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Pinning down recurring patterns or combinations of macroeconomic indicators is indispensable for adequate policy adjustments to prevent a looming crisis. We investigate the ability of several macroeconomic variables telling crisis countries apart from non-crisis economies. We introduce a self-calibrated clustering-algorithm, which accounts for both similarity and dissimilarity in macroeconomic fundamentals across countries. Furthermore, imposing a desired community structure, we allow the data to decide by itself, which combination of indicators would have most accurately foreseen the exogeneously defined network topology. We quantitatively evaluate the degree of matching between the data-generated clustering and the desired community-structure.<\/jats:p>","DOI":"10.1007\/s41109-020-00280-4","type":"journal-article","created":{"date-parts":[[2020,8,4]],"date-time":"2020-08-04T21:02:31Z","timestamp":1596574951000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Indicators of economic crises: a data-driven clustering approach"],"prefix":"10.1007","volume":"5","author":[{"given":"Maximilian","family":"G\u00f6bel","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tanya","family":"Ara\u00fajo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,8,4]]},"reference":[{"issue":"1","key":"280_CR1","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1080\/14697680601019530","volume":"7","author":"T Ara\u00fajo","year":"2007","unstructured":"Ara\u00fajo, T, Lou\u00e7\u00e3 F (2007) The geometry of crashes. a measure of the dynamics of stock market crises. 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