We use cookies in order to improve the quality and usability of the HSE website. More information about the use of cookies is available here, and the regulations on processing personal data can be found here. By continuing to use the site, you hereby confirm that you have been informed of the use of cookies by the HSE website and agree with our rules for processing personal data. You may disable cookies in your browser settings.

  • A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
  • HSE University
  • News
  • Considering News Background Can Improve GDP Projections in Periods of Instability

Considering News Background Can Improve GDP Projections in Periods of Instability

Considering News Background Can Improve GDP Projections in Periods of Instability

© iStock

The accuracy of Russian GDP forecasts during periods of instability improves in 45% of cases when news reports are taken into account. However, during more stable periods, this advantage nearly disappears. News provides an up-to-date view of the economy and enables quicker responses to emerging challenges. This was revealed by an analysis of over 500,000 news reports conducted by Ivan Stankevich and Natalia Makeeva of the HSE Faculty of Economic Sciences (FES), and Nikita Lyubaykin. The study results have been published in Voprosy Ekonomiki.

Statistical agencies do not publish economic statistics in real time. For example, quarterly GDP data is published with a two-month delay. However, more up-to-date data is essential for understanding the current economic situation, especially considering the impact of the coronavirus pandemic and sanctions pressure. Therefore, experts attempt to forecast economic indicators using current data, such as daily bank card transactions or export and import volumes. However, these estimates may not always be very accurate. Assistant Professor at HSE FES Ivan Stankevich, lecturer Natalia Makeeva, and researcher Nikita Lyubaykin have examined how incorporating news reports can influence the accuracy of Russian GDP forecasts.

The authors analysed over 500,000 news reports from Telegram channels of major media and news outlets with audiences exceeding 100,000 people, spanning from 2014 to 2023. 'We used a diverse range of channels to avoid any bias from uneven coverage of events,' said the HSE FES researchers. Using deep learning methods, each news item was classified into one of 19 categories (such as 'economics and business,' 'society,' or 'culture') and assessed for tonality ('positive,' 'negative,' or 'neutral'). The data was then incorporated into existing forecasting models to determine whether incorporating news reports improved the accuracy of the forecasts. The authors also divided the observations into two periods: before and after the introduction of large-scale economic sanctions in 2022. The mean absolute error (MAE) of the forecasts was used as the primary measure of accuracy, representing the deviation of the model’s results from the actual indicators over the entire observation period. A lower MAE indicates a better model. 

It was found that incorporating news reports during periods of instability improves forecast accuracy in 45% of cases and reduces the MAE for GDP by 0.64 percentage points (p.p.). This is a significant result. Before incorporating news reports, the average error was around 2 p.p., while in the updated model, this error decreased to less than 1.3 p.p. Considering that GDP fell by 2.4 p.p. in 2022 and increased by 3.6 p.p. in 2023, the improvement is quite substantial. 

Ivan Stankevich

'Incorporating the emotional tone of the news is an effort to formalise and quantify how experts assess the current state of the economy. Often, economic problems are apparent to specialists before showing up in "traditional" statistics, such as low unemployment, stable stock markets, and a steady exchange rate. Experts write about this, causing the overall news sentiment to worsen, and models are signalling a risk of recession,' according to Ivan Stankevich, Assistant Professor at the HSE Faculty of Economic Sciences. 

However, this approach is effective only during crises and periods of instability. In the pre-sanctions period, taking into account the news background has minimal impact on forecast accuracy, affecting only 30% of models, and decreasing MAE by only 0.26 p.p. The authors also note that models incorporating news of all tonalities, rather than just negative ones, perform best. 

While news can help quickly assess the state of the economy during unstable times, it is advisable to explore additional methods to enhance the accuracy of short-term economic forecasts.

Hari the Robot Recommends

We created Hari the robot and named him after Hari Seldon, a character who can predict the future in the works of science fiction writer Isaac Asimov. He is based on a machine-learning model that selects news based on the behavioural metrics of HSE website users.

Don’t worry — we don’t collect any personal data for this.

‘You Should Study Mathematics, Combinatorics, and Catalan Numbers instead of Playing Computer Games’

In early November, the final of the MTS True Tech Champ—which brought together more than 12,500 schoolchildren, students, and young programmers—took place. Alexander Babin, student of the HSE Faculty of Computer Science, was named the winner of the ‘Algorithmic Programming’ track.

November 19, 2024

Concert-Research on Pokrovka

The Fusion of Music and Science in the Presentation of the Album ‘RefleXions’

November 13, 2024

Maxim Reshetnikov: ‘An Effective Open Market Economy Has Been Built in Russia’

On November 11, 2024, during Economist Day in Russia, Maxim Reshetnikov, Russian Minister of Economic Development, spoke to students of the HSE Faculty of World Economy and International Affairs about Russia’s foreign economic activities, how the country managed to withstand unprecedented sanctions pressure, and the current state of its development.

November 13, 2024