VI. KESIMPULAN DAN SARAN 97
6.3 Saran Penelitian Lanjutan 98
Mengingat adanya keterbatasan pada penelitian ini, maka berikut adalah saran penelitian lebih lanjut mengenai tata kelola pemerintahan:
1. Hubungan tata kelola pemerintahan dan pertumbuhan ekonomi bersifat kompleks, untuk itu perlu dieksplorasi hubungannya melalui jalur lain, seperti jalur investasi maupun perdagangan.
2. Jika data tersedia data dapat ditambah cakupan kabupaten/kota dan jenis infrastrukturnya.
3. Untuk menangkap adanya hubungan simultan, pada penelitian selanjutnya dapat digunakan metode lain seperti analisis jalur atau SEM (structural equation model).
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LAMPIRAN
Lampiran 1 Hasil Estimasi Model Infrastruktur Jalan dengan Program STATA SE 10
. r egr ess l nj l n10 q61 q64r 1 q64r 3 q64r 5 q71 q79r 1 q79r 2 q79r 4 q79r 5 q82 q114br 1 l npdr bkap09 l nbi n l nbi n_d79r 3 dkot a dj awa
Sour ce | SS df MS Number of obs = 245
- - - +- - - - F( 16, 228) = 14. 63 Model | 401. 871882 16 25. 1169926 Pr ob > F = 0. 0000
Resi dual | 391. 331048 228 1. 71636425 R- squar ed = 0. 5066
- - - +- - - - Adj R- s quar ed = 0. 4720
Tot al | 793. 20293 244 3. 25083168 Root MSE = 1. 3101
- - - - l nj l n10 | Coef . St d. Er r . t P>| t | [ 95% Conf . I nt er v al ] - - - +- - - - q61 | - . 0032264 . 0059065 - 0. 55 0. 585 - . 0148647 . 0084119 q64r 1 | - . 0027805 . 0111499 - 0. 25 0. 803 - . 0247505 . 0191895 q64r 3 | . 0119546 . 0073092 1. 66 0. 098 - . 0024476 . 0263569 q64r 5 | - . 0017167 . 0079836 - 0. 22 0. 830 - . 0174477 . 0140144 q71 | . 00026 . 0059197 0. 04 0. 965 - . 0114043 . 0119243 q79r 1 | - . 0069329 . 0109197 - 0. 63 0. 526 - . 0284493 . 0145836 q79r 2 | - . 0030451 . 0067707 - 0. 45 0. 653 - . 0163863 . 010296 q79r 4 | . 0023979 . 0041946 0. 57 0. 568 - . 0058672 . 010663 q79r 5 | - . 0101051 . 007988 - 1. 27 0. 207 - . 0258447 . 0056346 q82 | . 0107978 . 0128054 0. 84 0. 400 - . 0144342 . 0360298 q114br 1 | - . 0038791 . 0010433 - 3. 72 0. 000 - . 0059349 - . 0018232 l npdr bk ap09 | . 1099678 . 1739669 0. 63 0. 528 - . 2328206 . 4527562 l nbi n | - . 1112153 . 0587499 - 1. 89 0. 060 - . 2269776 . 0045469 l nbi n_q79r 3 | . 0014887 . 000597 2. 49 0. 013 . 0003123 . 002665 dk ot a | 2. 319122 . 2494501 9. 30 0. 000 1. 827599 2. 810644 dj awa | 1. 502165 . 2300491 6. 53 0. 000 1. 04887 1. 955459 _c ons | 4. 718952 1. 246827 3. 78 0. 000 2. 262175 7. 175729 - - - - . est at vi f Var i abl e | VI F 1/ VI F - - - +- - - - q64r 1 | 7. 94 0. 125885 q79r 1 | 7. 30 0. 137041 q64r 5 | 4. 38 0. 228168 l nbi n_q79r 3 | 4. 32 0. 231291 q64r 3 | 3. 60 0. 277784 q79r 5 | 3. 29 0. 303692 q79r 2 | 3. 20 0. 312247 l nbi n | 2. 89 0. 346523 q71 | 1. 80 0. 557060 q82 | 1. 79 0. 559314 q61 | 1. 58 0. 633949 l npdr bk ap09 | 1. 33 0. 753195 q79r 4 | 1. 30 0. 769065 dk ot a | 1. 29 0. 778016 q114br 1 | 1. 21 0. 826171 dj awa | 1. 15 0. 868007 - - - +- - - - Mean VI F | 3. 02 . est at het t es t
