The temperature effect on perceived income

TL;DR

Higher temperatures on survey days lead people to report lower incomes, likely due to mood effects rather than actual income changes.

Contribution

This study reveals that temperature affects self-reported income data through behavioral and mood factors, not actual income.

Findings

Survey-day temperature negatively correlates with self-reported annual income.

The temperature effect is stronger on hot days and weaker or reversed on cooler days.

Mood, not cognitive ability, is the main driver of the temperature-income reporting bias.

Abstract

Extensive research has focused on the impact of weather on working capacity and income. However, in regions where income data largely relies on surveys, a pivotal yet underexplored question is whether weather not only influence real income but also introduce biases into survey-collected income data. We analyze longitudinal data from the China Health and Nutrition Survey and corresponding weather records from the Global Surface Summary of the Day, and uncover a negative correlation between survey-day temperature and self-reported annual income from the previous year. With a series of robustness checks, we confirm that the effect is primarily driven by behavioral factors rather than actual income changes. And threshold regression analyses show that the impact of temperature is more pronounced on hot days and relatively subdued or even reversed on cooler days. Further analyses indicate that mood, rather than cognitive capacity, plays a central role in causing the observed downward bias.