{"id":11161,"date":"2003-04-13T00:00:00","date_gmt":"2003-04-13T00:00:00","guid":{"rendered":"https:\/\/cinve.org.uy\/metodos-cuantitativos-para-el-analisis-y-prediccion-de-la-actividad-industrial-uruguaya\/"},"modified":"2019-10-24T21:19:37","modified_gmt":"2019-10-24T21:19:37","slug":"metodos-cuantitativos-para-el-analisis-y-prediccion-de-la-actividad-industrial-uruguaya","status":"publish","type":"post","link":"https:\/\/cinve.org.uy\/en\/metodos-cuantitativos-para-el-analisis-y-prediccion-de-la-actividad-industrial-uruguaya\/","title":{"rendered":"Quantitative methods for analysis and forecast of Uruguayan industrial activity"},"content":{"rendered":"<p>This paper presents a set of statistical-econometric models for the<br \/>\nPhysical Volume Index (IVF) of the Uruguayan manufacturing industry. They are considered<br \/>\nmonthly data for the period between 1985 and 2003. They are provided<br \/>\nestimates of univariate time series models with Intervention Analysis and<br \/>\nMultivariate Transfer Function in which the influence is analyzed and quantified<br \/>\nof Holy Week, Carnival Week, the so-called Calendar Effect, the holidays<br \/>\nnationals and general strikes. The representative index is modeled<br \/>\nof the total industry (excluding the oil refinery) and a sector disaggregation<br \/>\nprepared according to the commercial specialization pattern of each of the branches<br \/>\nIndustrial The results obtained indicate that the disaggregated analysis allows a<br \/>\nbetter understanding of the behavior of industrial activity and that contributes to<br \/>\nImprove prediction accuracy.<\/p>\n<p><a href=\"https:\/\/cinve.org.uy\/wp-content\/uploads\/2012\/12\/04-2003-Lorenzo-Lanzilotta-Sueiro-v2.pdf\">Descargar\/Download<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents a set of statistical-econometric models for the Physical Volume Index (IVF) of the Uruguayan manufacturing industry. They are considered monthly data for the period between 1985 and 2003. They are provided estimates of univariate time series models with Intervention Analysis and Multivariate Transfer Function in which the influence is analyzed and quantified [&hellip;]<\/p>\n","protected":false},"author":30,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[138],"tags":[194],"class_list":{"0":"post-11161","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-articulos-2","7":"tag-macroeconomia-y-finanzas-en"},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/posts\/11161","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/users\/30"}],"replies":[{"embeddable":true,"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/comments?post=11161"}],"version-history":[{"count":2,"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/posts\/11161\/revisions"}],"predecessor-version":[{"id":14081,"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/posts\/11161\/revisions\/14081"}],"wp:attachment":[{"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/media?parent=11161"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/categories?post=11161"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cinve.org.uy\/en\/wp-json\/wp\/v2\/tags?post=11161"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}