DOI: 10.3886/e234701v1
title: National Survey of College Graduates, (NSCG) , United States, 1993-2021

description: The National Survey of College Graduates (NSCG) provides data on the characteristics of the nation’s college graduates, with a focus on those in the science and engineering workforce. It samples individuals who are living in the United States during the survey reference week, have at least a bachelor’s degree, and are younger than 76. By surveying college graduates in all academic disciplines, the NSCG provides data useful in understanding the relationship between college education and career opportunities, as well as the relationship between degree field and occupation. The survey is sponsored by the National Center for Science and Engineering Statistics (NCSES) within the U.S. National Science Foundation.
description: Weighting. Because the NSCG is based on a complex sampling design and subject to nonresponse bias, sampling weights were created for each respondent to support unbiased population estimates. The final analysis weights account for several factors, including the following:Adjustments to account for undercoverage of recent immigrants and undercoverage of recent degree-earnersAdjustment for incorrect names or incomplete address information on the sampling frameDifferential sampling ratesAdjustments to account for non-locatability and unit nonresponseAdjustments to align the sample distribution with population controlsTrimming of extreme weightsOverlap procedures to convert weights that reflect the population of each frame (2015 ACS, 2017 ACS, 2019 ACS, and 2021 ACS) into a final sample weight that reflects the 2023 NSCG target populationThe final sample weights enable data users to derive survey-based estimates of the NSCG target population. The variable name on the NSCG public use data files for the NSCG final sample weight is WTSURVY.<br><br>Variance estimation. The successive difference replication method (SDRM) was used to develop replicate weights for variance estimation. The theoretical basis for the SDRM is described in Wolter (1984); Fay and Train (1995); Ash (2014); and Opsomer et al. (2016). As with any replication method, successive difference replication involves constructing numerous subsamples (replicates) from the full sample and computing the statistic of interest for each replicate. The mean square error of the replicate estimates around their corresponding full sample estimate provides an estimate of the sampling variance of the statistic of interest. The 2023 NSCG produced 320 sets of replicate weights.
description: Response Rates: Mode. About 91% of the participants completed the survey by Web, 7% by mail, and 2% by CATI<br>Response rates. Response rates were calculated on complete responses, that is, from instruments with responses to all critical items. Critical items are those containing information needed to report labor force participation (including employment status, job title, and job description), college education (including degree type, degree date, and field of study), and location of residency on the reference date. The overall unweighted response rate was 61%; the weighted response rate was 61%. Of the roughly 161,000 persons in the 2023 NSCG sample, 94,606 completed the survey.
description: Survey DesignTarget population. The NSCG target population includes individuals who meet the following criteria:Earned a bachelor’s degree​ or higher prior to 1 January 2022Are not institutionalized and reside in the United States or Puerto Rico as of 1 February 2023Are younger than 76 years as of 1 February 2023Sampling frame. Using a rotating panel design, the 2023 NSCG includes new sample cases from the 2021 American Community Survey (ACS) and returning sample cases from the 2021 NSCG.The NSCG sampling frame for new sample cases included the following eligibility requirements:Were residing in the United States or Puerto Rico as of the ACS interview dateWere noninstitutionalized as of the ACS interview dateHad earned at least a bachelor’s degree as of the ACS interview dateWould be under the age of 76 as of 1 February 2023Did not have an inaccurate name or incomplete address on the ACS data fileReturning sample cases from the 2021 NSCG originated from three different frames (the 2015 ACS, 2017 ACS, and 2019 ACS) and had the following eligibility requirements:Were a complete interview or temporarily ineligible during their initial NSCG survey cycleWould be under the age of 76 as of 1 February 2023During the 2021 NSCG survey cycle, did not refuse to participate and did not request to be excluded from future NSCG cyclesSample design. The NSCG sample design is cross-sectional with a rotating panel element. As a cross-sectional study, the NSCG provides estimates of the size and characteristics of the college graduate population for a point in time. As part of the rotating panel design, every new panel receives a baseline survey interview and three biennial follow-up interviews before rotating out of the survey.The NSCG uses a stratified sampling design to select its sample from the eligible sampling frame. In the new sample, cases were selected using systematic probability proportional to size (PPS) sampling.​ Among the returning sample, all eligible cases were selected. The sampling strata were defined by the cross-classification of the following variables:Highest degree type (3 levels)Field of bachelor’s degree (7 levels)Occupation group (8 levels)Underrepresented minority status (2 levels)Recent degree status (2 levels)Nativity (U.S.-born or foreign-born) (2 levels)As has been the case since the 2013 NSCG, the 2023 NSCG includes an oversample of young graduates to improve the precision of estimates for this important population. The 2023 NSCG includes approximately 161,000 sample cases drawn from the following:Returning sample from the 2021 NSCG who were originally selected from the 2015 ACSReturning sample from the 2021 NSCG who were originally selected from the 2017 ACSReturning sample from the 2021 NSCG who were originally selected from the 2019 ACSNew sample selected from the 2021 ACSApproximately 106,000 cases were selected from the returning sample members for one of the three biennial follow-up interviews that are part of the rotating panel design. For the baseline survey interview, about 55,000 new sample cases were selected from the 2021 ACS.Data Collection and Processing Methods
description: Smallest Geographic Unit: United States
description: computer-assisted telephone interview (CATI); mail questionnaire; web-based survey;