EFFICIENCY ANALYSIS IN DIFFERENT TYPOLOGIES OF FARMING IN ITALIAN FADN DATASET

Italian farms are characterized by modest plots of usable agricultural area scattered in many rural villages. The purpose of this analysis was to assess by a quantitative method technical, economic and allocative efficiency in Italian farms over the time 20042013 in function of different typologies of farms (TF) and their own farm productive specialization. Hence, the main question of the paper has been to estimate if the farm’s specialization in cultivating crops or in breeding livestock has influenced the efficiency of Italian farms. Findings have pointed out an important impact of financial subsidies allocated by the Common Agricultural Policy on the level of technical and economic efficiency; outcomes have also emphasized as a cut in costs of some inputs such as fertilizers and crops protection is essential in increasing efficiency in Italian farms.


Introduction
Main findings in the most recent Italian Agricultural Census in 2000, 2010 and in the Eurostat database have emphasized as more than 90% of Italian farms has got an average amount in usable agricultural area lower than 10 hectares (Istat, 2012). Reasons of this growth in can been found in a significant decrease of agrarian enterprises as a consequence of an intensified process of exodus from the countryside because of the economic recession in 2008 and also because of a squeezing of farmer's income (Van der Ploeg et al., 2002). The typology of farms, in terms of farm's specialization in crops and or in breeding, and the location of farms have been two main factors influencing the level of farm's income and consequently the out rural emigration. Comparing outcomes in all other European countries, it emerges that more than 95% of farms has got an usable agricultural size lower than 5 hectares (Festuccia, 2013;Istat, 2012). This value is far low to the European average of agrarian area equal to 12.6 hectares EP 2017 (64) 2 (451-465) (Greco and Di Cristofaro, 2011) and it arose significantly over the time due to the rural depopulation and emigration from the countryside. In order to contrast these downsides, the diversification in farm's activities has been one of the most useful action both to get better the farmer's income and also to restructure socio-economic relationships inside rural communities (Galluzzo, 2014; Stockdale, 2006;2004; Van der Ploeg, Renting, 2000; Shucksmith, Chapman, 1998) Focusing the attention on Italy, ninety-five percent of Italian farms are owned by a sole agrarian entrepreneur, who has got both the absolute ownership of the farm and also the management of it with the same level of technical efficiency than the medium size farms as well as of other agrarian enterprises managed by limited companies (Galluzzo, 2013;2015a). The typical context and features of the Italian agrarian socioeconomic fabric is made by small family farms, whose ownership is in the hands of a single person, who is the householder. These farms are predominately scattered in upland and in less favored rural areas hence, in these territories farmers are the main tile in the complex mosaic of multifunctionality such as a priority factor in the holistic rural development process able to reduce partially environmental degradation in a perspective of multifunctionality (Galluzzo, 2015b). As previously mentioned, findings on the analysis of efficiency and on the agricultural property have emphasized the role and function of smallholder farmers, that have got tiny units of production, mostly fragmented and located dispersedly in the Italian countryside considered wrongly because of their dimension, inefficient as assessed and argued in other European countries (Galluzzo, 2013;2015a;Camelia, Vasile, 2016).
In literature many scholars have investigated before and after the enlargement of the European Union in 2004 the technical and economic efficiency, addressing their research attention on the nexus between efficiency and some variables such as level of farm net income, dimension of farm, crop specialization and financial subsidies allocated by the Common Agricultural Policy (Galluzzo, 2015a;2016 Latruffe, 2009;Bielik, Rajcaniova, 2004). Some of these latter authors have argued as a critical downside of smallholder farms is intrinsic in their small fragmentized poor plots of land which does not allow an efficient use of productive factors such as capital land and labor capital with no opportunities in reducing the cost of inputs by new investments. Other studies have deemed as big farms and medium sized ones should be considered more efficiently than small enterprises ones; in particular, if the ownership is in the hands of limited companies or cooperatives the level of assessed efficiency have been better than family small farms (Galluzzo, 2013; Camelia, Vasile, 2016). These latter farms are able to diversify their activities and to improve their income due to a high level of investments in technologies and to a highest level of labour capital and its intensity. Therefore, among variables such as property of farm, dimension of usable agricultural surface and economic and technical efficiency there is a positive correlation and a direct nexus (Bravo-Ureta et al., 2007). In the same EP 2017 (64) 2 (451-465) time, few studies only have been addressed to investigate connections among typology of property and efficiency in the primary sector (Bravo-Ureta, Pinheiro, 1993; Chavas, Aliber, 1993;Galluzzo, 2016) underlining the role of farm size on the efficiency (van Zyl et al., 1996).
In order to assess the impact of the Common Agricultural Policy on farmers in different European Countries, the EU in the 1965, by the Council Regulation number 79, has established an analysis on a sample of farmers called Farm Accountancy Data Network (FADN). This is an annual survey which covers approximately 80,000 farms and a population of about 5,000,000 farmers located in the European Union equal to the 90% of usable agricultural area (UAA) and approximately 90% of the total European agricultural production (European Commission, 2014). Comparing also limited company agrarian enterprises and agricultural cooperatives because of their own level of social capital endowment and the structure of their politic, managerial decisions, findings have pointed out a direct relationship among these typologies of farms and the context of productive specialization, which is able to act positively on the level of efficiency and maximization of output (Latruffe, 2010).
Lots of scholars have pointed out as there are relationships between farm size and the technical, economic efficiency by stratifying the sample of farms in function of the variable cropping specialization (Garcia et al., 1982) using a multi-output approach of investigation or a multi-input methodology (Bojnec, Latruffe, 2008). Focusing the attention on an analysis about the spatial and geographical diffusion of studies on the economic efficiency in farms, many of them have been carried out in developing countries (Bravo-Ureta, Pinheiro, 1993) and in some European countries using a parametric approach (Curtiss, 2000) with the purpose to investigate the role of crop specialization on the allocative and technical efficiency in farms.
The aim of this analysis has been to assess the technical, economic and allocative efficiency in a sample of small Italian farms belonging to the Farm Accountancy Data Network ( The typology of farming grouping was: specialist COP (cereals, oilseed and protein crops), specialist other field crops, specialist horticulture, specialist vineyards, specialist orchards-fruits such as specialist fruit and citrus fruit, specialist olives (for example various permanent crops combined), specialist milk (milk and cattle rearing), specialist sheep and goats, specialist cattle as specialist cattle-rearing and fattening, cattle rearing, cattle fattening and cattle-dairying, rearing and fattening combined, specialist granivores (pigs and poultry), mixed crops, mixed livestock and mixed crops and livestock.

