Hasil Dan Interpretasi

Kuis Ekonometrik

Nama : Suci Safitriani

NIM : 09.6147

Kelas : 4 SE3

Soal Quiz 3

Data yang digunakan adalah data yang berasal dari 609 perusahaan yang

dengan series waktu 1998-2008. Variabel-variabel yang digunakan terdiri atas nilai

produksi, tenaga kerja, capital dan bahan baku. Dan dalam pengolahannya, variabel-

variabel tersebut di logaritma naturalkan. Berikut ini adalah hasil pengolahan dengan

menggunakan eviews :

1. Uji Unit Root

Uji ini digunakan untuk melihat kestasioner data yang digunakan.

Hipotesis :

Ho : ρ¿=1

H 1: ρ¿<1

Output :

Group unit root test: Summary Series: LNY_30_1Date: 11/22/12 Time: 14:50Sample: 1998 2008Exogenous variables: Individual effectsAutomatic selection of maximum lagsAutomatic selection of lags based on SIC: 0 to 1Newey-West bandwidth selection using Bartlett kernel

Cross-Method Statistic Prob.** sections ObsNull: Unit root (assumes common unit root process) Levin, Lin & Chu t* -1504.01 0.0000 2422 23800

Null: Unit root (assumes individual unit root process) Im, Pesaran and Shin W-stat -70.0799 0.0000 2422 23800ADF - Fisher Chi-square 10124.2 0.0000 2422 23800PP - Fisher Chi-square 11619.5 0.0000 2422 24220

** Probabilities for Fisher tests are computed using an asymptotic Chi -square distribution. All other tests assume asymptotic normality.

Keputusan : Tolak Ho, karena 0,00<0,05

Kesimpulan : Dengan tingkat kepercayaan 95% dapat disimpulkan bahwa data

sudah bersifat stasioner.

Berdasarkan output di atas dapat dilihat bahwa nilai probabilitas = 0,000 sehingga

dapat dikatakan bahwa data sudah stasioner sehingga bisa dilanjutkan ke proses

pengolahan selanjutnya.

2. Estimasi Model

Model Pooled

Model Common effect merupakan teknik yang paling sederhana untuk

mengestimasi data panel, yaitu dengan mengkombinasikan data time series dan cross

section dengan metode Ordinary Least Square (OLS). Dalam pendekatan ini, tidak

memperhatikan dimensi individu maupun waktu. Sehingga diasumsikan intersep dan

slope antar individu tetap sepanjang waktu dan individu.

Persamaan Umum : Y ¿=α+ β ' X ¿+ε ¿

Output :

Dependent Variable: LNY_30?

Method: Pooled Least Squares

Date: 11/22/12 Time: 15:03

Sample: 1998 2008

Included observations: 11

Cross-sections included: 609

Total pool (balanced) observations: 6699

Variable Coefficient Std. Error t-Statistic Prob.

C 3.923850 0.179383 21.87414 0.0000

LNL_30? 0.336357 0.043808 7.677954 0.0000

LNK_30? 0.035424 0.012361 2.865730 0.0042

LNM_30? 0.616664 0.004774 129.1794 0.0000

LNK_30?*LNL_30? 0.004378 0.002972 1.473101 0.1408

R-squared 0.869777 Mean dependent var 14.55332

Adjusted R-squared 0.869699 S.D. dependent var 1.645467

S.E. of regression 0.593968 Akaike info criterion 1.796763

Sum squared resid 2361.629 Schwarz criterion 1.801846

Log likelihood -6013.259 Hannan-Quinn criter. 1.798519

F-statistic 11177.52 Durbin-Watson stat 0.531390

Prob(F-statistic) 0.000000

Model Fixed (FEM)

Pendekatan Model Fixed Effect mengasumsikan bahwa perbedaan antar individu

dapat diakomodasi melalui perbedaan intersepnya. Model ini didasarkan oleh adanya

perbedaan intersep antara individu, namun intersepnya sama antar waktu (time

invariant). Disamping itu, model ini juga mengasumsikan bahwa koefisien regresi

(slope) tetap antar individu dan antar waktu.

