Workshop on Modern Research Methods Held at the Higher School of Economics and Business

On January 14, within the framework of the Winter School for Young Faculty Members of the Higher School of Economics and Business, a workshop was held by Doctor of Economic Sciences, Professor Ainagul Amangeldinovna Adambekova on the topic “Research Methods: Fundamental and Neural Network Approaches.”

The workshop was dedicated to current methodological issues in economic research and attracted considerable interest from participants. During the session, practical examples of applying fundamental research methods in economic studies were presented, along with a discussion of modern requirements imposed by academic journals on the description and justification of research methodologies.

Special attention was given to qualitative research methods, including a comparative overview of literature reviews, content analysis, and free-content analysis. These topics generated active engagement among participants involved in academic writing and publication activities.

In addition, quantitative research methods were extensively discussed, particularly techniques applied under data lag conditions. The workshop covered the use of proxy variables, extrapolation and interpolation methods, data imputation techniques, and other econometric tools commonly employed in empirical economic research.

A significant level of interest was sparked by recommendations on the application of neural network and machine learning methods, such as LSTM, Neural Mapping, ML-SAE, and others. It was emphasized that these approaches help reduce noise in data, account for nonlinear trends and external shocks, and expand the use of programming languages such as Python and R in economic analysis.

The workshop received a highly positive response from both early-career and experienced faculty members and researchers, highlighting the relevance of the topic and the practical value of the methods presented.