Assessing Democracy Essay

Matthew Morgan Due: 3/05/08 Prof. Carey “On Democracy”

Determining what makes a person happy can be a difficult task, and determining what makes a country happy is even more of a difficult task. Some believe that the happiness of a person is directly related to how free that person is, and others believe that happiness is independent of freedom. Paul Woodruff, the author of First Democracy: The

Challenge of an Ancient Idea, states, “Democracy matters because it is the best kind of government that leads to the greatest good for the greatest number” (Woodruff, 2005).

Our goal was to test this hypothesis by comparing and contrasting different countries with different “levels” of freedom and GDP per capita, verses four social indicators to determine the overall wellbeing of a country. Without any prior knowledge of the final data analysis, our group hypothesized that the well being of a people living in a country directly corresponds to how free that country is.

In order to test our hypothesis we needed to choose the countries to compare and contrast. Our group wanted a good variation of countries so that our data set was not bias to a specific social indicator, so our choosing method was to take the twenty five wealthiest countries and the twenty five most impoverished countries. This way our conclusive data would be more accurate if one wanted to use our results as a prediction for the countries we did not consider. Once we had the country list, (On the back page), we needed to choose four social indicators that would reflect the wellbeing of the people within each country. The social indicators that we decided on were literacy rate, unemployment rate, average number of airports per square kilometer, and number of telephone lines per person. Our group wanted two social indicators that would directly represent the quality of life in each country, literacy and unemployment, and two social indicators that would indirectly represent the quality of life in each country, airports and telephone lines. But most of all we wanted all of the indicators to reflect the infrastructure of each country, that way it would be more likely that the correlations between the social indicators we related.

Each social indicator that we had was measured in a different way so we had to be consistent with our data in order to see an accurate correlation. They way we measured the literacy rate of a country was the percent of the population that could read and write the official language of that country. We chose literacy rate because we thought that it was a good measure of how educated the people of a specific country was, and we also thought that it was a good social indicator because it most likely represented the resources a country had available to put into education. Although one of the problems with this method though was that there are a decent amount of countries that have multilingual populations but may not be literate in the official language. This was a problem that we did not have the resources to fix, so all we could do was realize that this may have an affect on the correlations.

The way we measured the unemployment rate of a country was the percent of the population that was able to work but currently out of work. We thought that this was a good social indicator because it’s a good measure of those who are receiving money for their living, and also because it demonstrates the current state of a country’s economy.

One of the things that we had to consider when analyzing these correlations though was that GDP per capita already accounts for unemployment rates, so it was expected that there would be a very strong correlation between unemployment and GDP.

Airports were an interesting social indicator to measure. At first we just took the raw number of airports in a specific country and compared them to the freedom score and

GDP. After seeing virtually no correlation we realized that the landmass of the country is extremely important to consider, so we did extra calculations and came up with a ratio.

We then measured airports as a ratio with the units of number of airports per square kilometer, but we then inversed that number to represent average number of square kilometers between each airport to make the data more “eye friendly”. The problems with this method were that we didn’t take into consideration the population or population density of each country, but again we were aware of this when we analyzed the correlations.

Like airports, telephone lines were an interesting indicator to measure. Again, we just took the raw number of telephone land lines and compared them to the freedom score and GDP of each country. We then realized that we had to take population into consideration, and when we did the final calculations we came up with near perfect correlations. The biggest problem that we could think that would affect these correlations was that we only considered land lines and not cell phone lines, but since we came up with near perfect correlations we didn’t think that it was a significant factor with the majority of the countries we chose.

Our final results were not too surprising and for the most part supported our hypothesis. All of the social indicators had strong correlations with the freedom score of each country, but what was interesting was the fact that GDP per capita had stronger correlations than the freedom score in all comparisons. So we decided that this data supported our hypothesis to a point depending how one looked at the data. Our hypothesis was that the well being of a people living in a country directly corresponds to how free that country is. The strong correlations between the social indicators and the freedom score support this hypothesis, but out hypothesis didn’t mention anything about

GDP. So to answer the question of if democracy matters, yes democracy does in fact matter in the well being of a person, but according to our data money matters more to a person’s wellbeing.

Works Cited:

(2007). Freedom house: Country reports. Retrieved February 11, 2008, from Freedom

House Web site: http://freedomhouse.org/template.cfm?page=21&year=2007

(2008). CIA World Fact Book. Retrieved February 11, 2008, from CIA The World

Factbook Web site: https://www.cia.gov/library/publications/the-world- factbook/index.html

Woodruff, P (2005). First Democracy: The Challenge of an Ancient Idea. Oxford

University Press. Country List

Norway Ethiopia Switzerland Liberia Ireland Somalia Denmark Rwanda UK Afghanistan USA Sierra Leone France Tanzania Sweden Togo Australia Mali Singapore Sri Lanka South Korea Ghana Spain Laos Mexico Haiti Czech R Chad Israel Egypt Russia Sudan Poland Vietnam Chile Pakistan Venezuela India Brazil Iraq Finland Nigeria Austria Philippines Canada Honduras Germany Syria Belgium Guatemala