{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:54:43Z","timestamp":1760151283599,"version":"build-2065373602"},"reference-count":57,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T00:00:00Z","timestamp":1646265600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Relatedness is a key concept in economic complexity, since the assessment of the similarity between industrial sectors enables policymakers to design optimal development strategies. However, among the different ways to quantify relatedness, a measure that takes explicitly into account the time correlation structure of exports is still lacking. In this paper, we introduce an asymmetric definition of relatedness by using statistically significant partial correlations between the exports of economic sectors and we apply it to a recently introduced database that integrates the export of physical goods with the export of services. Our asymmetric relatedness is obtained by generalising a recently introduced correlation-filtering algorithm, the partial correlation planar graph, in order to allow its application on multi-sample and multi-variate datasets, and in particular, bipartite temporal networks. The result is a network of economic activities whose links represent the respective influence in terms of temporal correlations; we also compute the statistical confidence of the edges in the network via an adapted bootstrapping procedure. We find that the underlying influence structure of the system leads to the formation of intuitively-related clusters of economic sectors in the network, and to a relatively strong assortative mixing of sectors according to their complexity. Moreover, hub nodes tend to form more robust connections than those in the periphery.<\/jats:p>","DOI":"10.3390\/e24030365","type":"journal-article","created":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T09:24:53Z","timestamp":1646299493000},"page":"365","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Asymmetric Relatedness from Partial Correlation"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5704-4053","authenticated-orcid":false,"given":"Carlos","family":"Saenz de Pipaon Perez","sequence":"first","affiliation":[{"name":"Department of Mathematics, King\u2019s College London, The Strand, London WC2R 2LS, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4478-3292","authenticated-orcid":false,"given":"Andrea","family":"Zaccaria","sequence":"additional","affiliation":[{"name":"Istituto dei Sistemi Complessi (ISC)\u2014CNR, UoS Sapienza, P.le A. Moro, 2, 00185 Rome, Italy"},{"name":"Centro Ricerche Enrico Fermi, Piazza del Viminale, 1, 00184 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5913-3268","authenticated-orcid":false,"given":"Tiziana","family":"Di Matteo","sequence":"additional","affiliation":[{"name":"Department of Mathematics, King\u2019s College London, The Strand, London WC2R 2LS, UK"},{"name":"Centro Ricerche Enrico Fermi, Piazza del Viminale, 1, 00184 Rome, Italy"},{"name":"Complexity Science Hub Vienna, Josefst\u00e4dter Stra\u00dfe 39, A 1080 Vienna, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"046113","DOI":"10.1103\/PhysRevE.78.046113","article-title":"Two classes of bipartite networks: Nested biological and social systems","volume":"78","author":"Burgos","year":"2008","journal-title":"Phys. Rev. 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