Persamaan Umum : Y ¿=α i+ β ' X¿+ε¿

Output :

Dependent Variable: LNY_30?Method: Pooled Least SquaresDate: 11/22/12 Time: 15:03Sample: 1998 2008Included observations: 11Cross-sections included: 609



C 5.700524 0.155975 36.54767 0.0000LNL_30? 0.248196 0.036903 6.725620 0.0000LNK_30? -0.011129 0.009460 -1.176420 0.2395LNM_30? 0.575883 0.006194 92.96837 0.0000

LNK_30?*LNL_30? -0.000710 0.002324 -0.305684 0.7599

Effects Specification

Cross-section fixed (dummy variables)

R-squared 0.959743 Mean dependent var 14.55332Adjusted R-squared 0.955695 S.D. dependent var 1.645467S.E. of regression 0.346352 Akaike info criterion 0.804321Sum squared resid 730.0735 Schwarz criterion 1.427452Log likelihood -2081.074 Hannan-Quinn criter. 1.019517F-statistic 237.0787 Durbin-Watson stat 1.437555Prob(F-statistic) 0.000000

catatan : Fixed Effect Terlampir

Model Random (REM)

Estimasi data panel dengan model Fixed Effect melalui variabel dummy

menunjukkan ketidakpastian model yang digunakan. Untuk mengatasi masalah ini

kita bisa menggunakan variabel residual yang dikenal dengan metode Random Effect.

Di dalam model ini kita akan memilih estimasi data panel dimana residual mungkin

saling berhubungan antar waktu dan antar individu. Sehingga model Random Effect

mengasumsikan bahwa setiap individu mempunyai perbedaan intersep yang

merupakan variabel random atau stokastik.

Persamaan Umum : Y ¿=α+ β' X ¿+μi+ε¿

Output :

Date: 11/22/12 Time: 15:08

Sample: 1998 2008




Swamy and Arora estimator of component variances


C 5.040776 0.146339 34.44592 0.0000

LNL_30? 0.316948 0.035106 9.028410 0.0000

LNK_30? -0.012714 0.009245 -1.375315 0.1691

LNM_30? 0.597252 0.005496 108.6784 0.0000

LNK_30?*LNL_30? 0.001472 0.002265 0.649808 0.5158

Effects SpecificationS.D. Rho

Cross-section random 0.408319 0.5816Idiosyncratic random 0.346352 0.4184

Weighted Statistics

R-squared 0.713664 Mean dependent var 3.605993Adjusted R-squared 0.713493 S.D. dependent var 0.667818S.E. of regression 0.357459 Sum squared resid 855.3384F-statistic 4171.031 Durbin-Watson stat 1.236149Prob(F-statistic) 0.000000

Unweighted Statistics

R-squared 0.855214 Mean dependent var 14.55332Sum squared resid 2625.732 Durbin-Watson stat 0.402679

Catatan : Random Effect Terlampir

3. Pemilihan Model Terbaik

Uji Chow

Uji Signifikansi Fixed effect dilakukan dengan uji F statistik. Uji F ini digunakan

untuk mengetahui apakah teknik regresi data panel dengan Fixed Effect lebih baik

dari model regresi data panel tanpa variabel dummy (Common Effect) dengan melihat

Residual Sum of Squares (RSS).

Hipotesis :

Ho : Pooled Model lebih baik

H1 : Fixed Effect Model Leboh baik

Atau

Ho : α 1=α 2=……α i

H1 : minimal ada satu intersept yang berbeda.

Output :

Redundant Fixed Effects Tests

Pool: PANEL30

Test cross-section fixed effects

Effects Test Statistic d.f. Prob.

Cross-section F 22.369882 (608,6086) 0.0000

Cross-section Chi-square

7864.37000

8 608 0.0000

Cross-section fixed effects test equation:


Method: Panel Least Squares

Date: 11/22/12 Time: 15:07

Sample: 1998 2008





C 3.923850 0.179383 21.87414 0.0000

LNL_30? 0.336357 0.043808 7.677954 0.0000

LNK_30? 0.035424 0.012361 2.865730 0.0042

LNM_30? 0.616664 0.004774 129.1794 0.0000

LNK_30?*LNL_30? 0.004378 0.002972 1.473101 0.1408








Statistik Uji : F = (RSS1−RSS2)/(N−1)(RSS2) /(NT−N−k )

Dimana : RSS1 = Sum Square Resid pooled model, RSS2 = Sum Square Resid

FEM, N=banyaknya jumlah cross section, k = banyaknya variabel.

