BEE3062 Applied Economics for Business Assignment - University Of Exeter Business School, UK

Answer all questions.

I. Basic Descriptive Statistics

1. How many cities voted for Remain i.e. they received a larger number of votes for Remain as compared to Leave?

2. What fraction of cities that voted for Leave have a lower than average unemployment rate and also have a lower than average deprivation index? Interpret your answer.

3. Plot a graph of your choice to distinguish the unemployment rate distribution between cities which voted for Remain and Leave. Interpret the graph.

4. How many geographical regions in the data have the mean unemployment rate larger than their median unemployment rate? Interpret your answer.

5. Calculate the total number of invalid votes for each geographical region.

6. Claim: Cities that voted for Leave (vote=1) have a higher % of eligible voters who voted (pct turnout) than the cities that voted for Remain (vote=0), on average. True or False.

II. Linear Regression Analysis

pct_leave = β₀ + β₁immipop + β₂deprivationindex + β₃olderpop + β₄olderpop x unemp + error (1)

1. Estimate a linear regression model with pct leave as the dependent variable and immipop, deprivationindex, olderpop and (olderpop x unemp) as the independent variables (as shown in equation (1)). Interpret the meaning of the coefficients on immipop and (olderpop x unemp).

2. Plot a graph of your choice to comment on whether the residuals of the above regression model in equation (1) are normally distributed. Conduct a test to confirm your findings.

3. What is the average elasticity of pct leave with respect to immipop in the above regression model in equation (1)? Construct a 95% confidence interval around the average elasticity.

4. Use the regression model in equation (1) to predict the outcome of voting in the Edinburgh City. The characteristics of Edinburgh City are: olderpop=38.2%; unemp=5.4%; deprivationindex=28,000 and immipop=15.8%. Based upon the prediction, did Edinburgh City vote for Leave?

5. Plot a scatterplot graph of the residuals from the regression model in equation (1) versus the deprivationindex. Discuss it.

pct_leave = β₀ + β₁immipop + β₂deprivationindex + β₃olderpop + β₄4olderpop x unemp + β₅olderpop² + error (2)

6. Estimate the regression model above in equation (2). Answer the following questions based on this new regression model:

(a) In terms of the goodness-of-fit, is this new regression model in equation (2) preferred over the model in equation (1)?

(b) The marginal effect of olderpop on pct leave at an unemployment rate of 7% in a city is zero. What is the percentage of older population in this city?

Attachment:- Applied Economics for Business Assignment Files.rar