• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

HSE Researchers Uncover Causes of Gender Pay Gap among Recent University Graduates in Russia

HSE Researchers Uncover Causes of Gender Pay Gap among Recent University Graduates in Russia

© iStock

A study conducted at HSE University shows that despite having the same education and similar starting conditions, the pay gap between male and female recent graduates can be as high as 22%. This is partly because female students often choose less lucrative fields and also because they tend to seek jobs in sectors that offer lower pay but are perceived to have more stable and safer working conditions.

The study included more than 400,000 early-career professionals and was based on data from the nationwide Monitoring Graduate Employment database, which contains details on graduates' education and subsequent employment. The study focuses on 2021 graduates and examines their career outcomes in 2022. The authors emphasise that this is not survey data, but an administrative dataset encompassing all graduates in the country.  

The researchers found that women with the same educational characteristics earn 22% less than their male counterparts a year and a half after graduation. 'This disparity is not related to their abilities but rather to systemic factors,' according to Natalya Yemelina, co-author of the study and Senior Research Fellow at the Laboratory for Labour Market Studies of the HSE Faculty of Economic Sciences.

One of these systemic factors is that many young women still predominantly choose 'female' fields of study in the humanities and social sciences, as well as careers in education and medicine, where salaries are traditionally lower than those in engineering or IT, which are more commonly chosen by men.

Thus, over 50% of male graduates have studied engineering and technology, while nearly half of female graduates have chosen economics, law, and social sciences, where the starting salaries for graduates are, on average, 30% lower than in technology-related occupations.

'Although an increasing number of women have been choosing technology-related fields in recent years, a significant portion still prefers areas where salaries are lower. This affects their starting employment and earnings,' according to Ksenia Rozhkova, co-author of the article and Junior Research Fellow at the Laboratory for Labour Market Studies of the Faculty of Economic Sciences.

Such educational segregation accounts for one-third of the explained pay gap. Job characteristics such as industry, field of occupation, and company size appear to play a more significant role. Male graduates are more likely to secure jobs in high-paying industries such as mining and IT, where salaries in 2022 exceeded 80,000 roubles per month. In contrast, women tend to focus on sectors with lower earnings, such as education, healthcare, and administration, where salaries rarely exceed 50,000 roubles.

Another notable finding concerns the role of academic achievement. Women are more likely than men to graduate with honours, reflecting a high level of training attained. However, this does not necessarily result in tangible benefits. While graduating with honours increases employability, it does not guarantee women the same high salaries as their male counterparts.

© HSE University

The reasons for this gap may be linked to unobservable factors such as differences in working hours, career interruptions due to family obligations, and potential discrimination by employers.

In another article, the authors provide an even more detailed analysis, for the first time evaluating the dynamics of early-career gender inequality based on data from 2018 graduates. Despite the absence of family obligations or significant differences in work experience between men and women, a gender pay gap of 14% is observed in the first six months of their entry into the labour market. Within four years of graduation, the pay gap nearly doubles. While initially, right after graduation, 85% of the pay gap can be attributed to objective differences in education and work characteristics, a few years later, most of the gap remains unexplained. The largest gap is observed among the highest-paid professionals, indicating the presence of a glass ceiling effect from the very start of graduates' careers in the Russian labour market.

'The rapidly expanding early-career gender pay gap indicates that education policies may have limited ability to effectively address gender inequality in the labour market. The expectation that the pay gap can be minimised solely by reducing educational segregation is unfounded,' according to Sergey Roshchin, co-author of the study and Head of the Laboratory for Labour Market Studies at the HSE Faculty of Economic Sciences.

See also:

'Our Goal Is Not to Determine Which Version Is Correct but to Explore the Variability'

The International Linguistic Convergence Laboratory at the HSE Faculty of Humanities studies the processes of convergence among languages spoken in regions with mixed, multiethnic populations. Research conducted by linguists at HSE University contributes to understanding the history of language development and explores how languages are perceived and used in multilingual environments. George Moroz, head of the laboratory, shares more details in an interview with the HSE News Service.

