Field of Study, Earnings, and Self-Selection*

By L. Kirkebøen, E. Leuven, Magne Mogstad. 2016

581 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Education

View Paper: https://www.semanticscholar.org/paper/17fb66c1ff9dbcdd050ae8c7f694f8faf193572a

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Citations in the corpus

Shifting College Majors in Response to Advanced Placement Exam Scores (2017, unknown): “…lowest-paying majors is estimated to be several million dollars (Carnevale, Cheah, and Hanson 2015), and there is growing evidence that at least some portion of the connection between college major and wages is causal (Hastings, Neilson, and Zimmerman 2013; Kirkebøen, Leuven, and Mogstad, 2016).”
Contamination Bias in Linear Regressions (2021, unknown): “3Our analysis also relates to issues with interpreting multiple-treatment IV estimates (Behaghel et al., 2013; Kirkeboen et al., 2016; Kline & Walters, 2016; Hull, 2018c; Lee & Salanié, 2018; Bhuller & Sigstad, 2022). the non-linear dependence across multiple dependent treatments and controls.”
Human Capital Investments and Expectations about Career and Family (2016, unknown): “Using observational data, studies have shown that individuals sort into educational choices on the basis of ex post returns (Kirkeboen, Leuven, and Mogstad 2016; Heckman, Humphries, and Veramendi 2018).”
The Labor of Division: Returns to Compulsory High School Math Coursework (2019, unknown): “Recent work exploiting degree program admissions thresholds in international contexts shows that quantitative college majors have a positive impact on earnings (Hastings et al., 2013; Kirkeboen et al., 2016).”
Elite Colleges and Upward Mobility to Top Jobs and Top Incomes (2019, unknown): “The separability restriction is similar to Kirkeboen et al. (2016). I take log income as the outcome of interest, and focus on the BW = 20 specification because, as discussed above, the running variable is predictive of log income.”
Community Colleges and Upward Mobility (2019, methodology): “11E.g. Moffitt (2008), Carneiro and Lee (2009), Carneiro et al. (2011), Havnes and Mogstad (2015), Kirkeboen et al. (2016), Kline and Walters (2016), Carneiro et al. (2017), Cornelissen et al. (2017), Nybom (2017), and Walters (2017).”
Mobility Report Cards: The Role of Colleges in Intergenerational Mobility (2017, unknown): “(6)Several studies have estimated the returns to attending certain selective colleges using admissions cutoffs and other quasi-experimental or matching methods (e.g., Dale and Krueger 2002; Black and Smith 2004; Hoekstra 2009; Hastings et al. 2013; Zimmerman 2014; Hoxby 2015; Kirkeboen et al. 2016).”
Bartik Instruments: What, When, Why, and How (2020, unknown): “Because the overidentified TSLS estimator is biased in finite samples, we encourage researchers to use three alternative estimators which have better properties with many instruments: the Modified Bias-corrected TSLS (MBTSLS) estimator from Anatolyev (2013) and Kolesar et al. (2015), the Limited Inf”
Innovation agglomeration and urban hierarchy: evidence from Chinese cities (2021, background): “The test and treatment of endogeneity requires the use of instrumental variables (IV), which should be exogenous, have no correlation with the error term but have a significant relationship with the potential endogenous variables (Kirkeboen, Leuven, and Mogstad 2016).”
Beyond LATE with a Discrete Instrument (2017, background): “See Heckman, Urzua, and Vytlacil (2006), Heckman and Vytlacil (2007), Heckman and Urzua (2010), and Kirkebøen et al. (2016) for discussions of IV and MTE estimation with multiple treatment variables.”