Br eus c h- Pagan / Cook - Wei s ber g t est f or het er os k edas t i ci t y Ho: Const ant var i anc e
Var i abl es: f i t t ed val ues of l nj l n10
c hi 2( 1) = 2. 66
Lampiran 2 Hasil Estimasi Model Infrastruktur Air Bersih dengan Program STATA SE 10
. r egr es s l nai r 10 q61 q64r 4 q71 q79r 1 q79r 2 q79r 4 q79r 5 q114br 3 l npdr bk ap09 l nbi n l nbi n_d79r 3 dkot a dj awa
Sour ce | SS df MS Number of obs = 245
- - - +- - - - F( 13, 231) = 4. 57 Model | 459. 490573 13 35. 3454287 Pr ob > F = 0. 0000
Resi dual | 1785. 36174 231 7. 72883871 R- squar ed = 0. 2047
- - - +- - - - Adj R- s quar ed = 0. 1599
Tot al | 2244. 85232 244 9. 20021441 Root MSE = 2. 7801
- - - - l nai r 10 | Coef . St d. Er r . t P>| t | [ 95% Conf . I nt er v al ] - - - +- - - - q61 | - . 0053183 . 011802 - 0. 45 0. 653 - . 0285717 . 0179351 q64r 4 | . 0024567 . 012163 0. 20 0. 840 - . 0215079 . 0264213 q71 | - . 0151609 . 0100225 - 1. 51 0. 132 - . 0349081 . 0045863 q79r 1 | - . 0176535 . 013785 - 1. 28 0. 202 - . 0448138 . 0095068 q79r 2 | - . 0061704 . 0138045 - 0. 45 0. 655 - . 0333692 . 0210284 q79r 4 | . 0085748 . 0087749 0. 98 0. 329 - . 0087143 . 0258638 q79r 5 | . 0200062 . 0169056 1. 18 0. 238 - . 0133026 . 053315 q114br 3 | - . 0138075 . 0044454 - 3. 11 0. 002 - . 0225664 - . 0050487 l npdr bk ap09 | 1. 032273 . 3674977 2. 81 0. 005 . 3081972 1. 756349 l nbi n | - . 1247 . 1236205 - 1. 01 0. 314 - . 3682677 . 1188678 l nbi n_q79r 3 | . 0016862 . 0012616 1. 34 0. 183 - . 0007994 . 0041719 dk ot a | 1. 634095 . 5154508 3. 17 0. 002 . 6185092 2. 649681 dj awa | . 7341221 . 4808715 1. 53 0. 128 - . 2133327 1. 681577 _c ons | 6. 346358 1. 838035 3. 45 0. 001 2. 724903 9. 967813 - - - - . est at vi f Var i abl e | VI F 1/ VI F - - - +- - - - l nbi n_q79r 3 | 4. 29 0. 233248 q79r 5 | 3. 28 0. 305318 q79r 2 | 2. 96 0. 338245 l nbi n | 2. 84 0. 352429 q79r 1 | 2. 58 0. 387228 q64r 4 | 1. 72 0. 580735 q61 | 1. 40 0. 714997 l npdr bk ap09 | 1. 32 0. 760039 q79r 4 | 1. 26 0. 791339 dk ot a | 1. 22 0. 820514 q71 | 1. 14 0. 875089 q114br 3 | 1. 13 0. 884139 dj awa | 1. 12 0. 894564 - - - +- - - - Mean VI F | 2. 02 . est at het t es t
Br eus c h- Pagan / Cook - Wei s ber g t est f or het er osk edas t i c i t y Ho: Const ant var i anc e
Var i abl es: f i t t ed val ues of l nAI R
c hi 2( 1) = 2. 37
Lampiran 3 Hasil Estimasi Model Infrastruktur Listrik dengan Program STATA SE 10
. r egr es s l nl i s 10 q61 q64r 5 q114br 4 q108 l npdr bk ap09 l nbi n l nbi n_d79r 3 dkot a dj awa
Sour ce | SS df MS Number of obs = 245
- - - +- - - - F( 9, 235) = 11. 79 Model | 145. 754183 9 16. 1949092 Pr ob > F = 0. 0000
Resi dual | 322. 889847 235 1. 37399935 R- squar ed = 0. 3110
