{"title":"对csm和Tak的答复(2021年4月)","authors":"L. Stein, Constantine Yannelis","doi":"10.2139/ssrn.3893855","DOIUrl":null,"url":null,"abstract":"Stein and Yannelis (2020) (SY) study the short-term impact of the Freedman’s Savings Bank on human capital, labor market, and wealth outcomes. This short note is a response to Célérier and Tak (2021) (CT), which offers comments on SY, claiming to “empirically reject the assumptions of the study’s identification strategy” and arguing that “financial inclusion can be detrimental to minorities.” We show their claims are driven by a serious data error and by omitting data, and that their empirical tests do not evaluate the identification assumption in SY. After using an alternative matching strategy which throws out four-fifths of matches, CT present estimates with very large standard errors. We show that these estimates cannot statistically reject large effects, including many of the point estimates in SY.","PeriodicalId":331807,"journal":{"name":"Banking & Insurance eJournal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Response to Célérier and Tak (April 2021)\",\"authors\":\"L. Stein, Constantine Yannelis\",\"doi\":\"10.2139/ssrn.3893855\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stein and Yannelis (2020) (SY) study the short-term impact of the Freedman’s Savings Bank on human capital, labor market, and wealth outcomes. This short note is a response to Célérier and Tak (2021) (CT), which offers comments on SY, claiming to “empirically reject the assumptions of the study’s identification strategy” and arguing that “financial inclusion can be detrimental to minorities.” We show their claims are driven by a serious data error and by omitting data, and that their empirical tests do not evaluate the identification assumption in SY. After using an alternative matching strategy which throws out four-fifths of matches, CT present estimates with very large standard errors. We show that these estimates cannot statistically reject large effects, including many of the point estimates in SY.\",\"PeriodicalId\":331807,\"journal\":{\"name\":\"Banking & Insurance eJournal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Banking & Insurance eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3893855\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Banking & Insurance eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3893855","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
Stein和Yannelis (2020) (SY)研究了弗里德曼储蓄银行对人力资本、劳动力市场和财富结果的短期影响。这篇短文是对csamlsamrier and Tak (2021) (CT)的回应,后者对SY提出了评论,声称“从经验上拒绝了该研究的识别策略的假设”,并认为“金融包容性可能对少数群体有害”。我们表明他们的主张是由严重的数据错误和省略数据驱动的,并且他们的经验检验没有评估SY中的识别假设。在使用另一种匹配策略后,丢弃了五分之四的匹配,CT给出的估计具有非常大的标准误差。我们表明,这些估计不能在统计上拒绝大的影响,包括许多点估计在SY。
Stein and Yannelis (2020) (SY) study the short-term impact of the Freedman’s Savings Bank on human capital, labor market, and wealth outcomes. This short note is a response to Célérier and Tak (2021) (CT), which offers comments on SY, claiming to “empirically reject the assumptions of the study’s identification strategy” and arguing that “financial inclusion can be detrimental to minorities.” We show their claims are driven by a serious data error and by omitting data, and that their empirical tests do not evaluate the identification assumption in SY. After using an alternative matching strategy which throws out four-fifths of matches, CT present estimates with very large standard errors. We show that these estimates cannot statistically reject large effects, including many of the point estimates in SY.