Comparative analysis of total factor productivity in China's high-tech industries

Author(s):  
Xiaoqing Chen ◽  
Xinwang Liu ◽  
Qingyuan Zhu
Author(s):  
Metin Yildirim ◽  
Ferda Nakipoğlu Özsoy ◽  
Prof. Aslı Özpolat ◽  
Dr. Filiz Çayirağasi

An increase in competition power provides more profitability by affecting the amount of production and export. By the increase in technology, innovation and R&D investments in recent ages in the world, high technology industries became even more important for competitive power. In this study, two analyses covering the data from 1995 to 2015 have been considered. In the first analysis, the competitiveness of the high-tech and low-tech sectors has been compared by using RCA index for selected countries. In the second analysis, the relationship between competition power and growth, total factor productivity and R&D expenditures have been analyzed by using GMM.


2019 ◽  
Vol 85 (2) ◽  
pp. 12-20
Author(s):  
T. K. Kvasha

The Total Factor Productivity (TFP) is now widely recognized as an important factor in both long-term economic growth and short-term growth fluctuations. Researchers of the International Monetary Fund came to the conclusion that the growth of the TFP was the most important long-term factor in raising the living standards. Therefore, the IMF and academics from different countries has been scrutinizing the reasons for the slowdown in TFP and investigating the underlying factors. The low rates of GDP grow in Ukraine call for finding the drivers, one of which is TFP growth. It raises the importance of analysis of the factors promoting this growth in Ukraine.  The purpose of this work is to define TFP drivers, which would be most effective for Ukraine. TFP drivers in foreign countries are analyzed, TFP dynamics for Ukraine is calculated by use of Solow model, and TFP drivers over 2000–2017 are determined.         The analysis of publications about TFP drivers at global level shows that they include: international transfer of knowledge and technologies, activities of small innovative fast-growing firms, the enhanced quality of quality of education, the increased expenditures on R&D and innovations, especially by business sector, the increased investments in intangible assets, the intensified patent activity, access of enterprises to lending. The TFP dynamics in Ukraine, calculated by the Solow model, is characterized by high growth rates by 2012, a sharp fall in 2013-2015, and a return to the growth path in 2016-2017, but, as in the whole world, by very moderate pace. The factors contributing to this return are capital investment in intangible assets, the increasing patent activity of Ukrainian researchers, the intensified innovation in the high-tech sector. Factors constraining the TFP and the contribution of innovation to economic growth are a significant proportion of technology transfer in the form of “know-how, agreements for the acquisition (transfer) of technologies”, which holds back the widespread introduction of cutting-edge technologies, and the reduction of funding for R&D and innovation. Further studies should be focused on searching for political decisions promoting implementation of structural reforms aimed to solve the existing problems and eliminate their consequences, especially in of the innovation and education field.


2021 ◽  
Vol 4 (2) ◽  
pp. 146-156
Author(s):  
Kusuma Wardani (Universitas Indonesia) ◽  
Muhammad Halley Yudhistira (Universitas Indonesia)

AbstractThis study aims to analyze the impact of agglomeration in the form of localization economies and urbanization economies on the productivity of manufacturing industrial companies in Indonesia. Unlike previous studies, this study will look at the effect of technology level on the relationship between productivity and agglomeration by classifying research samples into low-tech and high-tech industries. In addition, this study also improves the estimation technique by addressing the endogeneity problem that has the potential to arise in estimating the relationship between productivity and agglomeration to be overcome by using instrument variable (IV). The study was conducted in two stages of estimation using company-level panel data from 2010 to 2014. First, productivity was measured at the company level using Total Factor Productivity (TFP). Then, the company productivity is estimated together with the company and industry characteristic variables, including the agglomeration measurement variable which represents localization economies and urbanization economies. The regression results show a positive impact from localization economies and a negative impact from urbanization economies.AbstrakPenelitian ini bertujuan menganalisis dampak aglomerasi berupa localization economies dan urbanization economies terhadap produktivitas perusahaan industri manufaktur di Indonesia. Berbeda dengan penelitian terdahulu yang juga meneliti dampak aglomerasi industri terhadap produktivitas perusahaan, pada penelitian ini akan melihat pengaruh tingkat teknologi terhadap hubungan produktivitas dan aglomerasi dengan mengklasifikasikan sampel penelitian ke dalam industri berteknologi rendah dan industri berteknologi tinggi. Selain itu, peneltian ini juga memperbaiki teknik estimasi dari penelitian sebelumnya dengan menangani masalah endogenitas yang berpotensi muncul dalam mengestimasi hubungan produktivitas dan aglomerasi akan diatasi dengan penggunaan instrument variable (IV). Penelitian dilakukan dalam dua tahap estimasi dengan menggunakan data panel level perusahaan dari tahun 2010 sampai 2014. Pertama, produktivitas diukur pada level perusahaan dengan menggunakan Total Factor Productivity (TFP). Kemudian, produktivitas perusahaan diestimasi bersama variabel karakteristik perusahaan dan industri, termasuk variabel pengukuran aglomerasi yang mewakili localization economies dan urbanization economies. Hasil regresi menunjukkan adanya dampak positif dari localization economies dan dampak negatif dari urbanization economies.


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