CREAT: Census Research Exploration and Analysis Tool

Comparing Earnings Outcome Differences Between All Graduates and Title IV Graduates

August 2021

Written by: Andrew Foote

Working Paper Number:

CES-21-19

Abstract

Recently, two public data products have been released that publish earnings outcomes for college graduates by program of study and institution: Post-Secondary Employment Outcomes and College Scorecard, from the Census Bureau and U.S. Department of Education, respectively. While the earnings data underlying the data products is similar, persons eligible for the frames of the two products is different, with College Scorecard restricted to only students that receive Title IV aid. This paper documents how these differences in the population studied affect the published earnings outcomes. I show that at an institution, of the institutions in my sample, an average of sixty percent of baccalaureate graduates receive Title IV aid, and that the lower the coverage, the large the difference in earnings measurement. Additionally, I show that short-run earnings outcomes are very similar for these two samples, while longer-run outcomes (10 years after graduation) are significantly lower for the Title IV population. I also show that program ranking can change significantly when considering the Title IV population rather than the entire graduate population.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
earnings, bias, education, university, college, graduate, institutional, enrolled

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
:
Internal Revenue Service, Department of Education, Department of Homeland Security, Longitudinal Employer Household Dynamics, Census Bureau Disclosure Review Board, Disclosure Review Board

Similar Working Papers Similarity between working papers are determined by an unsupervised neural network model know as Doc2Vec.

Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the capture of semantic meaning in a way that relates to the context of words within the document. The model learns to associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as document classification, clustering, and similarity detection by preserving the order and structure of words. The document vectors are compared using cosine similarity/distance to determine the most similar working papers. Papers identified with 🔥 are in the top 20% of similarity.

The 10 most similar working papers to the working paper 'Comparing Earnings Outcome Differences Between All Graduates and Title IV Graduates' are listed below in order of similarity.