2045 research outputs found
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Compliment or Substitute? Impact of Marijuana Legalization on Alcohol Consumption
Get PDFThis paper uses a state-level alcohol sales dataset to analyze how marijuana legalization affects alcohol consumption. I employ a difference-in-differences model to investigate the relationship between alcohol and marijuana in the short-term and long-term. In addition, marijuana legalization effects are estimated for different alcohol types – beer, wine and spirits. Overall, the results indicate a negative, yet insignificant relationship between the two narcotic drugs. There is not enough evidence to firmly conclude substitutability or complementarity of the two goods, therefore, leaving the debate unsolved
NFL Betting Market Efficiency: Finding a Profitable Betting Strategy
Get PDFThis paper uses pregame spread data to attempt to analyze the efficiency of the NFL betting market. I look at hot hand betting, performance during prime-time games, home field advantage, and favorites to test for inefficiencies in the market, thereby uncovering a profitable betting strategy. Using OLS regression analysis, I find no evidence of a profitable betting strategy betting on teams on streaks or home underdogs. However, my results suggest that it may be profitable to bet on the home team in prime-time games, regardless of their favorite or underdog status
Would Uber Help to Reduce Traffic Congestion?
Get PDFThis research explores the effects of Uber entry on New York City’s traffic. The two major questions I am trying to answer that might be of vital importance to transportation authorities are 1) does Uber substitute public transits? 2) does an introduce of Uber slow down average travel speed? After Uber was first introduced in year 2009, there are continuous debates on distinguishing its impact on traffic (Rayle et al., 2014; Li et al., 2016; Schaller, 2018; Castiglione et al., 2018). Considering that Uber is relatively new, relevant traffic data such as congestion indices are in general unavailable, which appears as a common limitation in previous analysis. In this research, I use monthly number of public transit trips in NYC to estimate a substitution effect of Uber on public transit ridership. To measure its direct impact on road traffic, I use Average Travel Speed generated from NYC yellow cab trips as a proxy for the citywide Average Travel Speed. A further application of monthly number of vehicles crossing nine major bridges and tunnels is used to capture a trend of traffic volume in NYC. The final dataset comprises 133 observations range from January 2008 to January 2018. Perceiving that Uber was introduced to NYC on May 2011 and was suspended on issuance of new vehicle licenses starting from August 2018, I use a regression discontinuity (RD) design and set the two events as cutoff points in the model. Additional use of Google Trend helps to more precisely determine the cutoff point. The regression results suggest that after Uber was introduced to NYC, 1) number of public transit trips has increased by about 3%; 2) average travel speed has decreased by .127 mph; and 3) traffic volume was not affected
IT Depends: The Maturity of Cultural Economics and Its Public Policy Debates
Get PDFThis paper explores a few core cultural economic theories such as Baumol’s Cost Disease and Crowding out/Crowding in effects, and it delves in the why, the how, and the how much of the public subsidy debate within economics. It asses all of these topics using an academic life cycle framework to determine if the field of cultural economics is mature enough to truly be giving recommendations to government. The author finds that there is conflict in terms of policy implication and a lack of data. Leading to the discovery that the field of Cultural Economics is not mature enough to be used in public policy debates
An Empirical Analysis of Debt/GDP+ Ratios
Get PDFThis thesis reviews past works that measured separately how public debt and private debt and household debt specifically affects GDP growth for both advanced and emerging economies for years generally up to 2009. This paper is meant to continue these analyses and update results for the years 2010-2015. This paper incorporates different factors including population, investment and dummy variables considered from each previous work as well as the some of the econometric analytical frameworks used. After conducting successful robustness checks, this paper concluded that private debt is beneficial to GDP growth in advanced countries once debt surpasses 120 percent of a country’s GDP. It can’t be concluded, however, that increases in public debt, household debt or population will continue to harm growth when either of these debt types reach past 90 percent of GDP due to insignificant results being calculated. It can be concluded, however, that public debt will cause inflation to decline when public debt is above 120 percent of GDP
The Traditional Individual in Society: A Study on Traditional Gender Roles and Mental Health
Get PDFGender roles are socially constructed norms prescribed for men and women in society to follow. Specifically, men and women have been assigned to traditional roles that are seen as correct for their assigned gender (i.e. men being the breadwinner and women being the housewife). Connecting traditional gender roles to mental health and well-being, this study investigates whether individuals who believe in traditional gender roles struggle more with mental health problems than those who do not. I propose that the more strongly an individual agrees with traditional gender roles, the more days of poor mental health they will report. To investigate the relationship between traditional gender roles and mental health, this study analyzes a sample of 701 full and part-time employees from the 2018 General Social Survey (GSS). The findings show that there is no statistically significant relationship between one’s attitude towards traditional gender roles and days of poor mental health reported. Therefore, the hypothesis was not supported. However, several controls, including sex, race, and age, are significant predictors of poor mental health. Further studies can improve on this topic by utilizing alternative measures of traditional gender roles since measures have focused on the traditional male breadwinner model
Seeing Green and Feeling Blue: The Effect of Natural Environment Exposure on Mental Health*
Get PDFDoes exposure to natural environments improve mental health? Past research shows benefits from spending time in green spaces, including improved well-being, as well as better mental and physical health (van den Berg et al. 2010; Atuoye et al. 2019; Bingley 2013). However, these studies focus on spending time in parks, gardens, or other natural environments and build their cases around the advantageous effects resulting from actual time spent in such places (Fan, Das, and Chen 2011; Litt et al. 2015; van den Berg et al. 2010). This study focuses instead on whether exposure to, regardless of time spent in green spaces, has similar effects. Using attention restoration theory and the theory of therapeutic landscapes, I hypothesize that the more one agrees that they have access to or views of natural environments, the fewer days of poor mental health they will have. This study uses data from the 2018 General Social Survey, with a restricted sample of only those who are employed or temporarily not working (N = 649). After controlling for race, family income, full-time employment status, size of place, and dwelling type, results show no significant relationship between access to or views of natural environments and days of poor mental health. However, multivariate results show that controlling for all other factors, white individuals had more days of poor mental health, and those who work full-time, live in single-family detached homes, or have higher family incomes had fewer days of poor mental health. While the results do not support the proposed hypotheses, the bivariate correlations begin to indicate which populations have access to green spaces, as well as which may be more likely to experience poor mental health based on demographic characteristics
The Influence of Household Income, Education, Gender on Fertility Willingness in Contemporary China
Get PDFWhy does the birthrate in China continuously decline? Why are Chinese people unwilling to have children now even after the One-Child Policy has been abandoned? I propose that the government policy was not the single crucial factor affecting the reduction of births in China. Household income, education, and gender also may have played a role. I use the 2015 Chinese General Social Survey to analyze the relationships between these three factors and the ideal number of children. The sample size of this subset is 2,373. Ordinary least square regression reveals that the ideal number of children increases as household income increases, while increasing education reduces the ideal number of children. Gender of potential parents does not have an effect on predicting the ideal number of children. The findings support the effects of household income and education on fertility willingness but reject that of gender. This study contributes to a sociological perspective on the demography of China. It suggests from an institutional perspective which factors would need to be changed to increase individuals’ fertility willingness