Output Growth, Total Factor Productivity, and Technical Efficiency in Nepalese Manufacturing Industries

2006 ◽  
Vol 29 (2) ◽  
Author(s):  
Udaya Raj Regmi
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Output Growth ◽  
Manufacturing Industries ◽  
Factor Productivity

Decomposition of Output and Productivity Growth in the Organised Manufacturing Industries in India: An Inter-State Analysis

2018 ◽  
Vol 66 (1-2) ◽  
pp. 25-41
Author(s):  
Prasanta Kumar Roy
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Manufacturing Sector ◽  
Stochastic Frontier ◽  
Output Growth ◽  
Manufacturing Industries ◽  
Growth Effect ◽  
Major Contributor ◽  
Factor Productivity ◽  
Reform Period

This article examines and applies the theoretical foundation of the decomposition of output and total factor productivity growth (TFPG) of the aggregate manufacturing industries in 15 major industrialised states in India as well as in all-India during the period from 1981–1982 to 2010–2011, during the entire period, during the pre-reform period (1981–1982 to 1990–1991) and post-reform period (1991–1992 to 2010–2011), and also during two different decades of the post-reform period, that is, during 1991–1992 to 2000–2001 and 2001–2002 to 2010–2011. Output growth is decomposed into input growth effect and TFPG where the three attributes of TFPG are adjusted scale effect, technological progress (TP) and technical efficiency change. A stochastic frontier model with a translog production function is used to estimate the growth attributes of output and total factor productivity (TFP). The empirical results show that input growth is the major contributor to output growth, whereas TP is found to be the major contributor to TFPG and the decline in TFPG of the organised manufacturing sector in India and in its major industrialised states during the post-reform period is mainly due to the decline in TP of the same during that period. JEL Codes: C23, D24, L6, O47

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 Pakistan’s Productivity Performance and TFP Trends, 1980–2015: Cause for Real Concern

2016 ◽  
Vol 21 (Special Edition) ◽  
pp. 33-63 ◽  
Author(s):  
Rashid Amjad ◽  
Namra Awais
Keyword(s):  
Economic Growth ◽  
East Asia ◽  
Total Factor Productivity ◽  
Labor Productivity ◽  
Productivity Growth ◽  
Output Growth ◽  
Factor Productivity ◽  
Sustained Growth ◽  
Growth Prospects ◽  
High Output

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.

scholarly journals A Study on the Efficiency of Tourism Poverty Alleviation in Ethnic Regions Based on the Staged DEA Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Jianchun Yang ◽  
Ying Wu ◽  
Jialian Wang ◽  
Chengcheng Wan ◽  
Qian Wu
Keyword(s):  
Ethnic Minority ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Poverty Alleviation ◽  
Malmquist Index ◽  
Great Difficulty ◽  
Local Economy ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Two Stages

Poverty alleviation through tourism is an important way for China to achieve targeted poverty alleviation and win the battle of poverty alleviation. As a region with deep poverty and great difficulty in poverty alleviation, whether tourism development has injected key impetus into ethnic minority areas needs to be tested by both qualitative analysis and quantitative measurement. This paper takes eight ethnic provinces (regions) in China as an example to conduct an empirical study. Based on the Data Envelopment Analysis (DEA)-BCC model and Malmquist index, it evaluates the tourism investment and tourism poverty alleviation efficiency of the ethnic regions in the two stages of tourism poverty alleviation, and analyzes them by classification. The results of the study show: (1) The pure technical efficiency in the first stage is relatively high, but the total factor productivity of each region is declining; (2) The pure technical efficiency in the second stage is also relatively high, but the scale efficiency is low, and the change rate of total factor productivity of the provinces in China has increased significantly; (3) The “double high” type includes Guangxi, Inner Mongolia, and Guizhou, and the “double low” type includes Qinghai, Yunnan, Tibet, Xinjiang, and Ningxia. The results of the study generally show that tourism poverty alleviation has brought about the improvement of the living standards of residents and the development of local economy, but the efficiency of tourism poverty alleviation needs to be improved. On this basis, the article puts forward corresponding improvement measures, in order to further help the ethnic minority areas get rid of poverty in a comprehensive way by promoting the efficient and sustainable development of tourism.

scholarly journals Agricultural basic industry subjects productivity development examination in the region Trnava (SR) by adopting the Malmquist indexes

2010 ◽  
Vol 56 (No. 3) ◽  
pp. 108-115
Author(s):  
P. Bielik ◽  
D. Hupková ◽  
M. Vadovič ◽  
V. Benda
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Future Trend ◽  
Factor Productivity ◽  
Technological Changes ◽  
Efficiency Change ◽  
Basic Industry ◽  
Factors Influencing ◽  
Two Factors ◽  
Malmquist Indexes

Analysis of the productivity and efficiency development could be used to asses the trend and factors influencing this process. The main goal of this paper is estimation of the Total Factor Productivity (TFP) development of agricultural farms in the Trnava region in the period 2002–2006. Results of this analysis could be used to detect the trend in the TFP development. The results of the analysis confirmed there is no evident trend in the average TFP indicators. This could be explained by the variation of technical efficiency change and technological changes during this period. These two factors represent the components of the TFP indicator. According to the present development of the TFP indicator, it is not possible to unambiguously forecast the future trend.

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