Announcing: CCS 2010 Now Available.  See description and download below.

The Colleges & Universities 2000 Project

The Colleges and Universities 2000 Project created two databases of interest to the higher education research community, the Institutional Data Archive (IDA) and the College Catalog Study (CCS) Database.

IDA and CCS databases are available for download online. User's downloading the data in Stata will need Stata 9 or later versions.  User's downloading the data in SAS or SPSS should experience no restrictions.

For queries about the databases, please contact: Steven Brint, CHASS Dean’s Office, 3405 HMNSS, University of California-Riverside, Riverside, CA 92521-0319 (steven.brint@ucr.edu) or Colleges & Universities 2000 data manager Kerry Mulligan (kmull001@student.ucr.edu).

A. The Institutional Data Archive

The Institutional Data Archive (IDA) consists of longitudinal and cross-sectional data on 384 institutions of higher education drawn from 24 separate data sets. IDA was created to allow researchers to take advantage of the large volume of data on higher education, which is spread across many separate data sets. IDA allows researchers to access this data without having to create composite data sets of their own.

The data cover earned degrees, enrollments, finances, faculty salaries, technology transfer activities, and institutional rankings over time. The longitudinal data cover the 40-year period, 1970-2010. IDA also includes data on university presidents, provosts, and faculty members, including disciplinary background, sex, age and opinions about current and future issues facing higher education. Census information concerning neighborhoods surrounding colleges and universities is also included. The data are organized in a panel design, with measurements taken at five year intervals: 1975-76, 1980-81, 1985-86, 1990-91, 1995-96, 2000-01, 2005-06, and 2010-11.

The sample of 384 institutions is based on stratified random sampling to over-sample elite institutions. The sample includes all highly selective colleges and leading research universities in the United States (n=71). It also includes more than 100 institutions from each of three other tiers. These three other tiers are: other selective colleges and research universities (tier 2); masters-granting comprehensive universities (tier 3); and non-selective baccalaureate-granting institutions (tier 4). The sample includes no specialized institutions (such as business colleges or art schools), for profit-institutions, or two-year colleges.

IDA data files are divided into sections based on whether or not institutional identifiers are attached to the data. Confidentiality agreements do not allow for the attachment of institutional identifiers in two of the 24 data sets.

The first section, IDA-Identifiable, includes data from the 20 data sets for which institutional identifiers could be included. Variables from the following data sets are included in this first section: (1) American Council on Education (ACE) surveys of college and university presidents; (2) Association of American Universities (AAU) membership; (3) Association of Research Libraries (ARL) library rankings and library holdings data; (4) Association of University Technology Managers (AUTM) technology transfer data; (5) Barron's Profile of American Colleges Selectivity Index and SAT/ACT data; (6) Carnegie Classifications; (7) The College Blue Book institutional data; (8) Consortium on Financing Higher Education (COFHE) membership; (9) Graham and Diamond institutional and departmental quality rankings; (10) Higher Education Directory institutional data; (11) Higher Education General Information System (HEGIS)/Integrated Postsecondary Education Data System (IPEDS) institutional characteristics data, enrollment data, financial data, six-year graduation rates and SAT scores data; (12) Huron Institute historical rankings of universities and professional schools and historical institutional data; (13) Morgan curricular clusters (measuring dominant curricular distributions); (14) National Science Foundation sources of research and development expenditures; (15) National Research Council (NRC) academic quality rankings of departments and divisions; (16) Open Doors data on international students; (17) U.S. Census Bureau data on neighborhoods surrounding universities 1990 and 2000; (18) U.S. Department of Agriculture’s classification of “land grant” institutions; (19) US News and World Report institutional quality rankings; (20) Zemsky Market Typology.

The second section, IDA-Not Identifiable, includes variables from two data sets in which institutional identifiers are confidential. Variables from the following data sets are included in this second section: (23) Colleges & Universities 2000 presidents survey and (24) Colleges & Universities 2000 provosts survey. We have attempted to make these data useful for comparative purposes by attaching six institutional characteristics to each data set. They are: Carnegie 1994 and Carnegie 2000 classification, selectivity level (on a five-point scale of average SAT/ACT scores), regional location, religious affiliation, and public-private control.

IDA data can be downloaded in SAS, SPSS, or Stata. The accompanying user's guide provides information on the approximately 2800 variables in IDA and includes information on weighting the data.

The National Science Foundation, the Atltantic Philanthropies, and the Spencer Foundation provided support for the construction of the Institutional Data Archive.

Suggested reference: Steven Brint, Kerry Mulligan, Matthew B. Rotondi, and Jacob Apkarian. 2011. The Institutional Data Archive on American Higher Education, 1970-2010. Riverside, CA: University of California, Riverside.

B. The College Catalog Study Database

The College Catalog Study (CCS) Database includes data on 286 four-year colleges and universities, a subset of institutions drawn from the Institutional Data Archive. The database includes every change in major academic units (schools and colleges), departments in arts and sciences, departments in professional schools, interdisciplinary degree-granting programs, and general education requirements over a 35-year period, 1975-6 through 2010-1. For schools and departments, changes in structure were coded, including new units, name changes, splits in units, units moved to new schools, reconstituted units, consolidated units, departments becoming programs, and eliminated units. Coding is based on college catalogs obtained from CollegeSource, Inc.

