LAMPIRAN Langkah-Langkah Pemilihan Model Regresi Data Panel

LAMPIRAN Langkah-Langkah Pemilihan Model Regresi Data Panel Hasil Common Effect Method: Panel Least Squares Date: 12/06/11 Time: 18:16 C 12.40080 1.872750 6.621707 0.0000 LOG(PDRB) 0.145885 0.114857 1.270151 0.2124 LOG(MYS) -5.157553 0.400902-12.86487 0.0000 SHARE_PERTANIAN -0.027868 0.005025-5.545917 0.0000 LOG(PENGANGGURAN) 0.054077 0.053468 1.011393 0.3188 R-squared 0.847999 Mean dependent var 2.530722 Adjusted R-squared 0.830628 S.D. dependent var 0.459488 S.E. of regression 0.189102 Akaike info criterion -0.376595 Sum squared resid 1.251581 Schwarz criterion -0.165485 Log likelihood 12.53190 Hannan-Quinn criter. -0.300264 F-statistic 48.81555 Durbin-Watson stat 0.470897

71 Hasil Fixed Effect Method: Panel Least Squares Date: 12/06/11 Time: 18:16 C 10.98810 1.465929 7.495657 0.0000 LOG(PDRB) -0.489244 0.139912-3.496797 0.0016 LOG(MYS) -1.040229 0.524818-1.982073 0.0574 SHARE_PERTANIAN -0.004925 0.003915-1.257805 0.2189 LOG(PENGANGGURAN) 0.038281 0.025106 1.524771 0.1385 Cross-section fixed (dummy variables) R-squared 0.990465 Mean dependent var 2.530722 Adjusted R-squared 0.986719 S.D. dependent var 0.459488 S.E. of regression 0.052953 Akaike info criterion -2.795490 Sum squared resid 0.078513 Schwarz criterion -2.288826 Log likelihood 67.90980 Hannan-Quinn criter. -2.612296 F-statistic 264.4081 Durbin-Watson stat 1.411928

72 Hasil Random Effect Method: Panel EGLS (Cross-section random effects) Date: 12/06/11 Time: 18:16 Swamy and Arora estimator of component variances C 9.498533 1.311218 7.244055 0.0000 LOG(PDRB) -0.203844 0.115235-1.768952 0.0856 LOG(MYS) -2.052676 0.435154-4.717122 0.0000 SHARE_PERTANIAN -0.005554 0.003581-1.551038 0.1299 LOG(PENGANGGURAN) 0.066210 0.023160 2.858769 0.0071 S.D. Rho Cross-section random 0.233854 0.9512 Idiosyncratic random 0.052953 0.0488 Weighted Statistics R-squared 0.562943 Mean dependent var 0.254971 Adjusted R-squared 0.512994 S.D. dependent var 0.089857 S.E. of regression 0.062708 Sum squared resid 0.137629 F-statistic 11.27028 Durbin-Watson stat 1.069881 Prob(F-statistic) 0.000006 Unweighted Statistics R-squared 0.455705 Mean dependent var 2.530722 Sum squared resid 4.481749 Durbin-Watson stat 0.032855

73 1. Uji Common Effect dengan Fixed Effect Signifikansi Model Fixed Effect Ho : α 1 = α 2 = =α i (intersep sama) H 1 : sekurang-kurangnya ada 1 intersep yang berbeda Wilayah kritis : F (0,05; 7;28 ) = 2,36 Statistik Uji F: 59.76427 Keputusan : Tolak H 0 Kesimpulan : Model Fixed Effect lebih baik daripada Common Effect pada α = 5 persen, intersep untuk tiap kabupaten/kota tidak sama.

74 2. Uji Fixed Effect dengan Random Effect (Hausman Test) H 0 : model Random Effect lebih baik daripada Fixed Effect H 1 : model Fixed Effect lebih baik daripada Random Effect Correlated Random Effects - Hausman Test Equation: Untitled Test cross-section random effects Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob. Cross-section random 18.082184 4 0.0012 Cross-section random effects test comparisons: Variable Fixed Random Var(Diff.) Prob. LOG(PDRB) -0.489244-0.203844 0.006296 0.0003 LOG(MYS) -1.040229-2.052676 0.086075 0.0006 SHARE_PERTANIAN -0.004925-0.005554 0.000003 0.6912 LOG(PENGANGGURAN) 0.038281 0.066210 0.000094 0.0040 Cross-section random effects test equation: Method: Panel Least Squares Date: 12/06/11 Time: 18:23 C 10.98810 1.465929 7.495657 0.0000 LOG(PDRB) -0.489244 0.139912-3.496797 0.0016 LOG(MYS) -1.040229 0.524818-1.982073 0.0574 SHARE_PERTANIAN -0.004925 0.003915-1.257805 0.2189 LOG(PENGANGGURAN) 0.038281 0.025106 1.524771 0.1385 Cross-section fixed (dummy variables) R-squared 0.990465 Mean dependent var 2.530722 Adjusted R-squared 0.986719 S.D. dependent var 0.459488 S.E. of regression 0.052953 Akaike info criterion -2.795490 Sum squared resid 0.078513 Schwarz criterion -2.288826 Log likelihood 67.90980 Hannan-Quinn criter. -2.612296 F-statistic 264.4081 Durbin-Watson stat 1.411928

