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Higher education researchers are often challenged by the difficulty of empirically validating causal links posited by theories or inferred from correlational observations. The instrumental variable (IV) estimation strategy is one approach that researchers can use to estimate the causal impact of various higher education-related interventions. In this chapter, we discuss how the body of quantitative research specifically devoted to higher education has made use of the IV estimation strategy: we describe how this estimation strategy was used to address causality concerns and provide examples of the types of IVs that were used in various subfields of higher education research. Our discussion is based on a systematic review of a corpus of econometric studies on higher education-related issues that spans the last 30 years. The chapter concludes with a critical discussion of the use of IVs in quantitative higher education research and a discussion of good practices when using an IV estimation strategy.

This article adds a political perspective to the phenomenon of higher education de-differentiation, by building on Gary Rhoades’ neo-institutionalist account. Diversity is operationalized on a hallmark dimension for Central and Eastern Europe: the public–private divide. Higher education is conceived of as a structured organizational field and its institutionalization in Central and Eastern Europe is surveyed in a comparative approach, focusing on the institutions governing the competition for (tuition paying) students and the normative images of higher education (accreditation, quality assurance, classifications and rankings). Critical junctures are identified in regard to the structuration and re-structuration of higher education in Romania, and the agency of the ministers is traced in relation to their academic background. The article builds on evidence from studies of system-level diversity or differentiation in higher education, the structuration of higher education as an organizational field, and the more recent empirical accounts on the impact of the agency of academics in policy formulation in Central and Eastern Europe (especially those in office as ministers of education).

The chapter sets out to answer a question that has long been on the mind of policy-makers, university leaders, scholars and students: does international student credit mobility have a positive impact on graduate employability? Traditionally, this question has been answered using survey data where internationally mobile students self-report their employment situation at a certain point after graduation. According to these studies, international student mobility positively affects the labour market outcomes of students. For instance, the European Commission reports that: (1) students who completed an Erasmus mobility program are half as likely to face long-term unemployment; (2) the unemployment rate of Erasmus students is 23% lower five years after graduation (European Commission 2014). While these studies provide important insights about the benefits associated with the cross-border credit mobility of students, the results can be plagued by self-selection bias in reporting post-mobility employment outcomes. In order to avoid the problems associated with survey data, in this chapter we offer an analysis based on register data from university records and employment records, using as a case study the West University of Timisoara, a leading comprehensive university in Romania. Using register data offers the possibility to study population-level data and compare the employment outcomes of mobile and non-mobile students. The chapter analyses the impact of credit mobility on insertion in the labour market, income levels and occupational prestige. While the research question that the chapter is trying to answer is important, the main message of the chapter is broader: ministries and higher education institutions should release data for research purposes. Register data is readily available and helps researchers make efficient use of resources. In turn, this can encourage evidence-based policymaking.