Optimal economic growth problems with high values of total factor productivity

2020 ◽  
pp. 1-15 ◽  
Author(s):  
Vu Thi Huong
2016 ◽  
Vol 21 (Special Edition) ◽  
pp. 33-63 ◽  
Author(s):  
Rashid Amjad ◽  
Namra Awais

This paper reviews Pakistan’s productivity performance over the last 35 years (1980–2015) and identifies factors that help explain the declining trend in labor productivity and total factor productivity (TFP), both of which could have served as major drivers of productivity growth – as happened in East Asia and more recently in India. A key finding is that the maximum TFP gains and their contribution to economic growth are realized during periods of high-output growth. The lack of sustained growth and low and declining levels of investment appear to be the most important causes of the low contribution of TFP to productivity growth, which has now reached levels that should be of major concern to policymakers vis-à-vis Pakistan’s growth prospects.


2021 ◽  
Author(s):  
Remzi Can Yılmaz ◽  
Ahmet Rutkay Ardoğan

According to the economics literature, there are two main sources of economic growth. While the first of the resources is the accumulation of production factors, the other is the part of the output that cannot be explained by the amount of input used in production, in other words, the total factor productivity. The level of total factor productivity is measured according to how efficiently the inputs are used in the production process. In this study, the hypothesis that public spending affects real economic growth through total productivity is investigated. In the first stage, whether the changes in public expenditures affect the total factor productivity or not; if it does, to what extent and in what direction it has been tried to be revealed. In the second stage, the effect of total factor productivity on economic growth was examined and the statistical significance, direction and extent of the relationship between variables were investigated. Annual data were used in the study and the year range is 2000-2017. The sampling economies were selected according to data availability, and there are a total of 20 developed and developing economies. Research was conducted using multiple panel regression analysis. According to the findings, the relationship between public expenditures and total factor productivity is statistically significant. An increase in public expenditures reduces the total factor productivity. The relationship between total factor productivity and economic growth is statistically significant, and an increase in total factor productivity also increases economic growth. An increase in public expenditures affects economic growth negatively by reducing the total factor productivity.


2018 ◽  
Vol 06 (02) ◽  
pp. 1850012
Author(s):  
Jiancui LIU ◽  
Shilin ZHENG

Total factor productivity represents not only the core of neo-classical growth theory research, but is also a key component in the understanding of the transitional processes of China from a factor-driven to an innovation-driven economy. In this paper, relying on 2000–2014 year statistical data, drawn from China’s four centrally administered and 283 provincial-level cities, the paper’s authors apply Cobb–Douglas production function methods to the calculation of urban total factor productivity rates of increase, and to changes in differing factor inputs, to show how, during the period of interest, involved changes impacted China’s economic growth. The analysis finds that: (1) between the years 2001 and 2005, changes in total factor productivity represented an important source of economic growth, but that after 2005 China’s economic growth clearly exhibited physical capital-driven features; (2) from 2012 onwards, influenced by resource-based and heavy chemical industries, the decrease in total factor productivity of China’s central region cities was the greatest (among the various areas), revealing an “extensive” aspect, and in 2014 the contribution rates of the region’s cities’ physical capital and total factor productivity were 127.77% and [Formula: see text]36.6%, respectively; (3) examining the cities based on their differing classifications, after 2012, the contribution rates of the fourth-tier cities’ total factor productivities underwent severe declines, while in China’s first- and second-tier cities the contribution rates of their total factor productivities exhibited signs of recovery.


2012 ◽  
Vol 12 (3) ◽  
pp. 1850263 ◽  
Author(s):  
Ekrem Erdem ◽  
Can Tansel Tugcu

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.


2014 ◽  
Vol 16 (2) ◽  
pp. 387-406 ◽  
Author(s):  
Jana Hanclova ◽  
Petr Doucek ◽  
Jakub Fischer ◽  
Kristyna Vltavska

The paper examines economic growth in old and new member countries of the European Union (EU-15 and EU-12) during the years of 1994–2000 and 2001–2008 mainly due to changes in information and communication technology (ICT) capital development. The first group EU-15 is presented by old EU countries and the second group EU-12 is presented by new member countries that joined the EU in 2004–2007. The threefactor Cobb-Douglas production function is estimated through the panel general least squares method. The input factors that might influence the economic growth are labour, ICT capital services and non-ICT capital services. Since ICT capital growth data are not available for all selected economies, the groups of countries were reduced to EU-14 and EU-7. The estimated panel production functions confirmed that the average growth of GDP in the EU-7 countries was supported by the stable growth of labour quantity and ICT-capital and increasing total factor productivity. A short-term drop in non-ICT capital growth with follow-up stagnation was caused rather by lower labour productivity. The research discovered that the drop in GDP growth in the EU-14 countries was a result of the slower growth of non-ICT capital and total factor productivity and the stagnated growth of ICT capital with low elasticity, and showed that even the compensation of growth in labour quality did not prevent a decrease in total factor productivity and economic growth.


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