This analysis was conducted in five phases, listed below. Each step is described in more detail below.
First, we identified educational institutions across the United States by downloading data from the National Center for Education Statistics’ Integrated Postsecondary Education Data System (IPEDS). We gathered meta-data from IPEDS on all 2-year, 4-year, public and private post-secondary institutions, including:
Next, we connected the institutions to federal spending data using information available on USAspending.gov and DUNS numbers. The USAspending data output consisted of:
To begin, we derived a unique identifier between the IPEDS data in step 1 and the USAspending.gov data listed above. IPEDS lists several unique identifiers for each institution, and we normalized the name and state associated with each institution for consistency. To normalize the name, we connected any variation of an institution name to one common name. Data normalization is a process in which values measured on different scales are adjusted to a common scale to enable an accurate analysis and/or comparison of values.
Next, we normalized the names of the institutions, grouping records by their DUNS number and the unique_recipient_id field. To easily identify a recipient name as an institution of higher education, the records were paired with the IPEDS version of the institution name. However, there were two types of instances when a judgement call was required:
The third step was to identify institutions in the USAspending data. We began by pulling 2017 USASpending contract and assistance data. Then, we filtered and isolated the unique recipient name and DUNS number combinations into a new data set. Lastly, we identified and standardized the institution names.
Once we had the institution names, we filtered the 2017 USASpending data by the Business Type field by: higher_education, public_institution_of_higher_education, and private_institiution_of_higher_education. For records where it was easy to identify the recipient name as an institution of higher education, the names were added to the DUNS list. However, for records where it was not clear if the recipient names corresponded with an institution of higher education, we conducted a reverse look up of their DUNS number to obtain the address. Two common scenarios emerged:
Next, we filtered 2017 USAspending data on the DUNS numbers that were identified in the previous three passes, and normalized the names of the selected records. The remaining records were analyzed again to ensure no minor or unusual entities were missed.
To update this data to fiscal year 2018 the process outlined in the above paragraph was repeated and the new identifiers were added to the fiscal year 2017 data. We also pulled student aid data for the 2017-2018 academic year, which included student loan programs, the Federal Pell Grant program, the Teacher Education Assistance for College and Higher Education program, and the Iraq Afghanistan Service Grant program. This data was converted to fiscal year. For annually reported federal student aid programs such as, Perkins loans, Federal Supplemental Educational Opportunity Grants, and Federal Work Study program data, the most recent data available is for the 2016-2017 academic year. This data was used as a proxy for 2018 data in our calculated totals.
The fourth step was to sort the USAspending award data into one of three investment categories: contracts, grants, and research grants (a subset of grants that were awarded for research purposes).
We created a chart with 2 rings that aggregates contracts and grants by category (inner ring) and program (outer ring).
The last step was to convert the academic year information into the federal fiscal year. We began by retrieving federal student assistance data from the Department of Education, which was organized by quarter and re-organizing it according to the federal fiscal calendar.
However, we did encounter a few areas where data could not converted, such as institution data for Federal Work Study, Perkins Loans, and Federal Supplemental Educational Opportunity Grant programs. In these instances, data is reported annually by calendar year.
For more information on Federal Student Aid, visit: https://studentaid.gov/data-center/student/portfolio.
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