File Name: Multinat_patent

Observations: 329,256

 

 

Description:

                         To construct this file, we begin with the set of large multinational firms that we identified, as discussed in the text.  For each such firm, we process the applicant_name field in the Chinese patent data.  We determine the set of patents, where the multinational’s name is included in the applicant_name field.  Note that in some cases multinationals have joint ventures between themselves, e.g. “SONY ERICSSON.” In such a case, the patent would appear twice in the data set, one for the multinational “SONY,” a second time for the multinational “ERICSSON.”  Duplicates are relatively rare (5,270 patents appear more than once out of 323,977 unique patents in the data set.)  When constructing Table 1, we eliminate duplicate patent records.

                         The file excludes multinationals based out of Taiwan, as discussed in the separate appendix.

                         At the bottom of this file is a table presenting a list of all the multinational firms with a count of patents over the period 2005-2010 for each firm.

 

Variables

 

 

Variable

Type

Len

Columns in Ascii File

Description

multinat_text

Char

23

1-23

The text field for the multinational name.

applicant_name

Char

80

24-103

The applicant name, as listed on the China patent.

app_numfix

Char

12

104-115

The unique identifier that we use for each China patent.  See the documentation on the file CNpub_basedat

multinat_id

Num

8

116-123

A numeric code we use for each foreign multionational

multinat_country

Char

2

124-125

The home country of the foreign multinational (2 digit code)

applicant_name2

Char

80

126-205

An upper case version of the application name, which some truncation of various symbols

locate_china

Num

8

206-213

=1 if there is a name of a Chinese location (e.g. city) on the applicant name, or if there is a name of a Chinese company.

=0 otherwise

has_CNinvt

Num

8

214-221

=1 if there is at least one inventor with a Chinese name.  See the separate appendix for a discussion of our algorithm for identifying Chinese names.

shared

Num

8

222-229

=1 if the multinational shares ownership of the patent with a Chinese firm.  See the separate appendix for a discussion of our procedure for classifying patents on this variable.

type

Char

8

230-237

=’Invent’ if an invention patent

=’Utility’ if a utility patent

gyear

Num

8

238-245

The year the patent was published

first_file_China

Num

8

246-253

=1 if there is no foreign priority claim made on the patent.  This generally means that China is the first place the patent is being filed.

auto

Num

8

254-261

=1 if multinat_text is one of the following: ('Toyota','Honda','Nissan','Hyundai','Ford','Volkswagen','General_Motors',

'Mazda','Daimler','Suzuki','Peugeot_Citroen','BMW')

 

Table Showing Distribution of Counts of Patents Published 2005-2010 by Multinational and Type of Patent

 

 

N

All

type

Invent

Utility

multinat_id

multinat_text

3,593

3,590

3

2

Nokia

3

Volkswagen

224

164

60

5

General_Motors

2,229

1,921

308

6

Motorola

1,927

1,922

5

7

Toyota

5,444

5,395

49

8

Honda

2,997

2,890

107

9

Samsung

22,426

21,254

1,172

10

Nissan

1,487

1,410

77

11

Total

249

249

.

12

Sony

11,979

11,954

25

13

Ericsson

3,383

3,379

4

14

Ford

1,136

976

160

15

Mazda

260

259

1

16

Seagate

140

140

.

18

Flextronics

89

69

20

19

BP

244

244

.

20

Hewlett_Packard

1,153

1,153

.

21

Hyundai

1,191

1,175

16

22

Shell

985

980

5

23

POSCO

213

213

.

24

Dell

133

121

12

25

Peugeot_Citroen

119

107

12

28

BASF

3,375

3,375

.

29

BMW

125

124

1

31

Sharp

5,094

5,054

40

32

Daimler

117

117

.

33

Alcatel

2,960

2,955

5

34

Walmart

6

6

.

35

Sumitomo

4,673

4,648

25

36

LG

18,390

18,092

298

37

Amway

1

1

.

39

Procter_Gamble

1,761

1,758

3

40

Freescale

602

602

.

41

Matsushita_Panasonic

16,250

15,171

1,079

43

Nisshin_Steel

24

24

.

44

Mitsui

932

930

2

45

Hanwa

1

1

.

46

Siemens

7,522

7,273

249

47

Philips

13,771

13,670

101

48

Nippon_Steel

777

748

29

49

Arcelor

51

50

1

51

Qimonda

1,307

1,307

.

52

Suzuki

133

117

16

53

IBM

6,542

6,542

.

54

Exxon

780

780

.

55

Saudi_Aramco

38

38

.

56

SK_Hynix

1,177

1,177

.

57

Jabil_Circuit

6

5

1

60

Schneider

315

222

93

61

Nippon_Mining_Metal

189

189

.

62

Fuji

1,607

1,603

4

63

Xerox

2,161

2,157

4

65

KIA

152

152

.

67

Canon

5,654

5,648

6

68

Otis_Elevator

385

328

57

69

Mitsubishi

7,093

7,057

36

70

Toshiba

5,334

5,250

84

71

NEC

3,617

3,521

96

75

Unilever

765

765

.

76

Komatsu

408

406

2

78

Hitachi

10,248

9,942

306

81

Doosan

98

58

40

82

Nike

278

242

36

83

Ricoh

2,349

2,345

4

84

ADM

29

29

.

86

Epson

5,688

5,567

121

87

Anheuser_Busch_InBev

34

34

.

91

Daikin

1,157

1,086

71

94

Brother

1,864

1,544

320

95

Cummins

135

107

28

97

Best_Buy

1

1

.

98

LOreal

530

530

.

99

Iveco

47

27

20

101

Kobelco

838

838

.

103

Nestle

71

67

4

104

Sanmina_SCI

11

11

.

106

Morgan_Stanley

2

2

.

107

Johnson_Controls

248

192

56

108

Wrigley

84

81

3

109

Inco

15

15

.

111

Itochu

5

4

1

112

Bayer

2,229

2,225

4

113

Cargill

123

123

.

114

Emerson

739

486

253

116

Bosch

4,602

4,524

78

117

Coca_Cola

155

154

1

119

Celestica

2

2

.

121

Makita

189

185

4

122

Adidas

26

26

.

123

Sanyo

3,962

3,869

93

124

Microsoft

3,106

3,106

.

125

UPM_Kymmene

24

24

.

128

Isuzu

170

170

.

130

Kyocera_Mita

1,407

1,395

12

131

Mitsumi

258

258

.

132

Pioneer

678

660

18

135

ABB

1,587

1,382

205

136

Caterpillar

611

577

34

139

Bridgestone

698

696

2

140

Krupp

282

238

44

142

Logitech

49

41

8

143

Delphi_Packard

14

.

14