3. Consider the gretl output below on the regression of the number of cigarettes (cigs) smoked per day on log income (lincome). With this information, answer the following: Model 1: OLS, using observations 1-807 Dependent variable: cigs Coefficient Std. Error t-ratio p-value const -3.62159 6.57698 -0.5506 0.5820 1.876 0.0610 lincome 1.27054 0.677100 Mean dependent var 8.686493 S.D. dependent var 151092.8 S.E. of regression Sum squared resid R² F(1,805) Log-likelihood Schwarz criterion 0.004355 Adjusted R² 3.521023 P-value(F) -3256.327 Akaike criterion 6526.040 Hannan-Quinn (a) Interpret the coefficient on lincome. Is this result intuitive? (b) Interpret the intercept coefficient. Is this result intuitive? 13.72152 13.70011 0.003118 0.060957 6516.654 6520.258 (c) Suppose we multipled cigs by 10 (for all observations). What will happen to the estimated intercept and slope parameters (be explicit)? 1 (d) Suppose we multiplied cigs by 10 (for all observations). What will happen to SST? What will happen to R²?

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3. Consider the gretl output below on the regression of the number of cigarettes (cigs) smoked per day
on log income (lincome). With this information, answer the following:
Model 1: OLS, using observations 1-807
Dependent variable: cigs
const
lincome
Coefficient Std. Error t-ratio p-value
-3.62159 6.57698 -0.5506 0.5820
1.27054 0.677100 1.876 0.0610
Mean dependent var
Sum squared resid
R²
F(1,805)
Log-likelihood
Schwarz criterion
8.686493 S.D. dependent var
151092.8 S.E. of regression
0.004355 Adjusted R²
3.521023 P-value(F)
-3256.327 Akaike criterion
6526.040 Hannan-Quinn
13.72152
13.70011
0.003118
0.060957
6516.654
6520.258
(a) Interpret the coefficient on lincome. Is this result intuitive?
(b) Interpret the intercept coefficient. Is this result intuitive?
(c) Suppose we multipled cigs by 10 (for all observations). What will happen to the estimated
intercept and slope parameters (be explicit)?
1
(d) Suppose we multiplied cigs by 10 (for all observations). What will happen to SST? What will
happen to R²?
Transcribed Image Text:3. Consider the gretl output below on the regression of the number of cigarettes (cigs) smoked per day on log income (lincome). With this information, answer the following: Model 1: OLS, using observations 1-807 Dependent variable: cigs const lincome Coefficient Std. Error t-ratio p-value -3.62159 6.57698 -0.5506 0.5820 1.27054 0.677100 1.876 0.0610 Mean dependent var Sum squared resid R² F(1,805) Log-likelihood Schwarz criterion 8.686493 S.D. dependent var 151092.8 S.E. of regression 0.004355 Adjusted R² 3.521023 P-value(F) -3256.327 Akaike criterion 6526.040 Hannan-Quinn 13.72152 13.70011 0.003118 0.060957 6516.654 6520.258 (a) Interpret the coefficient on lincome. Is this result intuitive? (b) Interpret the intercept coefficient. Is this result intuitive? (c) Suppose we multipled cigs by 10 (for all observations). What will happen to the estimated intercept and slope parameters (be explicit)? 1 (d) Suppose we multiplied cigs by 10 (for all observations). What will happen to SST? What will happen to R²?
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