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

Table 1 Innovation input–output matrix (Γ′) (excluding 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

0.009

(0.216)

−0.171

(0.133)

1.067

(0.300)

0.726

(0.362)

4.222

(1.935)

2.185

(11.579)

−9.059

(21.257)

1.898

(7.108)

Petroleum

18.055

(8.334)

0.432

(0.135)

−0.508

(1.164)

−0.250

(0.235)

Leather

24.978

(10.376)

−12.994

(4.843)

0.225

(0.120)

Clay glass

−3.116

(1.739)

26.303

(26.536)

−0.600

(2.233)

−0.267

(0.169)

−4.006

(2.623)

−47.194

(63.589)

29.058

(15.170)

0.069

(24.154)

Primary metal

20.926

(14.371)

0.330

(0.153)

1.524

(2.358)

−6.530

(6.652)

33.637

(942)

Fabricated metal

7.192

(11.749)

2.469

(4.189)

−0.024

(0.811)

0.132

(0.161)

8.073

(6.353)

54.333

(55.605)

Machinery

−1.016

(1.244)

2.279

(2.065)

−4.398

(2.177)

−1.261

(0.385)

0.812

(0.744)

0.001

(0.211)

0.957

(2.405)

Electrical machinery

14.029

(43.995)

−10.765

(11.523)

−186.645

(227)

8.637

(21.582)

−1.348

(0.762)

1.676

(1.818)

0.056

(0.198)

Motor vehicle

5.572

(3.558)

1.264

(0.506)

2.930

(1.051)

3.226

(2.742)

1.418

(1.084)

0.967

(0.839)

0.293

(0.706)

Transportation equipment

−42.926

(51.372)

5.327

(9.362)

153.309

(211)

4.083

(3.305)

59.253

(133)

Instrument

0.537

(0.729)

0.251

(1.930)

1.066

(3.979)

302.409

(96.902)

−2.004

(1.775)

−0.499

(0.262)

−2.405

(2.465)

Rubber

−20.284

(7.620)

−3.186

(19.413)

−91.628

(44.036)

3650.780

(10,519)

686.016

(1165)

−21.575

(47.887)

8.522

(20.171)

−0.794

(227)

Misc. manufacturing

0.659

(1.748)

−0.519

(1.612)

1.295

(0.839)

9.727

(6.270)

1.004

(0.497)

0.186

(1.088)

54.505

(48.644)

Transportation

−55.674

(57.145)

2.015

(10.425)

−539.495

(241)

−12.498

(3.694)

−173.413

(148)

Communication

8.489

(12.000)

 

30.121

(13.297)

6.081

(2.099)

−2.250

(11.403)

90.576

(26.440)

5.592

(0.078)

0.140

(0.136)

Variables

Motor

Tran. eq.

Inst.

Rubber

Misc.

Trans.

Comm.

Chemical

115.622

(92.532)

0.211

(2.199)

19.512

(7.290)

1664.010

(1783)

Petroleum

Leather

1.387

(3.316)

18.304

(6.370)

Clay glass

27.998

(25.270)

534.823

(1086)

138.125

(327)

Primary metal

−29.039

(16.059)

−30,813

(36,438)

Fabricated metal

4.100

(8.254)

204.481

(216)

49.682

(16.915)

−0.178

(0.475)

308.055

(197)

−455.735

(460)

Machinery

1.252

(0.523)

−0.054

(0.275)

0.637

(0.457)

−41.521

(21.468)

0.458

(0.565)

0.085

(0.248)

4.018

(8.197)

Electrical machinery

−2.247

(14.700)

−23.004

(12.822)

224.852

(145)

−0.656

(0.995)

0.338

(0.332)

Motor vehicle

0.039

(0.145)

−4.486

(12.202)

3.126

(3.675)

0.858

(0.475)

3.063

(1.248)

5.640

(11.221)

−5.251

(26.525)

Transportation equipment

−0.100

(0.370)

0.269

(0.143)

−1.391

(2.345)

2.811

(9.900)

0.507

(1.017)

Instrument

−1.799

(11.468)

43.559

(48.389)

−0.238

(0.179)

0.206

(12.569)

−5.016

(6.397)

−11.296

(44.343)

−5.433

(4.708)

Rubber

−0.429

(0.232)

−6.540

(2.348)

209.731

(396)

Misc. manufacturing

−2.124

(3.084)

7.452

(18.527)

2.112

(3.530)

0.854

(1.201)

−0.103

(0.126)

35.448

(17.031)

140.672

(262)

Transportation

−0.791

(0.362)

−0.706

(1.209)

0.996

(2.314)

−23.525

(10.584)

−0.077

(0.142)

Communication

115.622

353.197

(205)

1.467

(1.244)

0.211

−44.246

(62.574)

297.278

(184)

0.144

(0.171)

  1. The number of observations is 53. 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