to over-apply nutrients, therefore the decision to apply a ”little extra just in case” is particularly appropriate if the cost of over-application is low compared to the cost of under application (Rajsic, 2008) (a little extra risk averse). This idea is supported by Sherriff (2005), arguing that farmers will apply more fertilizer than a crop can use due to a perception that the general recommendations are not appropriate for their individual situations. Smill (1999) argues that the application of N is fairly inefficient in most farms, since farmers are applying nitrogen at levels that exceed those suggested by either government extension services or by the optimal nitrogen appliance (Rajsic and Weersink, 2008) (N inefficiency). Approximately half of Nitrogen applied during a growing season is typically recovered in the crop biomass throughout that season, therefore this inefficiency represents a noteworthy cost to farmers and an important consequences for ecosystem and human health as Nitrogen moves beyond the farm level in several aqueous or gaseous forms, such as N2O(Matson et al., 1997, 1998; Galloway, 1998).
In practice evidence suggests that farmers systematically over-estimate the impact of additional nitrogen relative to agronomists’ models and therefore they maintain their beliefs after seeing results from experimental plots (SriRamaratnam et al., 1987). If farmers’ perceptions are incorrect, these beliefs will lead to over-application, conversely if their sensitivity is correct, analysts may infer excess nutrient applications where none exist. Thus if weather, the relation between fertiliser prices and output prices and soil features are not main and/or the only drivers behind fertiliser application, which characteristics does the farmer have to apply more or less fertiliser compared to those with the same features and constraints?
The effect of fertilizers on the environment
The relatively cheap price of Nitrogen in relation to its yield improvement benefits, and allowing farmers substantial management flexibility, has been a central contributory factor in determining its overuse and consequently the environmental impacts reported below.
It is known that Agricultural emissions of nitrous oxide have fallen by 13 per cent over the 10 years up to 2005 and the trend is continuing (DEFRA, 2007).However despite this reduction in the UNITED KINGDOM and other major developed countries, the major direct emissions of greenhouse gases (GHGs) are from agriculture methane (CH4) caused by enteric fermentation by ruminant livestock and manure management, and nitrous oxide (N2O) from soils (Gibbons, 2005). Additionally methane has a global warming potential 21 times greater than carbon dioxide while nitrous oxide global warming potential (GWP) is considered 296 times that of the same mass of carbon dioxide (Houghton et al., 2001), consequently fairly small concentrations of this gas are sufficient to induce drastic changes in the atmosphere. At current estimates N2O contributes about 7 per cent of the greenhouse gas emissions in terms of the GWP (Winiwarter, 2005). As a result, among the gases considered by the Kyoto Protocol, N2O is ranked third in importance behind carbon dioxide (CO2) and methane (CH4) (Winiwarter, 2005). Seinfeld and Pandis (1998) add that N2O is a very stable compound in the atmosphere, with a mean lifetime of 120 years, so the emissions will have an effect on the global concentrations in the atmosphere for many decades. The same authors argue that N2O is able to strongly absorb infrared light, thus it also exerts a considerable effect on the earth’s radiation absorption. Therefore is obvious the magnitude of nitrogen fertilization emissions has a dramatic effect on the environment.
Approximately 1per cent of the anthropogenic Nitrogen input into agricultural systems is emitted as nitrous oxide, with agriculture as a whole contributing to 66per cent of total UNITED KINGDOM nitrous oxide emissions in 2006, 95per cent of it via direct emissions from agricultural soils (IPCC, 2006). In addition, fertiliser manufacturing is energy-intensive (Rounsevell and Reay, 2009). Carbon dioxide emissions from ammonia production – most of which is for fertiliser use – made up 0.3per cent (1.6 million tonnes) of UNITED KINGDOM CO2 emissions in 2006 (DEFRA, 2006). Nitrogenous fertiliser consumption in the UNITED KINGDOM increased by nearly 300 per cent between 1961 and the late 1980s, regardless of the decline in agricultural land area (roughly 15per cent in the same time interval) – indicating a large increase in application rates per unit area of land over this period (Rounsevell and Reay, 2009). As stated previously, fertiliser Nitrogen consumption gradually declined after 1990, reaching a rate of around 1.2 million tonnes per year in 2006 (DEFRA, 2008).
As Smil (2000, 2001) argues, Nitrogen (N) is a key input in agriculture, therefore we cannot simply exclude or limit the application of it to meaningless values. We should instead open a new channel of discussion in order to improve or formulate new policies in an enhanced cost-efficient way that decreases damaging effects on the environment and improves farms’ profits. This can only be achieved if each of determinants of fertilizer application are well understood.
