Hasil Dan Interpretasi 5f5f6d

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, variabelvariabel 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 :



Output :

Group unit root test: Summary Series: LNY_30_1 Date: 11/22/12 Time: 14:50 Sample: 1998 2008 Exogenous variables: Individual effects Automatic selection of maximum lags Automatic selection of lags based on SIC: 0 to 1 Newey-West bandwidth selection using Bartlett kernel CrossMethod Statistic Prob.** sections Null: Unit root (assumes common unit root process)

Obs

Levin, Lin & Chu t*

-1504.01

0.0000

2422

23800

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

23800 23800 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 , 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 :



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

F-statistic

11177.52

Prob(F-statistic)

0.000000

Hannan-Quinn criter. 1.798519 Durbin-Watson stat

0.531390

 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 :



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 LNL_30? LNK_30? LNM_30? LNK_30?*LNL_30?

5.700524 0.248196 -0.011129 0.575883 -0.000710

0.155975 0.036903 0.009460 0.006194 0.002324

36.54767 6.725620 -1.176420 92.96837 -0.305684

0.0000 0.0000 0.2395 0.0000 0.7599

Effects Specification Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic)

0.959743 0.955695 0.346352 730.0735 -2081.074 237.0787 0.000000

Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat

14.55332 1.645467 0.804321 1.427452 1.019517 1.437555

catatan : Fixed Effect Terlampir

 Model Random (REM) Estimasi data 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 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 :



Output :

Date: 11/22/12 Time: 15:08 Sample: 1998 2008

Included observations: 11 Cross-sections included: 609 Total pool (balanced) observations: 6699 Swamy and Arora estimator of component variances Variable

Coefficient

Std. Error

t-Statistic

Prob.

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 Specification S.D. Cross-section random Idiosyncratic random

0.408319 0.346352

Rho 0.5816 0.4184

Weighted Statistics R-squared Adjusted R-squared S.E. of regression F-statistic Prob(F-statistic)

0.713664 0.713493 0.357459 4171.031 0.000000

Mean dependent var S.D. dependent var Sum squared resid Durbin-Watson stat

3.605993 0.667818 855.3384 1.236149

Unweighted Statistics R-squared Sum squared resid

0.855214 2625.732

Mean dependent var Durbin-Watson stat

14.55332 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 dengan Fixed Effect lebih baik

dari model regresi data 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 :



H1 : minimal ada satu intersept yang berbeda.

Output :

Redundant Fixed Effects Tests Pool: 30 Test cross-section fixed effects Effects Test

Statistic

Cross-section F

d.f.

Prob.

22.369882 (608,6086)

0.0000

7864.37000 Cross-section Chi-square

8

608

Std. Error

t-Statistic

0.0000

Cross-section fixed effects test equation: Dependent Variable: LNY_30? Method: Least Squares Date: 11/22/12 Time: 15:07 Sample: 1998 2008 Included observations: 11 Cross-sections included: 609 Total pool (balanced) observations: 6699 Variable

Coefficient

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

F-statistic

11177.52

Prob(F-statistic)

0.000000



Hannan-Quinn criter. 1.798519 Durbin-Watson stat

0.531390

Statistik Uji : F = 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 (  H1 : Cov ( 

Output :

Correlated Random Effects - Hausman Test Pool: 30 Test cross-section random effects Chi-Sq. Test Summary

Statistic Chi-Sq. d.f.

Cross-section random

440.226889

Prob.

4

0.0000

Random Var(Diff.)

Prob.

Cross-section random effects test comparisons:

Variable

Fixed

LNL_30?

0.248196

LNK_30? LNM_30?

0.316948

0.000129

0.0000

-0.011129 -0.012714

0.000004

0.4294

0.575883

0.597252

0.000008

0.0000

-0.000710

0.001472

0.000000

0.0000

(LNK_30?*LNL_30 ?)

Cross-section random effects test equation: Dependent Variable: LNY_30? Method: Least Squares Date: 11/22/12 Time: 15:09 Sample: 1998 2008 Included observations: 11 Cross-sections included: 609 Total pool (balanced) observations: 6699 Variable

Coefficient

Std. Error

t-Statistic

Prob.

