BEHAVIOURAL-MARKET APPROACH TO ASSESSING BUSINESS ACTIVITY

Abstract

The article substantiates a behavioural-market approach to assessing business activity as an operational analytical tool for monitoring short-term economic dynamics under conditions of high uncertainty. The study develops a methodological framework for constructing composite business activity indicators that integrate enterprise surveys, consumer sentiment indices, recovery indicators, and high-frequency market signals. The proposed algorithm includes time-series normalization, extraction of latent components using principal component analysis, and nowcasting models (ARIMAX, MIDAS, and machine-learning techniques).

Empirical testing is conducted on Ukrainian data, including the National Bank of Ukraine’s Business Activity Expectations Index, the Ukrainian Business Index (UBI), the Consumer Sentiment Index, and the Business Recovery Index. The results demonstrate that behavioural indicators provide earlier and more sensitive signals of cyclical changes than traditional macroeconomic statistics and significantly improve the short-term predictive accuracy of business activity models. The complementarity of the analysed indices allows for the identification of sectoral asymmetries, adaptive capacity of firms, and the persistence of precautionary business strategies during wartime economic conditions.

The dynamics of UBI and recovery indicators reveal a prolonged regime of cautious pessimism, reflecting liquidity constraints, energy risks, logistical disruptions, and heightened uncertainty. At the same time, the near-neutral values of the expectations index indicate gradual adaptation of enterprises and the stabilising role of domestic demand and public reconstruction programmes. The consumer sentiment index captures the behavioural transmission channel from household expectations to business activity, confirming the importance of confidence effects in shaping short-term economic fluctuations.

The practical contribution of the study lies in the development of an integrated monitoring model that combines behavioural and market-based metrics into a unified composite signal of current economic conditions. The proposed approach can be applied by public institutions, central banks, and business analytics units for real-time economic assessment, early detection of turning points, and evidence-based policy responses. The findings support the use of behavioural data as a core component of modern nowcasting systems in economies exposed to structural shocks and information volatility.