scholarly journals Human Capital Spillovers, Productivity and Growth in the Manufacturing Sector of Pakistan

2009 ◽  
Vol 48 (2) ◽  
pp. 125-140
Author(s):  
Abdul Hamid ◽  
J. Hanns Pichler
Keyword(s):  
Developing Countries ◽  
Human Capital ◽  
Total Factor Productivity ◽  
Production Technology ◽  
Manufacturing Sector ◽  
Value Added ◽  
Jel Classification ◽  
Factor Productivity ◽  
Major Factors

Manufacturing is an important sector of Pakistan’s economy. The main focus of this paper is to analyse the major factors of value-added growth and productivity in the manufacturing sector by using Translog Production Technology over the period 1971-72 to 2004-05. The empirical findings show that the contribution of productivity and human capital is around one- third of the total value-added growth in manufacturing sector which is less than the contribution attributed to these factors in developed and many other developing countries. Conventional factors like capital and labour are still the mainstay in the value-added growth of Pakistan’s manufacturing sector. JEL classification: O1, O3, O4, O14, O15, O31 Keywords: Human Capital Spillovers, Total Factor Productivity, Absolute and Relative Shares

Resource misallocation of SMEs in Vietnamese manufacturing sector

2019 ◽  
Vol 26 (3) ◽  
pp. 290-303
Author(s):  
Phuong Thi Nguyen ◽  
Minh Khac Nguyen
Keyword(s):  
Developing Countries ◽  
Total Factor Productivity ◽  
Design Methodology ◽  
Large Scale ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Content Type ◽  
Resource Misallocation ◽  
Productivity Decomposition ◽  
Enterprise Survey

Purpose The purpose of this paper is to examine resource misallocation among Vietnam’s small- and medium-sized enterprises (SMEs) in the manufacturing sector. The paper also aims to consider selective factors on reducing the level of resource misallocation in SMEs. Design/methodology/approach Resource misallocation and efficiency gains in total factor productivity (TFP) are assessed using Vietnam’s annual enterprise survey data for the period 2000–2015 and an appropriate productivity decomposition framework. Findings Resource misallocation is found to be higher among SMEs than large scale enterprises. TFP is found to 116.3 per cent greater if there is no resource misallocation among SMEs. Smaller scale, lower market concentration, trade liberalisation and corruption control are found to be associated with lower level of resource misallocation in SMEs. Research limitations/implications The major limitation of this study is that it has only decomposed misallocation of resources arising from output and capital distortions and that it focusses on selective factors contribution to reducing misallocation level in SMEs. Originality/value Resource misallocation is attracting attention in both developed and developing countries. However, knowledge about resource misallocation among SMEs is limited, particularly in the context of developing countries. This paper assesses the level of resource misallocation among SMEs in Vietnamese manufacturing sector.

scholarly journals DINAMIKA TOTAL FACTOR PRODUCTIVITY INDUSTRI BESAR DAN SEDANG INDONESIA

2014 ◽  
Vol 16 (3) ◽  
pp. 277-308
Author(s):  
Ndari Surjaningsih ◽  
Bayu Panji Permono
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Manufacturing Sector ◽  
Jel Classification ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Catching Up ◽  
Using Data

This paper calculates and decomposes the Total Factor Productivity (TFP) for large and medium scale industry in Indonesia covering the period of 2000-2009. By using Data Envelopment Analysis (DEA)  method, the result shows there is a shift of the supporting factors on the growth of TFP on manufacturing sector within the 2 (two) sample period. In the period of 2000-2004, efficiency change becomes the main contributor on the growth of TFP. Whereas in the period of 2005-2009, technical change becomes the main supporting factor of TFP,however it goes along with the growth of negative efficiency change or the decline of the company’s catching-up effect ability to adapt with the more advance technology. The grouping of the sample across subsectors, technical change and also efficiency change shows the declining amount of manufacture industry with superior productivity. Furthermore, the number of low and weakening catching-up industry is increasing.  Keywords: Indonesian manufacturing, total factor productivity, technical change, efficiency change, economic scale change, Data Envelopment Analysis JEL Classification: L6, M11

