Az iparágak közti hasonlóság mérésének hálózati módszerei és relevanciájuk a gazdaságfejlesztésben

Similarities of the applied technology and human resources make learning between industries easier and spillover effects stronger. For this reason, economic growth of countries and regions is largely dependent on the relatedness structure between their industries, which affects the appearance and development of new industries in regions and countries. Several attempts have been made to measure the relatedness of industries, of which the revealed relatedness and skill-relatedness methods are among the most accepted ones. In our study, we examine the relatedness of Hungarian industries using these two network methods. We present the concepts of the revealed relatedness and skill-relatedness methods, followed by the empirical methodology of their calculations. We visualize the relatedness networks of the Hungarian industries using the two methods, and then analyze their relationships with each other and with the traditional sectoral classification. Finally, using the data of the Central Transdanubian Region, we argue that both approaches are relevant for regional development policy. As an attachment to the article, we publish the calculated relatedness measures, making them available for future regional development policy and empirical economic research.