Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics

TL;DR

This paper introduces a computational index derived from online search data to measure Chinese consumer confidence, revealing complex collective psychological dynamics that can enhance economic forecasting.

Contribution

It presents a novel behavioral index (C3I) linking online search behavior to consumer confidence, demonstrating the potential of large-scale data for socio-economic analysis.

Findings

C3I correlates with traditional consumer confidence measures

Online search data captures psychological dynamics of consumers

Computational indices improve economic forecasting accuracy

Abstract

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.