Ooo AT&T; 10:22 AM 76% HW 2.pdf Done You have collected data for countries to ad
ID: 3150205 • Letter: O
Question
Ooo AT&T; 10:22 AM 76% HW 2.pdf Done You have collected data for countries to address the difficult questions of the determinantsfor ndard of living among the countries of the world. You recall from your 1 of 4 ures that the neoclassical growth model suggests that output per worker (per are determined by, among others, the saving rate and population growth rate. To ....-...r..-..- ns of this growth model, you run the following regression: RdPersINE-0.339 12.sou n 4 1.397 sk, R2-0.621, SER -0.177 where RelPersinc is GDP per worker relative to the United States mis the average population growth rate, 1960-1990, and SK is the average investment share of GDP from 1960 to 1990erememberinvestment equals saving). Numbers in parentheses are for heteroskedasticity robust standard errors (a) Calculate the I-statistics and test whether or not each of the population parameters are significantly different from zero. What is your decision on the null hypothesis? (c You remember that human capital in addition to physical capital also plays arole in determining the standard of living of a country. You therefore collect additional data on the average educational attainment in years for 1985, and add this variable (Eda)tothe above regression This results in the modified regression output (00V9) (2.2380 (029N low has the inclusion of Educ affected your previous (d)Upon checking the regression output, you realize that there areonly observations since data for Educ is not available for all 104 countries in your sample. Do you have to modify some of your statements in (d)? 4) Consider the following multiple regression model You want to consider certain hypotheses involving more than one parameter, and you know that the regression error is homoskedastic. You decide to test the joint hypotheses using the homoskedasticity- only F-statistics Foreach of the cases below specify a restricted model and indicate how you wouldExplanation / Answer
answer a) from the above table it can be seen that absolute value of t of each coefficeint is more than critical t=1.98, so each of the regression coefficient is significantly different from zero.
answer b) the critical F at 5% and 1 % is given as
since the calcualted F is more than critical F at both 1% and 5% , so we reject null hypothesis at 1% level of significance
answer c) after adding the new variable in the model the recalculate coefficent and t-value are as
absolute t-value of all the coefficent are more than critical t(.05,101)=1.9837, so inclusion of additional variable is giving better performance of model(also R2, increased).
d) only t-critical(0.05,83)=1.9889 will change, and all other inferences will be same in c)
Regression coefficient SE t=coefficient/SE intercept 0.339 0.068 4.985294118 n -12.894 3.177 -4.058545798 Sk 1.397 0.229 6.100436681 df(regression)= 2 df(error)= 101 df(total)= 103 critical t(0.05,101)= 1.98373095 Critical F(0.05,2,101)= 3.086371219 Critical F(0.01,2,101)= 4.821677235Related Questions
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