ISSN 2284-7995, ISSN Online 2285-3952
 

THE IMPACT OF THE COMMON AGRICULTURAL POLICY ON THE EUROPEAN AGRICULTURAL SECTOR SUSTAINABILITY BY USING A MACHINE-LEARNING APPROACH

Published in Scientific Papers. Series "Management, Economic Engineering in Agriculture and rural development", Vol. 21 ISSUE 2
Written by Ștefan-Mihai PETREA, Alina MOGODAN, Ira-Adeline SIMIONOV, Aurelia NICA, Dragoș Sebastian CRISTEA, Mihaela NECULIȚĂ

The present research evaluates the sustainability of EU agricultural sector in relation to Common Agricultural Policy by using a custom-developed analytical framework, based on relevant indicators: gross domestic product in rural areas (GDP), gross value added (GVA), GVA for agriculture, direct payments (DP), agricultural factor income (AFI), agriculture employment rate (AER), rural employment rate (RER), degree of rural poverty (DRP), agricultural entrepreneurial income (AEI), agriculture research and development investments (ARD), labour productivity in agriculture (LPA), total factor productivity (TFP), cereal crop yield (CCY), fertilizers use (FU), CO2 emissions and ammonia emissions (EA). The EA are mostly related to CCY (+0.47%), DP (+0.45%), ARD (+0.49%), AFI (-0.59%) and GDP (-0.52%). The CO2 emissions are influenced mostly by TFP (+2.82%), RER (+2.49%), DRP (+0.53%) and EA (+0.46%). The FU most significant feature importance weights are CCY (0.79%), CO2 (0.21%) and TFP (0.19%). The GVA model is related mostly to RER (+1.30%), GVA Agriculture (+0.67%), AER (-0.35%) and FU (+0.31%). The ARD most significant feature importance weights are GVA (0.23), DP (0.16) and GVA agriculture (0.15). The results revealed excellent performance metrics.

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© 2019 To be cited: Scientific Papers. Series “Management, Economic Engineering in Agriculture and Rural Development“.

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