Full Citation

Title: CORRECTING MEDICAID ENROLLMENT UNDERREPORTING BY THE CURRENT POPULATION SURVEY: A STOCHASTIC FRONTIER ANALYSIS

Citation Type: Dissertation/Thesis

Publication Year: 2016

ISBN:

ISSN:

DOI:

NSFID:

PMCID:

PMID:

Abstract: The Current Population Survey (CPS) is the most widely cited source for estimates on Medicaid enrollment. However, previous literature has shown the CPS underreports enrollment by 30-40% in comparison to state-level records. The question then is how to correct the Medicaid enrollment gap brought on by the CPS. Gross adjustments for the discrepancy may be made, but only if the true amount of enrollees is known. In years when administrative records are delayed or incomplete this is not possible. To date, the methods for correcting underreporting require access to the state-level data which is usually infeasible or unpublishable due to privacy issues. Redesigning the CPS questionnaire itself might alleviate a good part of the undercount but doing so is well beyond the scope of most researchers. A better correction would rely only on the CPS count of Medicaid enrollees so as to avoid privacy concerns and time delays. We propose using stochastic frontier analysis to shrink the gap between the CPS count of Medicaid enrollees and the state records by adjusting the CPS counts to be closer to the state records.

Url: http://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1049&context=honorstheses

User Submitted?: No

Authors: Champion, Brachel R

Institution: University of Central Florida

Department:

Advisor:

Degree:

Publisher Location: Orlando, Florida

Pages:

Data Collections: IPUMS CPS

Topics: Methodology and Data Collection, Other

Countries: