Economics: Econometric Analysis

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Economics: Econometric Analysis

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https://hdl.handle.net/1853/70819

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School of Economics

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Now showing 1 - 10 of 21

Poverty and Obesity in the Developed World

(Georgia Institute of Technology, 2014-12) Firstman, Rachel ; Whitaker-Shepard, Kyra ; Cherecwich, Michael

In the past three decades worldwide obesity rates have skyrocketed, contributing to a myriad of health problems in the affected regions. We have tested for the effects of various factors on obesity, primarily the effect of poverty on obesity rates. At first we used a single regression model to compare country GDP and average population BMI in 162 different countries with the assumption that the two will be positively correlated. Next we focused on the developed world to draw conclusions about the correlations between obesity, poverty, and factors such as education levels using a single and multiple regression model. We found significance between per capita income and prevalence of obesity in the United States in our single regression model at the 10% level but were unable to find meaningful data correlation in our multiple regression; however, we did find a very significant negative impact of high school graduation rates on obesity rates and a positive correlation between the percentage of non-Hispanic white population and obesity rates by state.
The Effects of Water Access on Government Health Care Spending Worldwide

(Georgia Institute of Technology, 2014-12) Furman, Daniel ; Morjaria, Mala ; Roseen, Dillon

Water access worldwide affects numerous areas of personal health. This paper attempts to analyze the effects that water access has on total government health care expenditure in different countries. By utilizing a cross-sectional analysis on data from over 80 countries, we provide a unique view of how lack of water access may burden health care. This paper grounds its hypothesis in Pareto economic welfare policy, which helps explain the relationship between these variables. In addition to water access, we utilized additional independent variables such as private health care spending and tobacco use and a dummy variable adjusting for differences in developed and non-developed countries. These variables enabled us to gain a holistic view of the effects of water access on health care spending. Our study is founded upon existing economic theory and is thus related to other empirical works. It is unique in the way in which health care spending is explained using distinct variables and data sets.
Cross-‐Country Effects of Inflation on National Savings

(Georgia Institute of Technology, 2014-12) Cheng, Qun ; Li, Xiaoyang

Inflation is considered to be one of the most crucial factors in daily life since it has a direct impact on some people’s savings. This paper seeks to examine whether or not there is a relationship between national savings and inflation rate. In a more complex multiple regression model, we take into account unemployment rate, HDI, population and income per capita. We found that inflation has a statistically significant positive effect on the national savings in both our simple and multiple regression models.
The Effect of Research and Development Investment on Patents

(Georgia Institute of Technology, 2014-12) Ming, Thomas ; Liu, Zhen ; Palanivel, Tharangini

Economists today mostly assume that investment results in gains for that particular field. In this paper, we test for the effect investment in research and development (R&D) has on technological growth. We utilize cross sectional data from 2010 and test a variety of other factors including Gross Domestic Product (GDP) per capita; average years of education; export volume into the United States; and the Leamer Index, a measurement for natural resource abundance in a country. The results from the experiment show that the R&D Expenditure has a significant effect on number of patents filed. In addition, whether or not a country was developed was found to significantly influence the number of patents filed. The various other variables including: average years of education, GDP per capita, and the Leamer Index were found to be insignificant while the exports to the US were found to have a significant effect on patents filed.
Transit ridership and poverty in urbanized areas: a cross-sectional analysis

(Georgia Institute of Technology, 2014-12) Cox, Kevin ; Crees, Curtis ; Kaul, Raghav

Despite theory claiming that transit provides mobility to the lowest-income members of society, empirical evidence for poverty as a determinant for transit ridership is lacking. Most studies of transit ridership encounter two hurdles. Either they simply try to estimate a demand function, relying on individual perceptions of transit utility, without a response variable that accurately reflects demand, or they miss several important explanatory variables for demand itself. This research proposes a novel and statistically robust multivariate regression model to estimate ridership as the intersection of supply and demand, rather than explaining solely a demand curve. It also adds several explanatory variables to existing models of ridership estimation.
Effects of Minimum Wage on Unemployment Rates Across the United States

(Georgia Institute of Technology, 2014-12) Abdeljawad, Aeishah ; Panjwani, Rahim ; Ramani, Hamsika

In recent years, there has been widespread discussion on the effects of minimum wage on unemployment. In this paper, we have compiled extensive data on the variation of minimum wage levels across states, as well as looking at other variables that have an effect on earnings such as educational levels, weekly unemployment benefits, and the CPI. Using simple and multiple regression analysis and other statistical tests on our variables, we have come to the conclusion that there is evidence that supports a positive relationship between minimum wage and unemployment, which ultimately supports our hypothesis that raising the minimum wage, increases unemployment.
How Does Savings Rate Affect Economic Growth?

