library(vdemlite)
# Uncomment this code to start working on it.
#vdem_data <- fetchdem(indicators = c(???),
# start_year = ???, end_year = ???) |>
# mutate(regime_dummy = ifelse(v2x_regime >= 2, 1, 0)Homework 3
Analyzing Democracy
In this homework assignment, we are once again going to be exploring the correlates of democracy with V-Dem. But this time we are going to do so in the context of regression analysis.
Step 1: Load the data (12.5 pts.)
Using fetchdem from vdemlite, select the v2x_regime variable, a continuous measure of democracy like v2x_polyarchy, and at least three variables that you believe correlate with democracy for all countries and one year of your choosing. Use mutate() to transform v2x_regime into a binary variable that indicates whether a country is a democracy or not (I have provided this part of the code for you).
Step 2: Hypotheses (12.5 pts.)
Talk about why you chose the indicators you did and why you think your independent variables should be related to democracy.
Step 3: Run a bivariate linear regression model (12.5 pts.)
Run a bivariate linear regression model with your selected continuous measure of democracy as the dependent variable and one of your selected predictors as the independent variable. Use the lm() function to run the model and the summary() function to view the results.
Step 4: Interpret the results (12.5 pts.)
Interpret the results of the regression model. What is the coefficient on the predictor variable? What does this coefficient tell you about the relationship between the predictor and democracy? Is the relationship stastically significant? How about the constant (intercept term)?
Step 5: Run a Multiple Linear Regression Model (12.5 pts.)
Run a multiple linear regression model with your selected continous measure of democracy as the dependent variable and at least three of your selected predictors as the independent variables. Use the lm() function to run the model and the summary() function to view the results.
Step 6: Interpret the Results of Your Multiple Regression (12.5 pts.)
Interpret the results of the multiple regression model. What is the coefficient on each of the predictor variables? What does this coefficient tell you about the relationship between the predictors and democracy? Are the relationships statistically significant? How would you interpret the constant (intercept term)?
Step 7: Run a Multiple Logistic Regression (12.5 pts.)
Using your dichotomous measure of regime type (democratic or not) as the dependent variable, run a multiple logistic regression model with your three predictors. Use the glm() function to run the model and the summary() function to view the results.
Step 8: Interpret the Results of Your Logistic Regression (12.5 pts.)
Interpret the results of the logistic regression model. Interpret the direction and significance of each predictor. Exponentiate the coefficient of one of the predictors and interpret it?
Extra Credit (3 pts.)
Use the marginaleffects package to give the predicted probabilities of regime transition for three countries in your dataset.
Submission Instructions
After rendering your document, export your project folder and submit it on Blackboard. You will find the link to the Coding Assignment one submission portal under the Assignments link. There is a screen capture video in the Discord server that will help you understand how to do this.