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

0.002324 -0.305684

0.7599

LNK_30?*LNL_30? -0.000710

Effects Specification Cross-section fixed (dummy variables) R-squared

0.959743

Mean dependent var

14.55332

Adjusted R-squared

0.955695

S.D. dependent var

1.645467

S.E. of regression

0.346352

Akaike info criterion

0.804321

Sum squared resid

730.0735

Schwarz criterion

1.427452

Log likelihood

-2081.074

F-statistic

237.0787

Prob(F-statistic)

0.000000



Hannan-Quinn criter. 1.019517 Durbin-Watson stat

1.437555

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

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

Tolak Ho jika



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 :  H1 :



Output :

LM test for hetero versus homo chi-sqr(608) = p-value =



3348.500 0.000000

Statistik Uji : LM = ∑ dimana T=jml observasi, n=jml individu;

=varian residual persamaan ke-i;

=varian residual persamaan system. Keputusan Tolah Ho, jika LM test >



Keputusan : Tolak H karena Prob <

atau Prob <  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: 12:25 Sample: 1998 2008 Included observations: 11 Cross-sections included: 609 Total pool (balanced) observations: 6699 Linear estimation after one-step weighting matrix Variable

Coefficient

Std. Error

t-Statistic

Prob.

C LNL_30? LNK_30? LNM_30? LNK_30?*LNL_30?

4.983707 0.182928 -0.009014 0.641990 -0.000327

0.099668 0.022731 0.005790 0.004995 0.001459

50.00324 8.047643 -1.556819 128.5368 -0.224289

0.0000 0.0000 0.1196 0.0000 0.8225

Effects Specification Cross-section fixed (dummy variables) Weighted Statistics R-squared Adjusted R-squared S.E. of regression F-statistic Prob(F-statistic)

0.984378 0.982807 0.340977 626.6249 0.000000

Mean dependent var S.D. dependent var Sum squared resid Durbin-Watson stat

22.41908 11.83751 707.5897 1.349710

Unweighted Statistics R-squared Sum squared resid

0.958943 744.5808

Mean dependent var Durbin-Watson stat

14.55332 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

-0.184164 0.056264 -0.244613 -0.120153 0.044157 -0.173715 0.743540 -0.167695 0.344795 -0.053677 0.324038 0.106637 0.710463 0.938371 0.078749 0.050713 0.905453 0.643211 0.356384 0.649270 1.171264 0.461360 0.447439 0.447330 0.330393 0.480367 0.532342 0.397759 0.071642 -0.116818 -0.087054 -0.102039 -0.248820 -0.120554 -0.110880 -0.115877 -0.157926 0.335928 -0.221769 0.190057 0.221738 -0.264027 0.223545 -0.363568 0.066870 -0.337466

_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

1.557996 1.110788 -0.077363 -0.170898 -0.250871 -0.258666 0.068738 -0.125148 -0.310263 0.365909 0.127111 0.378453 -0.677130 -0.360533 -0.281347 -0.392143 -0.475579 -0.377696 -0.454246 -0.057038 -0.180709 -0.261408 -0.228611 -0.189643 -0.151347 -0.277730 -0.079951 -0.083907 -0.122808 -0.255302 -0.735563 -0.291777 -0.225223 -0.423486 0.070196 1.532391 -0.334930 -0.359718 -0.323838 -0.363008 0.172504 0.250925 -0.225298 0.052596 -0.137545 0.708346

_407--C _408--C _409--C _410--C _411--C _412--C _413--C _414--C _415--C _416--C _417--C _418--C _419--C _420--C _421--C _422--C _423--C _424--C _425--C _426--C _427--C _428--C _429--C _430--C _431--C _432--C _433--C _434--C _435--C _436--C _437--C _438--C _439--C _440--C _441--C _442--C _443--C _444--C _445--C _446--C _447--C _448--C _449--C _450--C _451--C _452--C

0.050854 0.312085 0.203026 -0.161983 0.157799 -0.522037 -0.013894 -0.489142 -0.021984 -0.179110 0.644385 -0.323347 0.228211 -0.294373 0.557884 0.107561 -0.361189 0.113011 -0.621699 -0.480737 -0.393616 -0.457961 -0.289650 1.067360 0.241062 -0.090227 0.109453 -0.067586 2.269500 0.513683 0.418408 0.808294 -0.025717 0.049210 0.027113 1.054636 0.491314 0.869275 -0.129330 0.057795 -0.112936 0.115493 -0.098917 -0.726489 0.589618 -0.007466

