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Does Militarization Hinder Female Labor Income Share?

  • Adem Yavuz Elveren ORCID logo EMAIL logo
Veröffentlicht/Copyright: 19. Dezember 2023

Abstract

This study addresses the underexplored dimension of the relationship between military expenditures and gender inequality, drawing upon the insights of feminist security and international relations scholars. The influence of militarization on gender inequality is profound, manifesting itself significantly in both conflict and peacetime situations. The destruction of essential infrastructure further restricts women’s access to vital resources. In peacetime, the convergence of militarization and patriarchy reinforces women’s secondary roles in society, while higher military expenditures can divert resources from social spending, disproportionately affecting women and children reliant on public services. Despite extensive theoretical discussions, empirical studies on this nexus are limited. This paper contributes by presenting original evidence using a comprehensive dataset spanning 1991–2019, examining the Female Labor Income Share across over 100 countries. Findings reveal that militarization correlates with reduced the Female Labor Income Share, underscoring the urgency of addressing this critical linkage between militarization and gender inequality.

JEL Classification: C23; B54; H56

Corresponding author: Adem Yavuz Elveren, American University in Bulgaria, Blagoevgrad, Bulgaria; and Izmir University of Economics, Izmir, Türkiye, E-mail:

Appendix: List of Countries

Low-income group (n = 6): Burkina Faso, Chad, Mozambique, Rwanda, Sierra Leone, Sudan*

Low-middle income group (n = 26): Angola, Bangladesh, Bolivia, Cabo Verde*, Cambodia, Cameroon, Egypt*, India, Indonesia, Iran*, Kenya, Kyrgyzstan*, Lesotho, Mauritania, Mongolia, Morocco, Nicaragua*, Nigeria, Philippines, Senegal, Sri Lanka, Tajikistan, Tanzania, Tunisia, Ukraine, Zimbabwe.

Upper-middle income group (n = 29): Argentina, Armenia, Azerbaijan, Belarus, Botswana, Brazil, Bulgaria, China, Colombia, Dominican Republic, Ecuador, Fiji, Guatemala, Jamaica, Jordan, Kazakhstan, Lebanon*, Malaysia, Mauritius, Mexico, Moldova, Namibia, Paraguay, Peru, Romania, Russian Federation*, South Africa, Thailand, Türkiye.

High-income group (n = 42): Australia, Austria, Bahrain, Belgium, Canada, Chile, Croatia, Cyprus, Czech Republic*, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Japan, South Korea*, Kuwait, Latvia, Lithuania, Luxembourg, Malta*, Netherlands, New Zealand, Norway, Oman, Poland, Portugal, Saudi Arabia, Singapore, Slovakia*, Slovenia, Spain, Sweden, Switzerland, UK, US, Uruguay.

Table A1:

Coefficients of various democracy variables.

Variables Low* Middle High
Polity2 0.019 0.060*** 0.018**
(0.019) (0.021) (0.008)
Polyarchy 0.020*** 0.014** 0.056***
(0.003) (0.006) (0.004)
Libdem 0.022*** 0.021*** 0.049***
(0.005) (0.007) (0.003)
Partipdem 0.025*** 0.004 0.054***
(0.005) (0.014) (0.004)
Delibdem 0.013** 0.015* 0.032***
(0.005) (0.008) (0.003)
Egaldem 0.029*** 0.012 0.058***
(0.008) (0.014) (0.004)
Empower 0.019*** −0.011 0.009***
(0.003) (0.016) (0.002)
  1. Coefficients are taken from standard GMM estimations to save space. All estimations were conducted with two-step efficient GMM and small sample corrections to the covariance matrix estimate. Standard errors in parentheses ***p < 0.01, **p < 0.05, *p < 0.10. Low* includes low-income and low-middle-income countries.

*Not included in GMM analysis due to nonavailability of data.

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Received: 2023-09-30
Accepted: 2023-11-29
Published Online: 2023-12-19

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 24.10.2025 von https://www.degruyterbrill.com/document/doi/10.1515/peps-2023-0057/pdf
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