Tolak Ho jika F hitung > F tabel atau Prob < α

Keputusan : Karena Prob < α (α=0,05) 0,00 < 0,05 maka Tolak Ho

Kesimpulan : Dengan tingkat kepercayaan 95% dapat disimpulkan bahwa Fixed

Effect Model lebih baik digunakan untuk data dibanding Pooled Model.

Berdasarkan hasil output eviews yang dihasilkan dapat dilihat bahwa probabilitas

uji F nya 0,00 dan lebih kecil dari alpha = 5% sehingga dapat disimpulkan bahwa

model fixed effect lebih baik digunakan daripada model pooled.

Uji Hausman (Fixed vs Random)

Untuk melihat apakah model mengikuti random effect atau fixed

effect.

Hipotesis :

Ho : Random effect (individual effect uncorelated) lebih baik

H1 : Fixed effect lebih baik

Atau

Ho : Cov (v i , x¿¿=0

H1 : Cov (v i , x¿¿≠0

Output :

Correlated Random Effects - Hausman Test

Pool: PANEL30

Test cross-section random effects

Test Summary

Chi-Sq.

Statistic Chi-Sq. d.f. Prob.

Cross-section random 440.226889 4 0.0000

Cross-section random effects test comparisons:

Variable Fixed Random Var(Diff.) Prob.

LNL_30? 0.248196 0.316948 0.000129 0.0000

LNK_30? -0.011129 -0.012714 0.000004 0.4294

LNM_30? 0.575883 0.597252 0.000008 0.0000

(LNK_30?

*LNL_30?) -0.000710 0.001472 0.000000 0.0000

Cross-section random effects test equation:


Method: Panel Least Squares

Date: 11/22/12 Time: 15:09

Sample: 1998 2008





C 5.700524 0.155975 36.54767 0.0000

LNL_30? 0.248196 0.036903 6.725620 0.0000

LNK_30? -0.011129 0.009460 -1.176420 0.2395

LNM_30? 0.575883 0.006194 92.96837 0.0000

LNK_30?*LNL_30? -0.000710 0.002324 -0.305684 0.7599










Statistik Uji :X2hitung= (b−β )' Var ¿

Dimana : b= koefisien random effect; â=koefisien fixed effect

Tolak Ho jika X2hitung>X 2

k ,α (k=jumlah koef slope) atau p-value < α

Keputusan : Karena Prob<α (α=0,05) 0,00<0,05 maka Tolak Ho

Kesimpulan : Dengan tingkat kepercayaan 95% dapat disimpulkan bahwa Fixed

Effect Model lebih baik digunakan untuk data dibanding Random Effect Model.

Berdasarkan hasil output dapat dilihat bahwa probabilitas F statistiknya 0,00 atau

kurang dari alpha 5% sehingga diperoleh model terbaik yang digunakan untuk data

ini adalah FIXED EFFECT MODEL (FEM).

4. Pemilihan Estimator

Uji LM (Heteroskedastis vs Homoskedastis)

Hipotesis :

Ho : σ 2i=σ2

H1 : σ 2i ≠ σ2

Output :

LM test for hetero versus homo

chi-sqr(608) = 3348.500p-value = 0.000000

Statistik Uji :

LM = T2∑i=1

n

(σ i

2

σ 2 −1)2

X (n−1, α )

dimana T=jml observasi, n=jml individu; σ i2=varian residual persamaan ke-i; σ 2

=varian residual persamaan system.

Keputusan Tolah Ho, jika LM test > X (n−1 ,α ) atau Prob < α

Keputusan : Tolak H karena Prob < α 0,0000 < 0,05

Kesimpulan : Dengan tingkat kepercayaan 95% dapat disimpullan bahwa struktur

varian covarian residual bersifat heteroskedastik lebih baik dibandingkan dengan

yang bersifat homoskedastik

5. Interpretasi Model Terbaik :

Jadi berdasarkan uji-uji yang telah dilakukan, diperoleh model estimasi terbaik adalah

Fixed Effect Model dangan Cross-Section Weight. Adapun outputnya dapat dilihat

pada tabel di bawah ini :

Dependent Variable: LNY_30?Method: Pooled EGLS (Cross-section weights)Date: 11/23/12 Time: 12:25Sample: 1998 2008Included observations: 11Cross-sections included: 609Total pool (balanced) observations: 6699Linear estimation after one-step weighting matrix


