Putting the Bias in Skill-Biased Technological Change? A Relational Perspective on White-Collar Automation at General Electric

2013 ◽  
Vol 58 (3) ◽  
pp. 400-415 ◽  
Author(s):  
Caroline Hanley
Keyword(s):  
Technological Change ◽  
White Collar ◽  
General Electric ◽  
Relational Perspective ◽  
Biased Technological Change

scholarly journals Mechanisms of Environmental Regulation’s Impact on Green Technological Progress—Evidence from China’s Manufacturing Sector

2021 ◽  
Vol 13 (4) ◽  
pp. 1600
Author(s):  
Weijiang Liu ◽  
Mingze Du ◽  
Yuxin Bai
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Technological Change ◽  
Environmental Protection ◽  
Technological Progress ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
The Sustainable Development ◽  
Biased Technological Change ◽  
Chinese Manufacturing Industry

As the world’s largest developing country, and as the home to many of the world’s factories, China plays a crucial role in the sustainable development of the world economy regarding environmental protection, energy conservation, and emission reduction issues. Based on the data from 2003–2015, this paper examined the green total factor productivity and the technological progress in the Chinese manufacturing industry. A slack-based measure (SBM) Malmquist productivity index was used to measure the bias of technological change (BTC), input-biased technological change (IBTC), and output-biased technological change (OBTC) by decomposing the technological progress. It also investigated the mechanism of environmental regulation, property right structure, enterprise-scale, energy consumption structure, and other factors on China’s technological progress bias. The empirical results showed the following: (1) there was a bias of technological progress in the Chinese manufacturing industry during the research period; (2) although China’s manufacturing industry’s output tended to become greener, it was still characterized by a preference for overall CO2 output; and (3) the impact of environmental regulations on the Chinese manufacturing industry’s technological progress had a significant threshold effect. The flexible control of environmental regulatory strength will benefit the Chinese manufacturing industry’s technological development. (4) R&D investment, export delivery value, and structure of energy consumption significantly contributed to promoting technological progress. This study provides further insight into the sustainable development of China’s manufacturing sector to promote green-biased technological progress and to achieve the dual goal of environmental protection and healthy economic growth.

scholarly journals Skill-Biased Technological Change and Inequality in the U.S.

2020 ◽  
pp. 91-107
Author(s):  
Ana Ferreira
Keyword(s):  
Income Inequality ◽  
Technological Change ◽  
Incomplete Markets ◽  
Gini Coefficient ◽  
Income Tax ◽  
Overlapping Generations ◽  
Overlapping Generations Model ◽  
Biased Technological Change ◽  
Household Heterogeneity ◽  
The U.S

Since the 1980s, income inequality has increased markedly and has reached the highest level ever since it started being recorded in the U.S. This paper uses an overlapping generations model with incomplete markets that allows for household heterogeneity that is calibrated to match the U.S. economy with the purpose to study how skill-biased technological change (SBTC) and changes in taxation quantitatively account for the increase in inequality from 1980 to 2010. We find that SBTC and taxation decrease account for 48% of the total increase in the income Gini coefficient. In particular, we conclude that SBTC alone accounted for 42% of the overall increase in income inequality, while changes in the progressivity of the income tax schedule alone accounted for 5.7%.

scholarly journals DIRECTED TECHNOLOGICAL CHANGE: A KNOWLEDGE-BASED MODEL

2013 ◽  
Vol 19 (1) ◽  
pp. 116-143 ◽  
Author(s):  
Tailong Li ◽  
Shiyuan Pan ◽  
Heng-fu Zou
Keyword(s):  
Technological Change ◽  
Wage Inequality ◽  
Scale Effects ◽  
Developed Countries ◽  
Skilled Workers ◽  
Developed Country ◽  
Knowledge Based ◽  
Biased Technological Change ◽  
Unskilled Workers ◽  
Directed Technological Change

In a knowledge-based growth model where skilled workers are used in innovation and production, skill-biased technological change may lower average R&D productivity via an innovation possibilities frontier effect that eliminates scale effects. We show that skill-biased technological change increases the skill premium even if the elasticity of substitution between skilled and unskilled workers is less than two. Trade between developed countries promotes skill-biased technological change, thus raising wage inequality. Trade between developed and developing countries has differing effects: it induces relatively skill-replacing technological change and lowers wage inequality in the developed country but has the opposite effects in the developing country. Finally, we show that trade can stimulate or hurt economic growth.

scholarly journals Technological Bias and Its Influencing Factors in Sustainable Development of China’s Transportation

2020 ◽  
Vol 12 (14) ◽  
pp. 5704
Author(s):  
Shuai Zhang ◽  
Xiaoman Zhao ◽  
Changwei Yuan ◽  
Xiu Wang
Keyword(s):  
Sustainable Development ◽  
Technological Change ◽  
Total Factor Productivity ◽  
Influencing Factors ◽  
Technological Progress ◽  
Transportation Industry ◽  
Factor Productivity ◽  
The Sustainable Development ◽  
Biased Technological Change ◽  
Technological Bias

The bias of technological progress, particularly relating to energy saving and carbon emissions reduction, plays a significant role in the sustainable development of transportation, and has not yet received sufficient attention. The objectives of this paper were to examine the bias of technological change (BTC), input-biased technological change (IBTC), and output-biased technological change (OBTC), and their influencing factors in the sustainable development of China’s regional transportation industry from 2005 to 2017. A slack-based measure (SBM) Malmquist productivity index was adopted to measure the BTC, IBTC, and OBTC by decomposing green total factor productivity. The results revealed that: (1) Continuous technological bias progress and input-biased technological progress existed in China’s transportation development from 2005 to 2017, making an important contribution to green total factor productivity. The output-biased technological change was close to 1, indicating a slight impact on the sustainable development of the transportation industry; (2) The bias of technological progress in eastern regions was slightly greater than that in central regions, and obviously greater than that in western regions. Moreover, different provinces experienced different types of technological bias change, with four major types observed during the research period; (3) The input-biased technology of a majority of provinces tended to invest more capital relative to labor, using more capital comparing to energy, and consume more energy relative to labor, while the output-biased technology of most provinces tended to produce desirable outputs (value added in transportation) and reduce the byproduct of CO2 relatively; (4) Average years of education, green patents in transportation, industrial scale, and local government fiscal expenditure in transportation significantly contributed to promoting the bias of technological progress, which was inhibited by the R&D investment. This study provides further insight into the improvement of sustainable development for China’s transportation, thereby helping to guide the government to promote green-biased technological progress and optimize the allocation of resources.

Sign in / Sign up

Export Citation Format

Share Document