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Productivity and technological progress of the Japanese manufacturing industries, 2000–2014: estimation with data envelopment analysis and log-linear learning model

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A Correction to this article was published on 20 September 2019

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Abstract

How has the Japanese manufacturing sector fared in productivity and technological learning in recent years? To answer this, we summarized the manufacturing industry into 3-digit sub-sector (25 sub-sectors) and evaluated the entire manufacturing industry. Our study covers 15 years of production cycles (2000–2014). Using data envelopment analysis and loglinear learning models, we empirically estimated the productivity and technological learning of these industries. The result shows negative (− 0.6%) total factor productivity (TFP) growth between 2000 and 2014. TFP was particularly affected by 2001, and 2008/2009 financial crisis. TFP regress also deepened in recent years (2011–2014) which we blamed on both internal and external shocks in the system. We showed that positive TFP observed in other years resulted from technical progress and efficiency improvement. Industry-level results were consistent with the annual mean result which suggest a common economic downturn. Estimated progress ratios from learning models show that individual industry exhibits unique learning rates, with some industries showing technological learning (i.e., decreasing unit cost of production) between 2000 and 2007 and others between 2010 and 2014. Industries viz. production machinery, electrical devices and circuit, chemical, pharmaceutical, and food manufacturing showed sustained learning between 2001 and 2013, implying huge cost saving as outputs expand. The overall result, however, showed that learning got worst and was lost at some point between 2008 and 2014. We conclude that productivity differentials explained by learning rates show that technological progress and innovations in Japanese manufacturing were capital intensive and cost inefficient and that Japanese manufacturing industry has not fully regained its competitiveness as the world’s leading manufacturing hub. We argued that for productivity improvement in Japanese manufacturing industries, there is a need for policy thrust to restore and ensure sustained learning within and across the industries.

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Fig. 1

(Source: Karaoz and Mesut 2005)

Fig. 2

(Source: Author)

Fig. 3
Fig. 4

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Change history

  • 20 September 2019

    In the original publication of the article, the equation 12 was published incorrectly and the footnote was missing. The correct version of equation 12 and footnote is as below.

Notes

  1. All variables except number of employees are measured in yen.

  2. The value of \(\lambda\) indicates the technical biases associated with production expansion. \(\lambda = 1\) indicate neutrality in technological progress whereas \(\lambda > 1\), suggests that capital labour ratio proportionally increases as output expands (see Pramongkit et al. 2000; Karaoz and Mesut 2005).

  3. Published annually from 2007 onward and downloadable at http://www.meti.go.jp/english/report/index_whitepaper.html#monodzukuri.

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Acknowledgements

We thank Japan Ministry of Economy, Trade and Industry (METI) for publishing and making data on manufacturing industries of Japan openly free for research. And Japan International Cooperation Agency (JICA) for generously providing scholarship fund to Mr. ADUBA Joseph Junior during his study at Ritsumeikan Asia Pacific University, under the ABE initiatives program.

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Appendices

Appendix A: Test for return to scale production technologies

Panel A: Output-value added

lnva

Coef.

St.Err.

t value

p value

(95% Conf. Interval)

Sig

lnl

6.924

0.713

9.71

0.000

5.526

8.323

***

lnk

0.425

0.053

8.07

0.000

0.322

0.528

***

Constant

− 8.912

1.073

− 8.30

0.000

− 11.016

− 6.809

***

Mean dependent var

14.621

SD dependent var

1.393

Number of obs

375.000

Chi square

2140.085

Prob > Chi2

0.000

Akaike crit. (AIC)

− 49.022

lnva

Coef.

Std.Err.

z

p > z

(95% Conf. Interval)

IRS/DRS test

7.349

0.665

11.050

0.000

6.046

8.653

Chi2

91.15

Prob > Chi2

0.000

Panel B: Output-revenue

lnR

Coef.

St.Err.

t value

p value

(95% Conf. Interval)

Sig

lnl

6.004

0.788

7.61

0.000

4.458

7.549

***

lnk

0.499

0.054

9.16

0.000

0.392

0.606

***

Constant

− 4.923

1.194

− 4.12

0.000

− 7.264

− 2.582

***

Mean dependent var

16.189

SD dependent var

1.414

Number of obs

375.000

Chi square

1333.981

Prob > Chi2

0.000

Akaike crit. (AIC)

− 430.461

lnR

Coef.