C 4.983707 0.099668 50.00324 0.0000LNL_30? 0.182928 0.022731 8.047643 0.0000LNK_30? -0.009014 0.005790 -1.556819 0.1196LNM_30? 0.641990 0.004995 128.5368 0.0000

LNK_30?*LNL_30? -0.000327 0.001459 -0.224289 0.8225



Weighted Statistics

R-squared 0.984378 Mean dependent var 22.41908Adjusted R-squared 0.982807 S.D. dependent var 11.83751S.E. of regression 0.340977 Sum squared resid 707.5897F-statistic 626.6249 Durbin-Watson stat 1.349710Prob(F-statistic) 0.000000

Unweighted Statistics

R-squared 0.958943 Mean dependent var 14.55332Sum squared resid 744.5808 Durbin-Watson stat 1.438758

Fixed Effect : Terlampir

Berdasarkan output di atas probabilitas F nya 0,00 lebih kecil dari alpha 5%,

sehingga dapat disimpulkan secara simultan, variabel-variabel yaitu pertumbuhan

modal, pertumbuhan tenaga kerja dan pertumbuhan bahan baku berpengaruh

signifikan terhadap pertumbuhan nilai produksi.

Adjusted R-squarednya bernilai 0,98. Artinya, perubahan variabel pertumbuhan

nilai produksi dapat dijelaskan sebesar 98% oleh variabel independentnya yaitu

pertumbuhan modal, pertumbuhan tenaga kerja dan pertumbuhan bahan baku.

Sedangkan 2% dijelaskan oleh variabel lain. Nilai Durbin Watson mendekati 2 yaitu

1,349 sehingga dapat dikatakan bahwa tidak terjadi autokorelasi.

Untuk tingkat signifikansi 95%, variabel pertumbuhan tenaga kerja dan

pertumbuhan bahan baku berpengaruh signifikan terhadap variabel pertumbuhan nilai

produksi. Sedangkan variabel pertumbuhan capital tidak berpengaruh secara

signifikan terhadap pertumbuhan nilai produksi.

Berdasarkan output juga dapat dilihat bahwa pertumbuhan tenaga kerja sebanyak

1% dapat menaikkan pertumbuhan nilai produksi sebesar 0,18%. Setiap kenaikan 1%

pada pertumbuhan capital dapat menyebabkan penurunan pertumbuhan nilai produksi

sebesar 0,009%. Dan kenaikan pertumbuhan bahan baku sebesar 1% dapat

menyebabkan kenaikan pertumbuhan nilai produksi sebesar 0.64%.

Lampiran :

Random Effect

_1--C_2--C_3--C_4--C_5--C_6--C_7--C_8--C_9--C

_10--C_11--C_12--C_13--C_14--C_15--C_16--C_17--C_18--C_19--C_20--C_21--C_22--C_23--C_24--C_25--C_26--C_27--C_28--C_29--C_30--C_31--C_32--C_33--C_34--C_35--C_36--C_37--C_38--C_39--C_40--C_41--C_42--C_43--C_44--C_45--C_46--C_47--C

-0.1841640.056264

-0.244613-0.1201530.044157

-0.1737150.743540

-0.1676950.344795

-0.0536770.3240380.1066370.7104630.9383710.0787490.0507130.9054530.6432110.3563840.6492701.1712640.4613600.4474390.4473300.3303930.4803670.5323420.3977590.071642

-0.116818-0.087054-0.102039-0.248820-0.120554-0.110880-0.115877-0.1579260.335928

-0.2217690.1900570.221738

-0.2640270.223545

-0.3635680.066870

-0.337466-0.203057

_204--C_205--C_206--C_207--C_208--C_209--C_210--C_211--C_212--C_213--C_214--C_215--C_216--C_217--C_218--C_219--C_220--C_221--C_222--C_223--C_224--C_225--C_226--C_227--C_228--C_229--C_230--C_231--C_232--C_233--C_234--C_235--C_236--C_237--C_238--C_239--C_240--C_241--C_242--C_243--C_244--C_245--C_246--C_247--C_248--C_249--C_250--C

