# State’s Naval Power

In Canvas you will find a dataset labeled RAP_naval_rep.dta. This is a slightly different version of the Crisher and Souva (2014) naval data set from a paper I published in 2017.
The variables are:

• “navycat” Naval Categories. A 4-tier categorical variable of naval power.

• “democ” A binary measure of democracy. 1 = Democracy, 0 = Non-democracy .

• “advecon” A binary measure of advanced economy using energy consumption. 1 = Yes, 0 = no.

• “lrgstate” A binary measure of large state using urban population. 1 = yes, 0 = no.

• “ton10” Total tonnage (in ten thousands). So, 10,000 tons would be shown as 1 ton.

• “energy” Continuous measure of energy consumption.

• “urbprop” Continuous measure of portion of total population in urban areas.

• “polity2” Continuous measure of democracy. Higher numbers means more democratic.

Here’s the assignment: I want you to evaluate some potential explanations for a state’s naval power. In other words, we are going to use the tonnage measure (ton10) as a dependent variable. So, we have a simple research question – what factors impact a state’s naval power. This will require you to conduct the three different types of bivariate hypotheses tests we’ve been using in class.

1. Is there a relationship between regime type and naval category? How did you come up with your answer?
2. Is there a relationship between advanced economies and naval category? How did you come up with your answer?
3. Is there a relationship between large states and naval category? How did you come up with your answer?
4. Do democracies have more tonnage than non-democracies? How did you come up with your answer?
6. Do large states have more tonnage than small states? How did you come up with your answer?
7. Is there a correlation between tonnage, energy consumption, urban population, and the continuous measure of democracy? How is this different from what you found in the previous tests?
8. What is the main weakness for these different tests?
9. In a paragraph, sum up your findings.

The above questions can be answered without seeking outside academic resources (you should cite the textbook and the Crisher & Souva article). The Stata codes necessary for the above questions have all been discussed in class or were used in the in-class assignment.
Your paper is to be 2-3 pages long with typical formatting – double spacing, 12 point font, and 1 inch margins. Please include any graphs (you should include at least one scatter plot) as a separate page at the end of your paper with a proper title (Figure 1: XXXX). Graphs/figures do not count toward the 2-3 page count. You should include at least two tables as well.

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