Methodology
In order to study the efficiency there are two methods: a parametric or deterministic approach, which needs a specific function of production and other parametric variables such as labor, land capital, agrarian capital and a non-parametric model or DEA (Data Envelopment Analysis). The DEA approach is aimed at defining in function of the distance from the frontier of a hypothetical function of production an index of technical inefficiency or technical efficiency (Bielik, Rajcaniova, 2004). Efficient farms are located along the hypothetical function of production; some of them outside this frontier are not efficient.
In the non-parametric model, some fluctuations from the frontier of the function of production are considered no efficient thus, the technical efficiency is described as a set of capabilities of farmers in maximizing the output minimizing in the same time the used inputs or vice versa (Bojnec, Latruffe, 2008). In this research, the efficiency has been EP 2017 (64) 2 (451-465) estimated by a non-parametric model applied to specific assumptions of a constant return to scale or CRS in an input oriented model (Farrel, 1957;Battese, 1992;Coelli, 1996) using PIM-DEA software. Therefore, in this research a CRS approach has implied as an increase in all input has changed in the same proportion the produced output.
The purpose of DEA linear programming model is to minimize in a multipleoutput model the multiple-input in each farm that is a ratio of efficiency (h) and in a mathematical model it can be written (Papadas, 1991): In term of productivity if there are two farms, called also Decision Making Unit (DMUs), such as A and B able to produce two levels of output such as y a or y b using a specific quantity of input x a and x b , the productivity is a simple ratio between produced output out and used input or rather a ratio y a /x a and y b /x b .
The value of efficiency should be greater to 0 and lower than 1; any small but positive value of efficiency between these two extremes implies as none input and output can be ignored in estimating the efficiency pointing out which input or output have to be implemented in order to get better the technical or economic efficiency (Bhagavath, 2009; Galluzzo, 2013; 2016).
The non-parametric linear model throughout the Data Envelopment Analysis has been introduced for the first time in 1978 (Charnes et al., 1978) and it is useful to estimate the relative efficiency in each Decision Making Unit based on different level of input and output (Hadad et al., 2007) with the purpose to minimize the level of input in the process of production (Doyle, Green, 1994).
The goal of a non-parametric input oriented model, such as in our research, or DEA linear programming, is to minimize in a multiple-output model the multiple-input in each farm that is a ratio of efficiency. This model has lots of possible solutions and u r * and v i * are two variables able to solve the problem of efficiency in terms of price vector of produced output and the input price vector (Bhagavath, 2009;Papadas, 1991 -v i ≤ -ε i = 0, 1,….m and ε is a positive value s i + u r ≤ -ε r = 0, 1, …t and ε is a positive value s r λ j are shadow prices able to reduce the efficiency in each unit lower than 1 or 100% and a positive value of λ j is able to assess a peer group in some inefficient unit. In the dual problem, it is important to consider a dual variable in each constraint in the primary model (Charnes et al., 1978) but this paper did not take into account in the dual model a constraint able to classify and to discriminate DMUs using the super efficiency called A&P model (Andersen, Petersen, 1993). In mathematical terms the solution of the dual model is written as:

