pemilihan model data panel dengan eviews

Kuis Ekonometrik (Quiz3)

Nama : Dede Firmansyah Kelas : 4SE4 Absen : 06 NIM : 09.5918

PEMILIHAN MODEL TERBAIK DENGAN DATA PANEL

Cross Section: 609 perusahaan, Dengan time series : 11 tahun (1998-2008)

Variabel Dependen:

Lny6 : Pertumbuhan Nilai Produksi

Variabel Independen:

Lnl : Pertumbuhan Tenaga Kerja

Lnk : Pertumbuhan Modal

Lnm : Pertumbuhan Bahan Baku

Lnl.lnm : interaksi pertumbuhan Tenaga Kerja dan bahan baku

Tahapan yang dilakukan untuk memperoleh model terbaik dengan menggunakan data

panel :

1. Uji stasioner semua variabel.

2. Jika semua variabel stasioner, maka bentuklah model pool dan model fixed effect

(FEM).

3. Lakukan Chow test, untuk mengetahui apakah FEM lebih baik daripada model pool.

4. Jika FEM lebih baik, bentuk model random effect (REM).

5. Lakukan Hausman test, untuk mengetahui apakah FEM lebih baik daripada REM.

6. Interpretasi model terpilih.

LANGKAH-LANGKAH:

1. Uji Panel Unit Root

Ho : 𝜌 = 1 Data Tidak Stasioner

H1 : 𝜌 < 1 Data Stasioner

Group unit root test: Summary

Series: LNK_1

Date: 11/22/12 Time: 12:27

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 Cross-

Method Statistic Prob.** sections Obs

Null: 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 23800

ADF - Fisher Chi-square 10124.2 0.0000 2422 23800

PP - 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.

Berdasarkan hasil running, nilai Prob-nya 0,000 berarti keputusan tolak Ho yang berarti Data

stasioner.

2. Estimasi Model Pool

Dependent Variable: LNY6?

Method: Pooled Least Squares

Date: 11/22/12 Time: 12:29

Sample: 1998 2008

Included observations: 11

Cross-sections included: 609

Total pool (balanced) observations: 6699 Variable Coefficient Std. Error t-Statistic Prob. LNL? 1.246456 0.017940 69.47745 0.0000

LNK? 0.062025 0.003465 17.89974 0.0000

LNM? 0.849494 0.003850 220.6464 0.0000

LNL?*LNM? -0.054038 0.000886 -61.00791 0.0000 R-squared 0.861124 Mean dependent var 14.55332

Adjusted R-squared 0.861061 S.D. dependent var 1.645467

S.E. of regression 0.613339 Akaike info criterion 1.860799

Sum squared resid 2518.557 Schwarz criterion 1.864865

Log likelihood -6228.747 Hannan-Quinn criter. 1.862203

Durbin-Watson stat 0.536696

Berdasarkan hasil running data, didapatkan nilai prob untuk setiap variabel bernilai 0,000 yang

artinya signifikan mempengaruhi variabel dependen. Nilai Adjusted R squared nya sebesar

0,861061 yang artinya semua variabel independen mampu menjelaskan keragaman variabel

dependen sebesar 86,1% (hubungannya erat).

3. Estimasi model fixed effect


Method: Pooled Least Squares

Date: 11/22/12 Time: 12:30

Sample: 1998 2008



Total pool (balanced) observations: 6699 Variable Coefficient Std. Error t-Statistic Prob. C 5.184910 0.291286 17.80006 0.0000

LNL? 0.384156 0.074592 5.150078 0.0000

LNK? -0.013943 0.002257 -6.177092 0.0000

LNM? 0.612589 0.019257 31.81047 0.0000

LNL?*LNM? -0.009492 0.004726 -2.008421 0.0446

Fixed Effects (Cross)

