LAMPIRAN
Lampiran 1 Pengujian Regresi (Ordinary Least Square) untuk Persamaan dengan Variabel Investasi Pemerintah Total
. regress y L.y pad ip is tk to
Source | SS df MS Number of obs = 48 ---+--- F( 6, 41) = 3015.88 Model | 35.9292414 6 5.9882069 Prob > F = 0.0000 Residual | .081407907 41 .001985559 R-squared = 0.9977 ---+--- Adj R-squared = 0.9974
Total | 36.0106493 47 .766184028 Root MSE = .04456 ---
y | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---+--- y | L1. | .9947476 .0207137 48.02 0.000 .9529154 1.03658 pad | .0104697 .0229019 0.46 0.650 -.0357816 .0567211 ip | .0148429 .0201877 0.74 0.466 -.025927 .0556129 isr | .026357 .0577353 0.46 0.650 -.0902417 .1429557 tk | -.0159015 .0269769 -0.59 0.559 -.0703824 .0385795 to | -.0581091 .0313401 -1.85 0.071 -.1214016 .0051834 _cons | .0522852 .2150363 0.24 0.809 -.3819893 .4865598 ---
Lampiran 2 Pengujian Panel Statis Fixed Effect untuk Persamaan dengan Variabel Investasi Pemerintah Total
xtreg y L.y pad ip is tk to, fe
Fixed-effects (within) regression Number of obs = 48 Group variable: prov Number of groups = 12 R-sq: within = 0.8984 Obs per group: min = 4 between = 0.9493 avg = 4.0 overall = 0.9484 max = 4 F(6,30) = 44.23 corr(u_i, Xb) = 0.6823 Prob > F = 0.0000 --- y | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---+--- y | L1. | .3957105 .0959387 4.12 0.000 .1997775 .5916436 pad | .0081945 .0329362 0.25 0.805 -.0590703 .0754593 ip | .0848774 .0402406 2.11 0.043 .0026952 .1670596 isr | -.0477333 .048287 -0.99 0.331 -.1463484 .0508818 tk | .4245797 .1273521 3.33 0.002 .1644921 .6846673 to | -.0065183 .0467642 -0.14 0.890 -.1020235 .088987 _cons | 2.584141 1.820786 1.42 0.166 -1.1344 6.302682 ---+--- sigma_u | .27907226 sigma_e | .02971426
rho | .98879013 (fraction of variance due to u_i) --- F test that all u_i=0: F(11, 30) = 5.65 Prob > F = 0.0001 . est sto fixed
. xttest3
Modified Wald test for groupwise heteroskedasticity in fixed effect regression model
H0: sigma(i)^2 = sigma^2 for all i chi2 (12) = 428.88
Lampiran 3 Pengujian Panel Statis Random Effect untuk Persamaan dengan Variabel Investasi Pemerintah Total
. xtreg y L.y pad ip is tk to, re
Random-effects GLS regression Number of obs = 48 Group variable: prov Number of groups = 12 R-sq: within = 0.7538 Obs per group: min = 4 between = 0.9997 avg = 4.0 overall = 0.9977 max = 4 Random effects u_i ~ Gaussian Wald chi2(6) = 13801.56 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
---
y | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---+--- y | L1.| .9884906 .0232373 42.54 0.000 .9429462 1.034035 pad | .0086373 .0249878 0.35 0.730 -.0403378 .0576125 ip | .0194664 .0220619 0.88 0.378 -.0237741 .0627068 isr | .0241405 .0582071 0.41 0.678 -.0899434 .1382244 tk | -.0086702 .0300748 -0.29 0.773 -.0676158 .0502754 to | -.0568285 .0340416 -1.67 0.095 -.1235488 .0098918 _cons | .0100759 .2397706 0.04 0.966 -.4598659 .4800178 ---+--- sigma_u | .00888387 sigma_e | .02971426
rho | .08205262 (fraction of variance due to u_i) --- . est sto random
. xttest0
Breusch and Pagan Lagrangian multiplier test for random effects y[prov,t] = Xb + u[prov] + e[prov,t]
Estimated results: | Var sd = sqrt(Var) ---+--- y | .766184 .8753194 e | .0008829 .0297143 u | .0000789 .0088839 Test: Var(u) = 0 hi2(1) = 2.40 Prob > chi2 = 0.1214
Lampiran 4 Uji Kebaikan (Uji Hausman) antara Fixed dan Random Effect untuk Persamaan dengan Variabel Investasi Pemerintah Total
. hausman fixed random ---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B)) | fixed random Difference S.E.
