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Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models

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Abstract

In this paper, we carried out an empirical productive analysis on agricultural Italian farms. In this research area, we propose a new approach of stochastic frontier analysis adopting a generalized additive model framework also compared with Stochastic semi-Nonparametric Envelopment of Z variables Data. By using the Italian National Institute of Agricultural Economics micro-data, we were able to map out the overall level of efficiency thereby focusing also on the evaluation of the differences observed due to presence of contextual variables. We obtained overall measures for the citrus sector that suggests an evaluation framework that can uphold policies to encourage and support farms.

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Notes

  1. In this paper, we refer to a farm (specifically “firm” in the introduction) even if the methodology remains valid for any public or private economic unit.

  2. Various distributions can be assumed for the one-sided error term; e.g. half-normal, truncated normal, gamma, exponential, etc.

  3. For the model estimation we used the R Environment (R: A language and environment for statistical computing 2012) exploiting the functionality of the mgcv (2012) package.

  4. “The input-output data must be kept in the original units in order to use the Afriat inequalities for imposing concavity. Although the objective function involves logarithms of model variables” (Kuosmanen and Kortelainen 2012).

  5. Note that log-transformation concerns Step 1 and makes no difference in the estimation of Step 2.

  6. EEC Regulation No. 1859/82 establishes the minimum threshold of economic size for inclusion in the FADN field of observation. The economic size of a farm is defined by the total standard gross margin expressed in ESU, where \(1\) ESU corresponds to \(1,200\) Euro.

  7. Farms, in the European agricultural policy, are classified on the basis of type of farming (OTE). OTE provides information on the degree of specialization and production and it is determined on the basis of the percentage of the economic dimension (in terms of the standard gross margin) of one or more productive activities on the economic dimension of the total. The Community typological scheme provides \(58\) different combinations of production which are grouped into three successive levels of detail: General OTE, Main OTE and Particular OTE.

  8. Index of utilization of family labour (IUF) is the ratio between the hours worked by family members and the total working hours that they would have worked had they been full time employees (i.e. 2,200 h per employee).

  9. As dummy contextual variables.

  10. For the Italian demographic characteristics, we have considered this variable as a variable that explains a social context, for the increasing abandonment of the hills or mountainous land, but we are aware that it may capture other economic effects.

  11. ***= \(P\) value \(<\)0.001, **= 0.001 \(\le \) \(P\) value \(<\)0.05, *= 0.05 \(\le \) \(P\) value \(<\)0.10.

  12. All correlations are 0.05 significant.

  13. This would not make sense since \(\delta \) is estimated.

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Authors and Affiliations

  1. Department of Political Science, University of Roma Tre, Via G. Chiabrera, 199 , Rome, Italy

    Francesco Vidoli

  2. Department of Statistical and Economical Sciences, University of Palermo, Viale delle Scienze Ed. 13, Palermo, Italy

    Giancarlo Ferrara

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  1. Francesco Vidoli
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  2. Giancarlo Ferrara
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Correspondence to Francesco Vidoli.

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Vidoli, F., Ferrara, G. Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models. Empir Econ 49, 641–658 (2015). https://doi.org/10.1007/s00181-014-0879-6

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