Results and discussion
Findings over the time of investigation, since 2004 to 2013, have pointed out in all Italian farms part of the FADN dataset the worst performances, which in average value considering all type of farming specialization has been close to 86 % lower than the optimal value equal to 100% (Tab. 1).
Furthermore, both in term of cost efficiency and also in terms of allocative efficiency outcomes have been very poor with values of efficiency below 40% and in particular the cost efficiency has been more inefficient than the allocative one. Farms specialized in pig and poultry breeding have pointed out the highest level of technical, economical and allocative efficiency. By contrast agrarian enterprises specialized in cattle breeding (cattle-rearing and fattening) and in cereals, oilseed and protein crops (COP) have had the poorest level of efficiency.
Wine farms and farm specialized in fruit and orchards production have been efficient in technical terms but focusing the attention on the level of economic and allocative efficiency the value under 55% has been anyway inefficient because it is below the threshold of efficiency close to 100%.
Input oriented analysis of the technical efficiency using the constant return to scale (CRS) and the variable return to scale (VRS) has pointed out the same outcomes in terms of efficiency (Tab. 2), even if the total value in all data has been lower 100% with positive results in most of typologies of farming with the exception of mixed crops and livestock which have had the poorest level in terms of technical efficiency. In general, in specialized agrarian enterprises have been pinpointed the best performances in technical efficiency both in CCR approach and also in BCC model; instead, farmers with mixed cultivations and livestock, due to a different use of labour capital and other investments in input, have had the poorest performances.  Typology of farming such as granivores and sheep and goat specialized farms followed by wine and milk enterprises have had a guide role for lots of other typologies of farms such as cattle farms, mixed crops and other combined animals and crops (Tab. 4). In this case, if a type of farm specialization is efficient it is in the same time an enterprise able to lead other farms in a process of improvement of efficiency.
Four typologies of farm specialization out of 14 have pointed out some slacks, or rather an inefficient input or output allocation, even if focusing the attention on the whole typologies of farms findings have not been very positive in some inputs which should be increased such as labour input, cost for seeds and plants, fertilizers and crop protection (Tab. 5); in the same time, it is important to intensify financial subsidies allocated by the CAP, in particular assigning more financial resources in terms of payments in favour of disadvantaged rural areas.   In 4 typologies of farming specialization out of 14, findings have pointed out the need in reducing costs of seeds in particular in permanent combined crops; furthermore, a drop in the level of fiscal taxation is able to increase the level of efficiency in Italian farms (Tab. 6). In general, mixed agrarian enterprises have stressed the highest level of inefficiency due to high levels of farm's input cost.

Conclusions
Farm Accountancy Data Network is a useful tool in order to assess the impact of financial subsidies allocated by the Common Agricultural Policy and the level of efficiency on farms in function of their own productive specialization in terms of typology of farming. Despite the size of farms, the land capital is the main constraint in getting better the efficiency on farms; furthermore, findings have pointed out as more specialised are the farms higher are the levels of technical efficiency.
However, only Italian farms specialized in pig and poultry breeding have had the best performances both as economic efficiency and as allocative one. Findings have pointed out the need of intensifying financial payments allocated by the CAP and in particular some of them paid towards disadvantaged rural areas. National and regional authorities have to support by the National Rural Development Plan measures and investment initiatives able to increase the level of capital land throughout some specific agreements of cultivation or breeding among farms with the EP 2017 (64) 2 (451-465) aim of amortizing the costs of machinery, shrinking also, in a better way, the costs of cultivation. Summing up, this latter solution has the advantage of reducing the exodus from the countryside protecting in the same time the rural space in environmental terms as well, in particular after the economic recession in 2008 which has strongly lessened farmer's income.