1- Consider the following model that relates the percentage of a household's budget spent on food SFOOD to total expenditure TOTEXP, age of the household head AGE, and the number of children in the household NK. SFOOD" Bí + Ba In(TOTEXP) + BNK - BAGE + u This model was estimated using 1200 observations. An incomplete version of this output is provided: Dependent Variable: SFOOD Included observations: 1200 Variable C In(TOTEXP) NK AGE Coefficient 1.4515 2.7648 -0.1503 R-squared S.E. of regression (₂) Sum squared resid. (RSS) Std. Error 2.2019 0.3695 0.0235 1-Statistic 5.7103 -3.9376 -6.4019 Prob. 0.5099 0.0000 0.0001 0.0000 Mean dependent var (F) 6.19434 S.D. dependent var (o,) 6.39547 46221.62 a. Fill in the following blank spaces that appear in this table. 1. The t-statistic for Bi; il. The standard error for B2; II. The estimate B; iv. R²; v. d. b. Interpret each of the estimates B2, B3, and 4. c. Compute a 95% interval estimate for pe. What does this interval tell you? d. Are each of the coefficient estimates significant at a 5% level? Why? c. Test the hypothesis that the addition of an extra child decreases the mean budget share of food by 2 percentage points against the alternative that the decrease is not equal to 2 percentage points. Use a 5% significance level.
1- Consider the following model that relates the percentage of a household's budget spent on food SFOOD to total expenditure TOTEXP, age of the household head AGE, and the number of children in the household NK. SFOOD" Bí + Ba In(TOTEXP) + BNK - BAGE + u This model was estimated using 1200 observations. An incomplete version of this output is provided: Dependent Variable: SFOOD Included observations: 1200 Variable C In(TOTEXP) NK AGE Coefficient 1.4515 2.7648 -0.1503 R-squared S.E. of regression (₂) Sum squared resid. (RSS) Std. Error 2.2019 0.3695 0.0235 1-Statistic 5.7103 -3.9376 -6.4019 Prob. 0.5099 0.0000 0.0001 0.0000 Mean dependent var (F) 6.19434 S.D. dependent var (o,) 6.39547 46221.62 a. Fill in the following blank spaces that appear in this table. 1. The t-statistic for Bi; il. The standard error for B2; II. The estimate B; iv. R²; v. d. b. Interpret each of the estimates B2, B3, and 4. c. Compute a 95% interval estimate for pe. What does this interval tell you? d. Are each of the coefficient estimates significant at a 5% level? Why? c. Test the hypothesis that the addition of an extra child decreases the mean budget share of food by 2 percentage points against the alternative that the decrease is not equal to 2 percentage points. Use a 5% significance level.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:1. Consider the following model that relates the percentage of a household's budget spent on food
SFOOD to total expenditure TOTEXP, age of the household head AGE, and the number of children in
the household NK.
SFOOD" B + B: In(TOTEXP) + BJNK - B.AGE + u
This model was estimated using 1200 observations. An incomplete version of this output is provided:
Dependent Variable: SFOOD
Included observations: 1200
Variable
C
In(TOTEXP)
NK
AGE
Coefficient
1.4515
2.7648
-0.1503
R-squared
S.E. of regression (₂)
Sum squared resid. (RSS)
Std. Error t-Statistic
2.2019
0.3695
0.0235
5.7103
-3.9376
-6.4019
Prob.
0.5099
0.0000
0.0001
0.0000
Mean dependent var (Y) 6.19434
S.D. dependent var (o,) 6.39547
46221.62
a. Fill in the following blank spaces that appear in this table.
1. The t-statistic for Bi; il. The standard error for B; iii. The estimate B; iv. R²; v. &,
b. Interpret each of the estimates B2, B), and B.
c. Compute a 95% interval estimate for D. What does this interval tell you?
d. Are each of the coefficient estimates significant at a 5% level? Why?
e. Test the hypothesis that the addition of an extra child decreases the mean budget share of food by 2
percentage points against the alternative that the decrease is not equal to 2 percentage points. Use a 5%
significance level.
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VIEWStep 3: Interpret the coefficients of independent variables.
VIEWStep 4: Calculate the 95% confidence interval for the β4
VIEWStep 5: Determine which coefficient of the estimate is significant at the 5% level.
VIEWStep 6: Perform the test for H0:β3=-2 Vs H0:β3≠-2
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