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Drawing on a collaborative network of five research teams and methods experts, the article highlights six design challenges: limited baseline covariates, constrained counterfactual data, weak and inconsistent outcome measures, attrition-related internal validity threats, restricted external validity from oversubscribed competition, and difficulties linking site-level questions to child-level randomization. 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\nArticle reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)© The Author(s) 2024. [https://journals.sagepub.com/home/ero](https://journals.sagepub.com/home/ero)  \nLottery-Based Evaluations of Early Education Programs: Opportunities and Challenges for Building the Next Generation of Evidence  \nChristina Weiland  \nUniversity of Michigan  \nRebecca Unterman  \nMDRC  \nSusan Dynarski  \nHarvard University  \nRachel Abenavoli  \nChild Trends  \nHoward Bloom  \nMDRC  \nBreno Braga  \nUrban Institute  \nAnne-Marie Faria  \nHarmony Research LLC  \nErica Greenberg  \nUrban Institute  \nBrian A. Jacob  \nUniversity of Michigan  \nJane Arnold Lincove  \nUniversity of Maryland  \nKaren Manship  \nAmerican Institutes for Research  \nMeghan McCormick  \nMDRC  \nLuke Miratrix  \nHarvard University  \nCreative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons  \nAttribution-NonCommercial 4.0 License ([https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)) which permits non-commercial use,  \nreproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ([https://us.sagepub.com/en-us/nam/open-access-at-sage](https://us.sagepub.com/en-us/nam/open-access-at-sage)).  \nWeiland et al.  \nTomás E. Monarrez  \nFederal Reserve Bank of Philadelphia  \nPamela Morris-Perez  \nNew York University  \nAnna Shapiro  \nRAND Corporation  \nJon Valant  \nBrookings Institution  \nLindsay Weixler  \nTulane University  \nLottery-based identification strategies offer potential for generating the next generation of evidence on U.S. early education programs. The authors’ collaborative network of five research teams applying this design in early education settings and methods experts has identified six challenges that need to be carefully considered in this next context: (a) available baseline covariates that may not be very rich; (b) limited data on the counterfactual; (c) limited and inconsistent outcome data; (d) weakened internal validity due to attrition; (e) constrained external validity due to who competes for oversubscribed programs; and (f) difficulties answering site-level questions with child-level randomization. The authors offer potential solutions to these six challenges and concrete recommendations for the design of future lottery-based early education studies.  \nKeywords: early childhood, child development, program evaluation, experimental design, research methodology  \nDecaDes of research show that preschool 1 helps prepare children for kindergarten, and in some contexts, improves participants’ outcomes into adulthood (Phillips et al., 2017; Yoshikawa et al., 2013) . But much of this evidence comes from older, small programs, which differ substantially from modern preschools in their curriculum, funding, diversity of children served, and alternative options. More evidence on today’s large-scale public programs is needed for guiding policy and practice (Phillips et al., 2017) . This is especially the case in the wake of a pandemic that has been particularly devastating for the early care and education sector (Weiland et al. 2021) and in light of policy proposals to expand public preschool program to all U.S. 3- and 4-year-olds (White House, 2021) .  \nLottery-based school assignment systems used in many cities across the United States have potential for helping generate this needed evidence. In these systems, when programs are oversubscribed, a random process is used to choose among the applicants. Sometimes, these lotteries are generated via separate applications to individual schools and other times, by centralized school choice systems across an entire district. In both cases, this creates a natural experiment in which some children are gr","cbCaikGlFvIgme0F","https://ap.wps.com/l/cbCaikGlFvIgme0F","pdf",788732,23,"English","# Introduction\n## Rationale for lottery-based evidence\n# Design Opportunities and Core Challenges\n## Baseline covariates and counterfactual data\n## Outcome data quality and internal validity\n## External validity and oversubscription competition\n## Site-level questions vs. child-level randomization","[{\"question\":\"What is the main goal of using lottery-based evaluations in early education?\",\"answer\":\"To generate the next generation of evidence on U.S. early education programs by exploiting the randomness created when programs are oversubscribed.\"},{\"question\":\"Which six challenges do the authors identify for lottery-based early education studies?\",\"answer\":\"They include limited baseline covariates, limited counterfactual data, limited and inconsistent outcome data, attrition weakening internal validity, constrained external validity from who competes, and difficulties answering site-level questions with child-level randomization.\"},{\"question\":\"How do the authors propose to address these challenges?\",\"answer\":\"They provide potential solutions and concrete recommendations for designing future lottery-based early education studies.\"}]","Lottery-Based Evaluations of Early Education Programs - Opportunities and Challenges for Building the Next Generation of Evidence | PDF",1792069145,58]