As in IDA, the data are organized in a panel design, where measurements are taken at five-year intervals: 1975-76, 1980-81, 1985-86, 1990-91, 1995-96, and 2000-01, 2005-06, and 2010-11.   Data were collected on every IDA institution for which a full set of catalogs was available. In cases in which data were not available for a target year, catalogs from the adjacent later year were used. The larger and more complex institutions, and those with difficult-to-interpret catalogs, were coded independently by two coders.

CCS data can be easily merged with IDA through unique institutional identifiers used in both databases. 

The National Science Foundation, the Spencer Foundation, and the Atlantic Philanthropies provided support for the construction of the College Catalog Study Database.

Suggested reference: Steven Brint, Kerry Mulligan, Matthew B. Rotondi, and Jacob Apkarian. 2011. The College Catalog Study Database, 1975-2010. Riverside, CA: University of California, Riverside.

C. Great Recession

The Great Recession database includes every non-duplicated story written about 292 colleges and universities and covered in Lexis-Nexis during the Great Recession years dating from October 2007 through June 2012.  The stories are coded for institution, institutional characteristics, date, detailed and broad topic, anticipated actions, and completed actions.

D. Survey of Faculty Cluster Hires Database

Over the last three decades, interdisciplinary cluster hiring programs have become popular on research university campuses as a means to foster interdisciplinary collaboration and to align research faculty with federal funding priorities. These initiatives are based on the hiring of multiple faculty members, typically between three and eight, to interact in interdisciplinary teams, in most cases with the expectation that they will jointly pursue high-impact research. The Survey of Faculty Cluster Hires (SFCH) Database is a survey of 199 cluster hires across 20 research universities. The SFCH Database includes questions about cluster hiring practices in American colleges and universities. It focuses on three key areas: hiring experiences, research and collaborative experiences, and organizational experiences

General Notes: The dataset reports type of institution, rather than institution name, to preserve confidentiality. These data consist of faculty members hired into clusters at 20 U.S. research universities. All faculty members included had publication records of at least five years prior to their hiring into clusters and at least five years following their hiring into clusters. The subsample allows for comparisons of research output, collaborations, and impact pre- and post-hire.

The data presented in this dataset were collected as part of a National Science Foundation project entitled, “Cluster Hiring Initiatives at US Research Universities: An Analysis of Productivity and Variation in Outcomes.” (Grant number SES 1736146) during 2017 – 2019. Please direct correspondence to the principal investigator, Steven Brint at steven.brint@ucr.edu

Suggested Reference: Brint, Steven, Quinn Bloom, and Michaela Curran. 2019. Survey of Faculty Cluster Hires Database. Riverside: Colleges & Universities 2000 Project, University of California, Riverside. Accessed on [DATE] from [Colleges & Universities 2000 web address].

E. Faculty Cluster Hires Research Productivity and Impact Database

For U.S. research universities, cluster hiring has become a popular means to add faculty members in university-defined priority fields. The expectation of advocates is that these faculty members will collaborate on high-impact research. The Faculty Cluster Hires Research Productivity and Impact (FCHRPI) Database utilizes a national sample of 168 cluster-hire faculty members from eight U.S. research universities to investigate research output, collaborations, and research impact prior to and after hire.

General Notes: The dataset reports type of institution, rather than institution name, to preserve confidentiality. These data consist of faculty members hired into clusters at 8 U.S. research universities.  All faculty members included had publication records of at least five years prior to their hiring into clusters and at least five years following their hiring into clusters.  The subsample allows for comparisons of research output, collaborations, and impact pre- and post-hire.

The data presented in this dataset were collected as part of a National Science Foundation project entitled, “Cluster Hiring Initiatives at US Research Universities: An Analysis of Productivity and Variation in Outcomes.” (Grant number SES 1736146) during 2017 – 2019. Please direct correspondence to the principal investigator, Steven Brint at steven.brint@ucr.edu.

Suggested Reference: Brint, Steven, Quinn Bloom, and Michaela Curran. 2019. Faculty Cluster Hires Research Productivity and Impact Database. Riverside: Colleges & Universities 2000 Project, University of California, Riverside. Accessed on [DATE] from [Colleges & Universities 2000 web address].

F. Business and Political Elites Database, 2014-15

Data includes information on the educational backgrounds, ages, genders, racial-ethnic backgrounds, and nationality of nearly 4,000 senior executives in 15 industrial sectors, including top-level elected and appointed officials in federal and state governments.  Data collected from multiple sources by Steven Brint, Sarah R.K. Yoshikawa, and Cynthia E. Carr.  Citation: Steven Brint, Sarah R.K. Yoshikawa, and Cynthia E. Carr. 2015. Business and Political Elites Database.  Riverside: University of California, Riverside