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The paper addresses this scale-up “Catch-22” by proposing a method that reduces large-scale impact estimation costs. It develops a model of labor-market search and inelastic human capital supply, linking scale to higher average costs or declining quality. Using Bayesian learning and randomized sampling of inputs, it estimates supply curves relevant at large scale and highlights applications where provider prediction noise mitigates scale-up constraints.",{"@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/the-economics-of-scale-up-working-paper-23925/155891/",{"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/the-economics-of-scale-up-working-paper-23925/155891.png","ImageObject",300,407,{"name":92,"@type":93},"Cipher","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-17","2026-08-28",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does the paper address in social program scale-up?","Question",{"text":112,"@type":113},"It addresses the lack of evidence on whether promising interventions at small scale will work when implemented at large scale, given that learning requires testing at scale.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the paper explain why scaling can be costly or reduce quality?",{"text":117,"@type":113},"It models social programs as relying on labor with heterogeneous skill, where labor market search and inelastic human capital supply imply higher average costs for constant quality or falling quality if costs are held fixed.",{"name":119,"@type":110,"acceptedAnswer":120},"What is the core idea of the proposed method to study effects at large scale?",{"text":121,"@type":113},"It uses randomization to sample the inputs the provider would hire at large scale, enabling learning about input supply curves at a much larger effective scale without operating the full program at that scale.","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},155891,1787940693,{"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":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":36,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":143,"preview_page_count":4},687208528416,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","NBER WORKING PAPER SERIES  \nTHE ECONOMICS OF SCALE-UP  \nJonathan M.V. Davis  \nJonathan Guryan  \nKelly Hallberg  \nJens Ludwig  \nWorking Paper 23925  \n[http://www.nber.org/papers/w23925](http://www.nber.org/papers/w23925)  \nNATIONAL BUREAU OF ECONOMIC RESEARCH  \n1050 Massachusetts Avenue  \nCambridge, MA 02138  \nOctober 2017  \nThis paper was made possible by the generous support of the Abdul Latif Jameel Poverty Action Lab (J-PAL), Chicago Beyond, the Polk Bros Foundation, and the William T. Grant Foundation. For vital assistance in making this intervention possible we thank Barbara Algarin, Rukiya Curvey-Johnson, Antonio Gutierrez, Alan Safran and the staff of the Chicago Public Schools and SAGA Innovations, as well as the Crown Family Foundation, the Lloyd A. Fry Foundation, and the IMC Charitable Foundation. For help accessing administrative data we thank the Chicago Public Schools, Jeffrey Broom, Sarah Dickson, Kylie Klein, and Stacy Norris. For outstanding help with project fieldwork and data assembly and analysis, we thank Valentine Gilbert, Rowan Gledhill, Nathan Hess, Zachary Honoroff, Julia Quinn, Catherine Schwarz, Hannah Shaw, Maitreyi Sistla, and John Wolf. For his excellent assistance with the development of the translation exercises we thank Juchi Pratt. For their very helpful suggestions and comments we thank Esther Duflo, Joe Hotz, John List, Sendhil Mullainathan, Jesse Rothstein, Jesse Shapiro, Don and Liz Thompson, and seminar participants at Duke University and the 2016 FEW conference. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research, or any other funder or data provider. All opinions and any errors are our own.  \nNBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.  \n© 2017 by Jonathan M.V. Davis, Jonathan Guryan, Kelly Hallberg, and Jens Ludwig. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.  \nThe Economics of Scale-Up  \nJonathan M.V. Davis, Jonathan Guryan, Kelly Hallberg, and Jens Ludwig NBER Working Paper No. 23925  \nOctober 2017  \nJEL No. D24,I2,J2,L25,L38,M5  \nABSTRACT  \nMost randomized controlled trials (RCT) of social programs test interventions at modest scale. While the hope is that promising programs will be scaled up, we have few successful examples of this scale-up process in practice. Ideally we would like to know which programs will work at large scale before we invest the resources to take them to scale. But it would seem that the only way to tell whether a program works at scale is to test it at scale. Our goal in this paper is to propose a way out of this Catch-22. We first develop a simple model that helps clarify the type of scale-up challenge for which our method is most relevant. Most social programs rely on labor as a key input (teachers, nurses, social workers, etc.) . We know people vary greatly in their skill at these jobs. So social programs, like firms, confront a search problem in the labor market that can lead to inelastically-supplied human capital. The result is that as programs scale, either average costs must increase if program quality is to be held constant, or else program quality will decline if average costs are held fixed. Our proposed method for reducing the costs of estimating program impacts at large scale combines the fact that hiring inherently involves ranking inputs with the most powerful element of the social science toolkit: randomization. We show that it is possible to operate a program at modest scale n but learn about the input supply curves facing the firm at much larger scale (S × n) by randomly sampling the inputs the provider would have hired if they operated at scale (S × n)","cbCaici5paHefBWW","https://ap.wps.com/l/cbCaici5paHefBWW","pdf",540998,"English","# Abstract\n# Introduction","[{\"question\":\"What problem does the paper address in social program scale-up?\",\"answer\":\"It addresses the lack of evidence on whether promising interventions at small scale will work when implemented at large scale, given that learning requires testing at scale.\"},{\"question\":\"How does the paper explain why scaling can be costly or reduce quality?\",\"answer\":\"It models social programs as relying on labor with heterogeneous skill, where labor market search and inelastic human capital supply imply higher average costs for constant quality or falling quality if costs are held fixed.\"},{\"question\":\"What is the core idea of the proposed method to study effects at large scale?\",\"answer\":\"It uses randomization to sample the inputs the provider would hire at large scale, enabling learning about input supply curves at a much larger effective scale without operating the full program at that scale.\"}]","The Economics of Scale-Up - Working Paper 23925 | PDF",101]