{"title":"评论","authors":"L. R. Ngai","doi":"10.1086/663654","DOIUrl":null,"url":null,"abstract":"978-0-226-26034-1/2012/2011-0011$10.00 Spolare and Wacziarg (2009) construct a measure of genetic distance to proxy differences in customs, norms, and other ethnic traits. They establish a statistically signifi cant empirical relationship between genetic distance and crosscountry income differences. The current paper aims to provide a channel for this relationship through differences in adoption of technologies across countries. It estimates an empirical relationship between genetic distance and adoption of technologies across countries, where both measures are relative to a frontier country. More specifi cally, this is done by using data on genetic distance they used in their previous paper, and two data sets on technology adoption for the year 1500 and 2000. The frontier is the United Kingdom for the year 1500 and the United States for the year 2000. For the year 2000, the paper relates relative genetic distance to three layers of technology adoption: (1) 33 specifi c technologies in the CrossCountry Historical Adoption of Technology (CHAT) and 9 specifi c technologies in Comin, Easterly, and Gong (2010) (hereafter Comin et al.); (2) 4 sectors: agriculture, industry, communication, and transportation; and (3) Aggregate total factor productivity (TFP). I have two sets of comments. The fi rst concerns the data and the methodology on estimating the relationship of adoption of specifi c technologies and genetic distance. The second is about aggregating the adoption of specifi c technologies into sectoral and aggregate economy level.","PeriodicalId":353207,"journal":{"name":"NBER International Seminar on Macroeconomics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comment\",\"authors\":\"L. R. Ngai\",\"doi\":\"10.1086/663654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"978-0-226-26034-1/2012/2011-0011$10.00 Spolare and Wacziarg (2009) construct a measure of genetic distance to proxy differences in customs, norms, and other ethnic traits. They establish a statistically signifi cant empirical relationship between genetic distance and crosscountry income differences. The current paper aims to provide a channel for this relationship through differences in adoption of technologies across countries. It estimates an empirical relationship between genetic distance and adoption of technologies across countries, where both measures are relative to a frontier country. More specifi cally, this is done by using data on genetic distance they used in their previous paper, and two data sets on technology adoption for the year 1500 and 2000. The frontier is the United Kingdom for the year 1500 and the United States for the year 2000. For the year 2000, the paper relates relative genetic distance to three layers of technology adoption: (1) 33 specifi c technologies in the CrossCountry Historical Adoption of Technology (CHAT) and 9 specifi c technologies in Comin, Easterly, and Gong (2010) (hereafter Comin et al.); (2) 4 sectors: agriculture, industry, communication, and transportation; and (3) Aggregate total factor productivity (TFP). I have two sets of comments. The fi rst concerns the data and the methodology on estimating the relationship of adoption of specifi c technologies and genetic distance. The second is about aggregating the adoption of specifi c technologies into sectoral and aggregate economy level.\",\"PeriodicalId\":353207,\"journal\":{\"name\":\"NBER International Seminar on Macroeconomics\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NBER International Seminar on Macroeconomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1086/663654\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NBER International Seminar on Macroeconomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1086/663654","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
Spolare和Wacziarg(2009)构建了一个衡量遗传距离的方法来代表习俗、规范和其他种族特征的差异。他们在遗传距离和跨国收入差异之间建立了统计上显著的实证关系。本文旨在通过各国在采用技术方面的差异,为这种关系提供一个渠道。它估计了各国之间遗传距离和技术采用之间的经验关系,这两项措施都是相对于前沿国家的。更具体地说,这是通过使用他们在上一篇论文中使用的遗传距离数据,以及1500年和2000年的两组技术采用数据来完成的。边界是1500年的英国和2000年的美国。对于2000年,本文将相对遗传距离与三层技术采用联系起来:(1)在cross - country Historical adoption of technology (CHAT)中有33种特定技术,在Comin, Easterly, and Gong(2010)中有9种特定技术(以下简称Comin et al.);(2)农业、工业、通信、交通四大领域;(3)总全要素生产率。我有两套意见。第一部分是研究特定技术的采用与遗传距离关系的数据和方法。第二是将特定技术的采用汇总到部门和总体经济水平。
978-0-226-26034-1/2012/2011-0011$10.00 Spolare and Wacziarg (2009) construct a measure of genetic distance to proxy differences in customs, norms, and other ethnic traits. They establish a statistically signifi cant empirical relationship between genetic distance and crosscountry income differences. The current paper aims to provide a channel for this relationship through differences in adoption of technologies across countries. It estimates an empirical relationship between genetic distance and adoption of technologies across countries, where both measures are relative to a frontier country. More specifi cally, this is done by using data on genetic distance they used in their previous paper, and two data sets on technology adoption for the year 1500 and 2000. The frontier is the United Kingdom for the year 1500 and the United States for the year 2000. For the year 2000, the paper relates relative genetic distance to three layers of technology adoption: (1) 33 specifi c technologies in the CrossCountry Historical Adoption of Technology (CHAT) and 9 specifi c technologies in Comin, Easterly, and Gong (2010) (hereafter Comin et al.); (2) 4 sectors: agriculture, industry, communication, and transportation; and (3) Aggregate total factor productivity (TFP). I have two sets of comments. The fi rst concerns the data and the methodology on estimating the relationship of adoption of specifi c technologies and genetic distance. The second is about aggregating the adoption of specifi c technologies into sectoral and aggregate economy level.