75 Karena nilai probabilitas Chi-Square berdasarkan hasil estimasi diperoleh probabilitas sebesar 0,0012 yang berarti tolak Ho. Kesimpulan : model Fixed Effect lebih baik daripada Random Effect. 3. Uji Asumsi Homoskedastisitas Untuk medeteksi adanya heteroskedastisitas dapat menggunakan metode General Least Square (Cross section Weight) yaitu dengan membandingkan sum square Residual pada Weighted Statistics dengan sum square Residual Unweighted Statistics. Jika sum square Residual pada Weighted Statistics lebih kecil dari sum square Residual Unweighted Statistics, maka terjadi heteroskedastisitas. Hasil output memperlihatkan adanya indikasi heteroskedastisitas.

76 Method: Panel EGLS (Cross-section weights) Date: 12/06/11 Time: 18:24 Linear estimation after one-step weighting matrix C 11.38855 1.250168 9.109618 0.0000 LOG(PDRB) -0.517855 0.126073-4.107568 0.0003 LOG(MYS) -1.091039 0.430742-2.532929 0.0172 SHARE_PERTANIAN -0.002860 0.003038-0.941462 0.3545 LOG(PENGANGGURAN) 0.027069 0.020699 1.307705 0.2016 Cross-section fixed (dummy variables) Weighted Statistics R-squared 0.992760 Mean dependent var 3.058640 Adjusted R-squared 0.989916 S.D. dependent var 1.521740 S.E. of regression 0.052219 Sum squared resid 0.076350 F-statistic 349.0327 Durbin-Watson stat 1.785111 Unweighted Statistics R-squared 0.990284 Mean dependent var 2.530722 Sum squared resid 0.080003 Durbin-Watson stat 1.332777

77 Treatment pelanggaran ini dapat dilakukan dengan mengestimasi GLS dengan white-heteroscedasticity. Berdasarkan prosedur di atas, maka hasil estimasi Fixed Effect sebagai berikut: Method: Panel EGLS (Cross-section weights) Date: 12/06/11 Time: 18:25 Linear estimation after one-step weighting matrix White cross-section standard errors & covariance (d.f. corrected) C 11.38855 1.545020 7.371135 0.0000 LOG(PDRB) -0.517855 0.089410-5.791907 0.0000 LOG(MYS) -1.091039 0.274328-3.977127 0.0004 SHARE_PERTANIAN -0.002860 0.001622-1.763247 0.0888 LOG(PENGANGGURAN) 0.027069 0.007465 3.626274 0.0011 Cross-section fixed (dummy variables) Weighted Statistics R-squared 0.992760 Mean dependent var 3.058640 Adjusted R-squared 0.989916 S.D. dependent var 1.521740 S.E. of regression 0.052219 Sum squared resid 0.076350 F-statistic 349.0327 Durbin-Watson stat 1.785111 Unweighted Statistics R-squared 0.990284 Mean dependent var 2.530722 Sum squared resid 0.080003 Durbin-Watson stat 1.332777 4. Uji Asumsi Autokolerasi Hasil estimasi menunjukkan nilai statistic Durbin Watson sebesar 1,785111. Nilai Durbin Watson tersebut berada pada interval du < DW < 4-dU (1.721 < 1,785111 < 2.279). Hal ini menunjukkan tidak adanya autokolerasi.

78 5. Uji Multikolinieritas Berdasarkan matriks korelasi pearson antar variabel independen terlihat bahwa korelasi antarvariabel kurang dari 0,8, sehingga dapat disimpulkan model telah memenuhi asumsi terbebas dari multikolinieritas. Variabel PDRB MYS Share_Pertanian Pengangguran PDRB 1 MYS 0,347285 1 Share_Pertanian -0,580666-0,749964 1 Pengangguran 0,612862 0,590386-0,698824 1 6. Uji Normalitas. Hasil uji normalitas pada Eviews 6.0 sebagai berikut: 6 5 4 3 2 1 0-0.05 0.00 0.05 0.10 Series: Standardized Residuals Sample 2005 2009 Observations 40 Mean 9.02e-18 Median 0.002639 Maximum 0.090148 Minimum -0.085441 Std. Dev. 0.044246 Skewness 0.090564 Kurtosis 2.305704 Jarque-Bera 0.858091 Probability 0.651130 Berdasarkan nilai probabilitas Jarque-Bera yang lebih besar dari taraf nyata lima persen, dapat disimpulkan bahwa error term terdistribusi dengan normal.