{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T03:47:31Z","timestamp":1789012051647,"version":"build-2803163510"},"reference-count":85,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2014,6,10]],"date-time":"2014-06-10T00:00:00Z","timestamp":1402358400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[2015,2]]},"abstract":"<jats:p>Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo\u2019s ideas have had (and still have) to overcome and lays out a logical framework that has evolved from Haavelmo\u2019s insight and matured into a coherent and comprehensive account of the relationships between theory, data, and policy questions. The mathematical tools that emerge from this framework now enable investigators to answer complex policy and counterfactual questions using simple routines, some by mere inspection of the model\u2019s structure. Several such problems are illustrated by examples, including misspecification tests, nonparametric identification, mediation analysis, and introspection. Finally, we observe that economists are largely unaware of the benefits that Haavelmo\u2019s ideas bestow upon them and, to close this gap, we identify concrete recent advances in causal analysis that economists can utilize in research and education.<\/jats:p>","DOI":"10.1017\/s0266466614000231","type":"journal-article","created":{"date-parts":[[2014,6,10]],"date-time":"2014-06-10T12:52:36Z","timestamp":1402404756000},"page":"152-179","source":"Crossref","is-referenced-by-count":50,"title":["TRYGVE HAAVELMO AND THE EMERGENCE OF CAUSAL CALCULUS"],"prefix":"10.1017","volume":"31","author":[{"given":"Judea","family":"Pearl","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2014,6,10]]},"reference":[{"key":"S0266466614000231_ref84","first-page":"1","article-title":"On block-recursive regression equations (with discussion)","volume":"6","author":"Wermuth","year":"1992","journal-title":"Brazilian Journal of Probability and Statistics"},{"key":"S0266466614000231_ref80","volume-title":"Introduction to Econometrics","author":"Stock","year":"2011"},{"key":"S0266466614000231_ref78","first-page":"202","volume-title":"Error and Inference","author":"Spanos","year":"2010"},{"key":"S0266466614000231_ref77","doi-asserted-by":"publisher","DOI":"10.1257\/jep.24.2.59"},{"key":"S0266466614000231_ref76","doi-asserted-by":"publisher","DOI":"10.1086\/288105"},{"key":"S0266466614000231_ref75","first-page":"1941","article-title":"Complete identification methods for the causal hierarchy","volume":"9","author":"Shpitser","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"S0266466614000231_ref72","doi-asserted-by":"publisher","DOI":"10.1037\/h0037350"},{"key":"S0266466614000231_ref70","doi-asserted-by":"publisher","DOI":"10.2307\/2297101"},{"key":"S0266466614000231_ref65","doi-asserted-by":"crossref","unstructured":"Pearl J. & Bareinboim E. 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