_1--C -0.311143

_2--C -0.057237

_3--C -0.371483

_4--C -0.235319

_5--C -0.064897

_6--C -0.313765

_7--C 1.192363

_8--C -0.251563

_9--C 0.307043

_10--C -0.124489

_11--C 0.501734

_12--C 0.086628

_13--C 1.062834

_14--C 1.237188

_15--C 0.013940

_16--C 0.010897

_17--C 1.372488

_18--C 0.873449

_19--C 0.866517

_20--C 1.105799

_21--C 1.574967

_22--C 0.601247

_23--C 0.443125

_24--C 0.554908

_25--C 0.286908

_26--C 0.504228

_27--C 0.565101

_28--C 0.450377

_29--C 0.010678

_30--C -0.202960

_31--C -0.168810

_32--C -0.189797

_33--C -0.352233

_34--C -0.208290

_35--C -0.200581

_36--C -0.202056

_37--C -0.249777

_38--C 0.332498

_39--C -0.264430

_40--C 0.121460

_41--C 0.144582

_42--C -0.241115

_43--C 0.695245

_44--C -0.442522

_45--C 0.018410

_46--C -0.444950

_47--C -0.320080

_48--C 0.557839

_49--C 0.055970

_50--C 0.109863

_51--C 0.470922

_52--C 0.816575

_53--C 1.631240

_54--C 0.963765

_55--C 1.056274

_56--C 1.287597

_57--C 0.248255

_58--C -0.408844

_59--C -0.221692

_60--C -0.118141

_61--C -0.458936

_62--C -0.426842

_63--C 0.309771

_64--C -0.375311

_65--C -0.389338

_66--C 0.876917

_67--C -0.016797

_68--C -0.576536

_69--C -0.059784

_70--C 0.799247

_71--C 1.366946

_72--C -0.063489

_73--C 1.635633

_74--C -0.326756

_75--C -0.155210

_76--C 0.809747

_77--C 0.776098

_78--C 0.678712

_79--C 1.249317

_80--C 1.248339

_81--C 0.395813

_82--C 0.213060

_83--C -0.709211

_84--C 1.058901

_85--C -0.198225

_86--C -0.176487

_87--C 0.355737

_88--C -0.364645

_89--C -0.056437

_90--C -0.397131

_91--C -0.081765

_92--C -0.141077

_93--C 0.547614

_94--C 0.542886

_95--C -0.363562

_96--C -0.441945

_97--C -0.311349

_98--C -0.290113

_99--C -0.398140

_100--C -0.462229

_101--C -0.200454

_102--C -0.024110

_103--C -0.282662

_104--C 0.797976

_105--C -0.545477

_106--C -0.458459

_107--C -0.334301

_108--C 0.949472

_109--C 0.038443

_110--C -0.186955

_111--C -0.212941

_112--C 0.151843

_113--C -0.302957

_114--C 0.029188

_115--C -0.730812

_116--C -0.942077

_117--C -0.153339

_118--C -0.845244

_119--C -0.272035

_120--C -0.430569

_121--C -0.635985

_122--C 0.006815

_123--C 0.622246

_124--C 0.118252

_125--C -0.071108

_126--C 1.179167

_127--C 1.973182

_128--C 0.542971

_129--C 2.373694

_130--C -0.219176

_131--C -0.186734

_132--C -0.267794

_133--C -0.241240

_134--C -0.117691

_135--C -0.759567

_136--C -0.720087

_137--C 0.076369

_138--C -0.315738

_139--C -0.128694

_140--C 0.472221

_141--C -0.549611

_142--C -0.196297

_143--C -0.149168

_144--C 1.054673

_145--C 0.549205

_146--C 1.869737

_147--C 0.892174

_148--C 0.379784

_149--C 1.259862

_150--C -0.497287

_151--C -0.323970

_152--C 0.104575

_153--C 0.171596

_154--C -0.523909

_155--C 0.780772

_156--C -0.344256

_157--C 0.170061

_158--C -0.258827

_159--C -0.296338

_160--C -0.648418

_161--C -0.257638

_162--C -0.606787

_163--C -0.580175

_164--C -0.225279

_165--C -0.545192

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_169--C -0.462059

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_171--C -0.298299

_172--C -0.409087

_173--C -0.548755

_174--C 0.988984

_175--C -1.068392

_176--C -0.311893

_177--C -0.025332

_178--C -0.840166

_179--C -0.548822

_180--C -0.427048

_181--C 0.546716

_182--C -0.671736

_183--C 0.495873

_184--C -0.660209

_185--C -0.320709

_186--C 0.490829

_187--C 0.157453

_188--C -0.361419

_189--C 0.127509

_190--C 0.295047

_191--C 0.356280

_192--C -0.047758

_193--C 1.287221

_194--C 1.570202

_195--C 0.982317

_196--C 1.029582

_197--C 1.357870

_198--C 2.003045

_199--C 0.927517

_200--C 1.237852

_201--C 1.234346

_202--C 1.180822

_203--C 0.505566

_204--C 1.550285

_205--C 1.096144

_206--C -0.057849

_207--C -0.150357

_208--C -0.277032

_209--C -0.347602

_210--C 0.047005

_211--C 0.074720

_212--C -0.361294

_213--C 0.944584

_214--C 0.329610

_215--C 1.023369

_216--C -0.804622

_217--C -0.403763

_218--C -0.320984

_219--C -0.526846

_220--C -0.619208

_221--C -0.419738

_222--C -0.583707

_223--C -0.095465

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_225--C -0.324677

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_228--C -0.259771

_229--C -0.333373