(Georgia Institute of Technology, 2014-12) Remolina, Daniella ; Munoz, Emilio ; Martinez, Felipe

The following paper focuses on determining how the savings rate affects the economic growth in terms of income by analyzing a cross section data of 100 countries in 2010. In order to infer the relationship between these two variables, two types of studies are conducted: simple and multiple regressions. For the simple regression analysis between savings rate and income, it is shown that these two variables are positively correlated with a coefficient of correlation of about 25% indicating that there are other explanatory variables that should be taken into account when evaluating the disparities in income across countries. The first multiple regression analysis conducted replicates the studies found in “A Contribution to the Empirics of Economic Growth" (Mankiw, Gregory, Romer, Weil, 1992). For this analysis, population growth rate and education are introduced as explanatory variables, leading to a coefficient of correlation of 71%. Furthermore, our study introduces one more explanatory variable of number of science journals published as an indicative of technology growth in each country. For this analysis the correlation coefficient obtained is 72%, showing that the introduction of the new variable did not significantly contribute to the explanation of income disparities. Finally, the countries are divided into high and low-middle income in order to determine if the relationship between savings rate and income is altered by this factor. It is observed that the relationship still holds true for both cases and it is proved that technology growth is statistically significant for middle-low income countries whereas for high-income countries it is insignificant. It can be concluded that savings rate, education index and technology are positively correlated to income whereas population growth is negatively correlated to the dependent variable. In order to better understand and explain these relationships it is recommended to look into other indicators of technology that have a higher statistical significance in the model.
The Effect of Minimum Wage and Unemployment across Varying Economic Climates

(Georgia Institute of Technology, 2014-12) Greer, Scott ; Castrejon, Isai ; Lee, Sarah

This paper aims to model and quantify the relationship between minimum wage and unemployment rate. Both microeconomic and macroeconomic theory dictate that unemployment rate will increase with an increase in the minimum wage. This economic relationship is tested on a state-by-state basis in the United States from 2002 to 2012 based on data obtained from the bureau of labor statistics. This time period is broken up into three models: pre-recession, recession, and post-recession. The simple regression models made the conclusions that minimum wage has an effect on unemployment. For the multiple regression models, it was concluded that minimum wage had a significant effect on unemployment when the economy was unstable, during the recession and post-recession.
The Effects of the NFL on Metro-level GDP

(Georgia Institute of Technology, 2014-12) Garrett, TreVorski ; Earnest, Mitch ; Speller, Kyle

Behavioral economics studies the effects of psychological, social, cognitive, and emotional factors on economic decisions of individuals [1]. In this paper, we test for an observable relationship between the Gross Domestic Product (GDP) per capita of a metropolitan area with the performance of the local National Football League (NFL) team. The performance of the NFL team was defined using the team’s average winning percentage in a given period and Superbowl performances and locations. We compile panel data for the 32 NFL programs and GDP per capita of 30 metropolitan areas over a 8-year period. The data was divided into periods based on the Economic Recession of 2009. We hypothesize that a team’s performance will positively impact the GDP per capita of the specified metropolitan area due to a boost in local morale reflected through increased consumption. Our results indicate that there is no observable relationship between the performance of a NFL team and the GDP per capita of the metropolitan area that hosts the team.
On foreclosure rates and the house price index: A cross-sectional analysis

(Georgia Institute of Technology, 2014-12) Sullere, Shivang ; Liang, Kenneth ; Ondracek, Jakub

This paper attempts to firmly establish the dependence of house price index on foreclosure rates, a prerequisite to substantiating “let-sink” foreclosure policy. In our paper, we first examine a simple linear regression model to show that there are omitted variables in the model, and therefore, more variables other than just foreclosure rates have to be considered. We then continue with the multiple linear regression model by looking at the influence of foreclosure rates, education, property tax, income tax, stimulus, and legal system upon house price index. By using this model, we show that most variables do not have statistical significance, individually or jointly, except for foreclosure rates and legal system. Finally, we reject the null hypothesis and conclude that house price index is significantly dependent upon foreclosure rates and the state legal foreclosure system.