_47--C _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

-0.203057 0.520053 0.045857 0.137783 0.406097 0.850776 1.530906 1.006929 1.057786 1.272385 0.116794 -0.316295 -0.183156 -0.070334 -0.353670 -0.340988 0.252454 -0.286714 -0.273242 0.836243 0.016042 -0.438589 0.018774 0.606890 0.981866 -0.077515 1.551249 -0.209099 -0.078988 0.771059 0.728081 0.577957 0.884305 0.929501 0.413584 0.243008 -0.574171 0.841724 -0.149097 -0.196831 0.173190 -0.237395 0.038417 -0.292455 -0.069387 -0.032057 0.592437 0.372287 -0.254848 -0.314669 -0.265032 -0.344630 -0.285689 -0.364670 -0.126597

_250--C _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

-0.421393 -0.058375 -0.276907 -0.263358 0.708651 -0.393297 0.456970 0.491042 -0.569420 -0.272286 -0.199800 -0.167673 -0.710123 0.233475 0.115191 0.078015 0.229675 -0.192744 -0.083858 0.496039 -0.136687 0.117734 -0.358251 -0.000737 0.260181 0.161280 -0.186470 0.121293 0.160919 0.025494 0.132025 0.213579 0.238322 0.220604 -0.246314 0.064640 0.217445 -0.119291 0.186807 0.015973 0.081874 -0.517632 0.039575 0.226176 -0.218969 0.523666 0.222494 -0.219838 0.024246 0.113683 -0.037639 -0.457048 -0.004035 0.274797 0.143644

_453--C _454--C _455--C _456--C _457--C _458--C _459--C _460--C _461--C _462--C _463--C _464--C _465--C _466--C _467--C _468--C _469--C _470--C _471--C _472--C _473--C _474--C _475--C _476--C _477--C _478--C _479--C _480--C _481--C _482--C _483--C _484--C _485--C _486--C _487--C _488--C _489--C _490--C _491--C _492--C _493--C _494--C _495--C _496--C _497--C _498--C _499--C _500--C _501--C _502--C _503--C _504--C _505--C _506--C _507--C

-0.185343 0.982675 -0.049088 0.016760 -0.093884 -0.013827 -0.080389 -0.075825 -0.200917 -0.375585 -0.538817 -0.562132 -0.437434 -0.397688 -0.197564 -0.232746 -0.343604 -0.235129 0.737328 -0.155370 -0.127493 0.105637 -0.389343 -0.319170 -0.175429 -0.411365 1.097432 -0.228085 0.003323 -0.235683 -0.018306 -0.299304 0.186321 -0.072673 -0.101661 -0.029505 0.018303 0.025975 -0.229290 0.144701 -0.044775 0.129863 0.137271 -0.534153 -0.505128 0.601878 -0.106452 -0.125325 -0.103145 -0.133790 -0.124864 0.226633 -0.376669 0.762692 -0.277610

_102--C _103--C _104--C _105--C _106--C _107--C _108--C _109--C _110--C _111--C _112--C _113--C _114--C _115--C _116--C _117--C _118--C _119--C _120--C _121--C _122--C _123--C _124--C _125--C _126--C _127--C _128--C _129--C _130--C _131--C _132--C _133--C _134--C _135--C _136--C _137--C _138--C _139--C _140--C _141--C _142--C _143--C _144--C _145--C _146--C _147--C _148--C _149--C _150--C _151--C _152--C _153--C _154--C _155--C _156--C

-0.058029 -0.187202 0.587270 -0.454896 -0.360499 -0.230039 0.714345 0.081127 -0.097750 -0.125874 0.153691 -0.284679 -0.012651 -0.648206 -0.780947 -0.115768 -0.730314 -0.211855 -0.347342 -0.496469 0.069624 0.492067 0.146310 0.005495 0.796602 1.925529 0.623703 2.313116 -0.170136 -0.106230 -0.250086 -0.262139 -0.078832 -0.607216 -0.571977 0.015100 -0.211562 -0.018745 0.242485 -0.430345 -0.251724 -0.063782 0.820220 0.412296 1.376655 0.369572 0.370346 1.149535 -0.437243 -0.299011 0.078461 0.112699 -0.416193 0.390005 -0.296017

_305--C _306--C _307--C _308--C _309--C _310--C _311--C _312--C _313--C _314--C _315--C _316--C _317--C _318--C _319--C _320--C _321--C _322--C _323--C _324--C _325--C _326--C _327--C _328--C _329--C _330--C _331--C _332--C _333--C _334--C _335--C _336--C _337--C _338--C _339--C _340--C _341--C _342--C _343--C _344--C _345--C _346--C _347--C _348--C _349--C _350--C _351--C _352--C _353--C _354--C _355--C _356--C _357--C _358--C _359--C

