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The temperature effect on perceived income.

Ang Sun1, Wang Xiang2, Xu Jiang1

  • 1School of Finance, Renmin University of China, Beijing, China.

Scientific Reports
|March 15, 2024
PubMed
Summary
This summary is machine-generated.

High temperatures on survey days can negatively bias self-reported income, suggesting weather impacts survey data accuracy. This effect is linked to mood, not actual income changes.

Keywords:
Cognitive capacityIncomeMoodSurvey methodologyTemperature

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Area of Science:

  • Behavioral Economics
  • Survey Methodology
  • Environmental Psychology

Background:

  • Weather's impact on working capacity and income is well-researched.
  • The influence of weather on the accuracy of survey-collected income data remains underexplored, particularly in regions reliant on surveys.

Purpose of the Study:

  • To investigate whether weather conditions introduce biases into survey-collected income data.
  • To determine if temperature on the survey day affects self-reported annual income.

Main Methods:

  • Analysis of longitudinal data from the China Health and Nutrition Survey.
  • Correlation with historical weather records from the Global Surface Summary of the Day.
  • Robustness checks and threshold regression analyses were employed.

Main Results:

  • A negative correlation was found between survey-day temperature and self-reported annual income from the previous year.
  • The observed effect is attributed to behavioral factors, not actual income fluctuations.
  • Temperature's impact is more pronounced on hot days and less so on cooler days.

Conclusions:

  • Survey-day temperature can negatively bias self-reported income data.
  • Mood, rather than cognitive ability, appears to be the primary driver of this downward bias.
  • Findings highlight the importance of considering environmental factors in survey data interpretation.