Bibliographic Details
| Title: |
Technology Import and Biased Technological Progress in Transforming Economies: Evidence From China. |
| Authors: |
Dai, Shangze1 (AUTHOR) shangzedai@ufl.edu, Ji, James1 (AUTHOR), Yu, Haichao2 (AUTHOR) |
| Source: |
Review of Development Economics. Sep2025, p1. 21p. 3 Illustrations. |
| Subject Terms: |
*TECHNOLOGY transfer, *TECHNOLOGICAL progress, *TECHNOLOGICAL innovations, *ECONOMIC development, POPULATION aging, SPATIAL analysis (Statistics), ECONOMIC conditions in China |
| Geographic Terms: |
CHINA |
| Abstract: |
ABSTRACT Transforming economies increasingly face demographic headwinds and slowing capital accumulation and turn to technology imports from developed countries as an important strategy for bolstering growth. However, the effectiveness of this strategy depends on the direction of the technological bias it induces; labor‐saving progress can offset a shrinking workforce, while capital‐saving progress can alleviate investment slowdowns. Using a panel dataset of 282 Chinese cities from 2010 to 2019, we employ panel fixed‐effects, threshold, and spatial econometric models. We find three key results. First, technology import significantly promotes labor‐saving technological progress, suggesting that rising local labor costs dominate technological innovation. Second, this labor‐saving effect is heterogeneous, growing stronger in regions with a higher development stage, more advanced factor endowments, and higher knowledge production efficiency. Third, technology import creates negative spatial spillovers, inducing a capital‐saving bias in neighboring regions. These findings suggest that disruptions to global technology flows may hinder the ability of transforming economies to address the challenges of population aging. [ABSTRACT FROM AUTHOR] |
|
Copyright of Review of Development Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Business Source Index |