0.189159 0.004525 0.347008 -0.161438 0.230073 -0.187088 -0.488867 -0.245919 0.035217 -0.209467 -0.402009 -0.527847 -0.386042 -0.327737 -0.643220 -0.376954 -0.559391 -0.566716 -0.343431 -0.466183 -0.599310 -0.625048 -0.235842 -0.417912 -0.332316 -0.542218 -0.140831 -0.371926 -0.236036 -0.310421 -0.573577 -0.171573 -0.323935 0.288514 -0.166992 -0.088417 0.284759 0.046710 0.190915 -0.289675 0.882860 0.584468 0.860566 0.996977 0.740267 0.757953 0.678178 1.099859 0.835531 -0.208876 -0.113277 -0.137344 -0.266693 -0.127376 -0.437191

_508--C _509--C _510--C _511--C _512--C _513--C _514--C _515--C _516--C _517--C _518--C _519--C _520--C _521--C _522--C _523--C _524--C _525--C _526--C _527--C _528--C _529--C _530--C _531--C _532--C _533--C _534--C _535--C _536--C _537--C _538--C _539--C _540--C _541--C _542--C _543--C _544--C _545--C _546--C _547--C _548--C _549--C _550--C _551--C _552--C _553--C _554--C _555--C _556--C _557--C _558--C _559--C _560--C _561--C _562--C

-0.386411 -0.455206 -0.627258 -0.585207 -0.363991 -0.202453 -0.946349 0.563932 -0.325242 0.451449 -0.011910 1.610988 -0.080989 -0.077345 0.517683 -0.191488 -0.267267 -0.392208 -0.393794 -0.265100 -0.057402 -0.048035 -0.174887 1.531248 0.046320 -0.468113 -0.443064 -0.396742 -0.120444 -0.544556 -0.003494 0.073311 -0.191683 -0.536601 -0.996744 -0.992883 0.046195 0.270681 -0.272191 0.002977 -0.203674 -0.228432 -0.184376 -0.259724 -0.522471 -0.527807 0.081876 -0.049416 -0.278691 1.048856 1.007695 -0.704462 -0.001927 -0.259003 -0.606410

_157--C _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

0.195219 -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 -0.457921 0.634279 -0.896356 -0.265735 -0.073518 -0.689117 -0.458869 -0.332112 0.471020 -0.559039 0.322555 -0.543100 -0.231043 0.376198 0.155301 -0.264705 0.133614 0.082098 -0.030661 -0.175459 1.238233 1.556895 0.976444 1.070099 1.345445 1.966536 0.986958 1.230879 1.200054 1.176408 0.572415

_360--C _361--C _362--C _363--C _364--C _365--C _366--C _367--C _368--C _369--C _370--C _371--C _372--C _373--C _374--C _375--C _376--C _377--C _378--C _379--C _380--C _381--C _382--C _383--C _384--C _385--C _386--C _387--C _388--C _389--C _390--C _391--C _392--C _393--C _394--C _395--C _396--C _397--C _398--C _399--C _400--C _401--C _402--C _403--C _404--C _405--C _406--C

-0.369461 -0.057196 -0.034251 -0.048517 -0.192568 -0.455791 -0.123086 -0.301734 -0.153439 0.072543 -0.197636 -0.057779 0.075234 -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 -0.132312 0.245446 -0.315092 -0.350533 0.278788 -0.376882 0.074986 -0.054596 0.801793 -0.242825 -0.412471 -0.283495

_563--C _564--C _565--C _566--C _567--C _568--C _569--C _570--C _571--C _572--C _573--C _574--C _575--C _576--C _577--C _578--C _579--C _580--C _581--C _582--C _583--C _584--C _585--C _586--C _587--C _588--C _589--C _590--C _591--C _592--C _593--C _594--C _595--C _596--C _597--C _598--C _599--C _600--C _601--C _602--C _603--C _604--C _605--C _606--C _607--C _608--C _609--C

0.014101 0.300526 -0.400420 -0.433163 -0.399498 0.246158 0.937082 -0.066143 -0.005165 0.739379 0.840371 0.322412 1.487619 -0.412135 0.188416 -0.470584 -0.240668 -0.385653 -0.178472 -0.999186 -1.026581 -1.007610 -0.988358 -1.032861 -0.256166 -0.203485 0.338434 -0.079576 0.175150 0.304986 -0.032077 0.342196 0.014872 -0.144697 -0.374411 0.346202 0.402196 0.228103 -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

