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Using merged data for 4,323 YC companies (2005–2024) with S&P Global funding records, OLS regressions with batch-year fixed effects are estimated on 2,113 companies. Prior FAANG experience is associated with lower funding, but the effect is not robust. The only stable result is that larger founding teams raise more capital, with each additional co-founder linked to about 21% higher funding.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/founder-backgrounds-and-startup-funding-evidence-from-y-combinator/306478/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/founder-backgrounds-and-startup-funding-evidence-from-y-combinator/306478.png","ImageObject",442,249,{"name":88,"@type":89},"Dozel","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-11-04","2026-09-19",true,{"@type":98,"interactionType":99,"userInteractionCount":47},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What question does the study address about Y Combinator startups?","Question",{"text":108,"@type":109},"The study asks what drives the disparity in fundraising success between the most successful YC startups and those that struggle to raise substantial capital after the accelerator.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"How is the analysis conducted to test founder characteristics?",{"text":113,"@type":109},"The paper merges Y Combinator company records with S&P Global funding data for 4,323 companies (2005–2024) and runs OLS regressions with batch-year fixed effects, focusing on 2,113 companies in the regression sample.",{"name":115,"@type":106,"acceptedAnswer":116},"Which founder factor shows the most robust relationship with funding?",{"text":117,"@type":109},"Team size is the most robust predictor: each additional co-founder is associated with roughly 21% more capital raised, while observable credentials explain minimal variation.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},306478,1792202380,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":8,"category_name":11,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":47,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":135,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":15},962085662650,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","arXiv :2512 . 13755v1 [ econ .GN] 15 Dec 2025  \nFounder Backgrounds and Startup Funding: Evidence from Y  \nCombinator  \nRommin Adl  \nGrinnell College  \n[adlrommi@grinnell.edu](adlrommi@grinnell.edu)  \nDecember 2025  \nAbstract: While founder backgrounds account for less than 4% of funding variation among Y Combinator startups, this suggests that other factors, such as industry trends and product innovation, may play a more significant role in funding outcomes. Using data on 4,323 YC companies from 2005-2024 merged with S&P Global funding data, I estimate OLS regressions with batch year fixed effects on a regression sample of 2,113 companies. The coefficient on prior FAANG work experience is-0.251, indicating approximately 22% less funding. However, this result is not robust, as it changes direction in further analyses, suggesting that FAANG experience may not be a reliable predictor of funding. The most robust finding is that startups within Y Combinator that consist of larger founding teams tend to raise more funding, with each additional co-founder associated with approximately 21% more capital raised. While observable credentials such as prior FAANG work experience and top-tier education explain minimal variation in funding, the size of the founding team emerges as a more consistent predictor, highlighting the importance of team dynamics in securing capital. Unobserved factors like industry and product quality likely dominate funding decisions within this elite accelerator cohort.  \nJEL: L26, G24, M13, J24  \nKeywords: startup financing, founder human capital, startup accelerators, venture capital, Y Combinator, team composition, founder characteristics, Series A funding  \n1 Introduction  \nIn recent years, high-profile startups such as Airbnb and Dropbox reached multi-billion-dollar valuations after graduating from Y Combinator, most commonly known as YC, the world’s leading startup accelerator, located in San Francisco, California. Yet for every Airbnb, there are many more YC graduates who cannot raise substantial funding or scale their businesses. This gap truly raises the following question: what causes the disparity in success between the most successful YC startups and the struggling ones? One major theory is that the differences in founders’ backgrounds, e.g., education credentials, pre-startup experience at premier tech companies, and the composition of their founding teams, actually dictate the future of these startups after partaking in an accelerator. YC startup founders often have degrees from top universities like Stanford or prior work experience at Google and Meta as badges of credibility; likewise, investors and accelerators frequently underscore the significance of a strong founding team with a good story, as these investors not only bet on the companies but also on the people running them. This study asks whether such founder characteristics can predict a startup’s fundraising success after finishing Y Combinator. Particularly, this research examines if indicators of founders’ human capital (education level, industry experience, prior FAANG work experience) and team composition (e.g., number of co-founders) are associated with greater venture funding success following the YC accelerator program.  \nUnderstanding whether founder background matters for post-YC success is important in regards to both the theory and practice. In practical terms, accelerators and early-stage investors are able to make their selection of startups and advising/mentoring focus more efficient if they had a sense of which founder characteristics are linked to better performance. If, for example, prior experience at a large tech firm or a larger founding group increases the likelihood of acquiring a Series A round, then accelerators can train or recruit in that direction. For founders and entrepreneurs, having that awareness of desirable success drivers would guide professional development and talent acquisition. At the scholarly level, ","cbCaiqwB2TS2aSmZ","https://ap.wps.com/l/cbCaiqwB2TS2aSmZ","pdf",1482006,33,"English","# 1 Introduction","[{\"question\":\"What question does the study address about Y Combinator startups?\",\"answer\":\"The study asks what drives the disparity in fundraising success between the most successful YC startups and those that struggle to raise substantial capital after the accelerator.\"},{\"question\":\"How is the analysis conducted to test founder characteristics?\",\"answer\":\"The paper merges Y Combinator company records with S\\u0026P Global funding data for 4,323 companies (2005–2024) and runs OLS regressions with batch-year fixed effects, focusing on 2,113 companies in the regression sample.\"},{\"question\":\"Which founder factor shows the most robust relationship with funding?\",\"answer\":\"Team size is the most robust predictor: each additional co-founder is associated with roughly 21% more capital raised, while observable credentials explain minimal variation.\"}]","Founder Backgrounds and Startup Funding - Evidence from Y Combinator | PDF",1789837021]