2016
DOI: 10.1111/twec.12397
|View full text |Cite
|
Sign up to set email alerts
|

The Skill Structure of Export Wage Premium: Evidence from Chinese Matched Employer–Employee Data

Abstract: We study how the wage gap between exporting and non‐exporting firms (export wage premium) differs across skill groups, using unique matched employer–employee data from China. We find robust evidence that exporters pay relatively higher wages than non‐exporters to more educated workers. The differences in export wage premium across education groups are sizable. Further investigations show that the positive correlation between export wage premium and education is more pronounced in sectors with higher scope for … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 35 publications
(49 reference statements)
0
1
0
Order By: Relevance
“…3 A number of studies trace back exports to the implied demand of labour skills; starting from the seminal work by Bombardini et al (2012) to more recent contributions by Brambilla, Chauvin, et al (2017); Brambilla, Lederman, et al (2017); Dai and Xu (2017); and Lichter et al (2017). Other studies document the linkages between skills, product quality and characteristics of the destination market; see Bastos and Silva (2010), Brambilla and Porto (2016) and Macis and Schivardi (2016).…”
Section: Introductionmentioning
confidence: 99%
“…3 A number of studies trace back exports to the implied demand of labour skills; starting from the seminal work by Bombardini et al (2012) to more recent contributions by Brambilla, Chauvin, et al (2017); Brambilla, Lederman, et al (2017); Dai and Xu (2017); and Lichter et al (2017). Other studies document the linkages between skills, product quality and characteristics of the destination market; see Bastos and Silva (2010), Brambilla and Porto (2016) and Macis and Schivardi (2016).…”
Section: Introductionmentioning
confidence: 99%