Slim vs Fat: Overweight Russians Earn Less

Overweight Russians tend to earn significantly less than their slimmer counterparts, with a 10% increase in body mass index (BMI) associated with a 9% decrease in wages. These are the findings made by Anastasiia Deeva, lecturer at the HSE Faculty of Economic Sciences and intern researcher in Laboratory of Economic Research in Public Sector. The article has been published in Voprosy Statistiki.

Scientists Reveal Cognitive Mechanisms Involved in Bipolar Disorder

An international team of researchers including scientists from HSE University has experimentally demonstrated that individuals with bipolar disorder tend to perceive the world as more volatile than it actually is, which often leads them to make irrational decisions. The scientists suggest that their findings could lead to the development of more accurate methods for diagnosing and treating bipolar disorder in the future. The article has been published in Translational Psychiatry.

Scientists Develop AI Tool for Designing Novel Materials

An international team of scientists, including researchers from HSE University, has developed a new generative model called the Wyckoff Transformer (WyFormer) for creating symmetrical crystal structures. The neural network will make it possible to design materials with specified properties for use in semiconductors, solar panels, medical devices, and other high-tech applications. The scientists will present their work at ICML, a leading international conference on machine learning, on July 15 in Vancouver. A preprint of the paper is available on arxiv.org, with the code and data released under an open-source license.

HSE Linguists Study How Bilinguals Use Phrases with Numerals in Russian

Researchers at HSE University analysed over 4,000 examples of Russian spoken by bilinguals for whom Russian is a second language, collected from seven regions of Russia. They found that most non-standard numeral constructions are influenced not only by the speakers’ native languages but also by how frequently these expressions occur in everyday speech. For example, common phrases like 'two hours' or 'five kilometres’ almost always match the standard literary form, while less familiar expressions—especially those involving the numerals two to four or collective forms like dvoe and troe (used for referring to people)—often differ from the norm. The study has been published in Journal of Bilingualism.

Overcoming Baby Duck Syndrome: How Repeated Use Improves Acceptance of Interface Updates

Users often prefer older versions of interfaces due to a cognitive bias known as the baby duck syndrome, where their first experience with an interface becomes the benchmark against which all future updates are judged. However, an experiment conducted by researchers from HSE University produced an encouraging result: simply re-exposing users to the updated interface reduced the bias and improved their overall perception of the new version. The study has been published in Cognitive Processing.

Mathematicians from HSE Campus in Nizhny Novgorod Prove Existence of Robust Chaos in Complex Systems

Researchers from the International Laboratory of Dynamical Systems and Applications at the HSE Campus in Nizhny Novgorod have developed a theory that enables a mathematical proof of robust chaotic dynamics in networks of interacting elements. This research opens up new possibilities for exploring complex dynamical processes in neuroscience, biology, medicine, chemistry, optics, and other fields. The study findings have been accepted for publication in Physical Review Letters, a leading international journal. The findings are available on arXiv.org.

Mathematicians from HSE University–Nizhny Novgorod Solve 57-Year-Old Problem

In 1968, American mathematician Paul Chernoff proposed a theorem that allows for the approximate calculation of operator semigroups, complex but useful mathematical constructions that describe how the states of multiparticle systems change over time. The method is based on a sequence of approximations—steps which make the result increasingly accurate. But until now it was unclear how quickly these steps lead to the result and what exactly influences this speed. This problem has been fully solved for the first time by mathematicians Oleg Galkin and Ivan Remizov from the Nizhny Novgorod campus of HSE University. Their work paves the way for more reliable calculations in various fields of science. The results were published in the Israel Journal of Mathematics (Q1).

Large Language Models No Longer Require Powerful Servers

Scientists from Yandex, HSE University, MIT, KAUST, and ISTA have made a breakthrough in optimising LLMs. Yandex Research, in collaboration with leading science and technology universities, has developed a method for rapidly compressing large language models (LLMs) without compromising quality. Now, a smartphone or laptop is enough to work with LLMs—there's no need for expensive servers or high-powered GPUs.

AI to Enable Accurate Modelling of Data Storage System Performance

Researchers at the HSE Faculty of Computer Science have developed a new approach to modelling data storage systems based on generative machine learning models. This approach makes it possible to accurately predict the key performance characteristics of such systems under various conditions. Results have been published in the IEEE Access journal.