Papers written by Author(s): 'Evan Totty'
The following papers contain search terms that you selected. From the papers listed below, you can navigate to the PDF, the profile page for that working paper, or see all the working papers written by an author. You can also explore tags, keywords, and authors that occur frequently within these papers.
See Working Papers by Tag(s), Keywords(s), Author(s), or Search Text
Click here to search again
Frequently Occurring Concepts within this Search
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.
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.
No tags occur more than twice in this search.
Authors
No authors occur more than twice in this search.
Viewing papers 1 through 1 of 1
-
Working PaperA Task-based Approach to Constructing Occupational Categories with Implications for Empirical Research in Labor Economics
September 2019
Working Paper Number:
CES-19-27
Most applied research in labor economics that examines returns to worker skills or differences in earnings across subgroups of workers typically accounts for the role of occupations by controlling for occupational categories. Researchers often aggregate detailed occupations into categories based on the Standard Occupation Classification (SOC) coding scheme, which is based largely on narratives or qualitative measures of workers' tasks. Alternatively, we propose two quantitative task-based approaches to constructing occupational categories by using factor analysis with O*NET job descriptors that provide a rich set of continuous measures of job tasks across all occupations. We find that our task-based approach outperforms the SOC-based approach in terms of lower occupation distance measures. We show that our task-based approach provides an intuitive, nuanced interpretation for grouping occupations and permits quantitative assessments of similarities in task compositions across occupations. We also replicate a recent analysis and find that our task-based occupational categories explain more of the gender wage gap than the SOC-based approaches explain. Our study enhances the Federal Statistical System's understanding of the SOC codes, investigates ways to use third-party data to construct useful research variables that can potentially be added to Census Bureau data products to improve their quality and versatility, and sheds light on how the use of alternative occupational categories in economics research may lead to different empirical results and deeper understanding in the analysis of labor market outcomes.View Full Paper PDF
1
Total Results: 1
