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on Central and South America |
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Issue of 2023‒11‒20
three papers chosen by |
| By: | Mariana Marchionni (CEDLAS-IIE-FCE-UNLP & CONICET); Julián Pedrazzi (CEDLAS-IIE-FCE-UNLP & CONICET) |
| Abstract: | We assess whether motherhood could be the last hurdle to achieving gender equality in developing countries by exploring the link between motherhood and the overall gender gap in the labor market for 14 Latin American countries over the last two decades. Using pseudo- panels built from harmonized household surveys and an event study approach around the birth of the first child, we find that the arrival of the first child leads to a sharp and persistent 35% decline in mothers’ earnings. This result is explained by a reduction in employment and a prompting shift towards occupations that favor more flexible work arrangements, including part-time and informal jobs. These effects are pervasive across countries and population groups. Furthermore, using an extended version of the Oaxaca-Blinder decomposition, we identify motherhood as the primary source of income inequality between men and women. Motherhood explains 42% of the remaining gender gap and has progressively gained relative importance over the last two decades while other contributing factors, such as education and its associated returns, have shown a waning impact. Moreover, we find no clear cross- country association between the motherhood-related gap and per capita GDP or gender norms, while the contribution of other factors to the gender gap in earnings diminishes with higher per capita GDP and more gender-egalitarian social norms. This suggests that gender gaps stemming from the motherhood effect exhibit greater rigidity than other drivers of gender inequality. |
| JEL: | D63 J13 J16 J22 J31 |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:dls:wpaper:0321&r=lam |
| By: | Esteve, Albert; Becca, Federica; Castro, Andrés |
| Abstract: | This chapter provides an account of the major family transformations that occurred in recent decades across Latin American and Caribbean countries and examines the implications of such transformations for children’s school attendance and progress and women’s labor force participation. Latin American and Caribbean families and households have undergone substantial changes in recent years while keeping some of their distinctive features unchanged (Esteve et al., 2022; Esteve & Florez-Paredes, 2018a; Juárez & Gayet, 2014). This combination of stability and change has had profound transformations in the family status in which women raise their children and the family context in which children are raised. We refer to family context as the combination of women`s marital status and the type of households in which children reside. We combine references to the literature and own calculations based on Latin American and Caribbean population census samples, available at the Integrated Public-use Microdata Series International (IPUMS) (Minnesota Population Center, 2020). We use data from 25 countries based on the most recent census microdata and, in some instances, historical samples starting in the late 1950s (see Appendix 1). |
| JEL: | N0 |
| Date: | 2023–10–16 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:120485&r=lam |
| By: | Carlo Pizzinelli; Augustus J Panton; Ms. Marina Mendes Tavares; Mauro Cazzaniga; Longji Li |
| Abstract: | This paper examines the impact of Artificial Intelligence (AI) on labor markets in both Advanced Economies (AEs) and Emerging Markets (EMs). We propose an extension to a standard measure of AI exposure, accounting for AI's potential as either a complement or a substitute for labor, where complementarity reflects lower risks of job displacement. We analyze worker-level microdata from 2 AEs (US and UK) and 4 EMs (Brazil, Colombia, India, and South Africa), revealing substantial variations in unadjusted AI exposure across countries. AEs face higher exposure than EMs due to a higher employment share in professional and managerial occupations. However, when accounting for potential complementarity, differences in exposure across countries are more muted. Within countries, common patterns emerge in AEs and EMs. Women and highly educated workers face greater occupational exposure to AI, at both high and low complementarity. Workers in the upper tail of the earnings distribution are more likely to be in occupations with high exposure but also high potential complementarity. |
| Keywords: | Artificial intelligence; Employment; Occupations; Emerging Markets |
| Date: | 2023–10–04 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2023/216&r=lam |