The Gender Wage Gap: Extent, Trends, and Explanations

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The Gender Wage Gap: Extent, Trends, and Explanations Abstract Using PSID microdata over the 1980-2010, we provide new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably over this period. By 2010, conventional human capital variables taken together explained little of the gender wage gap, while gender differences in occupation and industry continued to be important. Moreover, the gender pay gap declined much more slowly at the top of the wage distribution that at the middle or the bottom and by 2010 was noticeably higher at the top. We then survey the literature to identify what has been learned about the explanations for the gap. We conclude that many of the traditional explanations continue to have salience. Although human capital factors are now relatively unimportant in the aggregate, women's work force interruptions and shorter hours remain significant in high skilled occupations, possibly due to compensating differentials. Gender differences in occupations and industries, as well as differences in gender roles and the gender division of labor remain important, and research based on experimental evidence strongly suggests that discrimination cannot be discounted. Psychological attributes or noncognitive skills comprise one of the newer explanations for gender differences in outcomes. Our effort to assess the quantitative evidence on the importance of these factors suggests that they account for a small to moderate portion of the gender pay gap, considerably smaller than say occupation and industry effects, though they appear to modestly contribute to these differences. JEL-codes: J160, J240, J310, J710. Terms of use: Documents in

The Gender Wage Gap Among College Graduates in Italy

“…In most cases, non-working people would like to continue studying or are doing some form of paid training, and this is true for both men and women, with few differences (Table 1). Moreover, the usual variables included as exclusion restrictions 9 in the Heckman procedure, such as children or non-labour income, could be argued to directly affect wages, and also alternative methodologies have been questioned (see Blau and Kahn 2017). In addition, such exclusion restrictions are even less suited to address selection bias issue among college graduates.…”

“…Moreover, women tend to lag particularly in Science, Technology, Engineering and Mathematics (STEM), while the gap narrowed in Biological and Natural sciences. The sorting of women in some majors is highly interconnected with their absence from the most profitable professions (Flabbi 2011;Blau and Kahn 2017), and thus considered among the causes of the persistent gender wage gap.…”

“…Among others, one of the main causes of the gender wage gap is considered the male-female sorting into different sectors and occupations: according to Blau and Kahn (2017), the Duncan and Duncan (1955) segregation index for the US declined from 1970, but in 2009 was still 51%. Moreover, the index has declined at a diminished pace in recent years.…”

How Uncertainty and Ambiguity in Tournaments Affect Gender Differences in Competitive Behavior

“…Despite large improvements over the past decades, there are still large gender differences with respect to wages and promotion opportunities, especially with respect to the fraction of women in high level executive positions and at high income levels (Weichselbaumer and WinterEbmer, 2007;Blau and Kahn, 2017). For instance, at the beginning of 2017, women accounted for less than 6% of CEOs within the S&P 500 and the Fortune 500.1 Although some of these differences can be explained by sorting effects, there is still a persistent gender gap in firm-specific pay (Card et al, 2016) and the gender pay gap remains even after parenting and family concerns are taken into account (Angelov et al, 2016).…”

Social-Institutional Structures That Matter: A Quantitative Monograph of Sexual/Gender Minority Status and Earnings in Japan

“…However, studies on gender inequality in Western countries tend not to focus on the gender wage gap within an organization, due to the low contribution of within-job gender differences in earnings (Kim and Shirahase 2014). Instead, these studies have focused more on occupational gender segregation to claim that occupational segregation is among the most important determinants of the gender wage gap (Blau and Kahn 2017). The results above, however, highlight the importance of employment status in contributing to gender pay gap in Japan (Chang and England 2011).…”