Several factors are deemed to influence farms' economic performance and competitiveness: endogenous characteristics, such as farm structure and entrepreneur's features, as well exogenous factors related to the infrastructure endowment, networks and immaterial factors. A deeper knowledge of the role each factor plays in different geographical areas can help to better address the rural policies and to improve their efficacy. In this respect, the present study aims at analyzing how factors that potentially affect competitiveness differ within Italian agriculture and the way those factors act on the economic performance of agriculture at provincial level. The analysis was carried out in two steps. First, in order to define the main characteristics of the Italian agricultural systems a Principal Component Analysis (PCA) has been carried out using data collected by the last Italian Agricultural Census, carried out in 2010, at provincial level and component scores have been used to characterize provincial agricultural systems. In a second step, PCA results were used as explanatory variables in regression models to evaluate their relationship with agricultural productivity and performance indicators at provincial level. The work highlighted two main results. First, agricultural differentiation factors identified in the PCA discriminate two main territorial agricultural models linked to different agricultural systems organization and development strategies. Secondly, the determinants of agricultural productivity and performance are mainly endogenous to the sector and only few context indicators seem to act as explanatory variables

Endogenous and Exogenous Determinants of Agricultural Productivity: What Is the Most Relevant for the Competitiveness of the Italian Agricultural Systems?

Gaetano Chinnici;Gioacchino Pappalardo;Mario D'Amico;Giuseppe Di VIta
2018-01-01

Abstract

Several factors are deemed to influence farms' economic performance and competitiveness: endogenous characteristics, such as farm structure and entrepreneur's features, as well exogenous factors related to the infrastructure endowment, networks and immaterial factors. A deeper knowledge of the role each factor plays in different geographical areas can help to better address the rural policies and to improve their efficacy. In this respect, the present study aims at analyzing how factors that potentially affect competitiveness differ within Italian agriculture and the way those factors act on the economic performance of agriculture at provincial level. The analysis was carried out in two steps. First, in order to define the main characteristics of the Italian agricultural systems a Principal Component Analysis (PCA) has been carried out using data collected by the last Italian Agricultural Census, carried out in 2010, at provincial level and component scores have been used to characterize provincial agricultural systems. In a second step, PCA results were used as explanatory variables in regression models to evaluate their relationship with agricultural productivity and performance indicators at provincial level. The work highlighted two main results. First, agricultural differentiation factors identified in the PCA discriminate two main territorial agricultural models linked to different agricultural systems organization and development strategies. Secondly, the determinants of agricultural productivity and performance are mainly endogenous to the sector and only few context indicators seem to act as explanatory variables
File in questo prodotto:
File Dimensione Formato  
374_agris-on-line-2018-2-coppola-ianuario-chinnici-di-vita-poppalardo-damico.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: Versione Editoriale (PDF)
Dimensione 1.55 MB
Formato Adobe PDF
1.55 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/330753
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 24
  • ???jsp.display-item.citation.isi??? ND
social impact