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Although he did not explicitly consider model selection, we apply it when theory-relevant variables, {<jats:bold>X<\/jats:bold><jats:sub><jats:italic>t<\/jats:italic><\/jats:sub>}, are retained without selection while selecting other candidate variables, {<jats:bold>W<\/jats:bold><jats:sub><jats:italic>t<\/jats:italic><\/jats:sub>}. Under the null that the {<jats:bold>W<\/jats:bold><jats:sub><jats:italic>t<\/jats:italic><\/jats:sub>} are irrelevant, by orthogonalizing with respect to the {<jats:bold>X<\/jats:bold><jats:sub><jats:italic>t<\/jats:italic><\/jats:sub>}, the estimator distributions of the<jats:bold>X<\/jats:bold><jats:sub><jats:italic>t<\/jats:italic><\/jats:sub>\u2019s parameters are unaffected by selection even for more variables than observations and for endogenous variables. Under the alternative, when the joint model nests the generating process, an improved outcome results from selection. This implements Haavelmo\u2019s program relatively costlessly.<\/jats:p>","DOI":"10.1017\/s0266466614000218","type":"journal-article","created":{"date-parts":[[2014,6,20]],"date-time":"2014-06-20T14:07:12Z","timestamp":1403273232000},"page":"93-114","source":"Crossref","is-referenced-by-count":55,"title":["MODEL DISCOVERY AND TRYGVE HAAVELMO\u2019S LEGACY"],"prefix":"10.1017","volume":"31","author":[{"given":"David F.","family":"Hendry","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S\u00f8ren","family":"Johansen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2014,6,20]]},"reference":[{"key":"S0266466614000218_ref26","doi-asserted-by":"publisher","DOI":"10.2307\/1913236"},{"key":"S0266466614000218_ref23","doi-asserted-by":"publisher","DOI":"10.2307\/1401917"},{"key":"S0266466614000218_ref21","doi-asserted-by":"crossref","unstructured":"Doornik J.A . 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