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This paper attempts to analyze different trends in self-employment from the years 2003-2013 using data from the Current Population Survey (CPS). Self-employment can be broken down into two categories: incorporated and unincorporated self-employment. Incorporated self-employed individuals are those who have formed a legal corporation whereas unincorporated self-employed individuals have not. The reason as to why both groups are studied is, typically, those who incorporate are more entrepreneurial than those who do no incorporate. For example, an incorporated business can be an individual who starts a law firm or medical practice. The trends analyzed here are based on age, industry, and educational attainment. Age, industry, and education are very important for this analysis. Education and age have been observed in a multitude of literature on self-employment and there are observable trends, such as those who are older are more likely to be self-employed. These trends hold true in this research The Great Recession started in December of 2007 and lasted until June 2009. The major cause of this recession was the popping of the housing bubble in the United States. This led to the value of securities bound to real estate pricing in the U.S. to fall drastically, devastating financial institutions. A major contribution of this paper is to see whether the recent financial crisis had a significant impact on self-employment rates. The study is restricted to white males, ages 18-65 who are full-time employed, not in school full-time, and are in non-agricultural occupations. I perform a regression analysis to see which variables have significant effects on overall self-employment, incorporated self-employment, and unincorporated self-employment by age, industry, and educational attainment. Carrasco (1999) references a "pull" and "push" effect in regards to the business cycle and self-employment. This refers to the belief that recessions pull people into self-employment because of the lack of jobs and that booms push entrepreneurial individuals into self-employment because of a higher access to capital. The data analysis in this study finds support for the recession-pull effect on self-employment. Using transnational data, Blanchflower et al. (2001) find that (i) education and self-employment have a negative relationship, and (ii) age and self-employment have a positive relationship. Using CPS data for years 2003-2013, there is support for the second claim of Blanchflower et al., but not for the first. Additional research has shown that higher local unemployment rates lead workers to self-select into self-employment. The process is different for white and non-whites, with education being irrelevant for white self-employed workers. For nonwhites, higher education reduces the probability of entering self-employment (Rissman, 2003). High unemployment leading to start-up activity among self-employed individuals is known as the refugee effect (Thurik et al., 2008). The data analyzed indicates that education is not irrelevant for white self-employed workers; this is also concluded in Evan's and Leighton's (1989) article Some Empirical Aspects of Entrepreneurship. This paper also analyzes the trends in self-employment per industry during the recession. Industry is important to evaluate self-employment because of the 2007 financial crisis. It is expected that construction will be highly affected by this crisis. Another section in this paper is directed towards an interesting finding in the data. In the year 2013, for the first time in the years analyzed, rates for those with less than a high school diploma in unincorporated self-employment have surpassed those with a doctoral degree, becoming the most likely group to become unincorporated self-employed.