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_234--C -0.898604

_235--C -0.348801

_236--C -0.271357

_237--C -0.515657

_238--C 0.056750

_239--C 2.161075

_240--C -0.442736

_241--C -0.464129

_242--C -0.371887

_243--C -0.461542

_244--C 0.293858

_245--C 0.592435

_246--C -0.273591

_247--C 0.026832

_248--C 0.062365

_249--C 1.068478

_250--C -0.514236

_251--C 0.124575

_252--C -0.175178

_253--C -0.112968

_254--C 1.225868

_255--C -0.234105

_256--C 0.976221

_257--C 0.686782

_258--C -0.711182

_259--C -0.329510

_260--C -0.300875

_261--C -0.264950

_262--C -0.889979

_263--C 0.704722

_264--C 0.069732

_265--C 0.042073

_266--C 0.178292

_267--C -0.208907

_268--C -0.149443

_269--C 0.555990

_270--C -0.199749

_271--C 0.118155

_272--C -0.411243

_273--C -0.065798

_274--C 0.282452

_275--C 0.181807

_276--C -0.268090

_277--C 0.085980

_278--C 0.287432

_279--C -0.028282

_280--C 0.098968

_281--C 0.242431

_282--C 0.311159

_283--C 0.319873

_284--C -0.364349

_285--C 0.177266

_286--C 0.295426

_287--C -0.171074

_288--C 0.152210

_289--C -0.061898

_290--C 0.037189

_291--C -0.623274

_292--C 0.217424

_293--C 0.186389

_294--C -0.313936

_295--C 0.491045

_296--C 0.204863

_297--C -0.319692

_298--C -0.019210

_299--C 0.093499

_300--C 0.134877

_301--C -0.527551

_302--C -0.075665

_303--C 0.309062

_304--C 0.176764

_305--C 0.166384

_306--C -0.061823

_307--C 0.348289

_308--C -0.255909

_309--C 0.435390

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_312--C -0.253832

_313--C 0.103605

_314--C -0.324377

_315--C -0.477904

_316--C -0.604226

_317--C -0.503809

_318--C -0.297855

_319--C -0.805735

_320--C -0.371479

_321--C -0.548423

_322--C -0.638975

_323--C -0.249577

_324--C -0.534967

_325--C -0.686535

_326--C -0.765975

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_328--C -0.467469

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_330--C -0.673244

_331--C -0.111618

_332--C -0.455776

_333--C -0.285277

_334--C -0.368783

_335--C -0.712370

_336--C -0.268379

_337--C -0.280270

_338--C 0.478955

_339--C -0.236558

_340--C 0.036460

_341--C 0.327292

_342--C 0.502367

_343--C 0.267155

_344--C -0.280755

_345--C 0.833347

_346--C 0.502222

_347--C 0.796563

_348--C 1.019269

_349--C 0.702662

_350--C 0.703025

_351--C 0.675516

_352--C 1.034729

_353--C 0.750404

_354--C -0.315026

_355--C -0.223865

_356--C -0.109653

_357--C -0.357605

_358--C -0.221086

_359--C -0.571090

_360--C -0.482286

_361--C -0.128107

_362--C -0.062601

_363--C -0.074474

_364--C -0.279448

_365--C -0.560823

_366--C -0.162865

_367--C -0.392855

_368--C -0.159915

_369--C 0.022490

_370--C -0.299888

_371--C 0.075019

_372--C 0.172594

_373--C -0.556603

_374--C -0.265939

_375--C -0.156501

_376--C -0.255552

_377--C -0.528462

_378--C -0.547925

_379--C -0.717400

_380--C -0.211991

_381--C -0.517784

_382--C -0.531142

_383--C -0.287227

_384--C -0.431434

_385--C -0.450051

_386--C -0.498673

_387--C -0.269320

_388--C -0.527395

_389--C -0.492366

_390--C -0.689567

_391--C -0.535733

_392--C -0.645916

_393--C -0.009139

_394--C -0.433696

_395--C -0.085105

_396--C 0.615762

_397--C -0.394308

_398--C -0.375565

_399--C 0.301634

_400--C -0.465172

_401--C 0.025563

_402--C -0.121656

_403--C 1.288985

_404--C -0.333983

_405--C -0.533178

_406--C -0.389860

_407--C 0.223881

_408--C 0.284683

_409--C 0.606896

_410--C -0.126370

_411--C 0.313049

_412--C -0.408834

_413--C -0.038220

_414--C -0.501540

_415--C 0.013538

_416--C -0.230563

_417--C 0.803723

_418--C -0.403205

_419--C 0.212750

_420--C -0.413175

_421--C 0.890169

_422--C 0.107951

_423--C -0.408129

_424--C 0.078861

_425--C -0.679446

_426--C -0.282776

_427--C -0.496968

_428--C -0.576217

_429--C -0.368615

_430--C 1.481957

_431--C 0.212102

_432--C -0.124974

_433--C 0.038567

_434--C -0.121677

_435--C 2.381745

_436--C 0.957961

_437--C 0.774706

_438--C 1.170549

_439--C -0.135882

_440--C 0.042048

_441--C 0.212775

_442--C 1.023366

_443--C 0.401533

_444--C 0.829202

_445--C -0.170848

_446--C 0.036200

_447--C 0.000776

_448--C -0.001790

_449--C -0.147884

_450--C -0.890952

_451--C 0.545758

_452--C 0.045170

_453--C -0.239278

_454--C 1.438250

_455--C -0.110358

_456--C 0.177343

