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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Changes in Out-of-Home Food and Alcohol Expenditure during the COVID-19 Pandemic

HSE Economic Journal. 2025. Vol. 29. No. 1. P. 132–159.
Voytenkov V.

This study investigates changes in the expenditure on out-of-home food and alcohol during the COVID-19 pandemic. Our research specifically explores intergroup variations among households, taking into account the dissimilarity of Russian regions in light of the degree of quarantine restrictions enforced. To test the research hypotheses, we use microdata from the Household Budget Survey conducted by the Federal State Statistics Service. To compare the expenditures on out-of-home food and alcohol in regions with soft, medium, and hard restrictive measures, we employ t-test for comparing means and the Kolmogorov-Smirnov test for comparing distributions. The Tobit model is applied to compare different social groups' household spending habits. The joint analysis of out-of-home food and alcohol expenditure enables the separation of involuntary savings from coping strategies using models for censored data, thereby facilitating an in-depth assessment of household well-being in the face of shocks. Our findings show a reduction in out-of-home food expenditure across all social groups and all levels of quarantine restrictions. The share of alcohol expenditure decreased in almost all social groups in regions with soft measures but significantly increased in those with medium and hard restrictions.

Research target: Economics and Management
Language: English
Full text
DOI
Text on another site
Keywords: householdsCOVID-19alcohol expenditureout-of-home food expenditureintergroup analysisrigidity of quarantine measures
Publication based on the results of:
Current Issues of Macroeconomic Dynamics and Macroeconomic Policy in Russia (2025)
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