Tema: Correlacion Jugarati
Enviado por mariana141092 • 1 de Mayo de 2016 • Tarea • 805 Palabras (4 Páginas) • 156 Visitas
10.29
a) y = 1520.71 + 41.2627 (X2) – 95.2608 (X3) + 5.5443 (X4) – 129.3817 (X5) + .1481 (X6)
Dependent Variable: Y | ||||
Method: Least Squares | ||||
Date: 04/20/16 Time: 23:31 | ||||
Sample: 1971 1986 | ||||
Included observations: 16 | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | 1520.709 | 7857.290 | 0.193541 | 0.8504 |
X2 | 41.26272 | 68.81948 | 0.599579 | 0.5621 |
X3 | -95.26076 | 50.69056 | -1.879261 | 0.0896 |
X4 | 5.544340 | 3.646186 | 1.520586 | 0.1593 |
X5 | -129.3817 | 149.8806 | -0.863231 | 0.4082 |
X6 | 0.148109 | 0.118955 | 1.245087 | 0.2415 |
R-squared | 0.765808 | Mean dependent var | 10005.13 | |
Adjusted R-squared | 0.648712 | S.D. dependent var | 1163.645 | |
S.E. of regression | 689.6867 | Akaike info criterion | 16.19035 | |
Sum squared resid | 4756677. | Schwarz criterion | 16.48007 | |
Log likelihood | -123.5228 | Hannan-Quinn criter. | 16.20518 | |
F-statistic | 6.540009 | Durbin-Watson stat | 1.591020 | |
Prob(F-statistic) | 0.005970 | |||
ly = -3.67 + 1.549 (lX2) -3.5481 (lX3) + 1.6801 (lX4) – 0.0705 (lX5) + 1.0227 (lX6)
Dependent Variable: LY | ||||
Method: Least Squares | ||||
Date: 04/20/16 Time: 23:32 | ||||
Sample: 1971 1986 | ||||
Included observations: 16 | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | -3.668388 | 16.83754 | -0.217870 | 0.8319 |
LX2 | 1.548963 | 0.873594 | 1.773094 | 0.1066 |
LX3 | -3.548067 | 1.525515 | -2.325816 | 0.0424 |
LX4 | 1.680129 | 1.147407 | 1.464283 | 0.1738 |
LX5 | -0.070407 | 0.116463 | -0.604546 | 0.5589 |
LX6 | 1.022710 | 1.805134 | 0.566556 | 0.5835 |
R-squared | 0.859057 | Mean dependent var | 9.204273 | |
Adjusted R-squared | 0.788586 | S.D. dependent var | 0.119580 | |
S.E. of regression | 0.054982 | Akaike info criterion | -2.683610 | |
Sum squared resid | 0.030231 | Schwarz criterion | -2.393889 | |
Log likelihood | 27.46888 | Hannan-Quinn criter. | -2.668774 | |
F-statistic | 12.19017 | Durbin-Watson stat | 1.768430 | |
Prob(F-statistic) | 0.000541 | |||
En este caso para una función de demanda es el modelo lineal ya que si suponemos que todas las variables son 1 la función logarítmica da negativa además que la R cuadrada es alta eso puede provocar un problema de multicolinealidad.
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