1.5579961.110788

-0.077363-0.170898-0.250871-0.2586660.068738

-0.125148-0.3102630.3659090.1271110.378453

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-0.421393


0.0508540.3120850.203026

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-0.1293300.057795

-0.1129360.115493

-0.098917-0.7264890.589618

-0.007466-0.185343

_48--C_49--C_50--C_51--C_52--C_53--C_54--C_55--C_56--C_57--C_58--C_59--C_60--C_61--C_62--C_63--C_64--C_65--C_66--C_67--C_68--C_69--C_70--C_71--C_72--C_73--C_74--C_75--C_76--C_77--C_78--C_79--C_80--C_81--C_82--C_83--C_84--C_85--C_86--C_87--C_88--C_89--C_90--C_91--C_92--C_93--C_94--C_95--C_96--C_97--C_98--C_99--C

_100--C_101--C_102--C

0.5200530.0458570.1377830.4060970.8507761.5309061.0069291.0577861.2723850.116794

-0.316295-0.183156-0.070334-0.353670-0.3409880.252454

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-0.0775151.551249

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-0.254848-0.314669-0.265032-0.344630-0.285689-0.364670-0.126597-0.058029

_251--C_252--C_253--C_254--C_255--C_256--C_257--C_258--C_259--C_260--C_261--C_262--C_263--C_264--C_265--C_266--C_267--C_268--C_269--C_270--C_271--C_272--C_273--C_274--C_275--C_276--C_277--C_278--C_279--C_280--C_281--C_282--C_283--C_284--C_285--C_286--C_287--C_288--C_289--C_290--C_291--C_292--C_293--C_294--C_295--C_296--C_297--C_298--C_299--C_300--C_301--C_302--C_303--C_304--C_305--C

-0.058375-0.276907-0.2633580.708651

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0.982675-0.0490880.016760

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-0.072673-0.101661-0.0295050.0183030.025975

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-0.534153-0.5051280.601878

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-0.277610-0.386411


-0.1872020.587270

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-0.097750-0.1258740.153691

-0.284679-0.012651-0.648206-0.780947-0.115768-0.730314-0.211855-0.347342-0.4964690.0696240.4920670.1463100.0054950.7966021.9255290.6237032.313116

-0.170136-0.106230-0.250086-0.262139-0.078832-0.607216-0.5719770.015100

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-0.437243-0.2990110.0784610.112699

-0.4161930.390005

-0.2960170.195219


0.0045250.347008

-0.1614380.230073

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-0.166992-0.0884170.2847590.0467100.190915

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-0.208876-0.113277-0.137344-0.266693-0.127376-0.437191-0.369461


-0.455206-0.627258-0.585207-0.363991-0.202453-0.9463490.563932

-0.3252420.451449

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-0.2721910.002977

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-0.049416-0.2786911.0488561.007695

-0.704462-0.001927-0.259003-0.6064100.014101

_158--C_159--C_160--C_161--C_162--C_163--C_164--C_165--C_166--C_167--C_168--C_169--C_170--C_171--C_172--C_173--C_174--C_175--C_176--C_177--C_178--C_179--C_180--C_181--C_182--C_183--C_184--C_185--C_186--C_187--C_188--C_189--C_190--C_191--C_192--C_193--C_194--C_195--C_196--C_197--C_198--C_199--C_200--C_201--C_202--C_203--C

-0.175767-0.316465-0.581744-0.214002-0.530728-0.509815-0.186331-0.490890-0.478385-0.312340-0.616793-0.471776-0.266620-0.308559-0.286764-0.4579210.634279

-0.896356-0.265735-0.073518-0.689117-0.458869-0.3321120.471020

-0.5590390.322555

-0.543100-0.2310430.3761980.155301

-0.2647050.1336140.082098

-0.030661-0.1754591.2382331.5568950.9764441.0700991.3454451.9665360.9869581.2308791.2000541.1764080.572415


-0.057196-0.034251-0.048517-0.192568-0.455791-0.123086-0.301734-0.1534390.072543

-0.197636-0.0577790.075234

-0.463832-0.181543-0.121351-0.261138-0.485531-0.415953-0.617321-0.220205-0.404660-0.400849-0.367342-0.345006-0.335272-0.392628-0.226619-0.410615-0.410244-0.540379-0.401752-0.535855-0.220115-0.345596-0.1323120.245446

-0.315092-0.3505330.278788

-0.3768820.074986

-0.0545960.801793

-0.242825-0.412471-0.283495


0.300526-0.400420-0.433163-0.3994980.2461580.937082

-0.066143-0.0051650.7393790.8403710.3224121.487619

-0.4121350.188416

-0.470584-0.240668-0.385653-0.178472-0.999186-1.026581-1.007610-0.988358-1.032861-0.256166-0.2034850.338434

