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International Handbook on the Economics of Education

Edited by Geraint Johnes and Jill Johnes

This major Handbook comprehensively surveys the rapidly growing field of the economics of education. It is unique in that it comprises original contributions on an exceptional range of topics from a review of human capital, signalling and screening models, to consideration of issues such as educational externalities and economic growth, funding models, determinants of educational success, the educational production function, educational standards and efficiency measurement. Labour market issues such as the market for teachers and the transition of students from school to work are also explored.
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Chapter 2: Signalling and Screening

Sarah Brown and John G. Sessions


Sarah Brown and John G. Sessions 1 Introduction The relationship between education and earnings has long intrigued economists and in recent years two contrasting views have emerged. The theory of human capital holds that education directly augments individual productivity and, therefore, earnings (Schultz, 1961; Mincer, 1974; Becker, 1975). By forgoing current earnings and acquiring, or more precisely, investing in, education, individuals can improve the quality of their labour services in such a way as to raise their future market value. Human capital, according to this view, is akin to physical capital, the acquisition of which entails a present cost but a future benefit. Thus education may be regarded as an investment good, and should be acquired until the point at which the marginal productivity gain equals the marginal opportunity cost. There is, however, an alternative line of thought. The ‘sorting’ hypothesis attests that education also ‘signals’ or ‘screens’ intrinsic productivity (Spence, 1973; Arrow, 1973; Stiglitz, 1975).1 Higher levels of education are associated with higher earnings, not because they raise productivity, but because they certify that the worker is a good bet for smart work. The intuition for this is straightforward. Educated workers are not a random sample. They tend, for example, to have lower propensities to quit or to be absent. They are also less likely to smoke, to drink or to use illicit drugs. Such attributes are attractive to firms, but are not readily observed at the time of hiring. It could be the case, then, that...

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