A hierarchical clustering based panel data approach: a case study of regional incentives

The main objective of this research is to propose a novel approach based on panel data analysis and hierarchical cluster analysis to investigate the determinants of foreign trade deficit and cluster provinces of Turkey. This study has two important contributions into the existing literature. First, the proposed approach uses provinces based panel data. Second, the proposed approach uses structural factors as explanatory variables. The estimates show that the number of patent, trademark, and design granted, the number of incentive documents prepared, fixed investments and employment corresponding to the energy sector and employment in agricultural sector significantly affect foreign trade deficit in provinces of Turkey. Afterward, hierarchical cluster analysis is also utilized based on the results obtained from the panel data analysis. The results of the proposed approach show that provinces of Turkey are clustered into three clusters and Istanbul is the only province forming the first cluster.