scholarly journals TECHNICAL EFFICIENCY OF FDI FIRMS IN THE VIETNAMESE MANUFACTURING SECTOR

2016 ◽  
Author(s):  
Vu Hoang Duong
Keyword(s):  
Technical Efficiency ◽  
Manufacturing Sector

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.

scholarly journals Technical Efficiency of the Malaysian Wooden Furniture Industry: A Stochastic Frontier Production Approach

2010 ◽  
Vol 3 (3) ◽  
pp. 10 ◽  
Author(s):  
Alias Radam ◽  
Mohd Rusli Yacob ◽  
Huda Farhana Mohd Muslim
Keyword(s):  
Technical Efficiency ◽  
Manufacturing Sector ◽  
Stochastic Frontier ◽  
Production Model ◽  
Furniture Industry ◽  
Conventional View ◽  
Maximal Output ◽  
Wood Furniture ◽  
Wooden Furniture ◽  
Medium Firms

Wood furniture industry is an important component in our manufacturing sector for it significantly contributes to the industrialization of Malaysia’s economy. Evaluating wood furniture industry’s level of efficiency is important to assist and provide a relative direction to small and medium firms on their business. The objective of this research is to examine the efficiency of wooden furniture industry by determining the technical efficiency using stochastic frontier production model. Results show that firm output is 54 per cent less than the maximal output which can be achieved from the existing inputs. The technical inefficiency on individual firm varies from 1.63 to 94.69 per cent and so does the potential to increase firm output from the existing inputs. This evidence suggests that many firms still operate below the efficiency level, confirming the conventional view that labor-intensive firms are most likely inefficient.

scholarly journals Technical Efficiency and Technical Change in Canadian Manufacturing Industries

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Samuel Gamtessa
Keyword(s):  
Technical Efficiency ◽  
Technical Change ◽  
Fixed Effects ◽  
Manufacturing Sector ◽  
Stochastic Frontier ◽  
Manufacturing Industries ◽  
Omitted Variables ◽  
Dynamic Panel ◽  
Data Set ◽  
Canadian Manufacturing

This study applies the “true fixed effects” panel stochastic frontier methodology to the Canadian KLEMS data set to estimate technical change and technical efficiency in the Canadian manufacturing sector. To account for the endogeneity of capital inputs as well as the possible problems related to omitted variables, a two-stage residual inclusion method is pursued. The first stage is estimated using the dynamic panel GMM method. The results show that Canadian manufacturing industries experienced significant declines in technical efficiencies during the last ten years. This suggests that the observed slowdown in TFP growth during the recent past is partly due to declining technical efficiency.

scholarly journals Distinction between Informal and Unorganized Sector: A Study of Total Factor Productivity Growth for Manufacturing Sector in India

2011 ◽  
Vol 3 (5) ◽  
pp. 296-310
Author(s):  
Indrajit Bairagya
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Informal Sector ◽  
Productivity Growth ◽  
Manufacturing Sector ◽  
Total Factor Productivity Growth ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Unorganized Sector

Since its very onset, the concept and definition of the informal sector has been a subject of debate both at the national and international levels. Existing literature uses the terms ‘informal sector’ and ‘unorganized sector’ interchangeably. However, in India, the characteristics of enterprises in the informal and non-informal unorganized manufacturing sectors are different and, thus, it is not justifiable to consider the informal and unorganized sector interchangeably for the manufacturing sector. Thus, the objective of this paper is to test the hypothesis on whether or not the total factor productivity growth (TFPG) of the informal manufacturing sector is different from the non-informal unorganized manufacturing sector. TFPG is decomposed into technical efficiency change and technological change. Later, technical efficiency change is further decomposed by pure efficiency change and scale efficiency change. Results show that the average TFPG of the non-informal sector is higher than the informal sector. The informal sector heavily concentrates in own account small enterprises, whereas the non-informal unorganized sector concentrates only in directory manufacturing enterprises (DME). Due to large in size, DME avails the advantages of economies of scale, which, in turn, helps the units for more growth in terms of total factor productivity growth. The main reason for productivity decrease of the enterprises, besides technology regress and the lack of adequate investments, is the limitation of activities and scale along with the optimal allocation of resources. This study provides a basis on how policies can be designed for enhancing the total factor productivity growth of the informal sector.

