Paper: Kirkeboen, Leuven & Mogstad (2016)

"Field of Study, Earnings, and Self-Selection", in the QJE. Read as part of the Applied Economics PhD Workshop at UCL (2023-24).
== Summary ==
=== I. Introduction ===
This article examines the labor market payoffs to postsecondary education, including the effect of field and institution of study.
Identification is made difficult by individuals choosing between several types of education, which are unordered alternatives. It requires: 
* A valid instrument for each alternative/type of education. 
* Deal with the issue that individuals who choose the same education may have different next-best alternatives: (1) info about individuals' ranking of education types, or (2) additional assumptions to those needed in settings with binary choices (e.g. college or not) or ordered choices (e.g. years of schooling). 
They use instruments to correct for selection bias, and exploit measures of info on individuals' ranking of institutions and fields to measure their preferred and next-best education type. Together, this allows them to identify the payoff to completing one type of education relative to a particular next-best alternative. 
Admin data from Norway on the postsecondary education system. Norway has a centralized admission process that covers almost all universities and colleges. Applicants are scored centrally based on their high-school GPA, and ranked. Then, the highest-ranked person gets their preferred choice, the next-highest the highest available for which they qualify, and so on. This creates instruments from discontinuities that effectively randomize applicants near unpredictable admission cutoffs into different institutions and fields.
Broad conclusions:
# Fields of study have substantially different labor market payoffs, even after accounting for institution and peer quality
# The effect on earnings from a more selective institution is small relative to payoffs to field of study
# Estimated payoffs to field of study are consistent with people choosing fields in which they have a comparative advantage
Need to keep in mind/caveats: (1) they only observe earnings early in one's career, so estimated payoffs should be be taken as internal rates of return to investments in human capital, (2) estimates are local average treatment effects of those at the margin of entry to particular fields, and (3) findings may be specific to the Norwegian context.
Contributions relative to the literature: (1) provide initial evidence on the payoff to a field of study relative to a particular next-best alternative, (2) quantify the relative importance of institution and field of study, and (3) assess whether individuals tend to prefer fields in which they have a comparative advantage. In addition, could be lessons from their identification work for other settings with unordered choices. 
=== II. IV in Unordered Choice Models ===
==== II.A. Regression Model, Potential Outcomes, and Choices ====
==== II.B. OLS Estimation of Payoffs to Field of Study ====
==== II.C. IV Estimation of Payoffs to Field of Study ====
=== III. Institutional Details and Identification Strategy ===
==== III.A. Admission Process ====
==== III.B. Admission Cutoffs, Instruments, and Next-Best Alternatives ====
=== IV. Data and Descriptive Statistics ===
Records for all applications to post-secondary education for the years 1998 to 2004. 
* Retain the first observed application, require they have no postsecondary degree at the moment of applications.
* Link this to the Norwegian population registry to retain info on their socioeconomic background (parental education, income of father, immigrant status).
* For treatment variables: have info on everyone's completed field and institution.
* Annual earnings come from the Norwegian tax registers over the 1998-2012 period, hence every cohort is observed for at least eight years after their application. 
==== IV.A. Data Sources and Sample Selection ====
==== IV.B. Descriptive Statistics ====
=== V. Graphical Illustration of Research Design ===
==== V.A. Admission Cutoffs and Field of Study ====
==== V.B. Admission Cutoffs and Sorting ====
==== V.C. Admission cutoffs and Postgraduation Earnings ====
=== VI. Baseline 2SLS Model ===
=== VII. Payoffs to Field of Study ===
==== VII.A. First-Stage Estimates ====
==== VII.B. Baseline 2SLS Estimates ====
==== VII.C. Robustness Analysis ====
==== VII.D. Peer Quality and Labor Market Experience ====
=== VIII. Comparison with Other Approaches ===
==== VIII.A. Comparison with Alternative IV Estimates ====
==== VIII.B. Comparison with OLS and ITT Effects ====
=== IX. Field Effects versus Institution Effects ===
==== IX.A. Robustness of Field of Study Effects ====
==== IX.B. Empirical Importance of Institution Effects ====
=== X. Sorting Pattern to Fields ===
==== X.A. Defining Comparative Advantage int he Context of Field of Study ====
==== X.B. Evidence on comparative Advantage among Compliers ====
==== X.C. Robustness of Comparative Advantage ====
==== X.D. Sorting Pattern and Economic Models ====
=== XI. Conclusion ===