Std.Err.

z

P > z

(95% Conf. Interval)

IRS/DRS test

6.503

0.740

8.790

0.000

5.052

7.953

Chi2

55.27

Prob > Chi2

0.0000

  1. IRS increasing returns to scale, DRS decreasing return to scale
  2. ***p < 0.01, ** p < 0.05, * p < 0.1

Appendix B: Estimated technical efficiency using VRS production technology assumption

Manufacturing industry

00

01

02

03

04

05

06

07

08

09

10

11

12

13

14

Business oriented machinery

77

76

68

64

64

53

54

46

42

50

49

39

36

34

37

Ceramic, stone and clay products

43

40

38

35

34

27

28

26

26

31

30

25

26

25

27

Chemical and allied products

84

83

81

75

80

72

75

75

78

85

89

87

81

81

79

Electrical machinery, equipment and supplies

100

100

100

100

100

63

72

64

59

69

70

64

66

69

74

Electronic parts, devices and electronic circuits

75

64

65

59

58

43

45

44

40

50

48

46

47

44

49

General-purpose machinery

67

66

62

60

64

36

40

37

39

44

40

36

36

32

37

Information and comm. electronic equipment

93

99

96

99

94

86

89

87

90

97

95

65

61

57

51

Iron and steel

60

57

54

52

57

54

59

62

70

63

74

68

55

56

62

Production machinery

64

57

51

54

58

47

51

48

45

43

45

39

39

35

43

Transport equipment

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

Beverages, tobacco and feed

75

75

69

70

65

47

46

41

46

60

61

42

43

41

43

Food

75

83

83

77

76

69

72

68

75

94

92

85

86

83

88

Furniture and fixtures

75

77

74

71

66

54

60

52

56

68

59

58

62

56

59

Leather tanning, leather products and fur skins

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

Lumber and wood products

79

80

88

76

69

59

72

53

55

66

60

58

60

59

62

Miscellaneous manufacturing industries

71

79

66

63

51

41

48

50

54

63

49

39

44

37

39

Printing and allied industries

63

65

58

51

49

39

41

37

39

54

45

38

40

36

35

Pulp, paper and paper products

41

40

39

36

34

27

29

28

29

38

35

30

30

30

32

Textile mill products

45

43

39

37

37

25

30

27

29

53

45

27

29

26

27

Fabricated metal and products

53

54

53

45

51

43

45

44

44

56

51

45

48

44

48

Non-ferrous metals and products

43

42

38

36

37

36

51

53

46

49

59

49

45

43

46

Petroleum and coal products

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

Plastic products

71

67

57

52

55

46

48

42

41

46

41

37

41

38

40

Ruber products

39

46

40

33

32

26

28

27

29

31

30

26

27

23

25

Industry average

70

70

67

64

64

54

58

55

55

63

61

54

54

52

54

Appendix C: Summary of Malmquist productivity index by industrial groups*

 

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Panel A: High tech industries

Business oriented machinery

 EFFCH

0.981

0.887

0.939

1.016

0.825

1.016

0.850

0.911

1.197

0.985

0.783

0.935

0.947

1.082

 TECHCH

0.961

1.098

1.112

1.053

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.942

0.974

1.044

1.070

1.003

0.982

0.947

0.862

0.835

1.199

0.940

0.863

1.036

0.976

Electronic dev. and electronic circuits

 EFFCH

0.848

1.019

0.911

0.984

0.741

1.050

0.872

1.012

1.256

0.839

0.772

1.026

0.946

1.150

 TECHCH

0.961

1.098

1.123

1.043

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.815

1.118

1.023

1.027

0.901

1.014

0.971

0.957

0.876

1.021

0.927

0.947

1.036

1.037

Info. and comm. Electronic equipment

 EFFCH

0.707

0.915

0.901

1.032

0.863

1.027

0.968

0.954

1.186

0.846

0.840

0.997

0.885

0.993

 TECHCH

0.984

1.098

1.089

1.072

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.695

1.004

0.982

1.106

1.050

0.992

1.078

0.902

0.828

1.030

1.009

0.921

0.968

0.896

Pharmaceutical industries

 EFFCH

0.970

0.942

0.858

0.993

0.847

1.050

0.962

1.013

1.308

0.886

0.792

1.067

0.955

1.077

 TECHCH

0.998

1.098

1.085

1.078

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.968

1.034

0.930

1.070

1.030

1.014

1.072

0.959

0.913

1.078

0.951

0.985

1.045

0.972

Panel B: Medium high-tech industries

General-purpose machinery

 EFFCH

0.950

0.891

0.948

1.025

0.661

1.090

0.942

1.040

1.121

0.929

0.890

0.990

0.893

1.172

 TECHCH

0.961

1.098

1.114

1.050

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.913

0.978

1.056

1.077

0.803

1.053

1.050

0.984

0.782

1.131

1.069

0.915

0.977

1.057

Production machinery

 EFFCH

0.892

0.903

1.045

1.079

0.811

1.092

0.932

0.938

0.954

1.056

0.861

0.996

0.900

1.231

 TECHCH

0.961

1.098

1.116

1.048

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.857

0.992

1.166

1.130

0.985

1.055

1.039

0.887

0.666

1.285

1.033

0.920

0.985

1.110

Electrical machinery, equip.

