Gender Gaps in the Labor Market and Economic Growth

Abstract

This paper studies the effects of policies aimed at mitigating discrimination against women in the marketplace on the gender wage gap, decisions to invest in skills, the composition of employment and unemployment, and long-run growth. The analysis uses a gender-based overlapping generations model with labor market rigidities. Gender bias in the workplace varies inversely with the presence of skilled women (as agents of change) in the labor market and has a direct impact on their bargaining power in the family. The model is calibrated for Morocco. Experiments show that although the benefits of policies aimed at mitigating gender bias in the workplace can promote growth and be significantly magnified through a stronger presence of skilled women in the labor market, a trade-off may emerge with respect to female unemployment when anti-discrimination policies are combined with policies aimed at subsidizing women's training. To internalize this trade-off, anti-discrimination policies in the marketplace may need to be complemented by measures aimed at reducing labor costs and raising productivity.

Are Human and Social Capital Linked? Evidence from India

“…The elasticity with respect to effective labor, is the same value that has been used in Agénor (), whereas the elasticity with respect to private capital, is consistent with the value used in Agénor and Alpaslan ().…”

Morocco's Growth and Employment Prospects: Public Policies to Avoid the Middle-Income Trap

“…One sensible way to address this issue is to view the results presented here as providing a lower bound, and determine whether, and how, to account for the growth and employment effects of these other policies. In the case of Morocco, it is the case that some recent modeling work on gender and growth is available, by Agénor et al (2017Agénor et al ( , 2018. These gender-based models have a very different structure than the model used in this paper (most notably by accounting explicitly for the time allocation of men and women), so one needs to be careful in evaluating their policy effects; in particular, one cannot simply "add up" the results.…”

“…We use primarily a version of the model developed by Agénor and El Aynaoui (2016) to assess alternative reform programs, for a set of public policies consistent with some of the key recommendations that form part of the proposed growth model. However, that model does not have a gender dimension; we therefore supplement estimates regarding growth and unemployment with the core predictions of two other contributions, by Agénor et al (2017Agénor et al ( , 2018 which have an explicit gender dimension and focus on policy measures aimed at promoting women's participation in the labor market and reducing unemployment across the board. In reality, of course, one cannot simply add predictions from two separate sets of models; doing so would not do full justice to the interactions that can occur in assessing the effects of reform programs on growth and unemployment.…”

“…They argue, in particular, that the slow pace of structural transformation has not allowed sufficient creation of manufacturing jobs where women with a secondary school education could be employed. 1 Another perspective is offered by Agénor et al (2018). They view women's decision to participate in the labor market essentially as a dichotomous, all-or-nothing choice in the presence of social norms that compel women to devote a significant share of their daily time to household chores and child rearing.…”

Charting a Pathway to Multisectoral Investments in Adolescent Health in Low- and Middle-Income Countries

“…In contrast, Symons et al note that the disproportionate mortality and disability rates from road accidents are a health risk largely for boys. Since most of the interventions to address this risk are related to mobility, transportation, and infrastructure, future analyses might benefit from undertaking a more comprehensive view of transportation-related health risks for adolescents, including, for example, the risk of sexual violence faced by girls due to poor or nonfemale friendly road and transportation infrastructure or their limited use of health services due to restricted mobility and transportation access [16].…”