_457--C -0.158892

_458--C -0.084911

_459--C -0.149046

_460--C -0.152230

_461--C -0.131736

_462--C -0.175290

_463--C -0.630274

_464--C -0.559625

_465--C -0.543347

_466--C -0.483980

_467--C -0.010110

_468--C -0.329588

_469--C -0.422333

_470--C -0.375371

_471--C 1.038916

_472--C -0.252822

_473--C -0.222547

_474--C 0.032883

_475--C -0.519562

_476--C -0.424722

_477--C -0.274580

_478--C -0.552271

_479--C 1.625577

_480--C -0.324569

_481--C 0.024770

_482--C -0.297086

_483--C -0.051642

_484--C -0.389806

_485--C 0.112049

_486--C -0.105435

_487--C -0.153916

_488--C -0.065271

_489--C -0.019473

_490--C -0.040632

_491--C -0.324348

_492--C 0.113242

_493--C -0.095041

_494--C 0.101397

_495--C 0.172182

_496--C -0.661663

_497--C -0.629253

_498--C 0.853397

_499--C -0.180067

_500--C -0.191760

_501--C -0.169864

_502--C -0.213667

_503--C 0.010041

_504--C 0.317091

_505--C -0.489577

_506--C 0.999566

_507--C -0.401341

_508--C -0.462174

_509--C -0.550161

_510--C -0.775057

_511--C -0.714335

_512--C -0.432625

_513--C -0.196659

_514--C -1.159043

_515--C 0.989836

_516--C -0.415387

_517--C 0.640227

_518--C -0.054623

_519--C 1.614043

_520--C -0.133518

_521--C -0.214105

_522--C 0.965108

_523--C -0.289271

_524--C -0.221098

_525--C -0.528366

_526--C -0.525352

_527--C -0.326548

_528--C 0.061448

_529--C -0.000817

_530--C -0.243898

_531--C 1.561075

_532--C 0.034272

_533--C -0.585007

_534--C -0.569699

_535--C -0.467670

_536--C -0.120207

_537--C -0.703493

_538--C -0.066301

_539--C 0.018784

_540--C -0.241135

_541--C -0.559097

_542--C -1.189383

_543--C -1.184762

_544--C 0.076082

_545--C 0.245497

_546--C -0.119375

_547--C -0.046141

_548--C -0.269856

_549--C -0.321890

_550--C -0.282724

_551--C -0.297394

_552--C -0.510799

_553--C -0.645776

_554--C 0.101909

_555--C -0.140403

_556--C -0.394462

_557--C 1.002770

_558--C 1.000567

_559--C -0.857859

_560--C -0.111638

_561--C -0.345129

_562--C -0.743185

_563--C -0.065123

_564--C 0.343155

_565--C -0.481973

_566--C -0.561113

_567--C -0.552261

_568--C 0.272272

_569--C 0.872004

_570--C -0.186916

_571--C 0.043143

_572--C 0.994476

_573--C 1.260566

_574--C 0.646969

_575--C 1.507807

_576--C -0.224264

_577--C 0.330286

_578--C -0.590978

_579--C -0.327062

_580--C -0.380451

_581--C -0.268169

_582--C -1.193208

_583--C -1.224477

_584--C -1.204214

_585--C -1.186288

_586--C -1.236709

_587--C -0.312401

_588--C -0.258489

_589--C 0.624188

_590--C -0.168450

_591--C 0.124204

_592--C 0.266243

_593--C -0.101975

_594--C 0.316609

_595--C -0.040073

_596--C -0.224412

_597--C -0.492921

_598--C 0.393529

_599--C 0.855090

_600--C 0.314784

_601--C -0.464140

_602--C -0.415891

_603--C -0.592825

_604--C -0.106789

_605--C -0.547365

_606--C -0.208726

_607--C -0.299180

_608--C -0.544058

_609--C -0.661338 Effects Specification Cross-section fixed (dummy variables) R-squared 0.959769 Mean dependent var 14.55332





F-statistic 237.2386 Durbin-Watson stat 1.437093

Prob(F-statistic) 0.000000 Berdasarkan hasil running model fixed, diperoleh nilai prob untuk variabel lnl, lnk, lnm dan lnl.lnm kurang dari 5%

yang artinya signifikan pada taraf 5 persen. Nilai prob F nya 0,0000 berarti model secala keseluruhan baik.

Bilai Adjusted R Squared nya 0,995723 yang berarti variabel independenmampu menjelaskan keragaman variabel

dependen sebesar 95,57 %.

4. Uji Chow untuk memilih Pooled atau Fixed effect model

Ho : 𝛼𝑖 = 𝛼 (pooled)

H1 : minimal ada satu 𝛼𝑖 yang berbeda (fixed)

Redundant Fixed Effects Tests

Pool: POOL

Test cross-section fixed effects Effects Test Statistic d.f. Prob. Cross-section F 22.166170 (608,6086) 0.0000

Cross-section Chi-square 7822.091146 608 0.0000

Cross-section fixed effects test equation:


Method: Panel Least Squares

Date: 11/22/12 Time: 12:32

Sample: 1998 2008




LNL? -0.007396 0.058975 -0.125402 0.9002

LNK? 0.051450 0.003378 15.23260 0.0000

LNM? 0.513297 0.015566 32.97540 0.0000

LNL?*LNM? 0.025816 0.003691 6.994813 0.0000 R-squared 0.870680 Mean dependent var 14.55332






Prob(F-statistic) 0.000000

Berdasarkan hasil Uji,nilai Prob-nya 0,0000 yang berarti keputusannya Tolak Ho. Sehingga

disimpulkan Model Fixed Lebih baik.