-0.321019 -0.069825 -0.380227 -0.244172 -0.073930 -0.329471 1.133240 -0.251124 0.305934 -0.124793 0.498413 0.093048 1.022983 1.220815 0.014378 0.015799 1.321807 0.864826 0.812450 1.051533 1.536097 0.603840 0.456616 0.561337 0.296873 0.516010 0.577870 0.460207 0.016946 -0.201314 -0.166278 -0.187935 -0.353726 -0.206988 -0.199138 -0.200201 -0.249095 0.341477 -0.256095 0.123640 0.142458 -0.226018 0.644056 -0.434685 0.022808 -0.448494

_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

1.542903 1.092581 -0.047497 -0.140827 -0.268774 -0.345134 0.054648 0.071146 -0.354797 0.869521 0.324158 0.923352 -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 -0.508193 0.071639 2.076636 -0.450242 -0.462802 -0.364326 -0.460926 0.312386 0.565125 -0.263087 0.034302 0.092397 1.038470

_407--C _408--C _409--C _410--C _411--C _412--C _413--C _414--C _415--C _416--C _417--C _418--C _419--C _420--C _421--C _422--C _423--C _424--C _425--C _426--C _427--C _428--C _429--C _430--C _431--C _432--C _433--C _434--C _435--C _436--C _437--C _438--C _439--C _440--C _441--C _442--C _443--C _444--C _445--C _446--C _447--C _448--C _449--C _450--C _451--C _452--C

0.223373 0.290879 0.563650 -0.108857 0.331073 -0.382831 -0.031502 -0.487657 0.039111 -0.225170 0.807424 -0.397230 0.220150 -0.420696 0.865024 0.117341 -0.399963 0.087539 -0.669996 -0.281768 -0.497904 -0.577502 -0.366674 1.440225 0.219859 -0.119323 0.040479 -0.109489 2.417289 0.895587 0.737610 1.137916 -0.138859 0.045552 0.217408 1.008423 0.378803 0.818904 -0.164602 0.053881 0.011209 -0.012911 -0.142261 -0.904478 0.542522 0.055391

_47--C _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

-0.333006 0.566908 0.065582 0.115378 0.480276 0.816892 1.660804 0.955648 1.062721 1.292117 0.272561 -0.408200 -0.214271 -0.110381 -0.465313 -0.426307 0.318811 -0.374352 -0.398804 0.897497 -0.008923 -0.587532 -0.062254 0.793686 1.330356 -0.052892 1.663966 -0.336869 -0.151819 0.824739 0.789181 0.691484 1.210333 1.217523 0.400766 0.218514 -0.715000 1.052518 -0.195068 -0.160413 0.394970 -0.380525 -0.063285 -0.400290 -0.065191 -0.153424 0.543927 0.539820 -0.371852 -0.454313 -0.303633 -0.280030 -0.402923 -0.463344 -0.197233

_250--C _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

-0.512059 0.122633 -0.162132 -0.106014 1.150769 -0.208362 0.889570 0.682618 -0.718602 -0.324696 -0.303816 -0.271877 -0.908091 0.637613 0.076262 0.049094 0.183531 -0.198645 -0.146321 0.566092 -0.202359 0.128244 -0.403691 -0.064071 0.292995 0.193399 -0.268203 0.091792 0.287750 -0.022662 0.106712 0.252029 0.318276 0.323729 -0.372924 0.182567 0.301930 -0.165326 0.160558 -0.058882 0.044693 -0.621034 0.214493 0.196217 -0.315493 0.493248 0.212957 -0.321143 -0.013864 0.101396 0.131302 -0.520898 -0.071827 0.318533 0.186032

_453--C _454--C _455--C _456--C _457--C _458--C _459--C _460--C _461--C _462--C _463--C _464--C _465--C _466--C _467--C _468--C _469--C _470--C _471--C _472--C _473--C _474--C _475--C _476--C _477--C _478--C _479--C _480--C _481--C _482--C _483--C _484--C _485--C _486--C _487--C _488--C _489--C _490--C _491--C _492--C _493--C _494--C _495--C _496--C _497--C _498--C _499--C _500--C _501--C _502--C _503--C _504--C _505--C _506--C _507--C

