Financial sustainability in Italian farms: an analysis of the FADN sample

Purpose The paper examines the factors that influence the production of cash flows in a sample of Italian farm accountancy data network (FADN) farms to generate information useful for calibrating policies to support farmers' investments. Design/methodology/approach An econometric analysis on the sample estimates the influence of structural, economic, commercial and financial variables on CAFFE, i.e. the cash flow that includes the payments to the farmer's resources and the free cash flow on equity (FCFE). The econometric problem of endogeneity is treated by adopting the Hausman test to choose between fixed and random effects models. The results for Italian agriculture and its types of farming (TFs) are examined based on the FCFE/capital depreciation ratio, where FCFE subtracts from CAFFE the opportunity cost payments to the farmer's resources. This ratio identifies TFs with problems of sustainability of the production system. Findings The results show that increasing the productive dimension, in particular the endowment of farmland and working capital, is still essential to stimulate the production of cash flows of Italian agriculture. Without this growth, increasing the depreciable capital base is ineffective. FCFE does not compensate for depreciation in several TFs, which in various cases could also improve by improving economic efficiency and commercial position. Research limitations/implications Assessing the factors that most influence cash flows can help to better calibrate rural development measures to the territories and farming types that most need public support. Our analysis procedure can be applied to all production systems equipped with farm accounting networks; however, the criteria for rewarding farmer resources and calculating the replacement value of agricultural capital need to be better discussed. Originality/value The specification of rural development policies rarely takes into account the financial sustainability conditions of farms, as well as the factors that determine them, in defining the support parameters and the selection criteria for funding. Our approach, based on the analysis of FADN data, considers these aspects and provides ideas for better calibrating public support for investments among agricultural territories, sectors and types of farms.