Econometric Analysis of Total Factor Productivity in India

2021 ◽  
pp. 001946622098806
Author(s):  
Mushtaq Ahmad Malik ◽  
Tariq Masood ◽  
Mehraj Ahmad Sheikh
Keyword(s):  
Total Factor Productivity ◽  
Global Economy ◽  
Negative Impact ◽  
Positive Impact ◽  
New Technology ◽  
Factor Productivity ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Time Period ◽  
Two Stages

This article attempts to investigate the potential relationship and significance of various determinants of Total Factor Productivity (TFP) in India for the 1980–2016 time period. Specifically, this is achieved in two stages. In the first, the standard growth accounting approach is used to measure the changes in TFP. Then, the main model for establishing the determinants of TFP growth is estimated using the autoregressive distributed lag (ARDL) model. Our results suggest that inflation and financial development have a statistically positive impact on TFP. Foreign direct investment, imports, and capital formation are found to have a positive but insignificant impact on the TFP. On the other hand, exports, government size, and natural calamities have a statistically negative impact on TFP. Therefore, in order to accelerate the TFP, governments and policymakers need to design and implement policies to increase financial access to the private sector, while maintaining price stability; exports of high-value products; and increased economic integration in the global economy to benefit from foreign investment flows, which brings in new technology.

The Dynamic Correlation Between Capital Deepening and Total Factor Productivity in China

2020 ◽  
Vol 24 (4) ◽  
pp. 524-531
Author(s):  
Wuliu Zhang ◽  
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Negative Impact ◽  
Positive Impact ◽  
Linear Structure ◽  
Physical Capital ◽  
Influence Coefficient ◽  
Factor Productivity ◽  
Capital Deepening ◽  
The Impact

The impact of capital deepening on total factor productivity (TFP) is a significant and controversial issue. Based on the calculation of relevant indicators, this study adopts a Bayesian time-varying parameter model, Bayesian quantile regression, and adaptive Bayesian quantile models for in-depth statistical analysis. TFP was found to have a complex non-linear structure, and physical and human capital deepening indicators show a significant upward trend. The deepening of physical capital has a negative impact on TFP, while the deepening of human capital has a positive impact. In the capital deepening structure, the level of TFP has been improved and its structure optimized. Primary human and non-production physical capital deepening has no significant effect on TFP, while secondary human capital deepening has some significant effects on TFP. Tertiary and productive human capital deepening of TFP present two different forms of significant effect: the influence coefficient of the former declines in the increasing quantile and the change is larger, while the latter has a stable negative impact. The results of this study provide insights in terms of the improvement of China’s productivity.

scholarly journals Impact of collaborative innovation on green total factor productivity in Yangtze River Economic Belt: Analysis based on endogenous spatial-temporal weight matrix

2021 ◽  
Author(s):  
lei Wu ◽  
Xiaoyan Jia ◽  
Jie Lv ◽  
Li Gao
Keyword(s):  
Total Factor Productivity ◽  
Yangtze River ◽  
Negative Impact ◽  
Positive Impact ◽  
Spatial Interaction ◽  
Evaluation Index System ◽  
Weight Matrix ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Collaborative Innovation

Abstract Technological innovation can promote high-quality economic growth. This paper discusses the promotion of green total factor productivity from the perspective of collaborative innovation in the Yangtze River Economic Belt. Firstly, the evaluation index system of collaborative innovation level is constructed from two aspects of collaborative innovation elements and collaborative innovation environment. Then the entropy method is used to measure its development level. The results show that the collaborative innovation level of provinces in the Yangtze River Economic Belt presents an increasing trend year by year. Meanwhile, there are regional differences, which is characterized by 'high in the middle reaches, middle in the downstream and low in the upstream' Secondly, the SDM model based on endogenous spatio-temporal weight matrix is constructed to analyze the influencing factors of green total factor productivity. The results show that collaborative innovation in the Yangtze River Economic Belt has significant negative impact on green total factor productivity in terms of spatial interaction and fiscal expenditure also has a negative impact. The spatial interaction between environmental protection and opening up has a significant positive impact on green total factor productivity. However, the spatial interaction between industrial structure and human capital on green total factor productivity is not obvious. Finally, this paper puts forward some policy suggestions to improve green total factor productivity.

scholarly journals FDI-Led-Growth in Malaysia: Autoregressive Distributed Lag (ARDL) Bounds Testing Approach

2018 ◽  
Vol 11 (11) ◽  
pp. 46
Author(s):  
Jerome Kueh ◽  
Yong Sze Wei
Keyword(s):  
Economic Growth ◽  
Financial Crisis ◽  
Global Financial Crisis ◽  
Negative Impact ◽  
Positive Impact ◽  
Bounds Testing ◽  
Policy Makers ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
The Impact

This study intends to investigate the validity of the foreign direct investment, FDI-led-growth hypothesis in Malaysia in this era. Autoregressive Distributed Lag (ARDL) bounds test approach is adopted to examine the impact of FDI inflow towards growth of Malaysia based on annually data from 1980 to 2016. Empirical results indicate that FDI inflow has significant positive impact on economic growth. This implies that FDI inflow remain important tool for stimulating economic growth of Malaysia. In addition, there is a negative impact of FDI inflow on economic growth during the 1997 Asian Financial crisis and positive impact during the 2008 Global Financial crisis. In terms of policy recommendation, the policy makers should continue to develop strategies to further attract FDI that will contribute to increasing the productivity in the country.

