研究大学工资溢价在种族间的差异，我们从综合公共使用微数据系列(IPUMS)获得数据。简单地说，IPUMS下有九种不同的普查和调查。在这些项目中，我们从美国政府获得数据。美国人口普查和美国社区调查。来自IPUMS-USA的数据包括从1790年到2010年每十年组织一次的人口普查和从2010年开始的美国社区调查。不像国家纵向调查(NLS)有很多缺失的观察，这个问题在IPUMS-USA数据中不那么明显。同样，我们的主要数据来源有超过100万个观察值，因此考虑到高中和大学毕业生不会影响样本量。由于我们对分析大学工资溢价如何随时间变化而变化很感兴趣，我们使用了1980年和2014年的数据。每一年，样本中只有男性。我们认为，大多数情况下，女性在生孩子时放弃了学业，转而照顾孩子。因此，我们无法真正衡量这些人的潜在经验。现有的数据没有提供任何关于妇女在照顾子女后重新接受教育的时间的资料。因此，为了克服计算个体潜在经验的问题，我们从样本中剔除了所有女性。
澳洲经济学论文代写:大学工资溢价
examine how the college wage premium differs within race, we obtain data from the Integrated Public Use Microdata Series (IPUMS). Briefly, there are nine different censuses and surveys under IPUMS. Among these projects, we obtain data from the U.S Census and American Community Survey. Data from IPUMS-USA consist of census organized every ten years from 1790 to 2010 and the American Community Survey which began in 2010. Unlike the National Longitudinal Survey (NLS) which has a lot of missing observations, this problem is less pronounced in the IPUMS-USA data. Again, our primary source of data has over a million observations, hence considering high school and college graduates will not affect the sample size. Since we are interested in analyzing how the college wage premium has been changing over time, we employ data from 1980 and 2014. For each year, only males are included in the sample. We argue that most of the time women quit their education and cater for their children upon giving birth. As a result, one cannot truly measure the potential experience of such individuals. The data available does not provide any information on the time females reentered into education after nursing their children. Therefore, to overcome the problem in computing the potential experience for individuals, we eliminate all females from the sample. There are 207650 observations in the 1980 data whereas the 2014 data includes 593774 observations.
