Date of Completion

2018

Document Type

Honors College Thesis

Department

Rubenstein School of Environment and Natural Resources

Thesis Type

Honors College

First Advisor

Jon Erickson

Second Advisor

Jennifer Pontius

Third Advisor

Rachelle Gould

Keywords

climate, wellbeing, happiness, modeling, climate change

Abstract

This study aimed to better understand how climatic factors such as temperature and precipitation may be linked to human happiness as judged by self-reported wellbeing. Climate has been shown to influence wellbeing, and with climate change set to drastically alter conditions in which we live, understanding these relationships are vital. Based on the findings of Rehdanz and Maddison (2005), a variety of economic, demographic, and climate data for U.S. states between 2010 and 2016 were examined using a stepwise regression analysis to develop models for two different measures of wellbeing, the Gallup State of American Wellbeing Survey and the Measure of America Human Development Index. Models incorporating the Measure of America Human Development Index found no significant influence of climate factors, however, significant variables included gross domestic product (GDP), percent GDP change, population density, and life expectancy. In contrast, wellbeing quantified by the Gallup State of American Wellbeing Survey found a significant relationship with temperature variability, measured as the standard deviation of monthly average temperatures (p < 0.0001), along with percent GDP change, population density, population in urban areas, and life expectancy. Wellbeing decreased as temperature variability increased, suggesting that living in areas with more variable temperatures is linked to unhappiness. Additional research to validate the findings of this work, and to expand this work to include extreme weather event data and other climate factors and wellbeing metrics, may be necessary before meaningful conclusions can be drawn.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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