Pollution, extreme weather, and global warming have become increasingly important in today’s society. This dissertation examines these topics in three chapters, analyzing the effects of pollution and environmental factors on human behavior.
The first chapter uses a dataset of unique daily crimes in the U.S. to unveil the relationship between weather/pollution and the crime rate for seven major U.S. cities. The results reveal that temperature significantly affects both violent and property crime rates. The rate of violent crime is lower on extreme and unpleasant weather days (i.e., when the temperature is above 99°F) in comparison to good or unremarkable days. There is little evidence on how air pollution affects the crime rate by using fine particulates (PM2.5) and coarse particulates (PM10). However, pollution does have an effect on crime if the area of analysis is located closer to an operated toxic release facility.
The second chapter examines how weekly hours worked by individuals vary with respect to snowfall in 265 metropolitan areas (about 75% of the US workforce) over the years 2004-2014. The results reveal that working hours are significantly affected by snow events, with magnitudes varying by types of workers, types of employment (class of worker, occupation, and industry), and regions. Overall, each average daily inch of snowfall, during a Current Population Survey (CPS) monthly reference week, reduces working hours by about 1 hour. Snow storms reduce weekly hours worked considerably more among construction workers and in the South than elsewhere in the U.S.. We find little evidence that hours lost from large snowfalls are “made-up” in subsequent weeks.
The third chapter investigates whether housing age, which has been missing in the conventional environmental justice literature, has an impact on the distribution of households in a pollution area. Income and race were believed to be predominant factors that affect the location choices of individuals. By controlling for this additional housing age variable in the conventional model, I examine which factor, income or race, is affected most. The results indicate that older houses are located closer to pollution sites. Additionally, once I control for the housing age, the marginal effect of income declines significantly, approximately by 50%. The effect on race was insignificant in empirical analysis.
| Identifer | oai:union.ndltd.org:GEORGIA/oai:scholarworks.gsu.edu:econ_diss-1136 |
| Date | 01 August 2017 |
| Creators | Liu, Bo |
| Publisher | ScholarWorks @ Georgia State University |
| Source Sets | Georgia State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Economics Dissertations |
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