(Continuation from Chapter 4, number 5)You have learned in one of your economics courses that one of the determinants of per capita income (the "Wealth of Nations")is the population growth rate. Furthermore you also found out that the Penn World Tables contain income and population data for 104 countries of the world. To test this theory, you regress the GDP per worker (relative to the United States)in 1990 (RelPersInc)on the difference between the average population growth rate of that country (n)to the U.S. average population growth rate (n_us )for the years 1980 to 1990. This results in the following regression output: $\widehat {\\text { RelPersInc }}$ = 0.518 - 18.831×(n - n_us), R²=0.522, SER = 0.197
(0.056)(3.177)
(a)Is there any reason to believe that the variance of the error terms is homoskedastic?
(b)Is the relationship statistically significant?

Question

(Continuation from Chapter 4, number 5)You have learned in one of your economics courses that one of the determinants of per capita income (the "Wealth of Nations")is the population growth rate. Furthermore you also found out that the Penn World Tables contain income and population data for 104 countries of the world. To test this theory, you regress the GDP per worker (relative to the United States)in 1990 (RelPersInc)on the difference between the average population growth rate of that country (n)to the U.S. average population growth rate (n_us )for the years 1980 to 1990. This results in the following regression output:

\widehat {\\text { RelPersInc }}

= 0.518 - 18.831×(n - n_us), R²=0.522, SER = 0.197
(0.056)(3.177)
(a)Is there any reason to believe that the variance of the error terms is homoskedastic?
(b)Is the relationship statistically significant?

Quizplus · Accepted Answer

The Answer of (Continuation from Chapter 4, number 5)You have learned in one of your economics courses that one of the determinants of per capita income (the "Wealth of Nations")is the population growth rate. Furthermore you also found out that the Penn World Tables contain income and population data for 104 countries of the world. To test this theory, you regress the GDP per worker (relative to the United States)in 1990 (RelPersInc)on the difference between the average population growth rate of that country (n)to the U.S. average population growth rate (n_us )for the years 1980 to 1990. This results in the following regression output: $\widehat {\text { RelPersInc }}$ = 0.518 - 18.831×(n - n_us), R²=0.522, SER = 0.197 (0.056)(3.177) (a)Is there any reason to believe that the variance of the error terms is homoskedastic? (b)Is the relationship statistically significant?

(Continuation from Chapter 4, Number 5)You Have Learned in One textRelPersInc^\widehat {\\text { RelPersInc }}textRelPersInc

(Continuation from Chapter 4, Number 5)You Have Learned in One $\widehat {\\text { RelPersInc }}$