5. Estimasi Model Random Effect


Method: Pooled EGLS (Cross-section random effects)

Date: 11/22/12 Time: 12:30

Sample: 1998 2008



Total pool (balanced) observations: 6699

Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-Statistic Prob. C 5.316836 0.265148 20.05234 0.0000

LNL? 0.245195 0.067252 3.645922 0.0003

LNK? -0.006921 0.002231 -3.101979 0.0019

LNM? 0.573871 0.017431 32.92307 0.0000

LNL?*LNM? 0.005957 0.004224 1.410269 0.1585

Random Effects (Cross)

_1--C -0.189679

_2--C 0.048858

_3--C -0.249644

_4--C -0.125767

_5--C 0.039354

_6--C -0.182256

_7--C 0.715739

_8--C -0.167642

_9--C 0.342517

_10--C -0.054853

_11--C 0.322654

_12--C 0.109652

_13--C 0.693282

_14--C 0.932776

_15--C 0.077728

_16--C 0.052814

_17--C 0.884424

_18--C 0.640104

_19--C 0.336187

_20--C 0.626493

_21--C 1.153912

_22--C 0.463351

_23--C 0.455032

_24--C 0.451153

_25--C 0.335868

_26--C 0.486695

_27--C 0.539253

_28--C 0.403386

_29--C 0.074942

_30--C -0.116410

_31--C -0.086069

_32--C -0.101350

_33--C -0.250297

_34--C -0.120443

_35--C -0.110457

_36--C -0.115283

_37--C -0.158050

_38--C 0.340558

_39--C -0.217720

_40--C 0.189881

_41--C 0.219216

_42--C -0.255645

_43--C 0.201413

_44--C -0.360141

_45--C 0.068955

_46--C -0.340070

_47--C -0.212016

_48--C 0.524691

_49--C 0.050822

_50--C 0.140277

_51--C 0.411268

_52--C 0.848953

_53--C 1.547587

_54--C 1.000808

_55--C 1.059820

_56--C 1.273538

_57--C 0.130596

_58--C -0.316987

_59--C -0.179248

_60--C -0.066900

_61--C -0.358239

_62--C -0.341620

_63--C 0.257371

_64--C -0.287164

_65--C -0.279952

_66--C 0.847472

_67--C 0.019897

_68--C -0.445216

_69--C 0.016571

_70--C 0.604533

_71--C 0.965425

_72--C -0.072084

_73--C 1.566475

_74--C -0.215765

_75--C -0.077516

_76--C 0.779384

_77--C 0.735448

_78--C 0.585322

_79--C 0.865343

_80--C 0.913169

_81--C 0.415091

_82--C 0.245597

_83--C -0.577930

_84--C 0.839142

_85--C -0.148309

_86--C -0.188023

_87--C 0.197488

_88--C -0.247683

_89--C 0.033097

_90--C -0.294957

_91--C -0.060733

_92--C -0.041056

_93--C 0.588756

_94--C 0.371274

_95--C -0.261367

_96--C -0.322832

_97--C -0.261076

_98--C -0.339041

_99--C -0.288977

_100--C -0.366119

_101--C -0.125422

_102--C -0.052150

_103--C -0.191222

_104--C 0.584705

_105--C -0.454009

_106--C -0.361087

_107--C -0.233259

_108--C 0.712287

_109--C 0.082445

_110--C -0.102573

_111--C -0.128571

_112--C 0.157724

_113--C -0.279606

_114--C -0.007778

_115--C -0.644324

_116--C -0.785570

_117--C -0.112616

_118--C -0.728698

_119--C -0.209099

_120--C -0.345939

_121--C -0.504267

_122--C 0.070306

_123--C 0.500364

_124--C 0.150209

_125--C 0.001501

_126--C 0.787844

_127--C 1.918171

_128--C 0.614387

_129--C 2.307999

_130--C -0.167996

_131--C -0.108416

_132--C -0.244265

_133--C -0.254161

_134--C -0.075345

_135--C -0.611166

_136--C -0.575441

_137--C 0.019884

_138--C -0.212571

_139--C -0.029154

_140--C 0.242975

_141--C -0.434497

_142--C -0.244974

_143--C -0.062574

_144--C 0.815705

_145--C 0.414714

_146--C 1.338786

_147--C 0.341881

_148--C 0.381879

_149--C 1.160149

_150--C -0.433054

_151--C -0.294091

_152--C 0.083512

_153--C 0.116993

_154--C -0.415767

_155--C 0.371758

_156--C -0.292622

_157--C 0.200386

_158--C -0.174719

_159--C -0.308997

_160--C -0.578294

_161--C -0.211314

_162--C -0.527753

_163--C -0.505527

_164--C -0.182827

_165--C -0.484987

_166--C -0.474487

_167--C -0.309462

_168--C -0.621132

_169--C -0.462037

_170--C -0.262812

_171--C -0.300164

_172--C -0.293823

_173--C -0.455544

_174--C 0.623613

_175--C -0.901391

_176--C -0.259685

_177--C -0.055475

_178--C -0.695712

_179--C -0.456255

_180--C -0.332048

_181--C 0.475556

_182--C -0.558571

_183--C 0.324320

_184--C -0.543492

_185--C -0.229887

_186--C 0.380946

_187--C 0.160270

_188--C -0.265550

_189--C 0.137559

_190--C 0.083172

_191--C -0.048028

_192--C -0.166666

_193--C 1.257008

_194--C 1.565785