- - - +- - - - Adj R- s quar ed = 0. 2846
Tot al | 468. 644031 244 1. 92067226 Root MSE = 1. 1722
- - - - l nl i s10 | Coef . St d. Er r . t P>| t | [ 95% Conf . I nt er v al ] - - - +- - - - q61 | - . 0035808 . 0047291 - 0. 76 0. 450 - . 0128977 . 0057361 q64r 5 | . 0078101 . 0043847 1. 78 0. 076 - . 0008282 . 0164484 q114br 4 | . 0001432 . 0025529 0. 06 0. 955 - . 0048863 . 0051727 q108 | - . 0811115 . 0389781 - 2. 08 0. 039 - . 1579027 - . 0043204 l npdr bk ap09 | . 6621737 . 1528661 4. 33 0. 000 . 3610107 . 9633367 l nbi n | - . 0126607 . 0428284 - 0. 30 0. 768 - . 0970374 . 071716 l nbi n_q79r 3 | - . 0000227 . 0003729 - 0. 06 0. 952 - . 0007574 . 0007121 dk ot a | . 9898073 . 2179475 4. 54 0. 000 . 5604266 1. 419188 dj awa | . 5309507 . 2247074 2. 36 0. 019 . 0882523 . 9736491 _c ons | 3. 489686 . 5185848 6. 73 0. 000 2. 468017 4. 511355 - - - - . est at vi f Var i abl e | VI F 1/ VI F - - - +- - - - l nbi n_q79r 3 | 2. 11 0. 474518 l nbi n | 1. 92 0. 521987 q64r 5 | 1. 65 0. 605554 q108 | 1. 48 0. 677091 dj awa | 1. 37 0. 728294 l npdr bk ap09 | 1. 28 0. 780900 q61 | 1. 26 0. 791647 dk ot a | 1. 23 0. 815885 q114br 4 | 1. 06 0. 942528 - - - +- - - - Mean VI F | 1. 48 . est at het t es t
Br eus c h- Pagan / Cook - Wei s ber g t est f or het er os k edas t i ci t y Ho: Const ant var i anc e
Var i abl es: f i t t ed val ues of l nl i s 10
c hi 2( 1) = 0. 44
Lampiran 4 Nilai korelasi Pearson infrastruktur Correlations Fit for lnjln10 Fit for lnjln10 Pearson Correlation 1 Sig. (2-tailed) N 245 Fit for lnair10 Fit for lnlis10 Fit for lnair10 Fit for lnlis10 Pearson Correlation .723** 1 Sig. (2-tailed) .000 N 245 245 Pearson Correlation .835** .817** 1 Sig. (2-tailed) .000 .000 N 245 245 245
Lampiran 5 Hasil Estimasi Metode 2SLS dengan Program SPSS 16
* 2-Stage Least Squares. TSET NEWVAR=NONE.
2SLS lnJLN10 WITH Q61 Q64R1 Q64R3 Q64R5 Q71 Q79R2 Q79R4 Q79R5 Q114bR1 lnPDRBKap09 lnBIN lnBIN_Q79R3 dKota dJawa
/INSTRUMENTS Q61 Q64R1 Q64R3 Q64R5 Q71 Q79R2 Q79R4 Q79R5 Q82 Q114b R1 lnPDRBKap09 lnBIN lnBIN_Q79R3 dKota dJawa lnJLN09
/CONSTANT.
Model Description
Type of Variable Equation 1 lnJLN10 dependent
Q61 predictor & instrumental Q64R1 predictor & instrumental Q64R3 predictor & instrumental Q64R5 predictor & instrumental Q71 predictor & instrumental Q79R2 predictor & instrumental Q79R4 predictor & instrumental Q79R5 predictor & instrumental Q114bR1 predictor & instrumental lnPDRBKap09 predictor & instrumental lnBIN predictor & instrumental lnBIN_Q79R3 predictor & instrumental dKota predictor & instrumental dJawa predictor & instrumental Q82 instrumental lnJLN09 instrumental MOD_3 Model Summary Equation 1 Multiple R .710 R Square .505 Adjusted R Square .474 Std. Error of the Estimate 1.307
ANOVA
Sum of Squares df Mean Square F Sig.