Project scope – UNITED KINGDOM agricultural features
UNITED KINGDOM land use is still largely dominated by agriculture. In June 2008 about 77 per cent of the total land area of the UNITED KINGDOM, which represents approximately 18.8 million hectares, was used for agriculture proposes (DEFRA, 2008). This proportion is relatively large compared with the average of 50 per cent in the EU27, and 54per cent, 47per cent and 50per cent for France, Germany and Spain, respectively (Angus et al, 2009). Despite these figures, agriculture’s contribution to GDP and employment in the UNITED KINGDOM is low, at about 0.5per cent and 1.8per cent respectively (DEFRA, 2009). Of this area, about 28 per cent is allocated to arable cropping, including fallow land, and 67 per cent to grassland, mostly permanent pastures, and 58 per cent (10.2 million hectares) is considered lowland, defined as land less than 240m above sea level. (Angus et al, 2009). In England due to patterns of agricultural land constraints relative to soils and topography features, the major concentration of grassland and livestock farming is located in the North and West, and arable farming in the East and South (Angus et al, 2009). Consequently, the largest farms in the UNITED KINGDOM are concentrated in southern and eastern England (Ward, 2000). The agricultural sector in the UNITED KINGDOM is composed of over 300,000 holdings, varying widely in size and type, employing an assortment of different farming practices and use of inputs such as soil and water as well as fertilizers, land and waste management (DEFRA, 2009). One common aspect among the major countries in the EU is that the farming population is getting older. Eurostat show in 2000 that in UNITED KINGDOM only 5.2 per cent of farmers were under 35 years old, compared to 7.4 percent in 1990. The absolute number of under 35s had fallen over the last decade by 6,000 which represents more than one third. Over the same period, the proportion of holders with 65 years old and over had risen from 22.1per cent to 25.3per cent (DEFRA, 2007).
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Regarding the educational level, between 1990 and 2005 there has been almost no change to the overall proportions, roughly three quarters of farmers have no formal agricultural training, with the remaining 25per cent equally divided between the higher education levels (DEFRA, 2007). Another important point relates to the fact that 38per cent of managers of the largest farms have ‘proper agricultural education’ compared to just 7 per cent on the smallest farms (DEFRA, 2007).
Personal Characteristics – effects on farm efficiency
In modern agriculture there is an increasing need to produce policy evaluation studies in order to be acquainted with the major drivers behind the decisions made by farmers within a socio-demographic context.
Numerous studies that have identified a significant variation in the physical and financial performance achieved by farmers operating within the same economic and environmental constraints (Wilson et al, 2001;Rougoor et al, 1998). Therefore, it is pertinent to inquire the reason why this variation occurs. Kay and Edwards (1994) argue that in many occasions the variation in management is the cause of performance fluctuation (farm management). However, unlike physical factors of production (e.g. land, labour, and capital) management is not directly observable, consequently this causes difficulties to any analysis that attempts to explain the management influence on farm performance. Rougoor et al. (1998) defined management capacity into two components: personal feature (e.g., drives, motivations, social factors and education) and features of the decision-making process (e.g., procedures in planning, implementation and control of decisions). Moreover, it is argued that the decision-making process is obviously influenced by the link of the factors stated above, and if any of them is excluded the cause of farm efficiency variation might be incorrectly measured (Wallace, 1974; Kay and Edwards, 1994; Poggi-Varaldo, 1998;Rougoor et al, 1998; Wilson et al, 2001) . Rougoor et al. (1998) highlights the argument that a manager may hold beneficial personal skills however fails to accomplish high performance due to a poor decision-making process.
Previous research made by Huffman (1974) found a positive impact of human capital on allocative efficiency in agriculture. In particular, these authors argued that education diminishes the time needed to “adjust” to changes in production options and/or price ratios. An additional factor that might explain the farm efficiency variation is the farmer’s age. Burton (2009) emphasises the strength of age as an indicator since age reflects the level of experience which might be a complement or even a substitute of education. In order to demonstrate the significance of education in this subject, Lockhead et al (1981) presented a detailed survey of studies analysing the effect of farmer education on farm management efficiency using the results from 37 data sets, investigating the effect of institutional education and non-formal education. They concluded that in 31 of these data sets, institutional education was found to have a positive and significant effect, and 8 of which provided evidence that non-formal education was also significantly positively related to productivity. An additional reason for more efficient input and output combinations being attained by more educated farmers is given by Welch (1978) and further by Gallacher (2001), both arguing that optimum firm size is correlated with education as it relates to optimum scale of production, usually the higher education level obtained, the larger the size of the farm being managed.
In this study, it will be exploit “formal education” as one of the explanatory causes in the possible efficiency dissimilarity between two or more farms with the same constraints, due to the difficulty in accurately measuring non-formal education. However, the author is conscious that the final outcome might be ambiguous since these two forms of education are usually complements (Lockhead, 1981; Mook, 1981; Asfaw, 2004).
Data Source – Farm Business Survey
The FBS is widely recognised as the most comprehensive and independent survey of farm incomes and provides an authoritative data source on the economic and physical performance of farm businesses in England and Wales. It is undertaken each year by the Department for Environment, Food and Rural Affairs (DEFRA) and the National Assembly for Wales (NAW). In England, the survey is conducted by a consortium of seven FBS Research Centres – Universities of Cambridge, Newcastle upon Tyne, Nottingham and Reading, and Askham Bryan, Duchy and Imperial Colleges, led by the University of Nottingham. Its members work in partnership, using uniform standard practices in reporting their findings to ensure consistent data quality, accuracy and validity.
The principal function of the Farm Business Survey (FBS) is to inform the UNITED KINGDOM Government and EU agricultural policy makers of the current financial state of the different sectors of UNITED KINGDOM farming. The FBS also provides full management accounting data on the agricultural activities of farm businesses, location, physical and environmental characteristics of the farm and several measures of non-agricultural activity, such as farm household characteristics.
The survey uses a sample of farms that is representative of the national population of farms in terms of farm type, farm size and regional location. Since 2005/06 approximately 2400 individual farms took part in this survey of which roughly 2000 are English (the rest being from Wales). Results are compiled using accredited documents and personal interviews and written up into ‘Farm Business Survey yyyy/yy’.
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