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Can institutions or education explain world poverty? An augmented Solow model provides some insights

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  • Breton, Theodore R.

Abstract

This article presents revised estimates of the external rates of return on investment in schooling provided in “Schooling and National Income: How Large Are the Externalities?” The analysis is based on data for the same set of countries, but it incorporates methodological improvements that yield lower estimates of these rates. The revised marginal external rates of return range from four percent in the highest-income countries to about 35 percent in the lowest-income countries. These rates are about half the private rates of return in high-income countries and about double the private rates in the lowest-income countries.
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  • Breton, Theodore R., 2004. "Can institutions or education explain world poverty? An augmented Solow model provides some insights," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(1), pages 45-69, March.
    • Handle: RePEc:eee:soceco:v:33:y:2004:i:1:p:45-69
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    Cited by:

    1. Andrés Rodríguez-Pose & Tobias Ketterer, 2020. "Institutional change and the development of lagging regions in Europe," Regional Studies, Taylor & Francis Journals, vol. 54(7), pages 974-986, July.
    2. Steve Loris Gui-Diby & Saskia Mösle, 2017. "Governance and development outcomes: re-assessing the two-way causality," MPDD Working Paper Series WP/17/09, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP).
    3. Cuong Le Van & Mathilde Maurel, 2006. "Education, corruption and growth in developing countries," Post-Print halshs-00129754, HAL.
    4. Tebaldi, Edinaldo & Mohan, Ramesh, 2008. "Poverty, Geography and Institutional Path Dependence," MPRA Paper 10201, University Library of Munich, Germany.
    5. Somlanaré Romuald Kinda, 2009. "Convergence des émissions par tête de dioxyde de carbone : Le rôle de l'éducation," Post-Print hal-00692146, HAL.
    6. José Aixalá & Gema Fabro, 2007. "A Model Of Growth Augmented With Institutions," Economic Affairs, Wiley Blackwell, vol. 27(3), pages 71-74, September.
    7. Hazal Colak Oz & Çiçek Güven & Gonzalo Nápoles, 2023. "School dropout prediction and feature importance exploration in Malawi using household panel data: machine learning approach," Journal of Computational Social Science, Springer, vol. 6(1), pages 245-287, April.
    8. Polimeni, John M. & Iorgulescu Polimeni, Raluca & Trees, W. Scott, 2007. "Extending The Augmented Solow Growth Model To Explain Transitional Economies," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(1), pages 65-76, March.
    9. Boyan Zhang & Mingming Wang, 2021. "How Will the Improvements of Electricity Supply Quality in Poor Regions Reduce the Regional Economic Gaps? A Case Study of China," Energies, MDPI, vol. 14(12), pages 1-18, June.

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    More about this item

    JEL classification:

    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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