---+--- L.y | .3957105 .9884906 -.5927801 .093082 pad | .0081945 .0086373 -.0004428 .0214571 ip | .0848774 .0194664 .0654111 .0336538 isr | -.0477333 .0241405 -.0718738 . tk | .4245797 -.0086702 .4332499 .1237499 to | -.0065183 -.0568285 .0503102 .0320634 --- b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg Test: Ho: difference in coefficients not systematic
chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 57.95
Prob>chi2 = 0.0000
Lampiran 5 Pengujian Panel Dinamis (FD-GMM) untuk Persamaan dengan Variabel Investasi Pemerintah Total
. xtabond y pad ip is tk to, two
Arellano-Bond dynamic panel-data est Number of obs = 36 Group variable: prov Number of groups = 12 Time variable: tahun Obs per group: min = 3
avg = 3 max = 3 Number of instruments = 12 Wald chi2(6) = 3395.12 Prob > chi2 = 0.0000
Two-step results
--- y | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---+--- y | L1. | .6459881 .0359854 17.95 0.000 .575458 .7165183 pad | .0240306 .0106641 2.25 0.024 .0031293 .0449319 ip | .0380402 .0126101 3.02 0.003 .0133248 .0627556 is | -.001116 .0007248 -1.54 0.124 -.0025365 .0003045 tk | .2134423 .0745279 2.86 0.004 .0673702 .3595144 to | -.0558758 .0099183 -5.63 0.000 -.0753152 -.0364363 _cons | 1.960779 .9210196 2.13 0.033 .1556137 3.765944 ---
Warning: gmm two-step standard errors are biased; robust standard errors are recommended.
Instruments for differenced equation GMM-type: L(2/.).y
Standard: D.pad D.ip D.is D.tk D.to Instruments for level equation
Standard: _cons . estat abond
Arellano-Bond test for zero autocorrelation in first-differenced errors +---+ |Order | z Prob > z| |---+---| | 1 |-1.0691 0.2850 | | 2 | 1.0287 0.3036 | +---+ H0: no autocorrelation . estat sargan
Sargan test of overidentifying restrictions H0: overidentifying restrictions are valid chi2(5) = 5.785619
Lampiran 6 Pengujian Regresi (Ordinary Least Square) untuk Persamaan dengan Variabel Investasi Pemerintah untuk Keperluan Infrastruktur
regress y L.y pad ipI isr tk to
Source | SS df MS Number of obs = 48 ---+--- F( 6, 41) = 2967.45 Model | 35.9279158 6 5.98798597 Prob > F = 0.0000 Residual | .082733473 41 .00201789 R-squared = 0.9977 ---+--- Adj R-squared = 0.9974
Total | 36.0106493 47 .766184028 Root MSE = .04492 ---
y | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---+--- y | L1. | .9989047 .0212455 47.02 0.000 .9559984 1.041811 pad | .0184909 .0186364 0.99 0.327 -.0191461 .056128 ipI | .0267158 .1109349 0.24 0.811 -.1973218 .2507535 isr | -.0018663 .0724478 -0.03 0.980 -.1481775 .1444449 tk | -.0210101 .0265037 -0.79 0.433 -.0745355 .0325153 to | -.0474691 .0284391 -1.67 0.103 -.1049031 .0099649 _cons | .1489365 .1456143 1.02 0.312 -.1451375 .4430105
Lampiran 7 Pengujian Panel Statis Fixed Effect untuk Model Persamaan dengan Variabel Investasi Pemerintah untuk Keperluan Infrastruktur xtreg y L.y pad ipI isr tk to, fe
Fixed-effects (within) regression Number of obs = 48 Group variable: prov Number of groups = 12 R-sq: within = 0.8868 Obs per group: min = 4 between = 0.9240 avg = 4.0 overall = 0.9237 max = 4 F(6,30) = 39.15 corr(u_i, Xb) = 0.1617 Prob > F = 0.0000 ---
y | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---+--- y | L1. | .4449883 .1018338 4.37 0.000 .237016 .6529606 pad | .0451719 .0302542 1.49 0.146 -.0166154 .1069593 ipI | .0472535 .1231376 0.38 0.047 -.2042271 .298734 is | -.0245487 .0633617 -0.39 0.701 -.1539505 .1048532 tk | .5622102 .1234363 4.55 0.000 .3101197 .8143007 to | -.0121819 .0501893 -0.24 0.810 -.1146822 .0903183 _cons | .6472756 1.819932 0.36 0.725 -3.069522 4.364074 ---+--- sigma_u | .2518568 sigma_e | .03137559
