Real-time Monitoring of Economic Shocks using Company Websites

TL;DR

This paper presents WAI, a real-time web-based tool that uses LLMs to monitor economic shocks by analyzing millions of company websites, providing timely insights into firm responses during crises like COVID-19.

Contribution

Introduction of WAI, a novel LLM-assisted platform for real-time economic shock monitoring using company website data, enabling timely and comprehensive analysis.

Findings

WAI correlates strongly with COVID-19 containment measures.

WAI reliably predicts firm performance during crises.

Provides timely, global firm-level information unavailable through traditional data sources.

Abstract

Understanding the effects of economic shocks on firms is critical for analyzing economic growth and resilience. We introduce a Web-Based Affectedness Indicator (WAI), a general-purpose tool for real-time monitoring of economic disruptions across diverse contexts. By leveraging Large Language Model (LLM) assisted classification and information extraction on texts from over five million company websites, WAI quantifies the degree and nature of firms' responses to external shocks. Using the COVID-19 pandemic as a specific application, we show that WAI is highly correlated with pandemic containment measures and reliably predicts firm performance. Unlike traditional data sources, WAI provides timely firm-level information across industries and geographies worldwide that would otherwise be unavailable due to institutional and data availability constraints. This methodology offers significant potential for monitoring and mitigating the impact of technological, political, financial, health or environmental crises, and represents a transformative tool for adaptive policy-making and economic resilience.