Is Liberalisation Associated with Higher Productivity? A Case Study of Punjab Manufacturing

2007 ◽  
Vol 11 (4) ◽  
pp. 53-65
Author(s):  
Ravi Kiran ◽  
Manpreet Kaur
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Manufacturing Sector ◽  
Research Work ◽  
Value Added ◽  
Business Environment ◽  
Empirical Literature ◽  
Factor Productivity ◽  
Policy Regime ◽  
Indian Economy

Productivity is an important concept in the context of the economic growth of a nation. The rate of productivity in accelerating the pace of economic growth is well recognised in both the theoretical as well as empirical literature on growth. The significance of productivity for economic growth was highlighted by Kuznets (1966) when he showed that rapid gain in industrial productivity was the crucial underpinning of Western Industrialization. The Indian Economy was thrust into throes of rapid change in the nineties when the then government of India adopted the New Economic Policy. Liberalization, Privatization and Globalization — became the three planks by which the Indian Economy was propelled into the fusion. This process has had maximum impact on the manufacturing sector, as it has radically changed its business environment and future growth dynamics. All the states of Indian union have been affected differently due to the structural changes. In response to changed policy regime different sub sectors of industry of Punjab have responded differently to adjust optimally. The present research work focuses on studying the response of manufacturing industries in Punjab to the changed policy regime after the advent of liberalisation and privatisation process in India. The present study analyses the trends in value added, labour, capital as well as trends in labour, capital and total factor productivity for sixteen industrial groups on the organised manufacturing sector for the period 1980 — 81 to 2002 — 03 and also for two sub periods, period I, 1980 — 81 to 1990 — 91 and period II, 1991 — 92 to 2002 — 03. The present study tries to examine the trends in partial productivities as well as total factor productivity in the two sub periods to see whether there has been an improvement in productivity in the post 1991 period, the period associated with liberalisation and globalisation. The study tries to analyse the industries which have been showing better performance in terms of partial and total factor productivity and also study the trends of the industries which have not performed well in the period of analysis.

scholarly journals Impact of Human Capital and Innovation towards Total Factor Productivity (TFP): A Case of Manufacturing Sector in Palm Oil Industry in Malaysia

2021 ◽  
Vol 12 (1) ◽  
pp. 73-73
Author(s):  
Noorasiah Sulaiman ◽  
Naiimah Mohd Sofia ◽  
Mohd Fahmy- Abdullah ◽  
Suliadi Sufahani Firdaus
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Palm Oil ◽  
Manufacturing Sector ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Skilled Workers ◽  
Total Employment ◽  
Agriculture Sector ◽  
Capital Productivity

Malaysian oil palm sector has contributed to the growth of gross domestic product (KDNK) by 37.9%, of manpower by a total of 40%, and of the total employment of agriculture sector by 22.1 million people in 2018 (DOSM, 2019). Furthermore, the exports performance shows that the palm oil production has increased from 180 thousand tons metric in 1965 to 27.86 million tons metric in 2019 (MPOB, 2019). The major importers of Malaysian palm oil include India, China, Pakistan, and the Netherlands. In 2016, India was the biggest importer (19.9 %), followed by China (10.1 %), Pakistan (6.4%) and Netherlands (5.5%). In addition to that, many oils are categorized according to the sources of oil and fat saturation which is produced globally (OWA, 2016). Palm oil register percent high by 28.0% compared with the oil other like oil bean soy (24.0 %), oil rapeseed (13.0 %) and spring sun (7.0 %), even more than the oils and fats from sources animals that only 25.0% only (OA, 2016). Although palm oil- based industries in Malaysia depend on inputs, especially human capital and technology to determine the overall performance and productivity, the sector is yet to use technology that depends on low-skilled workers. Thus, to improve the industries, the study was conducted to analyze the effects of the workers skills and technology on the total factor productivity (TFP). Keywords: Human Capital, Productivity, Palm Oil, Data Envelopment Analysis, Panel Data

scholarly journals The Effects Of Human Capital On Malaysias Maunfacturing Productivity Growth