-0.0795760.1751500.304986

-0.0320770.3421960.014872

-0.144697-0.3744110.3462020.4021960.228103

-0.435973-0.400100-0.498835-0.080871-0.450534-0.178623-0.187932-0.416375-0.531102

Fixed effect

_1--C_2--C_3--C_4--C_5--C_6--C_7--C_8--C_9--C

_10--C_11--C_12--C_13--C_14--C_15--C_16--C_17--C_18--C_19--C_20--C_21--C_22--C_23--C_24--C_25--C_26--C_27--C_28--C_29--C_30--C_31--C_32--C_33--C_34--C_35--C_36--C_37--C_38--C_39--C_40--C_41--C_42--C_43--C_44--C_45--C_46--C_47--C

-0.321019-0.069825-0.380227-0.244172-0.073930-0.3294711.133240

-0.2511240.305934

-0.1247930.4984130.0930481.0229831.2208150.0143780.0157991.3218070.8648260.8124501.0515331.5360970.6038400.4566160.5613370.2968730.5160100.5778700.4602070.016946

-0.201314-0.166278-0.187935-0.353726-0.206988-0.199138-0.200201-0.2490950.341477

-0.2560950.1236400.142458

-0.2260180.644056

-0.4346850.022808

-0.448494-0.333006


1.5429031.092581

-0.047497-0.140827-0.268774-0.3451340.0546480.071146

-0.3547970.8695210.3241580.923352

-0.806292-0.393659-0.308264-0.532950-0.627456-0.410279-0.592327-0.081222-0.284636-0.317776-0.270196-0.190155-0.266391-0.330624-0.135298-0.029484-0.126296-0.264591-0.908487-0.343977-0.264571-0.5081930.0716392.076636

-0.450242-0.462802-0.364326-0.4609260.3123860.565125

-0.2630870.0343020.0923971.038470

-0.512059


0.2233730.2908790.563650

-0.1088570.331073

-0.382831-0.031502-0.4876570.039111

-0.2251700.807424

-0.3972300.220150

-0.4206960.8650240.117341

-0.3999630.087539

-0.669996-0.281768-0.497904-0.577502-0.3666741.4402250.219859

-0.1193230.040479

-0.1094892.4172890.8955870.7376101.137916

-0.1388590.0455520.2174081.0084230.3788030.818904

-0.1646020.0538810.011209

-0.012911-0.142261-0.9044780.5425220.055391

-0.231627

_48--C_49--C_50--C_51--C_52--C_53--C_54--C_55--C_56--C_57--C_58--C_59--C_60--C_61--C_62--C_63--C_64--C_65--C_66--C_67--C_68--C_69--C_70--C_71--C_72--C_73--C_74--C_75--C_76--C_77--C_78--C_79--C_80--C_81--C_82--C_83--C_84--C_85--C_86--C_87--C_88--C_89--C_90--C_91--C_92--C_93--C_94--C_95--C_96--C_97--C_98--C_99--C

_100--C_101--C_102--C

0.5669080.0655820.1153780.4802760.8168921.6608040.9556481.0627211.2921170.272561

-0.408200-0.214271-0.110381-0.465313-0.4263070.318811

-0.374352-0.3988040.897497

-0.008923-0.587532-0.0622540.7936861.330356

-0.0528921.663966

-0.336869-0.1518190.8247390.7891810.6914841.2103331.2175230.4007660.218514

-0.7150001.052518

-0.195068-0.1604130.394970

-0.380525-0.063285-0.400290-0.065191-0.1534240.5439270.539820

-0.371852-0.454313-0.303633-0.280030-0.402923-0.463344-0.197233-0.013251


0.122633-0.162132-0.1060141.150769

-0.2083620.8895700.682618

-0.718602-0.324696-0.303816-0.271877-0.9080910.6376130.0762620.0490940.183531

-0.198645-0.1463210.566092

-0.2023590.128244

-0.403691-0.0640710.2929950.193399

-0.2682030.0917920.287750

-0.0226620.1067120.2520290.3182760.323729

-0.3729240.1825670.301930

-0.1653260.160558

-0.0588820.044693

-0.6210340.2144930.196217

-0.3154930.4932480.212957

-0.321143-0.0138640.1013960.131302

-0.520898-0.0718270.3185330.1860320.175362


1.385036-0.1087640.191011

-0.152511-0.079341-0.143382-0.147887-0.117776-0.171282-0.624353-0.539374-0.544738-0.480552-0.009492-0.326818-0.420674-0.3877891.017606

