Màster Oficial - Economia Laboral / Labour Economics

URI permanent per a aquesta col·leccióhttps://hdl.handle.net/2445/180458

Treballs Finals del Màster d'Economia Laboral / Labour Economics de la Facultat d'Economia i Empresa de la Universitat de Barcelona.

Estadístiques

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Mostrant 1 - 5 de 5

Grasping Wage Bargaining Power: trends, gaps and drivers
(2022) Quispe Contreras, Sergio-Martín; Sala Lorda, Hèctor
To measure the productivity-wage gap correctly, I depart from the basic Insider-Outsider model and extend it to encompass a Wage Bargaining Power Index, which is fundamental for understanding labour markets. This index takes the value of 0 if workers are paid as little as possible and takes the value of 1 if they are paid the value they generate. In the first part, I find an index for Peruvian labour market which move around 0.26 in the period 2007-2019. Additionally, there is a clear gender gap, which favors men, who have an index ranging from 0.25 to 0.31, while the index for women fluctuates between 0.21 and 0.25. In the second part, I explore the main drivers and I find, in general, some positive effects on education and fixed-term contracts, and negative effects of being women, non-white, working in a small-enterprise, violation of labour rights, the job search rate and tax revenues paid. By gender, I find that while men are disadvantaged by their class status and race, education and fixed-term contracts empower women's wage bargaining power. However, working in a small business and the job search rate have a greater negative effect on women than on men.
The impact of births on single parent’s earnings: Evidence from Spain
(2022) Carralero de las Heras, Natalia; Ayllón, Sara
Taking an event study approach with data from the 2019 Continuous Sample of Working Histories, I study the impact of having a child on single parent’s annual earnings. The main finding is that, although these individuals do not have a partner whom they can share responsibilities with, after the birth of the first child, women’s annual earnings fall, while men’s are unaffected, same as what the literature had found for families with both parents. When the analysis is split by educational level, I find that the birth of the first child has no statistically significant effect on annual earnings of college-educated single-mothers, while it has a negative impact for non-college-educated single mothers. The picture is the opposite for single fathers: annual earnings of highly-educated single fathers are negatively affected by the birth of their first child.
Educational Segregation in STEM/Non-STEM Fields and Wage Gender Gap: Evidence from the U.S.A.
(2022) Yang, Rui; Ruiz-Valenzuela, Jenifer
This paper uses the 2018–2020 U.S. Census and American Community Survey microdata to examine the extent to which gender differences in graduates' choice of degree fields - STEM or Non-STEM contribute to the gender pay gap in the United States. With the Blinder-Oaxaca wage decomposition method, this paper finds that among the highly-educated labor force in the U.S. for the period 2018-2020, the individual background characteristics (race, region), family characteristics (marital status, number of children), education-related characteristics (degree fields, the highest educational attainment, and school type), and job-related characteristics (hours worked, work experience, job sector, and occupation type) combined can explain 55.96% of the gender pay gap. Among them, whether an individual chooses a college major related to a STEM field (ie. whether or not to obtain a degree in a STEM field) contributes 2.4%-5.2% of the "explanatory part", and can only explain 1.35%-2.91% of the gender pay gap. Finally, the results of this study showed that, although the content of the field of study (STEM/Non-STEM) seems not to explain too much of the current gender wage gap in the U.S. highly-educated workforce, it is hard to deny that educational segregation is still a barrier to gender equality. In addition, this paper also found that the gender pay gap for STEM graduates is 3.77% smaller than the gender pay gap for Non-STEM graduates. What's more, the choice of degree subjects can explain 9.91% of the gender gap for STEM graduate samples.
The effects of technological change on labor markets: College wage premium in Europe
(2021) Sánchez Daniel, Ángel; Jerbashian, Vahagn
Technology has affected the demand for skills and disrupted labor markets . In particular, the evidence suggests that technological change has led to job polarization by increasing the demand for high- and low-wage occupations at the expense of medium-wage occupations. This thesis builds on the hypothesis that different types of technologies can affect the evolution of skill premium differently. More specifically, it explores the effects of different types of technological capital on skill premium in 17 European countries from 2008 to 2017. Research on this topic is less abundant in Europe than in the US and usually utilizes older databases. The contribution of this study is the analysis of the skill premium with updated information and various types of technological capital. The results show that intangible assets have positive and statistically significant effect on skill premium. IT complements high-educated workers in retail, transportation, construction and health industries and CT substitutes high-educated workers in transportation, construction and in public administration industries. Moreover, this thesis explores a comparison of these with previous literature and presents an explanation for the differences and similarities with the results.
The impact of stay-at-home orders on mental health: Evidence from search-based symptoms
(2021) Brugarolas, Pablo; Ayllón, Sara
I investigate the impact of the implementation of stay-at-home orders on the incidence of mental health conditions in the US during the first year of the coronavirus pandemic. I use a novel dataset that maps search queries to thirty mental health symptoms. Exploiting the staggered implementation of lockdowns, I document that the enaction of the stay-at-home orders increased mental health searches related to various anxiety disorders, severe forms of depression, sleep disorders, attention de cit, and epilepsy. Treated states are estimated to have experienced two mental distress waves in April-May and November-December

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