Free University? An Investigation of Australia’s 1974 Free Higher Education Policy and Its Impact on Enrollment, Degree Completion, Later-Life Occupational Status, and Income
by Yaxuan “Annie” Cui
Abstract
To what extent has the free higher education policy of 1974 impacted Australian students’ decisions of university enrollment, degree completion, and later-life human capital development? In this paper, I analyze the impact of the policy from both national descriptive statistics and individual-level enrollment and degree completion decisions using the Australian Household Income and Labour Dynamics Survey. I find that the policy has significantly increased the likelihood of female enrollment in higher education, low-income students’ likelihood of diploma degree completion, and is positively associated with later-life occupational status. However, this study does not find a clear relationship between the policy, bachelor’s degree attainment, and later-life disposable income. Policymakers need to carefully consider the efficiency and efficacy of broad-based tuition policy instruments when imagining bridges to achieve universal access to higher education.
Professor Robert Garlick, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
Professor Peter Arcidiacono, Faculty Advisor
JEL Codes: I2, I22; I23; I26
Student Effort and Parent Attitude on Education Attainment: Evidence from Multi-year Survey in Gansu, China
by Ridge Zhong-yuan Ren
Abstract
This paper explores whether student effort and parent attitudes have varying effects at different stages of a student’s life in terms of educational attainment and job outcomes. With survey data in Gansu, China, a largely rural province in Northwest China that lags behind the rest of China in education, this paper employs a multivariate regression model. This method allows me to measure the achievement or outcome of the child between each successive wave of surveys and estimate which factors held the strongest effect on the next wave. Student achievement in early waves is measured by the student’s score on assessments in math and Chinese, and the later outcome is measured by the student’s income and the highest level of education achieved. This paper finds that effort in Math and math achievement have a positive association with better education attainment and career outcomes later in life. In addition, I find that parental education levels also have a positive association with child outcomes.
Professor Pengpeng Xiao, Faculty Advisor
Professor Kent P. Kimbrough, Faculty Advisor
JEL Codes: I25, I26
An Analysis of the Labor Market Returns to Community College and Vocational Training
by Eli Levine
Abstract
Education and training are fundamentally linked with labor market performance. There is a significant body of work analyzing the role of education in wages with an emphasis on a comparison between a college degree and a high school diploma. However, as states have begun to shift their education policies to make community college and trade school more accessible, it is important to understand the expected labor market returns to these forms of education. In this paper, using data from the National Longitudinal Survey of Youth’s cohort that began in 1997, the returns for different levels of education using the Mincer equation are found. While there was a data limitation surrounding trade school, it was possible to analyze the impact of adding a vocational license or a training certificate to a high school diploma. When controlling for experience in three different ways, specifically by age, time at highest training and labor market experience, it was found that returns to a training certificate relative to high school are between 18.7% and 36.3% higher than a high school diploma. Furthermore for community college, the wage returns are between 26.4% and 45.8% higher relative to a high school diploma. These findings highlight that additional training and certification can be an effective tool for increasing labor market returns for high school graduates even without a bachelor’s degree.
Professor V. Joseph Hotz, Faculty Advisor
JEL Codes: I2, I26, J31
Peer Effects & Differential Attrition: Evidence from Tennessee’s Project STAR
by Sanjay Satish
Abstract
This paper explores the effects of attrition on student development in early education. It aims to provide evidence that student departure in elementary schools has educational impacts on the students they leave behind. Utilizing data from Tennessee’s Project STAR experiment, this paper aims to expand upon the literature of peer effects, as well as attrition, in public elementary schools. It departs from previous papers by utilizing survival analysis to determine which characteristics of students prolonged participation in the experiment. Clustering analysis is subsequently employed to group departed students to better understand the various channels of attrition present in STAR. It finds that students who left Project STAR were more likely to be of lower income and lower ability than their peers. This paper then uses these findings to estimate the peer effects of attrition on students who remained in the experiment and undertakes a discussion of potential sources of bias in this estimation and their effects on the explanatory power of peer effects estimates.
Professor Robert Garlick, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: I, I21, I26, H4, J13
Predictors of Student Loan Repayments: A Comparison Between Public, Private For-Profit and Private Nonprofit Schools
by Mannat Bakshi and Arjun Ahluwalia
Abstract
Using a sample of over 3,500 colleges from the College Scorecard Dataset , we investigate the association of average federal student loan repayment rates with institutional, regional, and student demographic characteristics of colleges. We consider educational cohorts from 2010 to 2016 at public, private for-profit, and private non-profit institutions. Our data do not allow us to see individual student characteristics, hence we control for traits of the average student in each college and focus on institutional traits that impact repayment rates. Our controls for demographics are consistent with prior research on student loan repayment rates (Lochner and Monge-Naranjo, 2014; Kelchen and Li, 2017).
We ran a Random Effects panel regression to determine how institutional, regional, and student demographic characteristics impact repayment rates. We see an important influence of the institution attended. Institution selectivity (lower admission and withdrawal rates) is associated with higher average repayment. Furthermore, the highest degree awarded is a more significant variable when it comes to describing the variation in repayment rates for public schools; private for-profit schools exhibit lower repayment rates and private nonprofit schools exhibit higher repayment rates regardless of the highest degree awarded. This could be due to a combination of signaling and screening effects. Local income and unemployment impact repayment for the average student in public and for-profit schools, but not in private non-profit schools.
A noticeable institutional finding is that, even after controlling for average school demographics, for-profit schools exhibit lower repayment rates across all types of degree-granting programs. Attending a for-profit school may be a negative signal of ability or value to potential employers. Median family income positively affects repayment twice as much for for-profit schools compared to other school types. These finding on for-profit institutions help explain Obama’s “crack down on for-profit career training colleges” (Simon & Emma, 2014).
Advisors: Michelle Connolly, Kent Kimbrough, Genna Miller | JEL Codes: I2, I22, I26
Bridging the Persistence Gap: An Investigation of the Underrepresentation of Female and Minority Students in STEM Fields
By Aaditya Jain and Bailey Kaston
Prior literature on mismatch theory has concentrated primarily on minority students, whose lower average levels of pre-enrollment preparedness tend to discourage them from persisting in STEM fields as often as their non-minority counterparts at selective universities. Our study shifts the focus to the persistence gap between men and women, invoking social cognitive career theory to investigate how factors beyond preparedness – such as self-confidence – cause women to switch out of selective STEM programs at higher rates than men. Using the High School Longitudinal Study of 2009, we investigate the drivers of STEM persistence for all students and arrive at two main conclusions. First, higher levels of STEM preparedness are more beneficial to STEM persistence at selective universities, confirming mismatch theory in the sample. We then simulate the counterfactual scenario and find that 33% of students at selective schools would have been more likely to persist in STEM had they attended less selective schools, a figure that reaches 50% for underconfident female students. This observation ties to our second conclusion – that underconfidence in math relative to one’s true performance decreases the likelihood of STEM persistence for all students at selective universities, and that female students at selective schools are more likely to be underconfident than their male counterparts. Our findings suggest that the appropriate policy solution to reduce STEM attrition rates among women should then become a two-pronged approach: (1) more selective universities should better support the STEM self-confidence levels of female students, and (2) home environments should ideally cultivate that self-confidence long before women even reach college. In our final set of analyses, we thus explore the factors that drive math overconfidence in the first place, and conclude that both student and parental biases against female STEM ability are detrimental to the STEM self-confidence of female students.
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Advisors: Professor Peter Arcidiacono, Professor Michelle Connolly | JEL Codes: I2, I24, I26
