Working papers of faculty, affiliated researchers and students at the Department of
Economics, University of California at Santa Barbara.
Although the negative health consequences of tobacco use are well-informed, smokers usuallydo not have an incentive to quit smoking immediately as the smoking interventions are notcompulsory and the illness caused by smoking is distant in time. Smoking behavior is denselystudied and proved to be associated with a wide range of genetic, social, and psychologicalfactors. This study is to learn how does COVID-19 spread influence the smoking prevalence inthe United State. The results show that smoking behavior is not geographically affected by thestrictness of lockdown orders and the severity of coronavirus spread. However, the cigaretteconsumption is associated with COVID-19 with a negative significance if people encounterdepression during COVID-19. The outcome provides some important information for thecessation-related organizations: it is necessary to take care of smokers’ emotion status in theprocess of quitting during COVID-19.
This paper examines the effects of the Great Recession of 2007 to 2009 on the number ofchildren entering foster care due to maltreatment using data1 for 2004 to 2015. I usestandard OLS regressions with heteroskedastic robust standard errors in order toexamine the impact of the Great Recession, measured by the yearly unemployment rate,on children entering foster care due to physical abuse or neglect. Overall, I find littleevidence that there was an impact of the unemployment rate on entry into foster care.However, when looking across racial and ethnic groups, I find that Black children andAsian children were more or less susceptible, respectively, to entering foster care due tomaltreatment when there were increases in the unemployment rate during and after theGreat Recession.
In this paper, I investigate how oil price shocks and volatility affect adoption ofrenewable energy technologies by private businesses and households. Additionally, I analyze thechanges in electric utilities’ energy supplies sourced from fossil fuel-powered generators asprivate renewable energy adoption increases. This paper considers net energy metering programadoption as a measure of renewable energy technology uptake. I estimate two models on a paneldataset of electric utility-level data of net energy metering programs. The empirical resultsindicate that oil price shocks and oil price volatility reduce renewable energy adoption throughnet metering programs by a significant magnitude. The findings also show that greater customernet metering subscription significantly reduces utilities’ reliance on fossil fuels for their retailelectricity supplies. Coal and natural gas generator usage is most reduced, while oil-firedgenerator reliance is affected fractionally. Recommendations for improving renewable energypolicies and considerations for further reducing utilities’ reliance on fossil fuels are made basedoff these findings.
Innovation appears to have a direct impact on broad measures of social mobility. The mechanism thought to be behind this is Joseph Schumpeter’s theory of creative destruction, where new entrant firms develop more sophisticated technologies in an incessant process of industrial turnover. Thus, the gains in social mobility are dependent on the success of new entrant firms.We hypothesize that in regions with dense concentrations of venture capital funding, new entrant firms will be more successful, and this will amplify the effect that innovation has on mobility. This study contributes meaningful nuance to the argument that innovation causes increases in mobility by showing that the effect may vary in magnitude depending on influencing factors such as venture investment.
This study provides an estimation and methodology update on previous paper that studies the effect of having a second major in undergraduate on future earnings. Using 2019 National Survey of College Graduates (NSCG) data and Propensity Score Matching (PSM) method, I find that double majoring increases earnings by around 3% for the general population, and this earnings premium is more remarkable for people under the age of 40, which amounts to about 4%. While the proportion of double majors in the population drops from over 20% in 2003 to slightly above 13% in 2019, the returns to double majoring increase from around 2.5% since 2003. I also compare results from OLS regressions and PSM and argue that PSM can relax some of the parametric assumptions imposed by OLS regressions and hence reduce misspecification and extrapolation bias from OLS regressions, which previous literature on this topic relies on.
This paper analyzes the effects of urbanization on college graduates’ future earnings and job placement rates. I hypothesize that students attending institutions in urban areas benefit from local knowledge spillovers through greater exposure to human capital and R&D at nearby firms, which translates to higher future earnings and job placement rates. Using data from the 2016/2017 Baccalaureate and Beyond data set (National Center for Education Statistics), I employ three regression models to investigate the relationship between urbanization and annualized salaries, employment, and employment requiring a bachelor's degree. I find that urbanization does not have a significant effect on earnings or job placement. Due to limitations in my model design and data, this study warrants further research. Examining state and county characteristics (e.g., percentage of college graduates in the labor force, average incomes) will help account for the variation of human capital among urban areas and will likely affect future results.
This paper explores the relationship between California wildfires and human migration, and whetherit can be reasonably assumed that California counties with a higher frequency and/or severity ofwildfires experience greater out-migration than counties that experience a lower fire risk. Usingcounty-to-county migration data from 2010 to 2018 and wildfire data from 2009 to 2017, I runregressions with two different models: the multiple regression and fixed-effect model. Sourcecounties, i.e. counties where people are migrating from, observed in this study are only in California,but destination counties, i.e. counties where people are migrating to, include all counties in the U.S.In the case where destination counties are out of state, I aggregate counties by state so that I havecounty-to-county flows within California and county-to-state flows for the other 49 states. While itis possible to find literature that explores the effects of extreme climate events on human migration,little research exists on climate-induced migration in California, specifically with respect to wildfires.
This paper uses the introduction of municipal rent control legislation in East Palo Alto,California in 2010 to estimate the effects of rent control. I examine housing data from theAmerican Community Survey (years 2000 and 2006) and the American Community Survey‘Place’ Data Profiles (years 2010-2019) to determine how city-level rent control regulationimpacted the local housing market, specifically in terms of the availability of rental units. Myresults suggest that rent control legislation had no statistically significant effect on theavailability of rental units, which I approximate with the proportion of total housing unitsoccupied by renters. However, further investigation indicates this legislation did little to mitigatethe increase of median rental prices in comparison to the rates of Fairfield (control group) orCalifornia. These findings suggest further research is needed to fully understand the efficacy andimpact of rent control legislation in East Palo Alto.
This paper seeks to show that the potential to lose money as a result of theft has adifferent effect on an individual’s risk aversion than the potential to lose money due to chance.This would indicate that an individual’s risk aversion is inconsistent under different scenarios,contrasting current literature that assumes an individual’s risk aversion is independent of thesituation they are in. We attempt to show this through an experiment that frames loss in the formof theft. We use Amazon Mechanical Turk to gather responses to our experiment online. We findthat our treatment has no statistical effect, that people do not act in a way that is inconsistent withtheir risk aversion simply because of the possibility of theft.