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  • Много ли мы тратим на еду? Доля потребления продуктов питания и доходы домашних хозяйств в России в 2001-2023 гг.
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News
June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Много ли мы тратим на еду? Доля потребления продуктов питания и доходы домашних хозяйств в России в 2001-2023 гг.

Проблемы прогнозирования. 2026. № 2(215). С. 6–22.
Ternovskiy D., Aleksandrova P., Voskoboynikov I., Nikulina Y., Метляхин А. И., Pankova D.

The work analyzes the correspondence between the share of food expenditure in Russia and per capita household income using the Engel curve. Generally, taking into account possible measurement errors, household behavior follows the classical empirical relationship observed in many countries - as income rises, household food consumption increases, and the share of food costs in total consumption expenses decreases.
The paper identifies four types of measurement anomalies that can distort the results of the Engel curve estimation. Firstly, when considering the long-term macroeconomic dynamics of 2001-2023, the classical empirical relationship is stable and statistically significant if the structural shift that occurred during the 2008 crisis is explicitly taken into account. Secondly, cross-country comparisons of the share of food costs and household income in 2019 showed the absence of abnormally high shares of food costs in Russia. In cross-country comparison, special attention should be paid to differences in income levels, taking into account imputed rents and meals outside the home in the structure of consumer spending. Thirdly, the calculation of the proportion of food expenses depends on the movement of relative prices.. This dependence is especially pronounced between 2001 and 2007. After 2010, the contribution from changes in relative prices becomes weaker. Finally, based on comparisons of parameters of the Engel curve using micro and macro data, systematic bias in macroeconomic estimates was revealed. The economic nature of these shifts is probably related to differentiation of households in terms of total spending and interregional differences in price levels.

Research target: Economics and Management
Language: Russian
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Keywords: российская экономикаhousehold incomethe Russian economyпотребление домашних хозяйствзакон ЭнгеляEngel curvesEngel's lawhouseholds consumptionкривая Энгелярасполагаемые доходы домашних хозяйств
Publication based on the results of:
The Impact of External Shocks on the Productivity and Social Sustainability of the Russian Economy (2025)
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