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Cited by 613

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Traditional Institutions Meet the Modern World: Caste, Gender, and Schooling Choice in a Globalizing Economy

Munshi, Kaivan, Rosenzweig, Mark·2006·American Economic Review

Abstract

This paper addresses the question of how traditional institutions interact with the forces of globalization to shape the economic mobility and welfare of particular groups of individuals in the new economy. We explore the role of one such traditional institution—the caste system—in shaping career choices by gender in Bombay using new survey data on school enrollment and income over the past 20 years. We find that male working-class—lower-caste—networks continue to channel boys into local language schools that lead to the traditional occupation, despite the fact that returns to nontraditional white-collar occupations rose substantially in the 1990s, suggesting the possibility of a dynamic inefficiency. In contrast, lower-caste girls, who historically had low labor market participation rates and so did not benefit from the network, are taking full advantage of the opportunities that became available in the new economy by switching rapidly to English schools.

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Metadata

Authors
Munshi, K., & Rosenzweig, M.
Venue
American Economic Review
Published
2006-09-01
Volume
96
Issue
4
Pages
1225-1252
ISSN
0002-8282 (ISSN-L)
OpenAlex
W2094095348
Cited by
613
References
2
FWCI
81.85
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Traditional Institutions Meet the Modern World: Caste, Gender, and Schooling Choice in a Globalizing Economy. https://app.cochat.ai/papers/10.1257/aer.96.4.1225
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Munshi, K., & Rosenzweig, M. (2006). Traditional Institutions Meet the Modern World: Caste, Gender, and Schooling Choice in a Globalizing Economy. American Economic Review. https://doi.org/10.1257/aer.96.4.1225

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.