solucion primera pratica calificada

UNIVERSIDAD NACIONAL DE PIURA
FACULTAD DE ECONOMIA
DPTO. ACAD. DE ECONOMIA
PRIMERA PRÁCTICA CALIFICADA DE ECONOMETRIA II
1º
El investigador especifica el siguiente modelo:
INFLA = a + b DEV + c INFLA(-1) + U1
DEV = e + f INFLA + g OM + U2
Se le pide:
1.1.
Determinar que tipo de variable es DEV. (3 puntos)
U2
OM
U1
DEV
INFLA
INFLA(-1)
DEV es una variable endógena porque la 1 ≠ 0; 1 ≠ 0; 1 = 0.
1.2.
Verificar que INFLA se puede tratar como exógena. (3 puntos)
Dependent Variable: INFLA
Method: Least Squares
Sample (adjusted): 1966 1995
Included observations: 30 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-82.57999
52.31249
-1.578590
0.1261
OM
1.881879
0.070400
26.73136
0.0000
INFLA(-1)
0.057916
0.036004
1.608608
0.1193
R-squared
0.969493
Mean dependent var
439.0467
Dependent Variable: DEV
Method: Least Squares
Sample (adjusted): 1966 1995
Included observations: 30 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
13.78205
68.01619
0.202629
0.8410
INFLA
3.551016
0.196643
18.05815
0.0000
OM
-1.196951
1.222981
-0.978716
0.3367
INFLAF
-1.798276
0.664943
-2.704408
0.0119
R-squared
0.981510
Mean dependent var
467.7206
Wald Test:
Equation: EQ02
Test Statistic
Value
df
Probability
F-statistic
7.313823
(1, 26)
0.0119
Chi-square
7.313823
1
0.0068
U1(-1)
2
Por lo tanto, INFLA no se puede tratar como exógena (0.0119 < 0.05).
1.3.
Determine si DEV precede a INFLA. (2 puntos)
Pairwise Granger Causality Tests
Sample: 1965 1995
Lags: 1
Null Hypothesis:
DEV does not Granger Cause INFLA
Obs
F-Statistic
Probability
30
37.2895
1.6E-06
29
96.3697
3.4E-12
28
254.866
1.1E-16
27
239.977
2.4E-15
26
259.265
5.3E-14
25
238.378
9.2E-12
24
113.790
4.7E-08
Lags: 2
DEV does not Granger Cause INFLA
Lags: 3
DEV does not Granger Cause INFLA
Lags: 4
DEV does not Granger Cause INFLA
Lags: 5
DEV does not Granger Cause INFLA
Lags: 6
DEV does not Granger Cause INFLA
Lags: 7
DEV does not Granger Cause INFLA
Por lo tanto, DEV precede a INFLA.
1.4.
Estimar la inflación por mínimos cuadrados bietápicos y verifique si los residuos son ruido blanco. (5 puntos)
Dependent Variable: INFLA
Method: Two-Stage Least Squares
Sample (adjusted): 1966 1995
Included observations: 30 after adjustments
Instrument list: C INFLA(-1) OM
Variable
Coefficient
Std. Error
t-Statistic
Prob.
34.69346
121.1971
0.286257
0.7769
DEV
0.895496
0.078979
11.33837
0.0000
INFLA(-1)
-0.032987
0.088073
-0.374546
0.7109
C
R-squared
0.830432
Mean dependent var
439.0467
3
Sample: 1966 1995
Included observations: 30
Autocorrelation
******| .
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Partial Correlation
******| .
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****| .
