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The study develops estimates of Italian potential GDP using structural VAR (SVAR) models. It leverages business survey data for detrending and evaluates reliability via end-of-sample revision, comparing output gaps across Italian expansion and recession phases.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/estimating-potential-output-using-business-survey-data-in-a-svar-framework-abstract-and-study-details/455657/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/estimating-potential-output-using-business-survey-data-in-a-svar-framework-abstract-and-study-details/455657.png","ImageObject",300,407,{"name":92,"@type":93},"Chumphorn","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-06","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What economic concepts does the paper focus on?","Question",{"text":112,"@type":113},"The paper centers on potential output and the output gap, where the output gap reflects the difference between actual and potential output and indicates cyclical position.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the paper estimate Italian potential GDP?",{"text":117,"@type":113},"It proposes estimates based on structural VAR models, incorporating business survey data into the SVAR framework for detrending and cyclical information.",{"name":119,"@type":110,"acceptedAnswer":120},"Why is the SVAR approach emphasized over univariate filters?",{"text":121,"@type":113},"The SVAR estimates are presented as free from end-of-sample problems and can reduce issues such as spurious cyclicality compared with some standard decomposition techniques.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},455657,1790974149,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":41},2336475401981,"https://ap-avatar.wpscdn.com/avatar/22000c94efd8d5204d?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786935347598174694","Munich Personal RePEc Archive  \nEstimating potential output using business survey data in a SVAR framework  \nCesaroni, Tatiana  \nFebruary 2008  \nOnline at [https://mpra. ub. uni-muenchen. de/16324/](https://mpra. ub. uni-muenchen. de/16324/)  \n[MPRA Paper No. 16324](MPRA Paper No. 16324) , [posted 17 Jul 2009 08:25 UTC](posted 17 Jul 2009 08:25 UTC)  \nEstimating potential output using business survey  \ndata in a SVAR framework  \nTatiana Cesaroni*  \n2008  \nAbstract  \nPotential output and the related concept of output gap play a central role in the macroeconomic policy interventions and evaluations. In particular, the output gap, defined as the difference between actual and potential output, conveys useful information on the cyclical position of a given economy. The aim of this paper is to propose estimates of the Italian potential GDP based on structural VAR models. With respect to other techniques, like the univariate filters (i.e. the Hodrick-Prescott filter), the estimates obtained through the SVAR methodology are free from end-of-sample problems, thus resulting particularly useful for short-term analysis.  \nIn order to provide information on the economic fluctuations, data coming from business surveys are considered in the model. This kind of data, given their cyclical profile, are particularly useful fordetrending purposes, as they allow to include information concerning the business cycle activity. To assess the estimate reliability, an end-of-sample revision evaluation is performed. The ability of the cyclical GDP component to detect business cycle turning points is then performed by comparing the estimated output gaps, extracted with different detrending methods, over the expansion and recession phases of the Italian business cycle chronology.  \nKey Words: potential output, business survey data, structural VAR models, end-of-sample revisions.  \nJEL Classification: C32, E32  \n*Italian Treasury Ministry of Economy and Finance  \n1 Introduction  \nPotential output and output gap are considered important indicators of the economic activity evolution. More in detail, the output gap, i.e. the difference between the actual output level and its potential, provides information concerning the cyclical position of the economy. In this sense it represents a benchmark to achieve non inflationary growth since if the output gap is positive (negative) the inflationary pressures raise (fall) and the policy makers are expected to tighten (ease) monetary policies. This indicator it is also used by central banks to fix interest rates according to the so-called Taylor rules (Taylor, 1993) .  \nHowever, in spite of the attention received, the estimates of those aggregates are still surrounded by a huge amount of uncertainty (cfr. Orphanides and van Norden, 1999 and 2001) . This is mainly due to the fact that the output decomposition into its trend and cyclical components are not unique depending on the method used.  \nIn the literature different methods have been used to estimate potential GDP. The most known univariate statistical techniques are based on the use of univariate filters (i.e. Hodrick and Prescott, 1997 and Baxter and King, 1995) . Other univariate approaches include unobserved components models (see for details, Harvey, 1985 and Clark, 1987) and the Beveridge and Nelson (1981) decomposition. In addition, multivariate decompositions based on those techniques (i.e. multivariate filters or multivariate unobserved components models) have also been developed. Recently, considerable attention has been focused on the use of VAR models. To this end St-Amant and van Norden (1997) use a VAR model with long run restrictions including output, inflation, unemployment and real interest rate to estimate the Canadian output gap. Similarly Claus (2003) employs a SVAR model with long run restrictions to estimate New Zealand output gap for the period 1970-99.  \nThe aim of this paper is to estimate Italian potential output using a multivariate decomp","cbCaiiBbTd3KEhsE","https://ap.wps.com/l/cbCaiiBbTd3KEhsE","pdf",1509081,12,"English","# Abstract\n## 1 Introduction\n## 2 Objective and approach","[{\"question\":\"What economic concepts does the paper focus on?\",\"answer\":\"The paper centers on potential output and the output gap, where the output gap reflects the difference between actual and potential output and indicates cyclical position.\"},{\"question\":\"How does the paper estimate Italian potential GDP?\",\"answer\":\"It proposes estimates based on structural VAR models, incorporating business survey data into the SVAR framework for detrending and cyclical information.\"},{\"question\":\"Why is the SVAR approach emphasized over univariate filters?\",\"answer\":\"The SVAR estimates are presented as free from end-of-sample problems and can reduce issues such as spurious cyclicality compared with some standard decomposition techniques.\"}]","Estimating potential output using business survey data in a SVAR framework - Abstract and study details | PDF",1790743786]