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The Official Journal of the Pan-Pacific Association of Input-Output Studies (PAPAIOS)

Table 2 Innovation input–output matrix (Γ′) (with the USA)

From: Estimating innovation input–output matrix and innovation linkages in the East Asian region and the USA

Variables

Chem.

Petro.

Leather

Clay

P. metal

F. metal

Machine

Electrical

Chemical

−0.082

(0.192)

−0.155

(0.136)

0.784

(0.309)

0.577

(0.368)

3.738

(2.107)

4.248

(10.908)

−3.301

(20.492)

2.764

(6.967)

Petroleum

17.518

(7.086)

0.407

(0.126)

−0.153

(1.124)

−0.137

(0.197)

Leather

20.913

(8.083)

0.138

(0.108)

Clay glass

−3.151

(1.662)

−9.753

(4.798)

−1.068

(2.409)

−0.251

(0.169)

−2.864

(2.817)

−79.588

(58.218)

20.326

(14.230)

−1.571

(23.405)

Primary metal

3.595

(24.938)

18.272

(13.184)

0.270

(0.149)

3.899

(1.941)

2.293

(5.749)

342.843

(824)

Fabricated metal

7.651

(10.546)

2.527

(4.034)

−0.015

(0.831)

0.206

(0.140)

13.743

(5.763)

71.777

(51.179)

Machinery

−0.851

(1.014)

2.947

(1.902)

−2.716

(1.974)

−0.896

(0.370)

0.680

(0.620)

0.009

(0.182)

0.950

(2.069)

Electrical machinery

12.181

(39.365)

3.382

(11.855)

−78.772

(222)

24.512

(22.762)

−1.126

(0.689)

2.382

(1.675)

0.140

(0.189)

Motor vehicle

4.807

(3.117)

0.912

(0.502)

1.885

(1.013)

1.679

(2.825)

0.880

(0.971)

0.596

(0.772)

0.178

(0.654)

Transportation equipment

−29.489

(49.358)

8.224

(9.661)

190.806

(187)

1.684

(2.998)

23.894

(123)

Instrument

0.618

(0.610)

−1.067

(1.844)

−1.631

(3.713)

193.623

(97.190)

−1.754

(1.512)

−0.526

(0.231)

−3.072

(2.229)

Rubber

−17.285

(6.807)

−64.012

(45.548)

4444.790

(10,798)

577.593

(1281)

−46.008

(45.009)

−3.179

(19.550)

−42.447

(225)

Misc. manufacturing

0.847

(1.456)

−0.272

(18.113)

−0.280

(1.529)

0.933

(0.802)

2.364

(6.437)

0.511

(0.428)

−1.300

(0.986)

15.565

(45.006)

Transportation

−47.833

(55.587)

2.715

(10.809)

−266.441

(213)

−7.478

(3.401)

−113.100

(138)

Communication

6.910

(10.677)

21.469

4.444

(2.088)

−12.869

(11.735)

66.259

(23.963)

−0.657

(6.109)

0.026

(0.482)

(13.860)

Variables

Motor

Tran. eq.

Inst.

Rubber

Misc.

Trans.

Comm.

Chemical

137.270

(94.429)

−0.312

(2.071)

18.825

(6.286)

2211.040

(1417)

Petroleum

Leather

0.551

(2.819)

13.657

(4.737)

Clay glass

22.374

(21.255)

525.281

(1006)

114.600

(255)

Primary metal

−20.827

(15.064)

−27,165

(26,678)

Fabricated metal

6.322

(7.737)

240.935

(184)

44.180

(15.411)

0.051

(0.416)

158.022

(170)

−399.937

(356)

Machinery

0.516

(0.428)

0.030

(0.194)

0.497

(0.331)

−29.293

(17.296)

0.506

(0.438)

−0.114

(0.176)

0.188

(6.088)

Electrical machinery

−3.457

(13.900)

−23.268

(10.275)

196.797

(131)

−0.780

(0.867)

0.256

(0.251)

Motor vehicle

0.132

(0.133)

−3.445

(10.284)

2.594

(2.868)

0.499

(0.418)

2.774

(1.066)

4.950

(9.492)

3.317

(20.069)

Transportation equipment

0.048

(0.342)

0.212

(0.118)

−1.337

(2.075)

2.303

(8.420)

0.966

(0.844)

Instrument

6.923

(10.207)

27.058

(39.817)

−0.186

(0.138)

−0.126

(10.652)

−5.043

(5.245)

25.527

(36.870)

−3.745

(3.449)

Rubber

−0.396

(0.220)

−6.435

(2.055)

103.231

(318)

Misc. manufacturing

−1.868

(2.796)

6.039

(15.051)

1.763

(2.765)

0.506

(1.071)

−0.055

(0.101)

29.762

(13.928)

171.921

(200)

Transportation

−0.529

(0.347)

−0.645

(1.006)

1.320

(2.132)

−20.209

(9.255)

0.001

(0.120)

Communication

347.673

(175)

1.526

(1.016)

−34.053

(53.830)

166.939

(159)

0.162

(0.140)

  1. The number of observations is 72. The dependent variable is productivity growth. All coefficients are estimated by random-effect models. Standard errors are shown in parentheses. Constant terms are omitted
  2. Data source: ICPA database