Factor Markets, Biased Technological Change and Total Factor Productivity - Empirical Evidence from a Sample of OECD Countries

2008 ◽  
Author(s):  
Cristiano Antonelli ◽  
Francesco Quatraro
Keyword(s):  
Technological Change ◽  
Empirical Evidence ◽  
Total Factor Productivity ◽  
Oecd Countries ◽  
Factor Productivity ◽  
Biased Technological Change ◽  
Factor Markets

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.

New Evidence on the Relationship Between Economic Freedom and Growth: A Panel Cointegration Analysis for The Case of OECD

2012 ◽  
Vol 12 (3) ◽  
pp. 1850263 ◽  
Author(s):  
Ekrem Erdem ◽  
Can Tansel Tugcu
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Total Factor Productivity ◽  
Economic Freedom ◽  
Global Financial Crisis ◽  
Oecd Countries ◽  
Cointegration Analysis ◽  
Factor Productivity ◽  
The Impact ◽  
The Relationship

The aim of this paper is to find a new answer to an old question “Is economic freedom good or not for economies?” which was refreshed after the Global Financial Crisis of 2008. For this purpose, the relationship between economic freedom and economic growth, and the relationship between economic freedom and total factor productivity in OECD countries were investigated by using panel data for the period of 1995-2009. Study employed the recently developed cointegration test by Westerlund (2007) and the estimation technique by Bai and Kao (2006) which account for cross-sectional dependence that is an important problem in the panel data studies. Although no significant relationship found between economic freedom and total factor productivity, cointegration analysis revealed that economic freedom matters for economic growth in OECD countries in the long-run, and estimation results showed that direction of the impact is negative.

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