Equation 1 Regression Residual Total 400.258 14 28.590 16.734 . 000 392.945 230 1.708
Coefficients Unstandardized
Coefficients
B Std. Error Beta t Sig. Equation 1 (Constant) 5.502 .823 6.687 .000 Q61 -.003 .006 -.033 -.567 .571 Q64R1 -.009 .008 -.103 -1.134 .258 Q64R3 .011 .007 .136 1.552 .122 Q64R5 -.001 .008 -.013 -.137 .891 Q71 .003 .005 .034 .672 .502 Q79R2 -.002 .007 -.030 -.372 .710 Q79R4 .002 .004 .029 .541 .589 Q79R5 -.012 .008 -.123 -1.542 .124 Q114bR1 -.004 .001 -.187 -3.680 .000 lnPDRBKap09 .108 .174 .033 .622 .534 lnBIN -.114 .059 -.154 -1.950 .052 lnBIN_Q79R3 .002 .001 .247 2.566 .011 dKota 2.347 .246 .496 9.526 .000 dJawa 1.537 .227 .333 6.776 .000
* 2-Stage Least Squares. TSET NEWVAR=NONE.
2SLS lnAIR10 WITH Q61 Q64R4 Q71 Q79R1 Q79R2 Q79R4 Q79R5 Q114bR3 lnPDR BKap09 lnBIN lnBIN_Q79R3 dKota dJawa
/INSTRUMENTS Q61 Q64R4 Q71 Q79R1 Q79R2 Q79R4 Q79R5 Q114bR3 lnPDRBK ap09 lnBIN lnBIN_Q79R3 dKota dJawa lnAIR09
Model Description
Type of Variable Equation 1 lnAIR10 dependent
Q61 predictor & instrumental Q64R4 predictor & instrumental Q71 predictor & instrumental Q79R1 predictor & instrumental Q79R2 predictor & instrumental Q79R4 predictor & instrumental Q79R5 predictor & instrumental Q114bR3 predictor & instrumental lnPDRBKap09 predictor & instrumental lnBIN predictor & instrumental lnBIN_Q79R3 predictor & instrumental dKota predictor & instrumental dJawa predictor & instrumental lnAIR09 instrumental MOD_5 Model Summary Equation 1 Multiple R .452 R Square .205 Adjusted R Square .160 Std. Error of the Estimate 2.780
ANOVA
Sum of Squares df Mean Square F Sig. Equation 1 Regression 459.495 13 35.346 4.573 .000
Residual 1785.357 231 7.729 Total 2244.852 244
Coefficients Unstandardized
Coefficients
B Std. Error Beta t Sig. Equation 1 (Constant) 6.346 1.838 3.453 .001 Q61 -.005 .012 -.031 -.451 .653 Q64R4 .002 .012 .016 .202 .840 Q71 -.015 .010 -.095 -1.513 .132 Q79R1 -.018 .014 -.121 -1.281 .202 Q79R2 -.006 .014 -.045 -.447 .656 Q79R4 .009 .009 .064 .977 .329 Q79R5 .020 .017 .126 1.184 .238 Q114bR3 -.014 .004 -.194 -3.106 .002 lnPDRBKap09 1.032 .367 .189 2.809 .005 lnBIN -.125 .124 -.100 -1.009 .314 lnBIN_Q79R3 .002 .001 .162 1.336 .183 dKota 1.634 .515 .205 3.170 .002 dJawa .734 .481 .095 1.527 .128
* 2-Stage Least Squares. TSET NEWVAR=NONE.