scholarly journals KONSENTRASI SPASIAL, AGLOMERASI DAN PRODUKTIVITAS PERUSAHAAN INDUSTRI MANUFAKTUR INDONESIA

2021 ◽  
Vol 4 (2) ◽  
pp. 146-156
Author(s):  
Kusuma Wardani (Universitas Indonesia) ◽  
Muhammad Halley Yudhistira (Universitas Indonesia)
Keyword(s):  
Total Factor Productivity ◽  
Negative Impact ◽  
Positive Impact ◽  
High Tech ◽  
Factor Productivity ◽  
Localization Economies ◽  
Instrument Variable ◽  
Urbanization Economies ◽  
The Impact ◽  
The Relationship

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.

scholarly journals The Influence of Complexity of Imported Products on Total Factor Productivity

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Nan Wang ◽  
Wei Liu ◽  
Shanwu Sun ◽  
Qingjun Wang
Keyword(s):  
Total Factor Productivity ◽  
Technological Progress ◽  
Negative Impact ◽  
Positive Impact ◽  
Factor Productivity ◽  
Product Complexity ◽  
Technological Efficiency ◽  
The World ◽  
Belt And Road ◽  
Import Trade

The research results show that, all over the world, the increase in complexity of China’s imported products has significantly promoted the growth of total factor productivity and technological progress but has no obvious impact on technological efficiency. In “Belt and Road” samples, the increase in import product complexity did not improve the total factor productivity and technological progress, which had a negative impact on technical efficiency. Whether it is anywhere in the world or in the scope of “Belt and Road” countries, the import product density has a significantly positive impact on total factor productivity but has no significant effect on the promotion of technological progress and efficiency. Therefore, it is necessary to focus on adjusting the import trade structure of “Belt and Road” countries. Relying on the domestic consumer market, the manufacturing imports from countries along the “Belt and Road” route should be expanded so as to stimulate the promotion of domestic industrial total factor productivity.

scholarly journals Dilemma Between Deposit And Lending Rate: Savings-Investment Perspective

2021 ◽  
Vol 65 (1) ◽  
pp. 65-85
Author(s):  
Lateef Yunusa ◽  
◽  
Ibrahim Adekunle ◽  
Tolulope Williams ◽  
Jamiu Akindele ◽  
...  
Keyword(s):  
Financial Institutions ◽  
Negative Impact ◽  
Positive Impact ◽  
Deposit Rate ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Ardl Approach ◽  
Lending Rate ◽  
The Interest Rate ◽  
The Impact

The dilemma between deposit and lending rate has created challenges for financial institutions in the course of intermediation. This dilemma also made it difficult for investors to make accurate decisions which has created a lacuna in the financial system. The objective of this study is to investigate the source of the dilemma between deposit and lending rate. The study also examined the impact of deposit and lending rate on saving and investment respectively in Nigeria using the AutoRegressive Distributed Lag (ARDL) approach. The empirical result revealed the main cause of the dilemma to be the fluctuation in the deposit and lending rate. The ARDL result shows that the deposit rate has a positive impact on savings while the lending rate has a negative impact on investment in Nigeria. The monetary authority should endeavor to maintain stability of the interest rate due to the significant impact of these rates on saving, investment and economic growth at large.

scholarly journals Globalization, Country Risks, and Trade in Tourism Services: Evidence from China

2020 ◽  
Vol 12 (14) ◽  
pp. 5869
Author(s):  
Wenwen Zhang ◽  
Yi-Bin Chiu
Keyword(s):  
Negative Impact ◽  
Positive Impact ◽  
Equilibrium Path ◽  
Service Trade ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Significant Negative Impact ◽  
Short Run ◽  
Tourism Service

This study applies the autoregressive distributed lag (ARDL) model to examine the impacts of globalization and country risks on China’s tourism service trade over the period 1984–2015. The results reveal that in the long run, globalization has a significant negative impact on tourism service exports and tourism service trade balances, while a significant positive impact on tourism service imports. In the short run, globalization has a significant negative impact on tourism service imports, while a significant positive impact on tourism service exports and trade balances. Country stability could roughly mitigate these negative and positive impacts of globalization on tourism service trade in both the short and long run. Moreover, the speed of adjustment from the short run to long run equilibrium path is relatively fast. These results are important for China’s policy makers when formulating a strategy for the development of tourism service trade.

scholarly journals TOTAL FACTOR PRODUCTIVITY CONVERGENCE CASE OF THE WESTERN BALKAN COUNTRIES

2021 ◽  
Vol 9 (21) ◽  
Author(s):  
Zoran Borović
Keyword(s):  
Total Factor Productivity ◽  
New Technology ◽  
Factor Productivity ◽  
Developed Country ◽  
Catching Up ◽  
Productivity Convergence ◽  
Time Period ◽  
Balkan Countries ◽  
Development Accounting ◽  
The Republic

This study examines Total Factor Productivity (hereinafter TFP) convergence in the Western Balkan countries (Republic of Slovenia-SL, Republic of Croatia-CR, Republic of Serbia-SR, and the Republic of Srpska-RS). Our analysis will cover the time period 2000- 2018. Our goal here is threefold. First, we will estimate the TFP for selected countries, and to do so, we will apply the growth accounting. Second, we will use the development accounting to test for the unconditional catching up. And third, we will test the country’s ability to learn or absorb new technology from the more advanced leader through the ``technology gap`` and ``technology spillovers``. In our survey, we will assume, apriori, that most developed country is Slovenia, followed by Croatia, Serbia, and the Republic of Srpska.

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