Chapter 28 reviews in detail how economists study the supply and demand for academic labor, presents a model of the factors that enter into academic salaries, and – because academic labor markets differ considerably across countries and these differences produce very different conditions in the way academic staff are hired and promoted – the review includes international aspects of faculty labor markets. The chapter also reviews studies that attempt to explain the factors that predict academic salaries in the United States, notably research productivity and teaching, the relation of those salaries to types of higher education institutions, and gender differences in academic pay, both in the United States and internationally. The chapter then analyzes various types of student admission systems across countries, including economic models of the higher education market for high- and low-ability students, and how students make choices among higher education institutions. The chapter ends with a discussion of affirmative action in the United States and the major affirmative action programs in India and Brazil.

Chapter 27 analyzes how economists and other social scientists have approached estimating the outputs of higher education, and – to the limited extent possible given available research – estimated how various inputs are used to produce these outputs. The chapter reviews two distinct types of approaches: (1) those that correspond to the production function analysis presented in Chapters 11 and 12 – that is, attempts to estimate the factors that affect, in the case of knowledge transfer, the value added of achievement (or earnings) and, in the case of knowledge production, affect some measure of research output; and (2) those approaches that attempt to estimate cost functions in terms of various higher education outputs – that is, total cost as a function of teaching, research, and social services. The chapter assesses a number of studies in various countries that have attempted to measure student gains in achievement and earnings across programs of study. It also reviews several US studies of retention/graduation rates and research output, as well as a case study of varying production functions across higher education programs in Morocco.

This chapter develops the economics theory of demonstration projects and then investigates the role of one demonstration project – the Kendeda Building for Innovative Sustainable Design – at lowering information barriers for the adoption of innovative energy and environmental technologies. The KBISD demonstration project allows us to observe the formation of a network around a demonstration project and how attitudes and behaviors relating to environmental technologies permeate and disseminate throughout the network. This section presents results from an industry-wide survey as well as several dozen semi-structured interviews related to the KBISD. The interviews reveal motivations, challenges, innovations, costs, and risks associated with participation in a demonstration project, as well as key differences between this living building approach and design–bid–build approaches often employed in traditional buildings.It finds that, while working on the building was not affiliated with increased levels of technology familiarity prior to building construction, being affiliated with the US Green Building Council is highly correlated with increased knowledge of emergent technologies. This points to professional knowledge networks as having a key role in disseminating information regarding emergent technologies.

This chapter develops a theory to explain how demonstration projects can help facilitate transformation in the marketplace. This theory is based primarily on a single economic concept: The costs of acquiring and utilizing new information. Understanding the role that pilot and demonstration projects can play in disseminating information is crucial to understanding the prospects for market transformation. These information flows occur both on the supply side and demand side of the (building) technologies market. This chapter details how information flows across supply networks and throughout markets can eventually shift standard operating practices, though these results are hardly guaranteed. We speculate that geographic networks and communities of practice are largely responsible for leveraging information spillovers, lowering costs, and facilitating dissemination of innovative technologies.