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A CLASSICAL MODEL OF EDUCATION, GROWTH, AND DISTRIBUTION

Published online by Cambridge University Press:  05 November 2018

Amitava Krishna Dutt and
Roberto Veneziani
Amitava Krishna Dutt
Affiliation:
University of Notre Dame and FLACSO-Ecuador
Roberto Veneziani*
Affiliation:
Queen Mary University of London
*
Address correspondence to: Roberto Veneziani, School of Economics and Finance, Queen Mary University of London, Mile End Road, London E1 4NS, United Kingdom; e-mail: r.veneziani@qmul.ac.uk
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Abstract

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We develop a classical macroeconomic model to examine the growth and distributional consequences of education. Contrary to the received wisdom, we show that human capital accumulation is not necessarily growth-inducing and inequality-reducing. Expansive education policies may foster growth and reduce earning inequalities between workers, but only by transferring income from workers to capitalists. Further, the overall effect of an increase in education depends on the actual characteristics of the educational system and on the nature of labor market relations. Although the primary aim of the paper is theoretical, we argue that the model identifies some causal mechanisms that can contribute to shed light on recent stylized facts on growth, distribution, and education for the USA.

Keywords

EducationGrowthDistribution

Information

Type
Articles
Information
Macroeconomic Dynamics , Volume 24 , Issue 5 , July 2020, pp. 1186 - 1221
Copyright
© Cambridge University Press 2018

Footnotes

Special thanks go to Peter Skott, Luca Zamparelli, and two anonymous referees for detailed and perceptive comments. We are grateful to Richard Arena, Philip Arestis, Deepankar Basu, Riccardo Bellofiore, Laura Carvalho, Meghnad Desai, Gerald Epstein, Giulio Fella, Peter Flaschel, John King, Gilberto Lima, Neri Salvadori, Rajiv Sethi, Engelbert Stockhammer, Daniele Tavani, Alessandro Vercelli, and audiences in London, Paris, Bristol, New York, Berlin, Kingston, and Washington for comments and suggestions. We also thank Kurt von Seekam for excellent research assistance. Roberto Veneziani worked on this project while visiting the University of Massachusetts, Amherst. Their hospitality and support are gratefully acknowledged. The usual disclaimer applies.

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