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News
September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Построение доверительного множества связанных акций фондового рынка

Журнал Новой экономической ассоциации. 2021. Т. 2. № 50. С. 12–34.
Koldanov A. P., Koldanov P., Semenov D.

. The problem of analysis of pairwise connections between stocks of financial market by observations on stock returns is considered. Such problem arise in stock market network analysis. It is assumed that joint distribution of stock returns belongs to the wide class of elliptical distributions. Classical Pearson correlation, Fechner correlation and Kendall correlation are used as measure of dependence. The construction problems of sets of stocks with strong connections between its returns are investigated. The construction problems of sets of stocks with strong connections between its returns are investigated. To construct such sets the multiple hypotheses testing procedures on values of correlations are used. The properties of these statistical procedures are investigated by simulations. The simulation results show that procedures based on individual Fechner and Kendall tests lead to such sets of stocks with given confidence probability unlike procedure based on Pearson individual tests which do not control the confidence probability. At the same time it is emphasized that for Student distribution the constructed set is nearly the same to the confidence set. The procedure of consistency testing with elliptical model is proposed and exemplified. The peculiarities of the model are discussed.

Research target: Economics and Management Mathematics Computer Science
Priority areas: IT and mathematics
Language: Russian
DOI
Text on another site
Keywords: Threshold graph Pearson correlationNetwork model of stock marketKendall correlationFechner correlationsufficient setmultiple hypotheses testing proceduresсетевая модель фондового рынкаотсеченный графклассический коэффициент корреляции Пирсонакорреляция Кендаллакорреляция Фехнера доверительное множествопроцедуры множественной проверки гипотез
Publication based on the results of:
Theoretical and algorithmic aspects of network analysis algorithms (2021)
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