-0.231627 1.385036 -0.108764 0.191011 -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 -0.387789 1.017606 -0.252562 -0.227629 0.033517 -0.527489 -0.428875 -0.279996 -0.565048 1.576576 -0.323312 0.052057 -0.292536 -0.046625 -0.390644 0.107092 -0.097618 -0.147740 -0.057920 -0.012758 -0.036954 -0.323752 0.123002 -0.087212 0.111043 0.180977 -0.667418 -0.633105 0.844351 -0.175943 -0.185987 -0.165224 -0.208007 0.021313 0.322886 -0.490961 0.993044 -0.405268

_102--C _103--C _104--C _105--C _106--C _107--C _108--C _109--C _110--C _111--C _112--C _113--C _114--C _115--C _116--C _117--C _118--C _119--C _120--C _121--C _122--C _123--C _124--C _125--C _126--C _127--C _128--C _129--C _130--C _131--C _132--C _133--C _134--C _135--C _136--C _137--C _138--C _139--C _140--C _141--C _142--C _143--C _144--C _145--C _146--C _147--C _148--C _149--C _150--C _151--C _152--C _153--C _154--C _155--C _156--C

-0.013251 -0.287254 0.790672 -0.542940 -0.458249 -0.338987 0.942826 0.042462 -0.192269 -0.215819 0.160948 -0.292791 0.038255 -0.721815 -0.949493 -0.146875 -0.840391 -0.266590 -0.424507 -0.647959 0.008946 0.635555 0.125758 -0.075972 1.151928 1.965466 0.527525 2.368310 -0.212964 -0.188465 -0.256452 -0.225761 -0.109818 -0.767790 -0.727548 0.085849 -0.317935 -0.144103 0.472129 -0.555601 -0.184410 -0.147022 1.044522 0.552311 1.797331 0.820233 0.402603 1.279318 -0.488675 -0.314332 0.113780 0.179809 -0.523339 0.740719 -0.337849

_305--C _306--C _307--C _308--C _309--C _310--C _311--C _312--C _313--C _314--C _315--C _316--C _317--C _318--C _319--C _320--C _321--C _322--C _323--C _324--C _325--C _326--C _327--C _328--C _329--C _330--C _331--C _332--C _333--C _334--C _335--C _336--C _337--C _338--C _339--C _340--C _341--C _342--C _343--C _344--C _345--C _346--C _347--C _348--C _349--C _350--C _351--C _352--C _353--C _354--C _355--C _356--C _357--C _358--C _359--C

0.175362 -0.057784 0.359075 -0.256159 0.446149 0.070633 -0.563880 -0.240185 0.154830 -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 -0.260374 0.493734 -0.229696 0.052426 0.335675 0.494202 0.278824 -0.265781 0.825551 0.497183 0.777238 1.034338 0.709436 0.700129 0.691854 1.004669 0.719845 -0.317033 -0.231175 -0.093781 -0.357187 -0.217538 -0.582129

_508--C _509--C _510--C _511--C _512--C _513--C _514--C _515--C _516--C _517--C _518--C _519--C _520--C _521--C _522--C _523--C _524--C _525--C _526--C _527--C _528--C _529--C _530--C _531--C _532--C _533--C _534--C _535--C _536--C _537--C _538--C _539--C _540--C _541--C _542--C _543--C _544--C _545--C _546--C _547--C _548--C _549--C _550--C _551--C _552--C _553--C _554--C _555--C _556--C _557--C _558--C _559--C _560--C _561--C _562--C

-0.457717 -0.545883 -0.782703 -0.718333 -0.423915 -0.184618 -1.180434 0.946151 -0.412774 0.636631 -0.049816 1.603613 -0.128037 -0.234226 0.906946 -0.289887 -0.209846 -0.539542 -0.536138 -0.318288 0.068899 0.013128 -0.237797 1.561370 0.042307 -0.585742 -0.574262 -0.458496 -0.106690 -0.721658 -0.064572 0.022881 -0.234013 -0.541489 -1.202412 -1.197665 0.084763 0.250137 -0.108699 -0.039448 -0.269625 -0.324031 -0.286625 -0.289658 -0.491350 -0.646060 0.111374 -0.141702 -0.400138 0.984958 1.009027 -0.864429 -0.122454 -0.343504 -0.745063

_157--C _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

0.179238 -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 -0.542995 0.962802 -1.076602 -0.299685 0.004768 -0.850693 -0.544537 -0.426098 0.554693 -0.671016 0.497902 -0.661307 -0.318528 0.498263 0.166615 -0.361999 0.135508 0.295537 0.322854 -0.026582 1.322022 1.589479 0.989170 1.014103 1.363158 2.010511 0.910080 1.234379 1.257827 1.188705 0.492280

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