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

Table 2 S-GMM estimation—dependent variable: LN EMPSHARE

From: Does innovative capacity affect the deindustrialization process? A panel data analysis

Regressors

Model 1

Model 2

Model 3

Model 4

Model 5

Model 6

Model 7

Model 8

Model 9

Model 10

BASELINE

R&D

RESEARCHERS

TECHNICIANS

ARTICLE

PATENTS

TRADEMARK

INCENG

INDOUT

INES

LN EMPSHARE(-1)

0.869828***

0.753016***

0.852285***

0.688778***

0.854859***

0.785399***

0.808471***

0.749371***

0.836689***

0.761309***

 

(0.013829)

(0.017692)

(0.052975)

(0.020220)

(0.030045)

(0.029720)

(0.025146)

(0.012561)

(0.026999)

(0.014860)

LN Y

0.117183**

0.424773***

0.643524***

0.882435***

0.525804**

0.297549***

0.104825*

0.321009***

0.254681**

0.357068***

 

(0.055889)

(0.119993)

(0.233292)

(0.187160)

(0.255377)

(0.109358)

(0.054473)

(0.090549)

(0.121120)

(0.109936)

(LN Y)2

− 0.008562***

− 0.026684***

− 0.039090***

− 0.053816***

− 0.031506**

− 0.020719***

− 0.009937***

− 0.021876***

− 0.017556***

− 0.023867***

 

(0.003056)

(0.006423)

(0.012662)

(0.009733)

(0.014096)

(0.005743)

(0.003217)

(0.004801)

(0.006654)

(0.005900)

FIXCAP

0.001076***

0.008070***

0.008560***

0.004329***

0.002517***

0.003945***

0.003080***

0.005462***

0.004552***

0.004869***

 

(0.000399)

(0.000410)

(0.000945)

(0.000602)

(0.000963)

(0.000622)

(0.000703)

(0.000804)

(0.000652)

(0.000416)

TRADEBAL

0.000334**

0.001860***

0.002393***

0.000813**

0.002678***

0.000826***

0.001388***

0.001156**

0.000599*

0.001752***

 

(0.000151)

(0.000226)

(0.000398)

(0.000411)

(0.001026)

(0.000318)

(0.000503)

(0.000493)

(0.000313)

(0.000215)

RIR

− 0.001737***

− 0.000308*

− 0.003644***

− 0.002852***

− 0.002534***

− 0.002195***

− 0.001252***

− 0.000516***

− 0.001165***

− 0.000392***

 

(0.000148)

(0.000165)

(0.000756)

(0.000366)

(0.000517)

(0.000463)

(0.000166)

(0.000142)

(0.000387)

(0.000107)

RER

0.000300***

0.000169**

0.000289**

0.000668***

0.000438**

0.000369***

0.000322***

0.000392***

0.000243***

0.000590***

 

(5.84E−05)

(7.99E−05)

(0.000130)

(0.000150)

(0.000209)

(8.89E-05)

(8.19E−05)

(5.83E−05)

(9.27E−05)

(5.60E−05)

INNOVATION

 

0.008713***

6.93E−06***

4.68E−05***

1.39E−07*

7.82E−08***

5.82E−08***

0.000591*

0.019317***

0.000145*

  

(0.003082)

(1.62E−06)

(9.93E−06)

(7.16E−08)

(1.43E−08)

(4.71E−09)

(0.000341)

(0.004156)

(8.41E−05)

Obs

1016

522

393

313

574

739

764

365

561

552

Countries

78

52

44

41

65

63

66

53

58

63

Number instruments/Number cross section ratio

0.782

0.942

0.977

0.951

0.554

.

0.788

0.849

0.776

0.952

Prob J

0.160384

0.243426

0.464088

0.395213

0.775799

0.295057

0.250042

0.384297

0.131712

0.557639

AR(1)

− 0.420420

− 0.385865

− 0.408203

− 0.342694

− 0.382980

− 0.436203

− 0.431961

− 0.472342

− 0.419081

− 0.387167

P-value

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

AR(2)

− 0.052266

− 0.087823

− 0.070758

0.011518

− 0.050546

− 0.040913

− 0.063828

− 0.063828

− 0.006831

− 0.057561

P-value

0.1607

0.1020

0.2742

0.8676

0.3325

0.3331

0.1354

0.5872

0.8925

0.2476

  1. i) Information in brackets is the standard error associated with the coefficient
  2. (ii) Level of statistical significance: (***) denotes 1%, (**) denotes 5% and (*) denotes 10%
  3. (iii) S-GMM: based on Arellano and Bover (1995), two stages and no time dummy. AR (1) and AR (2) tests to verify the presence of first-order and second-order serial correlation in the waste in difference
  4. iv) The number of instruments to the number of cross-section ratio needs to be higher than 1. Although the S-GMM estimates are adherent for samples with short periods and a high number of individuals, the diversity of instruments may generate the overlapping of instruments on the variables used, generating bias in the result (Roodman 2009)