Last week on Thursday, Undergraduate Research Conference (URC) was held in the Peter T. Paul College of Business and Economics at the University of New Hampshire (UNH). This year URC went online due to coronavirus pandemic. You can visit Paul College URC channel here. You can visit other URC events within UNH here. Below are a few abstracts summarizing some of the research projects conducted by ECON B.S. students.
Central Bank Independence and Gross Domestic Product
by Sarah Hobbs
My research was based on the intuition I had gained form previous study and experience that a country with an independent central bank should have more positive effects on that country’s economy then if it were to be controlled by the government. Specifically I looked at whether independent central banks caused a higher gross domestic product for those countries, since their would be no governmental “hand” in that countries monetary policy decision making. I had never studied or looked into this relationship before, not like the widely studied inflation and central bank independence concept, and I thought an analysis specifically on this topic would give deeper meaning to central bank independence. I used a multiple linear regression model that included a dependent variable of log of GDP per country (in millions) and the six independent variables of interest rate, savings rate, inflation rate, tertiary educational attainment, unemployment and a dummy variable used to denote whether there was an absence or presence of central bank independence in that country had an independent central bank or not, a 0 represented independence and a 1 represented dependence. The main driver in my determination if a country had an independent or dependent central bank was whether the government played a role in any of their monetary policy decisions. I included data from the countries that had either the most independent central banks or the least independent central banks. In total 44 countries were included in the data set with the majority of the data coming from the World Bank and the official central banks websites for each country. The countries were from six of the seven continents and included developed and developing countries.
My results indicated that only three of my six independent variables were significant, which were interest rate, savings rate and educational attainment. For example a 1% increase in real interest rate decreases GDP by .038%. Seeing that central bank independence was not a significant variable in this analysis showed that the varying types of independence such as goal, instrumental, operational, etc. and the varying degrees of central bank independence amongst all countries played a bigger role in this model then originally anticipated. Also, my results showed that most developed countries have a higher degree of central bank independence then developing countries, while developing countries tend to have higher GDP growth due to their developing economies. Lastly, 32% of the variation of my dependent variable log of GDP can be explained by the model in terms of the fluctuations in the independent variables interest, savings, unemployment, inflation and absence or presence of independence. This project reaffirmed my viewpoint of the positive effects on a nations economy that occurs when their central bank is independent, but it also showed that increases in GDP are not able to be linked to central bank independence.
The
Impact of Socio-Economist Factors on the Yearly Average SAT Score
by Ali Mara
The SAT it is an important test and can be the determining factor for most students regarding their college application. As an international student I had to take the test to get accepted in college in USA, even though the test was extremely expensive for my financial background. That meant I had to perform well to not risk having to pay a second time. With that said however, there are thousands of students not only outside USA , but even in the country who come from worse financial status , or family situations then mine. These reasons and recent articles I had read regarding the penalties that standardized test can have on students pushed me to come with my research idea. I wanted to lay a general model that showed that the SAT test can be discriminatory from a socio-economic perspective.
The first step that I undertook was to see if there was any previous research. Luckily there exist a variety of studies in the last thirty years that cover that topic. Reading these papers and with the help of my advisor , I decided to choose the independent socio-economic factors that would most likely affect the SAT-score. I decided to look at factors such as median family income and unemployment. To account for the effect of the family I choose the divorce rate. However , undoubtedly high school is a very influential factor on the test score. For that reason, with data from National Education Statistic Center, I built a ratio between the private and public high school enrollment and was also able to find data on ratio of students per teacher. For my dependent variables I used the combined scores of the math and reading sections from the Sat test, from 1972 to 2018.
I transformed all my non-percentage variables into natural logs. The regression model results showed that indeed socio-economic factors impact the yearly average SAT score. I was able to see that a percentage increase in the average median family income during four years of high school would positively increase the SAT score. The ratio of private/public enrollment showed that students at private high school’s fare better than students at public high schools regarding the SAT score, at the same time a decrease on the divorce rate corresponded with increase in the yearly average test Score. The model however has limitations because of time series nature of the data employed. One can observe general trends between the SES and the test score, but it can’t predict a single score.
Nonetheless, the results show that we need to take steps to allocate more funds to high schools in predominantly poor areas. There is also a need to be more involved with students that come from a stressful family life, this can be done by directing students towards psychological services which often can be stigmatized in our society. All these implications however are in the short term and offer nothing more then tunnel vision. If we think of the butterfly effect the results can show a gloomier picture. In the long term we will have thousands of students who come from disadvantaged backgrounds and will not able to attend higher education based on their test scores. As it happens to be the case, most of these students from these socio-economic background makes the majority of non-white Americans or recent legal immigrants. This shows that the SAT score will inadvertently help create discrimination in the labor force, as this population graphic not being able to attain higher education, will be able to compete only for low income jobs. This in turn increases the income gap between the poor and the rich even more.
The SAT it is an important test and can be the determining factor for most students regarding their college application. As an international student I had to take the test to get accepted in college in USA, even though the test was extremely expensive for my financial background. That meant I had to perform well to not risk having to pay a second time. With that said however, there are thousands of students not only outside USA , but even in the country who come from worse financial status , or family situations then mine. These reasons and recent articles I had read regarding the penalties that standardized test can have on students pushed me to come with my research idea. I wanted to lay a general model that showed that the SAT test can be discriminatory from a socio-economic perspective.
The first step that I undertook was to see if there was any previous research. Luckily there exist a variety of studies in the last thirty years that cover that topic. Reading these papers and with the help of my advisor , I decided to choose the independent socio-economic factors that would most likely affect the SAT-score. I decided to look at factors such as median family income and unemployment. To account for the effect of the family I choose the divorce rate. However , undoubtedly high school is a very influential factor on the test score. For that reason, with data from National Education Statistic Center, I built a ratio between the private and public high school enrollment and was also able to find data on ratio of students per teacher. For my dependent variables I used the combined scores of the math and reading sections from the Sat test, from 1972 to 2018.
I transformed all my non-percentage variables into natural logs. The regression model results showed that indeed socio-economic factors impact the yearly average SAT score. I was able to see that a percentage increase in the average median family income during four years of high school would positively increase the SAT score. The ratio of private/public enrollment showed that students at private high school’s fare better than students at public high schools regarding the SAT score, at the same time a decrease on the divorce rate corresponded with increase in the yearly average test Score. The model however has limitations because of time series nature of the data employed. One can observe general trends between the SES and the test score, but it can’t predict a single score.
Nonetheless, the results show that we need to take steps to allocate more funds to high schools in predominantly poor areas. There is also a need to be more involved with students that come from a stressful family life, this can be done by directing students towards psychological services which often can be stigmatized in our society. All these implications however are in the short term and offer nothing more then tunnel vision. If we think of the butterfly effect the results can show a gloomier picture. In the long term we will have thousands of students who come from disadvantaged backgrounds and will not able to attend higher education based on their test scores. As it happens to be the case, most of these students from these socio-economic background makes the majority of non-white Americans or recent legal immigrants. This shows that the SAT score will inadvertently help create discrimination in the labor force, as this population graphic not being able to attain higher education, will be able to compete only for low income jobs. This in turn increases the income gap between the poor and the rich even more.
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