Estimating the education-earnings equation using geographic variation

Doyle, William R.; Skinner, Benjamin T.

doi:10.1016/j.econedurev.2016.03.010

Cited by 22 publications

(13 citation statements)

References 33 publications

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“…Gender also features prominently in this literature in which men, historically, have earned more than women. Most of this research has focused on age, education, race, or gender (Card, 1999; Doyle and Skinner, 2016; Heckman et al., 2003; Mincer, 1974; Oreopoulos and Petronijevic, 2013; Price and Mills, 1985).…”

Section: Literature Reviewmentioning

confidence: 99%

The effects of population and housing density in urban areas on income in the United States

Hummel

2020

Local Economy

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Cities in the United States have become increasingly less dense either from sprawl from rapid development or vacancy due to decline. The benefits and costs of urban density have been a topic of research since the mid-20th century. The effect of urban density on incomes is one of these areas of research. Based on concepts rooted in urbanization economies and social output, it is assumed in this paper that an increase in urban density increases incomes. Urban density is defined as population and housing density. It was found using a cross-sectional lagged mediated multiple regression that population and housing density have statistically significant indirect effects on income in a sample of more than 300 metropolitan areas in the United States. The significant effects of these variables on employment and the effect of employment on income mediated these effects.

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Section: Literature Reviewmentioning

confidence: 99%

The effects of population and housing density in urban areas on income in the United States

Hummel

2020

Local Economy

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“…Be that as it may, Doyle and Skinner (2016) estimates the education earnings equation using geographic variation with data from the National Longitudinal Study of Youth, 1997, making use of a variety of 6 instruments based on geographic variation. The six instruments incorporated include: the distance weight tuitions, the presence of a colleague existing in the country for two years or for 4 years, distance weight enrolment in colleagues existing for two years within the state, the inverse log distance to colleague's existing for two years within the state and the inverse log of the distance to all the colleges.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The studies on education and earnings have benefitted from works of Jacob Mincer who is considered to be the father of modern labour Economics (Polachek, 2007;Fiaschi and Gabbriellini, 2013;Biyase and Zwane, 2015;Doyle and Skinner, 2016) Mincer is known for his earnings function which considers earnings as a function of education and years of experience.…”

Section: Model Specificationmentioning

confidence: 99%

“…Studies such as those of Becker (1946) attribute the positive relationship identified between earnings and education to the years of education attained by an individual, as this could serve as a signal for skill possession to possible potential employers, which will thus make it much easier for an educated person to find employment in more lucrative jobs. Doyle and Skinner, (2016) acknowledge that pursuing further education is commonly associated with pursuing a higher income. The real value of education in terms of obtaining a degree was given much attention in the 21 st century by researchers such as Oreopoulos and Petronijevic, (2013).…”

Section: Introductionmentioning

confidence: 99%

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Education and Earnings in South Africa: An Application of the Mincerian Function

Dunga¹,

Mothibi²

2019

Proceedings of the 45th International Academic Conference, London

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The understanding of the interaction between education and income can never be exhausted, mainly because education remains the leading mechanism for upward social mobility. The argument is that people with higher levels of income are more likely to earn a higher income that those with lower level of education, that's the rule, although there maybe exceptions to the rule, the numbers for such cases are arguable small. However, there exists differences in the extent to which education influences income, earnings differentials exist by countries and social groups. This paper uses data published in 2017 by Statistics South Africa collected in the general household survey (GHS) which interviewed 72291 individuals across all the 9 provinces of the country. Using a mincerian function the paper estimates returns to education in South Africa. The results show that as expected, there is a positive relationship between education and earnings. The regression results also showed that based on the South African Household data, there is significant difference by race and gender. The results set a basis for reexamining the measurement of the variable used to capture education. The fact that a unit change in years of education is used needs to be changed so that different levels of education a weighted correctly.

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“…The intuition behind this approach is that students who live closer to more expensive community colleges will likely borrow more money to attend. This assumption is backed by the extensive literature on variation in college opportunity and postsecondary attainment, which routinely finds that individuals who live in areas with more educational opportunity are more likely to attend and complete college (Card 1993; Doyle and Skinner 2016). We extend this reasoning by hypothesizing that individuals who live closer to higher-priced community colleges will be more likely to both attend a higher-priced community college and subsequently to borrow more.…”

Section: Model Specification and Empirical Approachmentioning

confidence: 99%

Impact of Community College Student Debt Levels on Credit Accumulation

Baker¹,

Doyle²

2017

The ANNALS of the American Academy of Political and Social Scie

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Most community college students do not borrow to pay for their education. However, in recent years more students are borrowing and, when they borrow, accumulating large amounts of debt. To help clarify whether increased debt burdens are aiding community college students or harming them, we explore the impact of borrowing on academic credit hour accumulation. Using data from the Education Longitudinal Study 2002–2012, we provide multiple estimates of the impact of borrowing on credit hour attainment among community college students. Standard estimates suggest that community college students who borrow complete fewer credit hours than students who do not borrow, although the influence is relatively small (about two credits two years after enrollment). Instrumental variables estimates suggest that the impact of borrowing on credits attained is not significant two years after enrollment but is substantial eight years after enrollment (allowing students multiple enrollment spells).

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Estimating the education-earnings equation using geographic variation

Cited by 22 publications

References 33 publications

The effects of population and housing density in urban areas on income in the United States

The effects of population and housing density in urban areas on income in the United States

Education and Earnings in South Africa: An Application of the Mincerian Function

Impact of Community College Student Debt Levels on Credit Accumulation

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