_195--C 0.978749

_196--C 1.059309

_197--C 1.346650

_198--C 1.968736

_199--C 0.975090

_200--C 1.226617

_201--C 1.212087

_202--C 1.179457

_203--C 0.563175

_204--C 1.551555

_205--C 1.107057

_206--C -0.071787

_207--C -0.165796

_208--C -0.246480

_209--C -0.257136

_210--C 0.072695

_211--C -0.126264

_212--C -0.307257

_213--C 0.332810

_214--C 0.124909

_215--C 0.335069

_216--C -0.678606

_217--C -0.355543

_218--C -0.275072

_219--C -0.395013

_220--C -0.479588

_221--C -0.373046

_222--C -0.460204

_223--C -0.050184

_224--C -0.183506

_225--C -0.257963

_226--C -0.224535

_227--C -0.183629

_228--C -0.155248

_229--C -0.276785

_230--C -0.079482

_231--C -0.078125

_232--C -0.117332

_233--C -0.249049

_234--C -0.741088

_235--C -0.289896

_236--C -0.221951

_237--C -0.420377

_238--C 0.077570

_239--C 1.498425

_240--C -0.341248

_241--C -0.358592

_242--C -0.320044

_243--C -0.362942

_244--C 0.183889

_245--C 0.239482

_246--C -0.220198

_247--C 0.056050

_248--C -0.116934

_249--C 0.694592

_250--C -0.420643

_251--C -0.058905

_252--C -0.268901

_253--C -0.259468

_254--C 0.672536

_255--C -0.374557

_256--C 0.410513

_257--C 0.490187

_258--C -0.573500

_259--C -0.270607

_260--C -0.202068

_261--C -0.172077

_262--C -0.719701

_263--C 0.200842

_264--C 0.117833

_265--C 0.081517

_266--C 0.231806

_267--C -0.187231

_268--C -0.082989

_269--C 0.501732

_270--C -0.139343

_271--C 0.123537

_272--C -0.354990

_273--C -0.000785

_274--C 0.266373

_275--C 0.167507

_276--C -0.187843

_277--C 0.123458

_278--C 0.160498

_279--C 0.027802

_280--C 0.136000

_281--C 0.219154

_282--C 0.242425

_283--C 0.222034

_284--C -0.251822

_285--C 0.067014

_286--C 0.220447

_287--C -0.116378

_288--C 0.190947

_289--C 0.017573

_290--C 0.085480

_291--C -0.516269

_292--C 0.038568

_293--C 0.232162

_294--C -0.220836

_295--C 0.523660

_296--C 0.226151

_297--C -0.221207

_298--C 0.026332

_299--C 0.117585

_300--C -0.040458

_301--C -0.453551

_302--C -0.002787

_303--C 0.279677

_304--C 0.148551

_305--C 0.193846

_306--C 0.006090

_307--C 0.352635

_308--C -0.162069

_309--C 0.237681

_310--C -0.167491

_311--C -0.486426

_312--C -0.238806

_313--C 0.064933

_314--C -0.214497

_315--C -0.399722

_316--C -0.524198

_317--C -0.389468

_318--C -0.322458

_319--C -0.650253

_320--C -0.366224

_321--C -0.549933

_322--C -0.561973

_323--C -0.337836

_324--C -0.462661

_325--C -0.595283

_326--C -0.628049

_327--C -0.235926

_328--C -0.407264

_329--C -0.318313

_330--C -0.547824

_331--C -0.134087

_332--C -0.369739

_333--C -0.230728

_334--C -0.306904

_335--C -0.572982

_336--C -0.174771

_337--C -0.313157

_338--C 0.297128

_339--C -0.164216

_340--C -0.078249

_341--C 0.289353

_342--C 0.050040

_343--C 0.197711

_344--C -0.281425

_345--C 0.876840

_346--C 0.581071

_347--C 0.848047

_348--C 1.004258

_349--C 0.742372

_350--C 0.754551

_351--C 0.686144

_352--C 1.080089

_353--C 0.815801

_354--C -0.209670

_355--C -0.117652

_356--C -0.128733

_357--C -0.267025

_358--C -0.124245

_359--C -0.444391

_360--C -0.371650

_361--C -0.053954

_362--C -0.029403

_363--C -0.044913

_364--C -0.192154

_365--C -0.456759

_366--C -0.118222

_367--C -0.301347

_368--C -0.148621

_369--C 0.076063

_370--C -0.195661

_371--C -0.056484

_372--C 0.096248

_373--C -0.462593

_374--C -0.182601

_375--C -0.118439

_376--C -0.255106

_377--C -0.479383

_378--C -0.419147

_379--C -0.616429

_380--C -0.212886

_381--C -0.404553

_382--C -0.403394

_383--C -0.358292

_384--C -0.344975

_385--C -0.339921

_386--C -0.393334

_387--C -0.222702

_388--C -0.411151

_389--C -0.407513

_390--C -0.547055

_391--C -0.404229

_392--C -0.536178

_393--C -0.220558

_394--C -0.344413

_395--C -0.126327

_396--C 0.234951

_397--C -0.314213

_398--C -0.344131

_399--C 0.283524

_400--C -0.376585

_401--C 0.076366

_402--C -0.053038

_403--C 0.780698

_404--C -0.241613

_405--C -0.413931

_406--C -0.285234

