Abstract:
The main goal of the paper is to map the performance of the 41 Romanian counties in 2013 from the perspective of livestock production using principal component analysis technique (PCA) and cluster analysis in order to classify the counties by the most important components obtained through the usage of PCA. The empirical results reveal that milk production of sheep and goats and wool production, agricultural cattle production, egg and poultry production have the highest power in explaining the evolution of the livestock production in Romanian counties. When clustering the counties after the first two principal components, (which are mostly correlated with milk production of sheep (PC1) and goats and wool production, agricultural cattle production (PC2)), which recover around 51.33% of the total variance of the original variables, three main classes of counties emerge: Botosani and Suceava (first cluster), Constanta and Timis (second cluster), and the rest of the counties (third cluster). The cluster analysis based on all three principal components revealed the existence of four classes of counties: Botosani, Suceava, Brasov and the rest of the counties.