AC
|
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PAC
Q-Stat
Prob
1 -0.706 -0.706
16.478
0.000
2
18.799
0.000
0.260 -0.473
Breusch-Godfrey Serial Correlation LM Test:
Obs*R-squared
19.04021
Probability
0.000013
Dependent Variable: RESID
Method: Two-Stage Least Squares
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.164135
3.965196
0.041394
0.9673
DEV
0.096410
0.059906
1.609353
0.1196
INFLA(-1)
0.061732
0.081109
0.761095
0.4534
RESID(-1)
-0.757757
0.182295
-4.156761
0.0003
R-squared
0.634674
Mean dependent var
-4.74E-14
Breusch-Godfrey Serial Correlation LM Test:
Obs*R-squared
25.41995
Probability
0.000003
Dependent Variable: RESID
Method: Two-Stage Least Squares
Variable
Coefficient
Std. Error
t-Statistic
C
0.262797
2.614112
0.100530
0.9207
DEV
-0.099776
0.051623
-1.932780
0.0647
INFLA(-1)
0.357758
0.073319
4.879495
0.0001
RESID(-1)
-1.916799
0.230260
-8.324508
0.0000
RESID(-2)
-0.907620
0.153804
-5.901147
0.0000
R-squared
0.847332
Prob.
Mean dependent var
-4.74E-14
White Heteroskedasticity Test:
F-statistic
18.29038
Probability
0.000000
Obs*R-squared
22.35953
Probability
0.000170
Dependent Variable: RESID^2
Method: Least Squares
Sample: 1966 1995
Included observations: 30
4
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-404686.6
159624.4
-2.535243
0.0179
DEV
1223.399
498.8658
2.452360
0.0215
DEV^2
-0.209424
0.044965
-4.657488
0.0001
INFLA(-1)
6877.288
1172.786
5.864059
0.0000
INFLA(-1)^2
-0.908351
0.155901
-5.826473
0.0000
R-squared
0.745318
Mean dependent var
353010.9
White Heteroskedasticity Test:
F-statistic
128.9509
Probability
0.000000
Obs*R-squared
28.92337
Probability
0.000024
Dependent Variable: RESID^2
Method: Least Squares
Sample: 1966 1995
Included observations: 30
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-166608.2
64244.77
-2.593335
0.0159
DEV
5303.023
387.6539
13.67979
0.0000
DEV^2
-3.261528
0.252905
-12.89626
0.0000
DEV*INFLA(-1)
8.505432
0.703145
12.09628
0.0000
INFLA(-1)
-917.8264
785.6013
-1.168311
0.2542
INFLA(-1)^2
0.025842
0.097632
0.264693
0.7935
R-squared
0.964112
Mean dependent var
353010.9
ARCH Test:
F-statistic
5.864728
Probability
0.022439
Obs*R-squared
5.175066
Probability
0.022913
Dependent Variable: RESID^2
Method: Least Squares
Sample (adjusted): 1967 1995
Included observations: 29 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
C
210907.4
236635.2
0.891277
0.3807
RESID^2(-1)
0.422434
0.174435
2.421720
0.0224
R-squared
0.178451
Mean dependent var
Prob.
365161.7
5
ARCH Test:
F-statistic
3.404235
Probability
0.049257
Obs*R-squared
5.993283
Probability
0.049955
Dependent Variable: RESID^2
Method: Least Squares
Sample (adjusted): 1968 1995
Included observations: 28 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
C
265455.7
248505.6
1.068208
RESID^2(-1)
0.509999
0.195457
2.609260
0.0151
RESID^2(-2)
-0.211910
0.195458
-1.084170
0.2886
R-squared
0.214046
Mean dependent var
Prob.
0.2956
378181.6
25
Series: Residuals
Sample 1966 1995
Observations 30
20
15
10
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
-4.74e-14
-25.18521
2586.527
-1678.946
604.3043
1.918302
14.27546
Jarque-Bera
Probability
177.3195
0.000000
5
0
-2000
-1000
0
1000
2000
3000
Modh = modrho*sqr(modt/(1-modt*modvb3)) = -4.411001
2º
Comente y fundamente su respuesta. (7 puntos)
2.1.
En todo modelo multiecuacional se puede aplicar la prueba de causalidad y de exogeneidad.
2.2.
La superexogeneidad requiere que exista precedencia.