Tracking the COVID-19 crisis with high-resolution transaction data.

Area of Science:

• Economics
• Data Science
• Public Health

Background:

• Official statistics often underutilize naturally occurring transaction data.
• Payment systems generate billions of data points with potential for economic measurement.
• The COVID-19 pandemic highlighted the need for timely and granular economic indicators.

Purpose of the Study:

• To assess the utility of payment transaction data as a source for official statistics.
• To analyze the impact of COVID-19 on consumption patterns in Spain.
• To investigate socioeconomic disparities in consumption and mobility during the pandemic.

Main Methods:

• Utilized billions of anonymized credit card transactions from Banco Bilbao Vizcaya Argentaria.
• Validated transaction data against official national accounts and consumption surveys.
• Analyzed consumption and mobility data in relation to COVID-19 policies and socioeconomic factors in Spain.

Main Results:

• Payment transaction data effectively complements traditional measures of consumption.
• Business closures had a significant impact on consumption, while capacity restrictions had a smaller effect.
• Spending declined more sharply in affluent areas, while lower-income neighborhoods showed increased mobility correlating with higher disease incidence.

Conclusions:

• Payment transaction data is a valuable, complementary source for constructing official statistics.
• COVID-19's economic impact varied significantly across socioeconomic groups and geographic areas.
• Mobility patterns during the pandemic were linked to income levels and disease spread.