Consumer Spending Responses to the COVID-19 Pandemic: An Assessment of Great Britain

ArXiv ID: ssrn-3586723 “View on arXiv”

Authors: Unknown

Abstract

Since the first death in China in early January 2020, the coronavirus (COVID-19) has spread across the globe and dominated the news headlines leading to fundame

Keywords: COVID-19, Volatility, Market Turbulence, Risk Management, Crisis Economics, Equity

Complexity vs Empirical Score

• Math Complexity: 2.0/10
• Empirical Rigor: 9.0/10
• Quadrant: Street Traders
• Why: The paper uses advanced econometric methods (e.g., time-series regressions with fixed effects) but is fundamentally an empirical study relying on a massive proprietary transaction dataset (23 million transactions) to analyze real-world consumer behavior, with no code/backtests presented but heavy data and implementation details.

  flowchart TD
    A["Research Goal:<br>Assess UK consumer<br>spending volatility<br>amid COVID-19"] --> B["Data Source:<br>UK Finance Admin Data<br>(n = 70M accounts)"]
    B --> C["Methodology:<br>Panel Regression &<br>Time-Series Analysis"]
    C --> D["Computational Process:<br>Compare Pre/Post-<br>Pandemic Spending Trends"]
    D --> E["Key Finding 1:<br>Immediate spending<br>contraction (Mar 2020)"]
    D --> F["Key Finding 2:<br>Shift from services<br>to durable goods"]
    D --> G["Key Finding 3:<br>Volatility spiked;<br>uncertainty persisted"]