Project 2.1

Higher education participation and macro-economic fluctuations: a historical and comparative study

Project methods

The research will consist of two distinct and complementary strands.

Strand 1: The qualification dataset

The first strand of the project will create a new dataset on higher education qualifications gathering historical statistics on the numbers of degrees and diplomas awarded and their distribution according to gender, levels, grades and disciplines. This focus on the formal qualification will complement our quantitative picture of higher education enrolment.

The series from the qualification dataset will be compared and contrasted to key data on funding and enrolment in higher education. They will then be matched with key historical socioeconomic data including GDP, productivity, labour market and datasets on inequality, taxation and public spending developed by Piketty (2014) and Lindert (2004).

Strand 2: The institutional dataset

The second strand of the project will develop a new dataset with original historical series on funding, enrolment and qualification of several representative higher education institutions or groups of institutions (for instance, old, civic and new universities in the UK; Grandes Ecoles and Universit├ęs in France; public, private and community colleges in the USA etc).

The institutional dataset will highlight specific or common evolutions of long-term funding and development of single institutions and evaluate the factors behind the differences to make comparisons and contrasts with earlier results on the whole higher education system.

The comparison of various time periods and countries raises obvious challenges. In order to mitigate these, the project will use the methodology of quantitative history which can be defined as a retrospective history ruled by the principles of national accounting principles.

Many existing data sources dating back to the 1920s have already been identified in all countries. They are in the public domain and available from key governmental departments and statistical agencies of the three countries (INSEE, HMSO, NCES).