_407--C 0.050591

_408--C 0.314623

_409--C 0.181076

_410--C -0.152984

_411--C 0.165932

_412--C -0.506642

_413--C -0.010571

_414--C -0.482239

_415--C -0.009013

_416--C -0.176625

_417--C 0.647050

_418--C -0.320564

_419--C 0.231783

_420--C -0.299250

_421--C 0.548044

_422--C 0.112544

_423--C -0.356891

_424--C 0.117879

_425--C -0.617046

_426--C -0.481139

_427--C -0.394200

_428--C -0.459455

_429--C -0.289167

_430--C 1.049399

_431--C 0.244713

_432--C -0.087905

_433--C 0.110535

_434--C -0.061876

_435--C 2.288821

_436--C 0.481395

_437--C 0.400369

_438--C 0.794689

_439--C -0.028829

_440--C 0.050946

_441--C 0.031424

_442--C 1.043950

_443--C 0.475768

_444--C 0.861633

_445--C -0.126634

_446--C 0.066889

_447--C -0.106291

_448--C 0.108498

_449--C -0.096332

_450--C -0.734768

_451--C 0.586629

_452--C -0.002224

_453--C -0.181122

_454--C 0.961022

_455--C -0.049357

_456--C 0.027224

_457--C -0.089732

_458--C -0.010206

_459--C -0.076548

_460--C -0.072904

_461--C -0.193003

_462--C -0.372826

_463--C -0.536407

_464--C -0.552797

_465--C -0.438736

_466--C -0.396154

_467--C -0.197067

_468--C -0.232138

_469--C -0.343588

_470--C -0.242000

_471--C 0.728592

_472--C -0.155514

_473--C -0.131655

_474--C 0.104927

_475--C -0.393985

_476--C -0.321644

_477--C -0.179524

_478--C -0.419417

_479--C 1.081922

_480--C -0.227148

_481--C 0.018499

_482--C -0.233649

_483--C -0.016377

_484--C -0.301038

_485--C 0.182383

_486--C -0.068509

_487--C -0.098396

_488--C -0.025602

_489--C 0.021627

_490--C 0.028292

_491--C -0.228504

_492--C 0.150935

_493--C -0.039649

_494--C 0.135255

_495--C 0.142000

_496--C -0.537937

_497--C -0.507267

_498--C 0.599024

_499--C -0.103604

_500--C -0.121653

_501--C -0.100126

_502--C -0.129663

_503--C -0.117507

_504--C 0.230016

_505--C -0.377227

_506--C 0.762124

_507--C -0.278855

_508--C -0.384539

_509--C -0.453325

_510--C -0.631404

_511--C -0.587654

_512--C -0.359893

_513--C -0.196528

_514--C -0.956774

_515--C 0.543543

_516--C -0.324832

_517--C 0.449577

_518--C -0.009772

_519--C 1.602317

_520--C -0.077932

_521--C -0.089272

_522--C 0.488942

_523--C -0.192500

_524--C -0.261554

_525--C -0.398616

_526--C -0.401091

_527--C -0.261273

_528--C -0.052159

_529--C -0.040009

_530--C -0.172350

_531--C 1.530347

_532--C 0.050288

_533--C -0.468640

_534--C -0.445580

_535--C -0.392292

_536--C -0.113851

_537--C -0.555710

_538--C -0.003232

_539--C 0.075909

_540--C -0.187686

_541--C -0.528059

_542--C -1.004142

_543--C -1.000211

_544--C 0.050992

_545--C 0.272211

_546--C -0.265298

_547--C 0.006864

_548--C -0.204336

_549--C -0.230381

_550--C -0.187220

_551--C -0.255259

_552--C -0.513512

_553--C -0.528115

_554--C 0.086814

_555--C -0.050504

_556--C -0.282668

_557--C 1.036663

_558--C 1.010665

_559--C -0.708337

_560--C -0.008518

_561--C -0.258304

_562--C -0.607316

_563--C 0.014708

_564--C 0.307899

_565--C -0.397982

_566--C -0.436758

_567--C -0.407928

_568--C 0.250395

_569--C 0.921228

_570--C -0.073177

_571--C 0.007619

_572--C 0.736297

_573--C 0.820618

_574--C 0.310343

_575--C 1.485276

_576--C -0.406031

_577--C 0.194441

_578--C -0.472579

_579--C -0.241239

_580--C -0.378441

_581--C -0.180449

_582--C -1.006841

_583--C -1.034704

_584--C -1.015253

_585--C -0.996719

_586--C -1.041958

_587--C -0.252755

_588--C -0.201556

_589--C 0.335026

_590--C -0.075975

_591--C 0.179817

_592--C 0.310371

_593--C -0.030818

_594--C 0.345351

_595--C 0.015672

_596--C -0.143721

_597--C -0.374675

_598--C 0.351372

_599--C 0.387998

_600--C 0.221807

_601--C -0.423075

_602--C -0.393354

_603--C -0.494990

_604--C -0.077050

_605--C -0.450047

_606--C -0.174078

_607--C -0.190160

_608--C -0.419237

_609--C -0.531972 Effects Specification

S.D. Rho Cross-section random 0.407762 0.5811

Idiosyncratic random 0.346240 0.4189 Weighted Statistics R-squared 0.713837 Mean dependent var 3.609520