2006 ◽  
Vol 5 (4) ◽  
Author(s):  
Elsadig Musa Ahmed
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Growth Rates ◽  
Manufacturing Sector ◽  
Annual Growth ◽  
Factor Productivity ◽  
Cost Component ◽  
Tfp Growth ◽  
Labour Input

The objective of this paper is to examine the effects of human capital on the productivity growth in Malaysias manufacturing sector. To achieve this, labour input was subdivided into skilled semi-skilled and unskilled. The study found that materials account for the largest cost component in the sector although shortages of skilled labour constitute a serious constraint on capital utilisation. In addition, the contribution of total factor productivity (TFP) growth of the sector was generally found to be very low particularly during the second sub-period of 1987-2001. The improvement and slowdown of TFP contribution to manufacturing sector in terms of average annual growth rates were dependent on the inputs used in production, believed to be of low quality and insufficient.

Impact of Determinants of Industrial Development on Employment and Wages in Indian Manufacturing

2020 ◽  
pp. 18-30
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Firm Level ◽  
Employment Level ◽  
The Impact ◽  
Level Performance

ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

Firm Characteristics and Total Factor Productivity: Evidence from Indian Manufacturing Firms

2017 ◽  
Vol 11 (1) ◽  
pp. 77-98 ◽  
Author(s):  
Lopamudra D. Satpathy ◽  
Bani Chatterjee ◽  
Jitendra Mahakud
Keyword(s):  
Total Factor Productivity ◽  
Ordinary Least Squares ◽  
Jel Classification ◽  
Raw Material ◽  
Firm Characteristics ◽  
Manufacturing Companies ◽  
Factor Productivity ◽  
Size Of Firms ◽  
Specific Factors

Measurement of the productivity of firms is an important research issue in productivity literature. Over the years, various methods have been developed to measure firm productivity across the globe. But there is no unanimity on the use of methods, and research on the identification of factors which determine productivity has been neglected. In view of these gaps, this study aims to measure total factor productivity (TFP) and tries to identify firm-specific factors which determine productivity of Indian manufacturing companies. The study is based on data of 616 firms from 1998–99 to 2012–13. To measure TFP, the Levinsohn–Petrin (L-P) method has been employed, and the fully modified ordinary least squares (FMOLS) method has been used to identify factors that affect TFP. The results reveal that embodied and disembodied technology plays a crucial role in the determination of productivity overall in manufacturing and other sub-industries. Similarly, the size of firms and intensity of raw material imports are also important for the determination of productivity across the sub-industries. JEL Classification: C14, C33, D24, L60

Determinants of Total Factor Productivity in Mexico, Indonesia, Nigeria, and Turkey (1980–2014)

2018 ◽  
Vol 4 (2) ◽  
pp. 192-217 ◽  
Author(s):  
Phillip Akanni Olomola ◽  
Tolulope Temilola Osinubi
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Negative Relationship ◽  
Annual Data ◽  
Factor Productivity ◽  
Distributed Lag ◽  
Long Run ◽  
The World ◽  
Government Stability ◽  
Short Run

This study analyzed the macroeconomic and institutional determinants of total factor productivity (TFP) in the MINT (Mexico, Indonesia, Nigeria, and Turkey) countries during the period 1980–2014. Annual data covering the period between 1980 and 2014 were used. Data on real gross domestic product (real GDP), labor force, gross fixed capital formation, foreign direct investment (FDI), human capital, and inflation were sourced from the World Development Indicators published by the World Bank. Also, data on corruption, government stability, and law and order were obtained from the database of International Country Risk Guide. Panel autoregressive distributed lag (PARDL) regression technique was used to estimate the model. Results showed that TFP growth rate declined on average by 1.4 per cent and 1.8 per cent in Mexico and Turkey, respectively, while Indonesia and Nigeria did not experience productivity growth on the average. Results also showed that in the long run, human capital and government stability had positive and significant effects on TFP, while FDI and corruption had negative but significant effects on TFP. In the short run, there existed a significant negative relationship between TFP and inflation. However, the effects of human capital and corruption on TFP were positive and significant. The study concluded that human capital and corruption were key drivers of TFP in the MINT countries both in the long run and short run.

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