2SLS lnLIS10 WITH Q61 Q64R5 Q114bR4 Q108 lnPDRBKap09 lnBIN lnBIN_Q79R3 dKota dJawa
/INSTRUMENTS Q61 Q64R5 Q114bR4 Q108 lnPDRBKap09 lnBIN lnBIN_Q79R3 d Kota dJawa lnLIS09
/CONSTANT. Model Description Type of Variable Equation 1 lnLIS10 Q61 Q64R5 Q114bR4 Q108 lnBIN dKota dJawa lnLIS09 dependent
predictor & instrumental predictor & instrumental predictor & instrumental predictor & instrumental predictor & instrumental
predictor & instrumental predictor & instrumental instrumental
Model Summary Equation 1 Multiple R .558 R Square .311 Adjusted R Square .285 Std. Error of the Estimate 1.172
ANOVA
Sum of Squares df Mean Square F Sig. Equation 1 Regression 145.746 9 16.194 11.786 .000 Residual 322.899 235 1.374 Total 468.644 244 Coefficients Unstandardized Coefficients
B Std. Error Beta t Sig. Equation 1 (Constant) 3.489 .519 6.728 .000 Q61 -.004 .005 -.046 -.757 .450 Q64R5 .008 .004 .124 1.781 .076 Q114bR4 .000 .003 .003 .056 .956 Q108 -.081 .039 -.137 -2.079 .039 lnPDRBKap09 .662 .153 .265 4.332 .000 lnBIN -.013 .043 -.022 -.296 .767 lnBIN_Q79R3 -2.248E-5 .000 -.005 -.060 .952 dKota .990 .218 .272 4.541 .000 dJawa .531 .225 .150 2.363 .019 GET FILE='D:\SUTARSONO\Tesis\Data\Data Tesis.sav'. DATASET NAME DataSet0 WINDOW=FRONT. * 2-Stage Least Squares.
TSET NEWVAR=NONE.
2SLS gpdrbkap1011 WITH lnpdrbkap10 Q40 Q54R2 Q68R1 Q106 lnJLN_cap ln AIR_cap lnLIS_cap lnmys lnbm
/INSTRUMENTS lnpdrbkap10 Q40 Q54R2 Q68R1 Q106 lnJLN_cap lnAIR_ca p lnLIS_cap lnmys lnbm
Model Description
Type of Variable Equation 1 gpdrbkap1011 dependent
lnpdrbkap10 predictor & instrumental Q40 predictor & instrumental Q54R2 predictor & instrumental Q68R1 predictor & instrumental Q106 predictor & instrumental lnJLN_cap predictor & instrumental lnAIR_cap predictor & instrumental lnLIS_cap predictor & instrumental lnmys predictor & instrumental lnbm predictor & instrumental MOD_1
Model Summary
Equation 1 Multiple R .382
R Square .146
Adjusted R Square .110
Std. Error of the Estimate 3.239
ANOVA
Sum of Squares df Mean Square F Sig. Equation 1 Regression 420.628 10 42.063 4.010 .000
Residual 2454.831 234 10.491 Total 2875.459 244
Coefficients
Unstandardized Coefficients
B Std. Error Beta t Sig. Equation 1 (Constant) 6.065 6.180 .981 .327 lnpdrbkap10 -1.955 .598 -.366 -3.270 .001 Q40 -.043 .021 -.133 -2.028 .044 Q54R2 -.032 .013 -.167 -2.389 .018 Q68R1 .027 .013 .148 2.011 .045 Q106 .030 .011 .169 2.629 .009 lnJLN_cap .171 .414 .064 .412 .681 lnAIR_cap .074 .272 .030 .274 .785 lnLIS_cap -.401 .907 .089 -.442 .659 lnmys 1.668 1.558 .083 1.070 .286 lnbm .199 .415 .032 .479 .632
* 2-Stage Least Squares. TSET NEWVAR=NONE.
2SLS gPDRBKap1011 WITH lnPDRBKap10 Q40 Q54R2 Q68R1 Q106 lnJLN_cap lnM YS lnBM
/INSTRUMENTS lnPDRBKap10 Q40 Q54R2 Q68R1 Q106 lnJLN_cap lnMYS lnBM /CONSTANT.
