This project analyzes cigarette demand in the United States from the years 1964 to 2018. Using the number of cigarette packs purchased in any given year as the dependent variable, a time series OLS regression is run with price, income, population, and the previous year’s dependent variable as the independent variables. Findings indicate price is insignificant, which is common in addictive substances. Income is significant, with its relationship to the dependent variable possibly attributed to societal factors. Population is significant, and its results remain in line with basic economic theory. The independent variable equal to the previous year’s dependent variable is proven to be the most significant factor, which is expected in addictive substances; the total number of smokers in one year, and therefore the number of cigarettes purchased, is heavily dependent upon the number of smokers in the year previous. Cigarette demand in the United States remains complicated by several societal factors, only some of which have been used in this regression. Further, more rigorous research into the reasons for the continued decline of cigarette demand must be completed, especially as new anti-smoking policies arise.
Arabica coffee beans are traditionally grown in cooler shaded environments, which benefit the quality of the beans. Shade-grown coffee beans also tend to have many positive impacts on surrounding environments, as the protection from the sun that these beans require, increases the variety of plants and animals around the coffee plant. However, reductions in income that coffee farmers and growers have received over decades have had impacts on the growing process of arabica coffee beans, with researchers and analysts examining whether this has impacted farmers to seek out more efficient ways to grow these beans that differs from the traditional shade-grown process. This transition out of shade-grown coffee, as researchers examine, allows for an increased quantity of beans produced which ensures more profit and income at the end of the production cycle, but might have adverse effects on surrounding environments. This research project puts the shade-grown preference of arabica coffee beans to the test, examining whether arabica coffee production has a significant positive or negative impact on the environment. The environmental indicator used in this research is biological capacity which measures the ability of ecosystems to regenerate an ongoing supply of renewable resources and to absorb waste from surrounding populations.
Major League Baseball is a widely studied topic among economists and has been studied since its start in 1869. Many of these studies focus on factors that affect attendance to home games. In this study, data has been collected on the thirty teams in Major League Baseball and the areas the teams are located in for the 2019 season. The data has been analyzed to determine the extent to which home game wins affect attendance, finding that for every additional home game win increase, attendance increases by nearly 23,000.
For the United States, one of the most important trends of concern is the growing level of inequality. It is widely accepted that the United States is currently experiencing historically high levels of economic inequality. There are numerous reasons for policymakers and citizens to be concerned about the rising level of inequality, such as its impact on the basic American social contract that says that hard work pays off; the diminishing of opportunity; the rise in societal unrest; and its impact on political functionality. It has been well established that inequality has a negative impact on undermining educational opportunities, lowering social mobility, hampering skills development, and less-productive labor inputs. Most research has studied the extent to which higher inequality is associated with less opportunity and mobility. This research studies if there is a causal linkage between higher inequality and slower macroeconomic growth. The main hypothesis is that inequality limits human capital accumulation primarily through the channel of educational attainment, which then dampens labor quality. Reductions in labor quality led to slower economic growth. This research attempts to measure this relationship through the dynamics of labor quality with the intention of incorporating economic inequality in the composition of labor quality. The results do not support the theory that economic inequality dampens economic growth. One suggestion is to use disaggregate data rather than aggregate data as some of the variation between the relationships are lost when conducting analysis in the aggregate.
The Environmental Kuznets Curve (EKC) is an economic model that describes the relationship between economic development and environmental degradation. This study aimed to determine if the pattern theorized by the EKC is visible in data from 32 countries from 1990 to 2015. The EKC states that as economic development increases within a country, there will be an increase in environmental degradation, but eventually a turning point will be reached, after which point environmental degradation will decrease as economic development continues to increase. This study used carbon dioxide emissions per capita as the measure of environmental degradation (dependent variable) and GDP per capita and the Human Development Index (HDI) as the measures of economic development (explanatory variables). The statistical analysis consisted of two fixed effects regressions; in the first carbon dioxide emissions per capita were regressed on GDP per capita, and in the second carbon dioxide emissions per capita were regressed on HDI. The result of both regression were significant and supported the EKC hypothesis; however, both regressions produced low R-squared values, which indicates that much of the variation in carbon dioxide emissions per capita was unaccounted for. In the future, a larger sample size and more explanatory variables should be included to provide a cleared picture of the relationship between environmental degradation and economic development.
Basic Annual Cable Subscriptions in the U.S. have been declining since 2001, which is the same year Netflix began recording subscribers. The annual number of basic cable subscriptions in the U.S. is calculated based on the total number of subscriptions to basic cable television. This means any extra channel packages or upgrades are not included in this variable, only the bare minimum subscription. The purpose of this study is to determine whether Netflix’s emergence directly impacted the rate of Basic Cable Subscriptions. This research is based on the years 1989-2019, for reference. This study contains has 4 independent variables. Basic Netflix subscriptions, which is the total amount of standard subscriptions on Netflix and should influence the Dependent Variable directly because it is a cable alternative. Basic Cable Subscription cost, which is the dollar amount for a basic cable subscription, no extra packages, or channels. Basic Netflix Subscription cost, which is the dollar amount of the standard Netflix subscription, no upgrades. Lastly, Annual U.S. Household Income, which is the average household income in the U.S. in dollars. In the years prior to Netflix (1989-2000), Basic Cable Subscriptions rose from 49.2 Million to 66.6 Million subscribers, a 35-percent increase. This was the peaking point for Basic Cable Subscriptions and since 2001, their subscriber count has fallen back down to 50.5 Million, nearly a 24-percent decrease. Given that Basic Cable Subscriptions is a normal good and tends to go up with income, seeing in the data that it declined in the past 15 to 20 years as Netflix emerged and grew rapidly draws the conclusion that Netflix directly impacted Cable TV subscriptions. The regression results are able to explain 77% of the variance in Cable TV Subscriptions and only contains Netflix, not any other widely used streaming services.
The COVID-19 Pandemic has caused the worst economic decline since the Great Depression. Both President Trump and Biden have passed stimulus packages to get the economy to recovery as quickly as possible. Since these packages have just been implemented there is no way to know the possible long term impacts they will have on the economy. The ARRA stimulus package that was implemented in 2009 was the last stimulus package to be passed by the US Government before the COVID-19 pandemic. This makes it the best comparison point for the most recent stimulus packages. This paper aims to find out the effectiveness of the ARRA stimulus using two approaches. One uses simulations of increasing government spending to see the impact of increasing all of the stimulus while the other looks at the estimated economic impact of each program funded by the ARRA. The first approach found that if the stimulus was five times greater then the economy would have recovered by 2012. The second approach found putting more funding into programs with a higher chance of increasing economic activity could have closed the worst part of the recession only if all of the funding was used at once. These approaches help to give insight to what can make a stimulus more effective at setting the economy on a course for recovery.