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Economics: Econometric Analysis
Economics: Econometric Analysis
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ItemEffect of Education on Income Inequality: A Cross-National Study(Georgia Institute of Technology, 2019-11) Jeng, Richard ; Gane, Julia ; Lages, RicardoThis paper explores the effects of education on income inequality. Data from over 50 countries was used and income inequality was measured through the Gini coefficient. Two regression models were created and controlled for other factors that might affect income inequality. We hypothesize that a negative correlation exists between education and income inequality, and the results corroborate that there is a slight negative relationship between these two variables. Additional methods to improve the model and suggestions are also provided.
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ItemAnalyzing the Effect of Income Inequality on Poverty(Georgia Institute of Technology, 2019-11) Burke, Abigail ; Berinhout, Kaylin ; Bonnie, PatrickThis paper seeks to add to the body of work surrounding the relationship between income inequality and poverty. In this research, we hope to demonstrate how the percentage of people living below the poverty line is related to the GINI coefficient, change in GDP per capita, literacy rate, Freedom House score, infant mortality rate, and income level for a range of different countries.
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ItemImpact of Educational Attainment on Wages(Georgia Institute of Technology, 2019-11) Sorel, Anri ; Shinners, ErinResearch in labor economics often tests the effect of educational attainment on wages. Our paper examines this relationship using individual-level data from the 2017 American Community Survey Public Use Microdata Sample for the state of Georgia. Across three regression models, we select four additional test variables: age, English fluency, race, and gender. We hypothesize that educational attainment will be the key determinant in wages. The results of our regression models did not fully support our hypothesis, with the explanatory variable gender having the most significant effect.
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ItemVoting in the United States: How Socioeconomic Status Influenced Voter Turnout in the 2008 Presidential Election(Georgia Institute of Technology, 2019-11) Bell, Joshua ; Heil, Andrew ; Reynolds, ConnerThe 2008 presidential election between Senators Barack Obama (D) and John McCain (R) occurred before the most severe economic recession since the great depression of the 1930s, and there is an abundance of evidence that shows economic status of voters during this period of time affected the voter turnout per state in this election. An example of this is the state GDP per capita within each individual state. The data collected in this study shows that, as state GDP per capita increases, the percent voter turnout for that state increases as well. The other variables studied included the number of students who enrolled in a degree granting institution in 2008, average state income tax, percent urban population, and state unemployment rate. However, it is not clear that these variables had significant effects on the percent voter turnout for each state in 2008.
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ItemDo States With High Income Also Have More Immigrants?(Georgia Institute of Technology, 2019-11) Gamble, Niall ; Campos Suarez, Adrian ; Yao, WilliamData was collected from the 50 states and the Capital of the United States of America in 2017 for evaluation. The main analysis investigates whether a state’s median household income is positively correlated with the state’s immigration. While a simple linear model showed a positive correlation. Subsequent models did not show the same relationship between a state’s immigration and a state’s income, and instead showed state immigration to be positively related to the presence of Fortune 500 Companies and Top 100 Universities. Future investigation should go into explaining the negative relationship.
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ItemEffects of Household Income on Graduation Level Across US Counties(Georgia Institute of Technology, 2019-11) Boss, Libby ; Lewis, Graham ; Patram, KarlThis paper analyzes the effect of household income on the graduation level on a county scale across the United States, following the hypothesis that household income should have a positive impact on graduation rates, measured in the percentage of people ages 18 to 24 with at least a high school degree as the dependent variable. Data from the 2010 US Census is used to estimate simple and multiple regression models. Other independent variables used are teen birth rate, average household size, poverty level, percent of people 25 and older with at least a high school degree, urban/rural location type, logarithm of household income, and percent of people ages 45 to 64 with at least a high school degree to take into account family history and regional differences and reduce omitted variable bias. The simple regression shows a positive relation between graduation rate and household income. The multiple regressions show that most independent variables have the hypothesized relation with the dependent variable, but fail to pr ovide conclusive evidence about the hypothesis.
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ItemAnalyzing the Relationship Between Trade and Economic Growth(Georgia Institute of Technology, 2019-11) Schmitt, Carly ; Imhof, Nicole ; Nechmad, TalThis paper examines how a country’s amount of total trade spurs economic growth within countries. The paper will analyze how the total trade activity, measured as the combined level of exports and imports, impacts economic growth, measured as changes in GDP per capita. The model is expanded to include a country’s amount of foreign direct investment, gross savings, unemployment level, amount of manufacturing in the economy, and the country’s overall status as a developed or developing economy as other potential factors and influencers of economic growth. The final model indicates that the most important influencers of economic growth are foreign investment, savings, unemployment, and the country’s development level.
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ItemThe Influence of Education Levels on Income Inequality(Georgia Institute of Technology, 2019-11) Cuadrado, Paula ; Fulmore, Olivia ; Phillips, ElizabethThis paper explores the role of education in income inequality. The data comes from the United Nations Development Programme Human Development Reports and the Organization for Economic Cooperation and Development. We started with a simple linear regression, using the sample countries’ Gini index as a proxy for income inequality and the average years of schooling as a gauge of education levels. The Gini index is regressed on the average years of schooling to determine if low education levels lead to income inequality. Many other factors may contribute to income inequality, so additional models perform multilinear regressions. The dependent variable, Gini, stays the same, but we add new independent variables such as median age, percentage of population engaged in vulnerable employment, log of GDP per capita, government education expenditure, government health expenditure, foreign direct investment inflows, and a dummy variable for OECD countries. The purpose is to inform public policy on the allocation of educational resources in countries seeking to combat inequality.
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ItemThe Impact of Research and Development Expenditure on Economic Growth(Georgia Institute of Technology, 2019-11) Mandel, Andrew ; Darcy, JohnExpenditure on research and development often signifies that a country is committed to making advancements in the fields of science and technology. This study attempts to reveal the relationship between economic growth (as measured by GDP per capita) and gross domestic expenditure on research and development as a percentage of gross domestic product (GERD). Other explanatory variables including the unemployment rate, GINI index, education expenditure as a percentage of GDP, labor productivity (as measured by GDP per hour worked), gross savings, and foreign direct investment inflow are also analyzed and utilized to determine this relationship. A time lag of 3 years between each country’s GERD (measured in 2012) and corresponding GDP per capita (measured in 2015) is used to allow time for the expenditure to be transformed into new developments that can impact GDP per capita. A positive correlation between GERD and GDP per capita is hypothesized and supported by the linear regression models developed in this study.
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ItemThe Effect of Trade Barriers and Governmental Regulation on Overall Economic Well-Being(Georgia Institute of Technology, 2019-11) Lawson, Cade ; Dietrich, Cavan ; Murray, ThomasBarriers to trade and other market regulations have long been thought to inhibit the ability of a nation’s economy to grow and prosper. We test this hypothesis using a multiple regression model and data from The Heritage Foundation and United Nations related to trade freedom and general economic regulation on a by-country basis to fully discern the impact of governmental regulation on a country’s GDP per capita. We find that GDP per capita rises significantly as a nation’s business freedom and trade freedom grow and that a nation’s status as developing or developed has additional bearing on GDP per capita. This provides strong confirmation for our hypothesis that deregulated economies experience higher levels of economic prosperity as measured by GDP per capita than their regulated counterparts and indicates that a market-specific look should be taken to fully understand the nuances of the results of different types of economic regulation.