S.E. of regression 0.357467 Sum squared resid 855.3774


Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.855829 Mean dependent var 14.55332

Sum squared resid 2614.576 Durbin-Watson stat 0.404811

Berdasarkan hasil running model, maka diperoleh niai prob. untuk variabel lnl, lnk, dan lnm sebesar 0,0000

sehingga signifikan pada taraf 5 persen, sedangkan untuk variabel interaksi lnl.lnm prob-nya 0,1585 yang

berarti tidak signifikan.

6. Uji Hausmann memilih model fixed atau random effect Ho : Corr (Xit, Uit) = 0

H1 : Corr (Xit, Uit) ≠ 0

Correlated Random Effects - Hausman Test

Pool: POOL

Test cross-section random effects

Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.

Cross-section random 445.168641 4 0.0000

Cross-section random effects test comparisons:

Variable Fixed Random Var(Diff.) Prob. LNL? 0.384156 0.245195 0.001041 0.0000

LNK? -0.013943 -0.006921 0.000000 0.0000

LNM? 0.612589 0.573871 0.000067 0.0000

LNL?*LNM? -0.009492 0.005957 0.000004 0.0000

Cross-section random effects test equation:


Method: Panel Least Squares

Date: 11/22/12 Time: 12:31

Sample: 1998 2008




LNL? 0.384156 0.074592 5.150078 0.0000

LNK? -0.013943 0.002257 -6.177092 0.0000

LNM? 0.612589 0.019257 31.81047 0.0000

LNL?*LNM? -0.009492 0.004726 -2.008421 0.0446 Effects Specification Cross-section fixed (dummy variables) R-squared 0.959769 Mean dependent var 14.55332






Prob(F-statistic) 0.000000

Berdasarkan hasil running model, diperoleh nilai prob sebesar 0,0000 berarti keputusannya

Tolak Ho. Sehingga Model Fixed lebih baik dibanding model random.

KESIMPULAN:

Model yang terbaik adalah model fixed effect :

Lny6it =( 5,18491 + 𝝉𝒊)* + 0,384156LnLit* - 0,013943LnKit* + 0,612589LnMit* –

0,009492LnL.LnMit*

*signifikanpada taraf 5 persen

𝜏𝑖= Koefisien effect

i= perusahaan 1(_1--C), perusahaan 2(_2--C),,……, perusahaan 609(_609--C),

Misalkan kita interpretasi untuk perusahaan 1, (𝝉𝟏).

Lny611 =( 5,18491 +(- 0.311143))* + 0,384156LnL* - 0,013943LnK* + 0,612589LnM* –

0,009492LnL.LnM*

Lny611=4,873767* + 0,384156LnL* - 0,013943LnK* + 0,612589LnM* – 0,009492LnL.LnM*

Interpretasi:

1. 𝛽0, Jika terjadi pertumbuhan modal, tenaga kerja, bahan baku dan interaksi antara tenaga

kerja dan bahan baku baik antar perusahaan maupun antarwaktu, maka perusahaan 1 akan

mendapat pengaruh individu terhadap pertumbuhan nilai produksi sebesar 4,873767

persen.

2. 𝛽1, Jika terjadi pertumbuhan tenaga kerja sebesar 1 persen dan faktor laninnya dianggap

tetap maka akan menaikkan pertumbuhan nilai produksi perusahaan 1 sebesar 0,384156

persen.

3. 𝛽2, Jika terjadi pertumbuhan modal sebesar 1 persen dan faktor lainnya dianggap tetap

maka akan menurunkan pertumbuhan nilai produksi perusahaan 1 sebesar 0,013943

persen.

4. 𝛽3, Jika terjadi pertumbuhan bahan baku sebesar 1 persen dan faktor lainnya tetap maka

akan menaikkan pertumbuhan nilai produksi perusahaan 1 sebesar 0,612589 persen.

5. Variabel interaksi antara ln L dan ln M, signifikan secara statistik dengan koefisien sebesar

0.009492. Hal ini mengakibatkan adanya efek parsial baik ln L terhadap ln M ataupun

sebaliknya. Sebagai contoh, jika tenaga kerja meningkat sebesar 1 persen dan variabel

independen lainnya diasumsikan tetap maka nilai produksi akan meningkat sebesar

0,612589 + 0.009492 = 0,622081 persen secara keseluruhan akibat adanya efek parsial ln L

terhadap ln M. Jika bahan baku meningkat 1 persen dan variabel independen lainnya

diasumsikan tetap maka nilai produksi akan meningkat sebesar 0,384156 +0.009492 =

0,393648 persen secara keseluruhan akibat adanya efek parsial ln M terhadap ln L.

pemilihan model data panel dengan eviews

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