-0.252562-0.2276290.033517

-0.527489-0.428875-0.279996-0.5650481.576576

-0.3233120.052057

-0.292536-0.046625-0.3906440.107092

-0.097618-0.147740-0.057920-0.012758-0.036954-0.3237520.123002

-0.0872120.1110430.180977

-0.667418-0.6331050.844351

-0.175943-0.185987-0.165224-0.2080070.0213130.322886

-0.4909610.993044

-0.405268-0.457717


-0.2872540.790672

-0.542940-0.458249-0.3389870.9428260.042462

-0.192269-0.2158190.160948

-0.2927910.038255

-0.721815-0.949493-0.146875-0.840391-0.266590-0.424507-0.6479590.0089460.6355550.125758

-0.0759721.1519281.9654660.5275252.368310

-0.212964-0.188465-0.256452-0.225761-0.109818-0.767790-0.7275480.085849

-0.317935-0.1441030.472129

-0.555601-0.184410-0.1470221.0445220.5523111.7973310.8202330.4026031.279318

-0.488675-0.3143320.1137800.179809

-0.5233390.740719

-0.3378490.179238


-0.0577840.359075

-0.2561590.4461490.070633

-0.563880-0.2401850.154830

-0.331411-0.473050-0.596408-0.509256-0.287333-0.818826-0.351848-0.527948-0.628656-0.241302-0.527651-0.678151-0.771495-0.315524-0.447117-0.247564-0.681317-0.099102-0.451473-0.274116-0.360865-0.712932-0.272350-0.2603740.493734

-0.2296960.0524260.3356750.4942020.278824

-0.2657810.8255510.4971830.7772381.0343380.7094360.7001290.6918541.0046690.719845

-0.317033-0.231175-0.093781-0.357187-0.217538-0.582129-0.485398


-0.545883-0.782703-0.718333-0.423915-0.184618-1.1804340.946151

-0.4127740.636631

-0.0498161.603613

-0.128037-0.2342260.906946

-0.289887-0.209846-0.539542-0.536138-0.3182880.0688990.013128

-0.2377971.5613700.042307

-0.585742-0.574262-0.458496-0.106690-0.721658-0.0645720.022881

-0.234013-0.541489-1.202412-1.1976650.0847630.250137

-0.108699-0.039448-0.269625-0.324031-0.286625-0.289658-0.491350-0.6460600.111374

-0.141702-0.4001380.9849581.009027

-0.864429-0.122454-0.343504-0.745063-0.061234


-0.256599-0.280845-0.640901-0.251607-0.600576-0.571167-0.218083-0.532753-0.529034-0.365561-0.773774-0.443684-0.315705-0.282604-0.419575-0.5429950.962802

-1.076602-0.2996850.004768

-0.850693-0.544537-0.4260980.554693

-0.6710160.497902

-0.661307-0.3185280.4982630.166615

-0.3619990.1355080.2955370.322854

-0.0265821.3220221.5894790.9891701.0141031.3631582.0105110.9100801.2343791.2578271.1887050.492280


-0.122810-0.053985-0.067092-0.278168-0.561351-0.154505-0.391803-0.1507210.028189

-0.2982800.0772100.207576

-0.552849-0.266462-0.149848-0.243576-0.515910-0.554328-0.713654-0.197630-0.518312-0.536612-0.270729-0.430003-0.456686-0.499437-0.261139-0.528995-0.487103-0.700975-0.541489-0.644740-0.009671-0.429650-0.0742240.585684

-0.391896-0.3626570.309837

-0.4628500.029284

-0.1185061.237539

-0.329687-0.533224-0.390445


0.356853-0.476706-0.567229-0.5674430.2803230.847811

-0.1986110.0654590.9839481.2147580.6189391.507285

-0.2137970.337949

-0.592638-0.326236-0.366095-0.270826-1.206764-1.239006-1.218040-1.201502-1.253387-0.305284-0.2534870.611626

-0.1642520.1329470.275987

-0.0983790.323148

-0.036686-0.222512-0.4947230.4029820.8154260.303929

-0.439165-0.402158-0.585598-0.099069-0.545511-0.199881-0.303239-0.549425-0.662781

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