Run this regression and show the results. Assess the overall significance of this model using the

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

State Name

Average Temperature in each State

Rate of food insecurity (Percentage of population)

GDP growth (Percentage)

Labor Force Participation (Percentage of Labor Force)

Obesity rates (Percentage of population)

Poverty rate (Percentage of population)

Percentage of Population with College Degree

Unemployment Rate

Net International Migration (Percentage of Population)

Logarithm of State Tax Collections per Capita

Logarithm of Income per Capita

Dummy variables for 7 regions in the US.

a. Based on the information above, write the population regression function for the case where we would like to explain poverty rate as function of the following variables : GDP growth (Percentage), Labor Force Participation (Percentage of Labor Force), Percentage of Population with College Degree, Unemployment Rate and Logarithm of Income per Capita

b. Run this regression and show the results. Assess the overall significance of this model using the F test. Interpret each coefficient and explain which ones are significant in explaining the poverty rate.

c. Test if, in this model, the relationship between poverty level and the log of income per capita is a quadratic one. If not, then continue with a linear specification.

d. A researcher claims that the Obesity rate and the logarithm of Tax Collection per capita should be included in this model. Include these variables and run a test for the marginal contribution of both variables. Depending on the result of the test you should decide if you leave these variables in your equation or you remove them.

e. Another researcher claims that international immigration should be positive related to poverty rates in different states. Include the Net International Immigration variable and test this hypothesis. If your results contradict this researcher, then you should not include this variable.

f. Finally, another researcher claims that two important variables are the average temperature in each state and the rate of food insecurity. Add these two variables and test their marginal contributions. Explain if you decide to include these variables in your model.

g. Test your final model for Multicollinearity. Show your results and explain if you decide to make any changes to your model.

h. Include some dummy variables to account for regional differences. You can use the seven categories included at the end of the test. Include these dummy variables, run the regression and show the results. Explain if there are any regional differences. (Note: use New England as your benchmark category. Do not delete any dummy variable from your model).

i. Run the RESET test for misspecification. Show the results. If you reject the null hypothesis, offer some ideas on variables that may be included to have a well-specified model.

j. Test for heteroscedasticity, show your results. If you have heteroscedasticity, then correct for it and show the results. Explain your final results. How good is your model? What are the main variables that explain poverty?

k. Predict the 95% confidence interval for the mean prediction of poverty for a state with the following characteristics:

State Name: State is in the East South Central Region

Average Temperature in each State: 61

Rate of food insecurity (Percentage of population): 11.5

GDP growth (Percentage): 1.5

Labor Force Participation (Percentage of Labor Force): 77.0

Obesity rates (Percentage of population): 30.0

Poverty rate (Percentage of population)

Percentage of Population with College Degree: 27

Unemployment Rate: 4.1

Net International Migration (Percentage of Population): 0.001

Logarithm of State Tax Collections per Capita: 7.2

Logarithm of Income per Capita: 10.5

States by Region:

• New England: Connecticut, Main, Massachusetts, New Hampshire, Rhode Island, and Vermont

• Mid-Atlantic: New Jersey, New York, and Pennsylvania

• East North-Central: Illinois, Indiana, Michigan, Ohio, and Wisconsin

• West North-Central: Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota

• South Atlantic: Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, and West Virginia

• East South-Central: Alabama, Kentucky, Mississippi, and Tennessee

• West South-Central: Arkansas, Louisiana, Oklahoma, and Texas

• Mountain: Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming

• Pacific: Alaska, California, Hawaii, Oregon, and Washington

Attachments:

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