 EFFCH

0.963

0.945

1.099

0.853

0.517

1.180

0.902

0.920

1.313

0.873

0.743

1.125

1.019

1.106

 TECHCH

0.961

1.098

1.121

1.044

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.925

1.037

1.233

0.890

0.629

1.140

1.005

0.871

0.916

1.063

0.892

1.039

1.115

0.997

Chemical

 EFFCH

0.970

0.942

0.858

0.993

0.847

1.050

0.962

1.013

1.308

0.886

0.792

1.067

0.955

1.077

 TECHCH

0.998

1.098

1.085

1.078

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.968

1.034

0.930

1.070

1.030

1.014

1.072

0.959

0.913

1.078

0.951

0.985

1.045

0.972

Transport equipment

 EFFCH

1.026

0.995

0.894

0.940

0.814

1.073

0.982

0.958

1.278

0.876

0.838

1.070

0.878

1.001

 TECHCH

0.982

1.098

1.097

1.067

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

1.007

1.093

0.981

1.004

0.989

1.036

1.095

0.906

0.892

1.066

1.006

0.988

0.961

0.903

Panel C: Medium low-tech industries

Iron and steel

 EFFCH

0.913

0.976

0.934

1.132

0.888

1.017

1.046

1.171

0.924

1.001

0.876

0.910

1.038

1.117

 TECHCH

1.016

1.098

1.075

1.087

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.927

1.071

1.004

1.230

1.079

0.982

1.166

1.107

0.645

1.218

1.052

0.840

1.136

1.008

Petroleum and coal products

 EFFCH

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000

 TECHCH

1.108

1.050

1.026

1.104

1.189

1.013

1.100

0.905

0.716

1.196

1.180

0.974

1.000

0.925

 TFPCH

1.108

1.050

1.026

1.104

1.189

1.013

1.100

0.905

0.716

1.196

1.180

0.974

1.113

0.925

Plastic products

 EFFCH

0.937

0.850

0.903

1.074

0.828

1.040

0.890

0.972

1.123

0.878

0.916

1.094

0.925

1.061

 TECHCH

0.961

1.098

1.116

1.044

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.000

0.902

 TFPCH

0.901

0.933

1.008

1.121

1.006

1.004

0.992

0.920

0.784

1.069

1.100

1.010

1.012

0.957

Rubber products

 EFFCH

1.178

0.888

0.806

0.976

0.803

1.084

0.969

1.065

1.091

0.978

0.840

1.045

0.870

1.088

 TECHCH

0.981

1.098

1.095

1.069

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.000

0.902

 TFPCH

1.155

0.975

0.883

1.044

0.976

1.047

1.080

1.008

0.762

1.191

1.009

0.965

0.952

0.982

Non-ferrous metals and products

 EFFCH

0.843

0.914

0.888

1.054

0.979

1.405

1.040

0.890

1.116

0.921

0.785

0.975

0.922

1.186

 TECHCH

1.009

1.098

1.076

1.086

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

0.979

0.902

 TFPCH

0.851

1.003

0.955

1.144

1.190

1.357

1.159

0.842

0.779

1.121

0.942

0.901

1.009

1.070

Fabricated metal and products

 EFFCH

1.014

0.982

0.858

1.090

0.870

1.067

0.977

0.994

1.265

0.870

0.802

1.094

0.935

1.092

 TECHCH

0.961

1.098

1.123

1.041

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.013

0.902

 TFPCH

0.974

1.078

0.964

1.134

1.057

1.030

1.088

0.941

0.883

1.059

0.963

1.010

1.024

0.985

Panel D: Low-tech industries

Food

 EFFCH

1.042

0.953

0.851

0.960

0.798

1.049

0.930

1.144

1.329

0.877

0.854

1.051

0.902

1.083

 TECHCH

0.961

1.098

1.126

1.039

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

0.941

0.902

 TFPCH

1.001

1.046

0.958

0.997

0.970

1.013

1.037

1.083

0.927

1.067

1.025

0.971

0.987

0.977

Beverages, Tobacco and Feed

 EFFCH

0.961

0.902

0.978

0.988

0.766

0.961

0.872

1.133

1.419

0.841

0.680

1.100

0.918

1.161

 TECHCH

1.009

1.098

1.077

1.085

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