Model Description
Type of Variable Equation 1 gPDRBKap1011 dependent
lnPDRBKap10 predictor & instrumental Q40 predictor & instrumental Q54R2 predictor & instrumental Q68R1 predictor & instrumental Q106 predictor & instrumental lnJLN_cap predictor & instrumental lnMYS predictor & instrumental lnBM predictor & instrumental MOD_31
Model Summary
Equation 1 Multiple R .381
R Square .145
Adjusted R Square .116 Std. Error of the Estimate 3.228
ANOVA
Sum of Squares df Mean Square F Sig. Equation 1 Regression 416.845 8 52.106 5.002 .000 Residual 2458.614 236 10.418 Total 2875.459 244 Coefficients Unstandardized Coefficients
B Std. Error Beta t Sig. Equation 1 (Constant) 6.447 6.110 1.055 .292 lnPDRBKap10 -1.684 .375 -.315 -4.489 .000 Q40 -.044 .021 -.135 -2.065 .040 Q54R2 -.031 .013 -.166 -2.397 .017 Q68R1 .028 .013 .154 2.117 .035 Q106 .029 .011 .165 2.592 .010 lnJLN_cap .382 .196 .142 1.944 .053 lnMYS 1.724 1.546 .086 1.115 .266 lnBM .220 .408 .036 .539 .590
* 2-Stage Least Squares.
TSET NEWVAR=NONE.
2SLS gPDRBKap1011 WITH lnPDRBKap10 Q40 Q54R2 Q68R1 Q106 lnAIR_cap lnM YS lnBM
/INSTRUMENTS lnPDRBKap10 Q40 Q54R2 Q68R1 Q106 lnAIR_cap lnMYS lnBM /CONSTANT.
Model Description
Type of Variable Equation 1 gPDRBKap1011 dependent
lnPDRBKap10 predictor & instrumental Q40 predictor & instrumental Q54R2 predictor & instrumental Q68R1 predictor & instrumental Q106 predictor & instrumental lnAIR_cap predictor & instrumental lnMYS predictor & instrumental lnBM predictor & instrumental MOD_32 Model Summary Equation 1 Multiple R .374 R Square .140 Adjusted R Square .111 Std. Error of the Estimate 3.237
ANOVA
Sum of Squares df Mean Square F Sig. Equation 1 Regression 403.102 8 50.388 4.810 .000
Residual 2472.356 236 10.476 Total 2875.459 244
Coefficients Unstandardized
Coefficients
B Std. Error Beta t Sig. Equation 1 (Constant) 5.637 6.160 .915 .361 lnPDRBKap10 -1.890 .426 -.354 -4.432 .000 Q40 -.042 .021 -.129 -1.983 .049 Q54R2 -.032 .013 -.169 -2.434 .016 Q68R1 .028 .013 .155 2.121 .035 Q106 .028 .011 .158 2.481 .014 lnAIR_cap .312 .199 .125 1.564 .119 lnMYS 2.385 1.455 .119 1.640 .102 lnBM .177 .408 .029 .433 .665
* 2-Stage Least Squares. TSET NEWVAR=NONE.
2SLS gPDRBKap1011 WITH lnPDRBKap10 Q40 Q54R2 Q68R1 Q106 lnLIS_cap lnM YS lnBM
/INSTRUMENTS lnPDRBKap10 Q40 Q54R2 Q68R1 Q106 lnLIS_cap lnMYS lnBM /CONSTANT.
Model Description
Type of Variable Equation 1 gPDRBKap1011 dependent
lnPDRBKap10 predictor & instrumental Q40 predictor & instrumental Q54R2 predictor & instrumental Q68R1 predictor & instrumental Q106 predictor & instrumental lnLIS_cap predictor & instrumental lnMYS predictor & instrumental lnBM predictor & instrumental MOD_33 Model Summary Equation 1 Multiple R .381 R Square .145 Adjusted R Square .116 Std. Error of the Estimate 3.227
ANOVA
Sum of Squares df Mean Square F Sig. Equation 1 Regression 417.537 8 52.192 5.011 .000 Residual 2457.922 236 10.415 Total 2875.459 244 Coefficients Unstandardized Coefficients
B Std. Error Beta t Sig. Equation 1 (Constant) 6.130 6.114 1.003 .317 lnPDRBKap10 -2.097 .460 -.392 -4.560 .000 Q40 -.042 .021 -.129 -1.987 .048 Q54R2 -.033 .013 -.173 -2.511 .013 Q68R1 .026 .013 .145 1.987 .048 Q106 .030 .011 .168 2.621 .009 lnLIS_cap .826 .421 .182 1.961 .051 lnMYS 1.750 1.537 .087 1.139 .256 lnBM .152 .404 .025 .376 .707
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