[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-203127-105":59,"doc-detail-203127-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","generalized-two-part-fractional-regression-with-cmp","Generalized two-part fractional regression with cmp","","Researchers modeling fractional dependent variables must address whether outcomes arise from a two-part data-generating process. Two-part models treat participation and magnitude decisions separately, yet existing user-written tools lack a specialized approach for fitting two-part fractional models with dependence across parts. This paper presents generalized two-part fractional regression, explains estimation using Stata’s cmp command, and demonstrates prediction, marginal effects, fit statistics, and the RESET test for evaluation.",{"@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/generalized-two-part-fractional-regression-with-cmp/203127/",{"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/generalized-two-part-fractional-regression-with-cmp/203127.png","ImageObject",300,407,{"name":92,"@type":93},"Himbo","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-08","2026-09-04",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does generalized two-part fractional regression address?","Question",{"text":112,"@type":113},"It addresses situations where fractional outcomes follow a two-part process, and the participation and magnitude decisions may be dependent rather than independent.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How can the model be estimated in Stata?",{"text":117,"@type":113},"The paper shows that Stata users can estimate generalized two-part fractional regression using the user-written cmp command and its conditional mixed-process framework.",{"name":119,"@type":110,"acceptedAnswer":120},"What results does the paper help readers compute for interpretation and evaluation?",{"text":121,"@type":113},"It demonstrates how to obtain predicted values, marginal effects, model fit statistics, and how to perform the RESET test for model evaluation.","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},203127,1788555847,{"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":24,"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":129,"read_time":36},687197100911,"https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1785132997149421697","Cover sheet  \nThis is the accepted manuscript (post-print version) of the article.  \nThe content in the accepted manuscript version is identical to the final published version, although typography and layout may differ.  \nHow to cite this publication  \nPlease cite the final published version:  \nWulff, J. (2019) . Generalized two-part fractional regression with cmp. Stata Journal, 19(2), 375–389.  \n[https://doi.org/10.1177/1536867X19854017](https://doi.org/10.1177/1536867X19854017)  \nPublication metadata  \nTitle: Generalized two-part fractional regression with cmp  \nAuthor(s): Jesper N. Wulff  \nJournal: Stata Journal, 19(2), 375–389  \nDOI/Link: 10. 1177/1536867X19854017  \nDocument version: Accepted manuscript (post-print)  \nGeneral Rights  \nCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners  \nThe Stata Journal (yyyy) vv, Number ii, pp. 1{15  \nGeneralized two-part fractional regression with  \ncmp  \nJesper N. Wul􀀋 Aarhus University  \nAarhus, Denmark jwul􀀋@econ.au.dk  \nAbstract. Researchers who model fractional dependent variables often need to consider whether their data were generated by a two-part process. Two-part models are ideal for modeling two-part processes as they allow us to model the participation and magnitude decision separately. While user-written commands currently facilitate estimation of two-part models, no specialized command exists for 􀀌tting two-part models with process dependency. In this paper, I describe generalized two-part fractional regression, which allows for dependency between models parts. I show how this model can be estimated using the user-written cmp command (Roodman 2011, Stata Journal 11: 159-20) . I use a data example on the  \n􀀌nancial leverage of 􀀌rms to illustrate how cmp can be used to 􀀌t generalized twopart fractional regression. Further, I show how to obtain predicted values of the fractional dependent variable and marginal e􀀋ects useful for model interpretation.  \nFinally, I show how to compute model 􀀌t statistics and perform the RESET test, which are useful for model evaluation.  \nKeywords: stxxxx, generalized two-part fractional regression, process dependence, fractional probit, cmp  \n1 Introduction  \nIn many di􀀋erent disciplines, researchers need to estimate regression models where the dependent variable is in the form of a fraction, percentage, or proportion. In 􀀌nance, a commonly examined fractional dependent variable (FDV) is the 􀀌nancial leverage ratio of 􀀌rms, i.e. the amount of debt a 􀀌rm issues relative to its amount of capital. Empirical research suggests that the 􀀌nancial leverage decision of 􀀌rms is best described as a two-step process: First, the 􀀌rm decides whether or not to issue debt and then it decides how much debt to issue (Ramalho and da Silva 2009) . However, the process determining which 􀀌rms choose to issue debt is non-random as 􀀌rms self-select into a leveraged position. Thus, we need a model that can not only separate the e􀀋ects on the debt-vs-no-debt from the e􀀋ects on the amount-of-debt decision, but can also take into account the non-random selection that leads to some 􀀌rms issuing debt. The generalized two-part fractional regression model (GTP-FRM) is such a model.  \nBefore we dig into the GTP-FRM, we need a short introduction on modeling FDVs. Modeling an FDV requires a fractional regression model (FRM) . If we use the QuasiMaximum Likelihood Estimator (QMLE) and the logit link, the model is known as the fractional logit (FL) or fractional probit (FP) if we use the probit (Papke and Wooldridge  \n􀀍c yyyy StataCorp LP stxxxx  \n2 Generalized two-part fractional regression  \n1996) . An FRM is preferable because it ensures predictions within the unit interval and only requires correct speci􀀌cation of the conditional mean. Estimation of FRMs with various link functions is straight-forward in Stata using the glm command and has become even more accessible with the Stata 14 ","cbCaiqgJHHxD9A1x","https://ap.wps.com/l/cbCaiqgJHHxD9A1x","pdf",439765,16,"English","# Introduction\n## Modeling fractional dependent variables (FDVs)\n## Two-part fractional models and dependence\n# Generalized two-part fractional regression\n## cmp-based estimation approach","[{\"question\":\"What problem does generalized two-part fractional regression address?\",\"answer\":\"It addresses situations where fractional outcomes follow a two-part process, and the participation and magnitude decisions may be dependent rather than independent.\"},{\"question\":\"How can the model be estimated in Stata?\",\"answer\":\"The paper shows that Stata users can estimate generalized two-part fractional regression using the user-written cmp command and its conditional mixed-process framework.\"},{\"question\":\"What results does the paper help readers compute for interpretation and evaluation?\",\"answer\":\"It demonstrates how to obtain predicted values, marginal effects, model fit statistics, and how to perform the RESET test for model evaluation.\"}]","Generalized two-part fractional regression with cmp | PDF"]