0.949

0.902

 TFPCH

0.970

0.990

1.054

1.072

0.931

0.928

0.972

1.072

0.991

1.023

0.817

1.016

1.004

1.047

Textile mill products

 EFFCH

0.957

0.902

0.956

0.995

0.693

1.164

0.910

1.055

1.874

0.843

0.599

1.080

0.885

1.067

 TECHCH

0.961

1.098

1.120

1.041

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.000

0.902

 TFPCH

0.919

0.990

1.072

1.036

0.842

1.124

1.014

0.998

1.308

1.026

0.719

0.998

0.969

0.962

Lumber and wood products

 EFFCH

0.976

1.083

0.861

0.950

0.862

1.193

0.747

1.030

1.216

0.897

0.968

1.043

0.984

1.046

 TECHCH

0.961

1.098

1.126

1.039

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

0.999

0.902

 TFPCH

0.938

1.189

0.970

0.987

1.047

1.152

0.832

0.974

0.849

1.092

1.162

0.963

1.077

0.944

Furniture and fixtures

 EFFCH

0.967

0.942

0.963

1.003

0.798

1.094

0.885

1.066

1.223

0.872

0.973

1.082

0.900

1.067

 TECHCH

0.961

1.098

1.126

1.039

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.002

0.902

 TFPCH

0.929

1.033

1.084

1.042

0.970

1.057

0.987

1.009

0.854

1.061

1.169

1.000

0.985

0.963

Pulp, paper and paper products

 EFFCH

0.943

1.000

0.867

0.951

0.795

1.087

0.931

1.084

1.330

0.842

0.821

1.099

0.997

1.087

 TECHCH

0.999

1.098

1.087

1.076

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.002

0.902

 TFPCH

0.942

1.098

0.942

1.024

0.966

1.050

1.038

1.026

0.928

1.025

0.986

1.015

1.091

0.981

Printing and allied industries

 EFFCH

1.026

0.900

0.872

0.981

0.788

1.044

0.909

1.056

1.386

0.830

0.837

1.066

0.907

0.972

 TECHCH

0.961

1.098

1.121

1.045

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.000

0.902

 TFPCH

0.986

0.988

0.978

1.025

0.958

1.008

1.013

0.999

0.968

1.011

1.005

0.984

0.993

0.877

Leather tan., products and fur skins

 EFFCH

0.546

0.963

0.967

1.805

0.788

0.782

1.135

0.784

1.314

0.985

0.847

1.026

0.954

1.418

 TECHCH

0.961

1.098

1.126

1.039

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

0.954

0.902

 TFPCH

0.525

1.057

1.089

1.874

0.958

0.756

1.265

0.742

0.917

1.199

1.017

0.948

1.044

1.279

Miscellaneous manufacturing industries

 EFFCH

1.094

0.831

0.964

0.831

0.804

1.150

1.052

1.082

1.169

0.774

0.797

1.130

0.838

1.045

 TECHCH

0.963

1.098

1.113

1.058

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

0.999

0.902

 TFPCH

1.054

0.912

1.073

0.878

0.977

1.111

1.173

1.024

0.816

0.942

0.957

1.044

0.917

0.943

Ceramic, stone and clay products

 EFFCH

0.913

0.957

0.933

0.818

0.880

1.084

0.927

1.024

1.168

0.945

0.797

1.080

0.944

1.105

 TECHCH

0.981

1.098

1.096

1.070

1.216

0.966

1.115

0.946

0.698

1.217

1.201

0.923

1.094

0.902

 TFPCH

0.895

1.050

1.022

0.875

1.070

1.047

1.033

0.968

0.815

1.151

0.957

0.997

1.034

0.997

  1. EFFCH efficiency change, TEHCH technical change, TFPCH total factor productivity change
  2. *Cells with TFPCH  greater than unity shows total TFP growth as explained by corresponding efficiency change and technical change

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Aduba, J.J., Asgari, B. Productivity and technological progress of the Japanese manufacturing industries, 2000–2014: estimation with data envelopment analysis and log-linear learning model. Asia-Pac J Reg Sci 4, 343–387 (2020). https://doi.org/10.1007/s41685-019-00131-w

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