The work is related to the detection of key international and Russian economic journals in cross-citation networks. A list of international journals and information on their cross-citations were taken from Web of Science (WoS) database while information on Russian journals was taken from Russian Science Citation Index (RSCI). We calculated classical centrality measures, which are used for key elements detection in networks, and proposed new indices based on short-range and long-range interactions. A distinct feature of the proposed methods is that they consider individual attributes of each journal and take into account only the most significant links between them. An analysis of 100 main international and 29 Russian economic journals was conducted. As a result, we detected journals with large number of citations to important journals and also journals where the observed rate of self-citation is a dominant in the total level of citation. The obtained results can be used as a guidance for researchers planning to publish a new paper and as a measure of importance of scientific journals.