nep-gen New Economics Papers
on Gender
Issue of 2017‒08‒13
six papers chosen by
Jan Sauermann
Stockholms universitet

  1. Gender score gaps of Colombia students in pisa test By Luz Karime Abadía Alvarado
  2. Women, Work, and Family By Francine D. Blau; Anne E. Winkler
  3. Gender wage gap and the role of skills: evidence from PIAAC dataset By Christl, Michael; Köppl-Turyna, Monika
  4. Do Females Always Generate Small Bubbles? Experimental Evidence from U.S. and China By Jianxin Wang; Daniel Houser; Hui Xu
  5. Detection and Prediction of Gender-Based Differential Item Functioning using the MIMIC Model By Kevin Krost; Joshua Cohen
  6. Bibliometrics vs. Diversity in the Top Academic Career Positions in Economics in Italy By Marcella Corsi; Carlo D’Ippoliti; Giulia Zacchia

  1. By: Luz Karime Abadía Alvarado
    Abstract: Abstract This paper measures the math and reading gender score gap of Colombian students in the Pisa test. Estimations confirm that on average, when comparing boys and girls with similar individual, family and school characteristics boys outperform girls in math and the opposite happens in reading. Moreover, using Blinder-Oaxaca decomposition I find that observables favor girls and account for the 22% and 34% of the gap in math and reading respectively. This effect is due mainly to individual factors, that is, if girls were not in a greater proportion in the last scholar grades of secondary education and they had not a lower repetition grade in comparison with boys, the gap would be greater in math and lower in reading. ****** Resumen Este trabajo mide la brecha de género académica en matemáticas y lectura de los estudiantes colombianos en las pruebas PISA. Los resultados de las estimaciones confirman que, en promedio, cuando se compararan niños y niñas con similares características individuales, familiares y escolares los niños obtienen mejores puntajes que las niñas en matemáticas y lo contrario sucede en lectura. Adicionalmente, usando la descomposición de Blinder-Oaxaca se encuentra que las características observables favorecen a las niñas y éstas explican el 22% y el 34% de la brecha en matemáticas y lectura respectivamente. Este efecto se debe principalmente a las características individuales, es decir, si las niñas no estuvieran en mayor proporción en los últimos grados del bachillerato y adicionalmente si ellas no tuvieran una menor tasa de repitencia escolar en comparación con los niños, la brecha en matemáticas sería mayor y la de lenguaje menor.
    Keywords: PISA, gender score gap, performance, math, reading, inequality****** PISA, brecha de género escolar, desempeño, matemáticas, lectura, desigualdad.
    JEL: I21 I24 J16 O15
    Date: 2017–04–27
  2. By: Francine D. Blau; Anne E. Winkler
    Abstract: This chapter focuses on women, work, and family, with a particular focus on differences by educational attainment. First, we review long-term trends regarding family structure, participation in the labor market, and time spent in household production, including time with children. In looking at family, we focus on mothers with children. Next we examine key challenges faced by mothers as they seek to combine motherhood and paid work: workforce interruptions associated with childbearing, the impact of home and family responsibilities, and constraints posed by workplace culture. We also consider the role that gendered norms play in shaping outcomes for mothers. We conclude by discussing policies that have the potential to increase gender equality in the workplace and mitigate the considerable conflicts faced by many women as they seek to balance work and family.
    JEL: J1 J12 J13 J16 J22
    Date: 2017–08
  3. By: Christl, Michael; Köppl-Turyna, Monika
    Abstract: Our paper makes a first attempt to address the impact of skills and skill use in the analysis of the gender wage gap using the PIAAC dataset. Using the case of Austria, we show that skill use as well as the skill match play an important role with regard to wage regressions of men as well as women. When we take skills into account in the gender wage gap analysis, the unexplained part of the gender wage gap is reduced by almost 4 percentage points along the whole wage distribution. Our results suggest that skill use and match play a crucial role in explaining the gender wage gap. Additionally, we show, that the self-selection problem biases the results, in particular in the lower and middle parts of the wage distribution and that we should control for it, although the effect is small. When we additionally consider discretionary bonus payments, we find that the unexplained part in the gender wage gap increases, especially in the upper part of the wage distribution.
    Keywords: gender wage gap,skills,Austria
    JEL: J31 J71
    Date: 2017
  4. By: Jianxin Wang (School of Business, Central South University); Daniel Houser (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University); Hui Xu (Department of Economics, Beijing Normal University)
    Abstract: Is it universal across cultures that females generate smaller bubbles than males? We conduct classic bubble experiments in China and the U.S. using groups of exclusively females, exclusively males and mixed gender participants. We find that female groups in China generate a similar level of bubbles as found in exclusively males groups in China and the U.S., which in turn is significantly larger than bubbles generated by exclusively female groups in the U.S. Our results imply that gender differences in financial markets may be sensitive to culture.
    Keywords: gender differences, bubbles, experimental asset markets, culture differences
    JEL: G01 G11 J16 Z13
    Date: 2017–07
  5. By: Kevin Krost (Virginia Tech); Joshua Cohen (Virginia Tech)
    Abstract: There has been extensive research indicating gender-based differences among STEM subjects, particularly mathematics (Albano & Rodriguez, 2013; Lane, Wang, & Magone, 1996). Similarly, gender-based differential item functioning (DIF) has been researched due to the disadvantages females face in STEM subjects when compared to their male counterparts. Given that, this study will apply the multiple indicators multiple causes (MIMIC) model, a type of structural equation model, to detect the presence of gender-based DIF using the Program for International Student Assessment (PISA) mathematics data from students in the United States of America then predict the DIF using math-related covariates. This study will build upon a previous study which explored the same data using the hierarchical generalized linear model and will be confirmatory in nature. Based on the results of the previous study, it is expected that several items will exhibit DIF which disadvantages females, and that mathematics-based self-efficacy will predict the DIF. However, additional covariates will also be explored and the two models will be compared in terms of their DIF-detection and the subsequent modeling of DIF. Implications of these results include females under-achieving when compared to their male counterparts, thus continuing the current trend. These gender differences can further manifest at the national level, causing US students as a whole to under-perform at the international level. Last, the efficacy of the MIMIC model to detect and predict DIF will be illustrated and become increasingly used to model and better understand differences and DIF.
    Date: 2017–08–10
  6. By: Marcella Corsi; Carlo D’Ippoliti; Giulia Zacchia
    Abstract: Following an international trend, Italy has reformed its university system, especially concerning methods and tools for research evaluation, which are increasingly focused on a number of bibliometric indexes. To study the impact of these changes, we analyse the changing profiles of economists who have won competitions for full professorship in the last few decades in Italy. We concentrate on individual characteristics and mainly on scientific production. We show that the identification of a univocal and standardized concept of “research quality” within the new research assessments has progressively imposed a strategy of “homologation”, especially for women. We find that women economists are at a higher risk of discrimination than their male colleagues and thus they are more likely to conform their research activities to the standardized profile imposed by the gender-blind application of biased bibliometric methods.
    Keywords: Discrimination; Pluralism; Diversity; Women Economists; Italy
    JEL: J16 J70 A14
    Date: 2017–08–07

This nep-gen issue is ©2017 by Jan Sauermann. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.