rho | .98471772 (fraction of variance due to u_i) --- F test that all u_i=0: F(11, 30) = 4.91 Prob > F = 0.0002 . est sto fixed
. xttest3
Modified Wald test for groupwise heteroskedasticity in fixed effect regression model
H0: sigma(i)^2 = sigma^2 for all i chi2 (12) = 427.94
Lampiran 8 Pengujian Panel Statis Random Effect untuk Persamaan dengan Variabel Investasi Pemerintah untuk Keperluan Infrastruktur . xtreg y L.y pad ipI isr tk to, re
Random-effects GLS regression Number of obs = 48 Group variable: prov Number of groups = 12 R-sq: within = 0.7357 Obs per group: min = 4 between = 0.9998 avg = 4.0 overall = 0.9977 max = 4 Random effects u_i ~ Gaussian Wald chi2(6) = 17804.70 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 ---
y | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---+--- y | L1. | .9989047 .0212455 47.02 0.000 .9572642 1.040545 pad | .0184909 .0186364 0.99 0.321 -.0180358 .0550177 ipI | .0267158 .1109349 0.24 0.810 -.1907127 .2441443 isr | -.0018663 .0724478 -0.03 0.979 -.1438613 .1401287 tk | -.0210101 .0265037 -0.79 0.428 -.0729565 .0309363 to | -.0474691 .0284391 -1.67 0.095 -.1032088 .0082706 _cons | .1489365 .1456143 1.02 0.306 -.1364623 .4343352 ---+--- sigma_u | 0 sigma_e | .03137559
rho | 0 (fraction of variance due to u_i)
--- . est sto random
. xttest0
Breusch and Pagan Lagrangian multiplier test for random effects y[prov,t] = Xb + u[prov] + e[prov,t]
Estimated results: | Var sd = sqrt(Var) ---+--- y | .766184 .8753194 e | .0009844 .0313756 u | 0 0 Test: Var(u) = 0 chi2(1) = 3.04 Prob > chi2 = 0.0811
Lampran 9 Uji Kebaikan (Uji Hausman) antara Fixed dan Random Effect untuk Persamaan dengan Variabel Investasi Pemerintah untuk Keperluan
Infrastruktur . hausman fixed random ---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B)) | fixed random Difference S.E.
---+--- L.y | .4449883 .9989047 -.5539164 .0995929 pad | .0451719 .0184909 .026681 .0238327 jlnr | .0472535 .0267158 .0205376 .0534444 isr | -.0245487 -.0018663 -.0226824 . tk | .5622102 -.0210101 .5832204 .1205573 to | -.0121819 -.0474691 .0352872 .0413543 --- b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg Test: Ho: difference in coefficients not systematic
chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 43.38
Prob>chi2 = 0.0000
Lampiran 10 Pengujian Panel Dinamis (FD-GMM) untuk Persamaan dengan Variabel Investasi Pemerintah untuk Keperluan Infrastruktur . xtabond y pad ipI isr tk to, two
Arellano-Bond dynamic panel-data est Number of obs = 36 Group variable: prov Number of groups = 12
Time variable: tahun Obs per group: min = 3 avg = 3 max = 3 Number of instruments = 12 Wald chi2(6) = 2041.09 Prob > chi2 = 0.0000
Two-step results
--- y | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---+--- y | L1. | .7391827 .0797895 9.26 0.000 .5827982 .8955673 pad | .0316399 .0109124 2.90 0.004 .0102519 .0530279 ipI | .1502803 .0733305 2.05 0.040 .0065553 .2940054 isr | .0625037 .0314307 1.99 0.047 .0009007 .1241067 tk | .3055488 .1178583 2.59 0.010 .0745507 .5365468 to | -.0636979 .0196757 -3.24 0.001 -.1022615 -.0251342 _cons | -.3889274 1.351338 -0.29 0.773 -3.0375 2.259646 ---
Warning: gmm two-step standard errors are biased; robust standard errors are recommended.
Instruments for differenced equation GMM-type: L(2/.).y
Standard: D.pad D.jlnr D.isr D.tk D.to Instruments for level equation
Standard: _cons . estat abond
Arellano-Bond test for zero autocorrelation in first-differenced errors +---+ |Order | z Prob > z| |---+---| | 1 |-1.0558 0.2911 | | 2 | 1.051 0.2933 | +---+ H0: no autocorrelation . estat sargan
Sargan test of overidentifying restrictions H0: overidentifying restrictions are valid chi2(5) = 5.465542
