Figure 1 presents the GRETL output from estimating the consumption function given by Consumption=β_0+β_1 Income+ε_i (1)
Posted: Sat Mar 19, 2022 5:49 pm
Figure 1 presents the GRETL output from estimating the
consumption function given by
Consumption=β_0+β_1 Income+ε_i (1)
where β_1 is the marginal propensity to consume. The
marginal propensity to save is given by 1-β_1.
Test that the marginal propensity to consume is zero. Use
a significance level of 0.05.
Test that the marginal propensity to save is zero. Use a
significance level of 0.05.
Find the correlation coefficient between Consumption and
Income.
Test the consumption function for first order serially
correlated errors using the Durbin-Watson Statistic.
Use a significance level of 0.05.
Figure 1: Estimated Consumption Function
Model 1: OLS, using observations 1940-1975 (T = 36)
Dependent variable: Consumption
Coefficient Std. Error t-ratio p-value
const 55.3748 379.473 0.1459 0.8848
Income 0.913830 0.0128644 71.04 <0.0001 ***
Mean dependent var 24664.17 S.D. dependent var 11195.21
Sum squared resid 29359196 S.E. of regression 929.2501
R-squared 0.993307 Adjusted R-squared 0.993110
F(1, 34) 5046.043 P-value(F) 1.48e-38
Log-likelihood −296.0905 Akaike criterion 596.1811
Schwarz criterion 599.3481 Hannan-Quinn 597.2865
rho 0.881474 Durbin-Watson 0.331420
consumption function given by
Consumption=β_0+β_1 Income+ε_i (1)
where β_1 is the marginal propensity to consume. The
marginal propensity to save is given by 1-β_1.
Test that the marginal propensity to consume is zero. Use
a significance level of 0.05.
Test that the marginal propensity to save is zero. Use a
significance level of 0.05.
Find the correlation coefficient between Consumption and
Income.
Test the consumption function for first order serially
correlated errors using the Durbin-Watson Statistic.
Use a significance level of 0.05.
Figure 1: Estimated Consumption Function
Model 1: OLS, using observations 1940-1975 (T = 36)
Dependent variable: Consumption
Coefficient Std. Error t-ratio p-value
const 55.3748 379.473 0.1459 0.8848
Income 0.913830 0.0128644 71.04 <0.0001 ***
Mean dependent var 24664.17 S.D. dependent var 11195.21
Sum squared resid 29359196 S.E. of regression 929.2501
R-squared 0.993307 Adjusted R-squared 0.993110
F(1, 34) 5046.043 P-value(F) 1.48e-38
Log-likelihood −296.0905 Akaike criterion 596.1811
Schwarz criterion 599.3481 Hannan-Quinn 597.2865
rho 0.881474 Durbin-Watson 0.331420