Estimating the Education-Earnings Equation Using Geographic Variation

Doyle, William R.; Skinner, Benjamin T.

doi:10.2139/ssrn.2639267

Cited by 10 publications

(16 citation statements)

References 33 publications

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“…In the specialized literature there are several works dealing with the performance of education and its returns; see, for example: Carnoy (1967), Mincer (1974), Griliches (1977), Bracho and Zamudio (1994) and (1995), Barceinas (2002), Giannelli and Monfardini (2003), Austria-Carlos and Venegas-Martínez (2011) and (2017), Aali-Bujari, Ortiz-Zarco and Rios-Bolívar (2013), Cellini and Chaudhary (2014), Denice (2015), Doyle and Skinner (2016), Austria-Carlos, Venegas-Martínez and Pérez-Lechuga (2018), and Fogarty and Hasegawa (2019). In particular, Giannelli and Monfardini (2003) analyze the effects of expected income of young adults with high school diploma.…”

Section: Literature Reviewmentioning

confidence: 99%

Schooling levels and wage gains in Mexico

Aali-Bujari

Venegas-Martı́nez

Garcı́a-Santillán

2019

Economics &Amp; Sociology

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This paper assesses the impact of the returns to education on income of the heads of family in Mexico in 2016. The analysis is based on Mincer's (1974) earnings function by using microdata from the National Household Income Survey (ENIGH acronym in Spanish) 2016. Estimations following Mincer equation are carried out by levels of schooling. The main conclusion is that as the level of education among Mexican heads of family increases, it magnifies the increase in income levels, which, in turn, enlarges human capital and learning capacity needed for sustained growth and welfare.

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Section: Literature Reviewmentioning

confidence: 99%

Schooling levels and wage gains in Mexico

Aali-Bujari

Venegas-Martı́nez

Garcı́a-Santillán

2019

Economics &Amp; Sociology

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“…Local college availability measures are first used by Card (1993) and Kane and Rouse (1993) as a proxy for direct costs of college attendance, and are subsequently widely used in the literature. Kane and Rouse (1993) use a distance to college measure as an instrument for schooling, and followed by Carneiro et al (2011), Nybom (2017), and Doyle and Skinner (2016) in recent 10For respondents, completion of their last level of schooling is available. When I construct the variable of years of schooling, I reduce the number by one year from the standard years for those who dropped out before finishing their last school.…”

Section: Capacity Of Universitiesmentioning

confidence: 99%

“…years. An indicator of presence of college in the county of residence is used by Card (1993) as a substitute for distance to college, and is commonly used in the literature, for example, by Kling (2001), Cameron and Taber (2004), Carneiro, Heckman, andVytlacil (2010, 2011), Carneiro, Meghir, and Parey (2013), and Doyle and Skinner (2016). Unfortunately, the JGSS only has information on the prefecture of residence at the age of 15, and because during the analyzed years, all prefectures in Japan contain at least one university, I am unable to use this local presence measure.…”

Section: Capacity Of Universitiesmentioning

confidence: 99%

“…The capacity measure used in this paper reflects both the existence and changes in the size of a university in the area of residence during adolescent years, and therefore more precisely approximates local university availability than the proxies commonly used in the literature. The literature uses the variation in local college accessibility and availability during adolescent years, for example, distance to college (Kane and Rouse, 1993;Carneiro et al, 2011;Doyle and Skinner, 2016;Nybom, 2017), presence of college in the county of residence (Card, 1993;Kling, 2001;Cameron and Taber, 2004;Carneiro, Heckman, andVytlacil, 2010, 2011;Carneiro, Meghir, and Parey, 2013;Doyle and Skinner, 2016) as a proxy for direct costs of college attendance, and the number of colleges (Currie and Moretti, 2003), the number of campuses (Belskaya, Sabirianova Peter, and Posso, 2014), and the number of admitted students (Kyui, 2016) as more precise measures of local college availability. Because capacity is numeric, I can control birth cohort and prefecture dummy variables when estimating the effects of local capacity on university enrollment decisions.…”

Section: Introductionmentioning

confidence: 99%

“…12For example,Sasaki (2006),Kobayashi (2009) use the number of enrollment as a proxy of the potential capacity of a prefecture Doyle and Skinner (2016). also use distance-weighted enrollment for an instrument to analyze postsecondary education in United States.13When I merge the year at age of 18, the acquired results are basically same.…”

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confidence: 99%

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Marginal Returns to Schooling and Education Policy Change in Japan

Kikuchi

2017

SSRN Journal

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This paper examines the returns to university education in Japan, using tuition, availability of universities, and labor market conditions as instrumental variables. To measure availability of universities, this paper uses total accredited capacity of all universities in the prefecture of residence at the age of 15. This measure captures cross-time and crossprefecture variations, because birth cohort and prefecture dummies are also controlled. A set of education policy-relevant instruments allows for estimation of the marginal effects for individuals who are induced to enroll in university by policy changes. Using the estimated marginal treatment effect, this paper recovers the average treatment effect parameters. The main empirical result shows that an additional year of university education increases hourly wage by about 9% on the population average. This paper also finds heterogeneous effects by subpopulation groups: the average effect of a year of university education for those enrolled in university is about 17%, but less than 2% for those who did not enroll. Finally, this paper investigates the average returns for those who are induced to enroll in university by a particular policy shift, such as free tuition or an increase in the capacity of local universities. The results suggest that such policy changes bring about positive effects of university education.

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Causal Inference Challenges and New Directions for Epidemiologic Research on the Health Effects of Social Policies

Matthay

Glymour

2022

Curr Epidemiol Rep

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Purposeof Review Epidemiologic research on the health effects of social policies is growing rapidly because of the potentially large impact of these policies on population health and health equity. We describe key methodological challenges faced in this nascent field and promising tools to enhance the validity of future studies. Recent Findings In epidemiologic studies of social policies, causal identification is most commonly pursued through confounder-control but use of instrument-based approaches is increasing. Researchers face challenges measuring relevant policy exposures; addressing confounding and positivity violations arising from co-occurring policies and time-varying confounders; deriving precise effect estimates; and quantifying and accounting for interference. Promising tools to address these challenges can enhance both internal validity (randomization, front door criterion for causal identification, new estimators that address interference and practical positivity violations) and external validity (data-driven methods for evaluating heterogeneous treatment effects; methods for transporting and generalizing effect estimates to new populations). Summary Common threats to validity in epidemiologic research play out in distinctive ways in research on the health effects of social policies. This is an active area of methodologic development, with ongoing advances to support causal inferences and produce policy-relevant findings. Researchers must navigate the tension between research questions of greatest interest and research questions that can be answered most accurately and precisely with the data at hand. Additional work is needed to facilitate integration of modern epidemiologic methods with econometric tools for policy evaluation and to increase the size and measurement quality of datasets.

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Estimating the Education-Earnings Equation Using Geographic Variation

Cited by 10 publications

References 33 publications

Schooling levels and wage gains in Mexico

Schooling levels and wage gains in Mexico

Marginal Returns to Schooling and Education Policy Change in Japan

Causal Inference Challenges and New Directions for Epidemiologic Research on the Health Effects of Social Policies

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