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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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Об устойчивости результатов для правил агрегирования

Журнал Новой экономической ассоциации. 2022. № 5(57). С. 24–37.
Karabekyan D.

Some distortions are possible in the process of preference aggregation. For example, one voter who is pivotal for some preference profi le may not read instructions properly and accidently submit wrong preference. We study how different voting rules react to these distortions for three, four and fi ve alternatives with computer modelling. One of the results is: contrary to the results for the degree of manipulability estimations the most stable rule is the rule that requires less information from preferences when calculating fi nal results — threshold rule. With more alternatives the difference between this rule and rules that require information about the whole ranking is more visible. So, for the rules that require less information the probability to infl uence the results goes down when the number of alternatives increases. Another result: the resoluteness (weighted average number of alternatives in the fi nal outcome) is positively correlated with the stability of aggregation procedures. Threshold rule is the best one for the most cases when we consider both stability and resoluteness.

Research target: Economics and Management Computer Science
Language: Russian
DOI
Text on another site
Keywords: устойчивостьstabilityманипулированиеmanipulabilitythreshold ruleпороговое правилоaggregation rulesправила агрегирования
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