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Economic Returns from Internet Use: Analysis of Three Panel Data SetsEconomic Returns from Internet Use: Analysis of Three Panel Data Sets

Other Titles
Economic Returns from Internet Use: Analysis of Three Panel Data Sets
Authors
김상문지인엽
Issue Date
Dec-2021
Publisher
동국대학교 사회과학연구원
Keywords
인터넷의 효용; 네트워크 효과; 선점 효과; 기술 확산; 소득 불평등; Internet premium; Network effect; First-mover advantage; Technology diffusion; Earnings inequality
Citation
사회과학연구, v.28, no.4, pp 161 - 182
Pages
22
Indexed
KCI
Journal Title
사회과학연구
Volume
28
Number
4
Start Page
161
End Page
182
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/4087
ISSN
1598-8996
Abstract
Despite the widely held notion that the proliferation of computers contributes to earnings inequality, a limited number of studies employ a more direct measure of technology use as a determinant of earnings. Moreover, these studies report the mixed findings, indicating that the empirical evidence on the wage effect of computer use is divided. As a contribution to this line of research, we attempt in this paper to formulate a formal logic behind Internet premium. More specifically, we argue that the utility of the Internet is determined by a combination of two opposing forces – network effect and first-mover advantage, and thus follows an inverted-U shape over time. That is, the opposing forces open a window of opportunity for a period of time. To examine this hypothesis that Internet premium is time-varying, we use the Current Population Survey, conducted by the US Bureau of Census between 1997 and 2010. Analyses of three two-wave panel data sets support the expected temporal pattern: Internet use wage premium was the highest in 2000–01, followed by 1997–98, and completely disappeared by 2009-10. We also find little interaction effect between Internet use and educational attainment. These findings suggest: 1) while the Internet, an externally-sourced technology, may not allow exclusive and proprietary skills, it can still provide a wage premium for a limited time; and 2) adoption timing is often more critical than adopter attributes. We also discuss some suggestions for future research.
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