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(solution) I need help answering question 2 for my project. I need a 1 page

I need help answering question 2 for my project. I need a 1 page analysis..

PEOPLE BOXES, INC.

APARTMENT COMPLEX CONSORTIUM PLANNING

EXPANSION BASED ON DEMOGRAPHIC CHANGES

BRIEF

People Boxes, Inc. is a consortium of real estate owners who seek out

growing real estate demand among young, affluent, highly-educated

workers entering the workforce or relocating to new cities. They

specialize in condominium-style new construction, saving on costs by

reusing blueprints in different cities and working with national

contracting firms. Their revenue growth depends on identifying new

markets to expand into, filling a niche in high-demand, high-income

cities.

They have collected data on demographics and income in a number of

metropolitan statistical areas (MSAs) in the United States and would like

assistance in analyzing the data to provide some background

information and some conclusions on the underlying relationships of

income and age, education levels, and rental prevalence, as well as the

determinants and effects of the supply of housing stock. 1. Youth

- Is income different between young cities and old cities? For

this, define ?young? as ?between 14 and 24?, and find the

proportion of each MSA that is young. Then split the data into

2 groups. Test to see if there?s a difference in average

household income between the youngest MSAs and the

oldest MSAs. Test to see if there?s a difference in the variance

across each of these two sub-groups.

- Use regression methods to address each of the following

models:

a. Household income depends on the percentage of the

population that is young. - b. Household income depends on the percentage of the

population that is young and the housing stock per

capita.

c. The housing stock per capita depends on the

percentage of the population is young.

Which model is better between a and b? What variables are

significant? What is your interpretation? Consider the

residual plots. Are there any problems with these

regressions? Draw any conclusions and make any

recommendations you?d like to offer your client. 2. Retirement

- Does income vary with retirement? For this, define ?retirees?

as ?people age 65 and up?, and find the proportion of each

city that is retirees. Then split the data into 2 groups. Test to

see if there?s a difference in household income between the

MSAs with the most and least retirees per capita. Test to see

if there?s a difference in the variance across each of these two

sub-groups.

- Use regression methods to address each of the following

models:

a. Household income depends on the percentage of the

population that is retirees.

b. Household income depends on the percentage of the

population that is retirees and the housing stock per

capita.

c. The housing stock per capita depends on the

percentage of the population is retirees.

- Which model is better between a and b? What variables are

significant? What is your interpretation? Consider the

residual plots. Are there any problems with these

regressions? Draw any conclusions and make any

recommendations you?d like to offer your client. 3. Education

Does income vary with college and graduate school

enrollment? For this, find the proportion of each city that is

currently enrolled in college, graduate, or professional

school. Then split the data into 2 groups. Test to see if there?s

a difference in household income between the MSAs with the

most and least proportions of the population in

postsecondary education. Test to see if there?s a difference in

the variance across each of these two sub-groups.

- Use regression methods to address each of the following

models:

a. Household income depends on the percentage of the

population that is currently enrolled in college,

graduate, or professional school.

b. Household income depends on the percentage of the

population that is currently enrolled in college,

graduate, or professional school and the housing

stock per capita.

c. The housing stock per capita depends on the

percentage of the population that is currently

enrolled in college, graduate, or professional school.

- Which model is better between a and b? What variables are

significant? What is your interpretation? Consider the

residual plots. Are there any problems with these

regressions? Draw any conclusions and make any

recommendations you?d like to offer your client. 4. Rental property

Does income vary with rental housing? For this, find the

proportion of each city?s housing stock that is currently

renter-occupied. Then split the data into 2 groups. Test to see

if there?s a difference in household income between the MSAs

with the most and least intensive rental markets. Test to see

if there?s a difference in the variance across each of these two

sub-groups.

- Use regression methods to address each of the following

models: - a. Household income depends on the percentage of the

housing stock that is renter-occupied.

b. Household income depends on the percentage of the

housing stock that is renter-occupied and the housing

stock per capita.

c. The housing stock per capita depends on the of the

housing stock that is renter-occupied.

Which model is better between a and b? What variables are

significant? What is your interpretation? Consider the

residual plots. Are there any problems with these

regressions? Draw any conclusions and make any

recommendations you?d like to offer your client. 5. Some full models

- What are the determinants of household income? Consider a

model that includes youth, retirement, education, rental

intensity, and the per-capita housing stock as independent

variables.

a. Does this model perform better than the best model from

the other portions of your report? Use an F test for joint

significance of a subset of variables to see which model

should be preferred.

b. What are your interpretations of the preferred model?

- What are the determinants of the available housing stock per

capita? Consider a model that includes youth, retirement,

education, and rental intensity as independent variables.

a. Does this model perform better than the best model from

the other portions of your report? Use an F test for joint

significance of a subset of variables to see which model

should be preferred.

b. What are your interpretations of the preferred model?

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DATE ANSWEREDJan 30, 2021

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