Learning-by-Exporting? Firm-Level Evidence for UK Manufacturing and Services Sectors



Table 4: Long-run ‘learning-by-exporting’ effect for certain UK industries, 1996-2004

______AGF

FBT

TCL

WPP

CRR

MET

ENG

OMF

IV model (GMM)

EXP_entry t+1

0.061

-0.013

0.066

0.678*

0.242

-0.004

0.112

-0.094

EXP_entry t

-0.012

_sksk
0.117**

0.173

-0.228

0.030

-0.043

0.278***

0.272***

EXP_entry t-1

-0.066

-0.019

-0.094

-0.238**

0.068

-0.052

_  _    _sksk

-0.215**

_ _ _ *

-0.084*

EXP_exit t+1

0.084

-0.126*

-0.284*

0.107

-0.186*

-0.264***

0.098

-0.068

EXP_exit t

0.133

-0.054

-0.072

0.118

_ _ .sksksk

-0.692***

0.120

-0.091

0.094

EXP_exit t-1

-0.447

-0.049

0.157

-0.236

0.399*

_ _ _sksksk
0.237***

-0.114*

0.055

EXP_both t+1

0.689***

-0.021

-0.086

0.076

-0.025

-0.072

-0.048

-0.045

EXP_both t

0.042

0.211**

-0.153

-0.013

-0.004

0.071

0.036

0.042

EXP_both t-1

0.260

sk

-0.104*

0.110

0.057

-0.017

-0.008

0.009

-0.055

No. of Obs.

1702

3065

2223

6903

4629

7075

9596

3731

No. of groups

508

741

530

1798

1107

1719

2252

948

Control function

EXP_entry t+1

0.074

-0.014

0.013

0.743**

0.256

-0.013

0.094

-0.102

EXP_entry t

-0.061

0.271**

0.298

0.390

-0.041

0.039

0.410*

0.353

EXP_entry t-1

-0.043

-0.013

-0.157

-0.329***

0.056

-0.065

-0.200*

-0.063

EXP_exit t+1

0.086

-0.108*

-0.272

0.127

sksk

-0.181**

_ .sksksk

-0.198***

0.043

-0.068

EXP_exit t

0.117

-0.257

-0.029

-0.433

-0.476

-0.001

-0.281

-0.066

EXP_exit t-1

-0.383

-0.015

0.174

-0.272**

0.295

_sksksk

0.215***

_ _ *

-0.102*

0.070

EXP_both t+1

0.693***

-0.054

-0.115

0.056

0.006

-0.053

-0.051

-0.051

EXP_both t

0.018

0.369**

-0.117

0.463**

-0.065

0.118

0.222

0.092

EXP_both t-1

0.283

-0.158*

0.103

0.035

0.001

-0.010

0.025

-0.045

λ1

0.009

-0.014

0.009

_   _ _ sksksk

-0.201***

0.109

-0.040

0.012

0.017

λ0

0.058

-0.240***

-0.014

0.352

0.015

0.007

-0.122*

-0.121

No. of Obs.

1702

3065

2223

6903

4629

7075

9596

3731

No. of groups

508

741

530

1798

1107

1719

2252

948

Matched sample

EXP_entry t+1

0.048

0.020

-0.043

__.sksk

0.533**

*
0.241
*

0.008

0.115

-0.063

EXP_entry t

0.009

0.093**

- _ - *
0.340*

-0.113

-0.001

-0.065

_ _ .sksksk

0.276***

0.278***

EXP_entry t-1

0.025

0.001

-0.031

-0.246***

0.082

-0.022

-0.201*

-0.136*

EXP_exit t+1

0.036

-0.092*

-0.349*

0.097

-0.192*

-0.281***

0.092

-0.067

EXP_exit t

-0.006

-0.077

0.039

0.120

___.sksksk

-0.729***

__ .sk

0.176*

-0.075

0.108

EXP_exit t-1

-0.415

-0.042

0.200

-0.254*

0.436*

.sksksk

0.212***

-0.106*

0.052

EXP_both t+1

0.694

-0.040

-0.091

0.086

-0.006

-0.072

-0.039

-0.058

EXP_both t

0.026

_ _sksk
0.185**

-0.057

-0.002

0.001

0.070

0.035

0.038

EXP_both t-1

_  _ -SkSkSk

0.309***

-0.063

0.205

0.064

-0.012

-0.010

-0.006

-0.088

No. of Obs.

682

2564

2100

5178

4525

6386

3731

3443

No. of groups_________

261

685

509

1526

1089

1610

948

890

Notes: Refer to Table 2 for details of industry group codes. The 2-step GMM system estimator in STATA 9 is used
using
FAME data in conjunction with weights; the instrument set includes lagged values of the RHS variables
in the model as well as
ln Ageit and Intangit . Standard errors are obtained using the ‘delta’ method. See

Table 3 for details of estimation of other variables. ***/**/* significant at the 1%/5%/10% level.

28



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