Productivity Growth and Efficiency Differences in Indian Manufacturing Sector: An Inter-State Analysis

2020 ◽  
pp. 43-50
Keyword(s):  
Technical Efficiency ◽  
Productivity Growth ◽  
Manufacturing Sector ◽  
Value Added ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Indian States ◽  
Entire Study ◽  
Indian Manufacturing Sector ◽  
Inter State

ABSTRACT The present study endeavours to analyze the productivity growth and technical efficiency of Indian manufacturing sector both at aggregate and disaggregate inter-state level by taking into account the entire study period of 35 years from 1980-81 to 2014-15 and three distinct sub-periods viz., (i) Pre-reforms period (1980-81 to 1990-91: Period-I) ii) Post-reforms period Phase-I (1991-92 to 2000- 2001: Period-II) and iii) Post- reforms period Phase-II (2001-02 to 2014-15: Period-III).The study utilizes the single output (gross value added) and two inputs (gross fixed capital stock and total employees) framework and employed Data Envelopment Analysis (DEA) approach to compute the total factor productivity growth and technical efficiency scores of sixteen major Indian states. The comparative analysis of pre-reforms and post-reforms period depicted a slower TFP growth in the post-reforms era as compared to the pre-reforms period. Further, a non-parametric decomposition of the Malmquist Productivity Index (MPI) into its two components revealed that both before and after reforms, technological progress rather than technical efficiency change contributed more towards the productivity growth of manufacturing sector of these Indian states.

Stochastic Frontier Analysis and Measurement of Productivity and Technical Efficiency of Indian Manufacturing Sector

2017 ◽  
Vol 5 (1) ◽  
pp. 52-69
Author(s):  
Manoj Kumar
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Manufacturing Sector ◽  
Stochastic Frontier ◽  
Value Added ◽  
Frontier Analysis ◽  
Use Of Resources ◽  
Plant Level ◽  
Indian Manufacturing Sector ◽  
Factor Inputs

It is generally believed the structural reforms that usher in competition and force companies to become more efficient were introduced later in India following the macroeconomic crisis in 1991. However, whether or not the post-1991 growth is an outcome of more efficient use of resources or greater use of factor inputs, especially capital, remains an open empirical question. In this article the author uses plant-level data from 1990 and 2015 to address this question. The results indicate that while there was an increase in the productivity of factor inputs during the 1990s, most of the growth in value added is explained by growth in the use of factor inputs. The author also finds that median technical efficiency declined in all but one of the industries between the two years, and change in technical efficiency explains a very small proportion in the change in gross value added.

Technical efficiency and its determinants in the Indonesian micro and small enterprises

2019 ◽  
Vol 46 (6) ◽  
pp. 1157-1173
Author(s):  
Maman Setiawan ◽  
Nury Effendi ◽  
Ratni Heliati ◽  
Alfi Syahrin Ario Waskito
Keyword(s):  
Technical Efficiency ◽  
Manufacturing Sector ◽  
Standard Industrial Classification ◽  
Small Enterprises ◽  
Truncated Regression ◽  
Firm Level ◽  
Content Type ◽  
Small Industry ◽  
Micro And Small Enterprises ◽  
Using Data

Purpose The purpose of this paper is to investigate the technical efficiency (TE) of micro and small enterprises (MSEs) and its determinants in the Indonesian manufacturing sector covering comprehensive subsectors. Design/methodology/approach This research uses the data from the micro and small industry survey sourced from the Indonesian Bureau of Central Statistics for the period 2010–2015. The TE is estimated using data envelopment analysis (DEA) with bootstrapping approach. The TE is also estimated at the firm-level survey data, classified at the five-digit level of the International Standard Industrial Classification system. In addition, a truncated regression model is applied to estimate the effects of the determinants on the TE. Findings This research finds that there is a low average TE of the MSEs for the subsectors investigated. It is also found that the TE is associated with firm size, location, export orientations on domestic and world markets, firm age, level of technology, and owner education. Originality/value The literature investigating the TE of the MSEs and its determinants is still rare in Indonesia. Most of the previous research limited the studies for specific subsectors and/or specific small regions. Therefore, this research has a contribution in measuring the TE of the MSEs for comprehensive subsectors as well as its relation with the determinants in the Indonesian manufacturing sector. Also, the DEA with bootstrapping approach is applied to estimate the TE of the firms based on each relevant subsector, which is rare in the previous research of the Indonesian MSEs.

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