Productivity and efficiency of labour intensive manufacturing industries in India

2016 ◽  
Vol 15 (2) ◽  
pp. 130-152
Author(s):  
Purna Chandra Parida ◽  
Kailash Chandra Pradhan
Keyword(s):  
Design Methodology ◽  
Manufacturing Industries ◽  
Stochastic Production Frontier ◽  
Production Frontier ◽  
Content Type ◽  
Annual Survey ◽  
Labour Intensity ◽  
Central Statistical ◽  
Stochastic Production ◽  
Rate Of Decline

Purpose This paper aims to make an attempt to identify labour intensity of organized manufacturing industries in India using the Annual Survey of Industry (ASI) data at three-digit level. It estimates total factor productivity growth (TFPG) and technical efficiency for both labour intensive and all manufacturing industries during the pre- and post-reforms periods. Design/methodology/approach The study uses three approaches to estimate TFPG. They are growth accounting (GA) (non-parametric), production function with correction for endogeneity – Levinsohn-Petrin (LP) (semi-parametric) and stochastic production frontier (SPF) analysis (parametric). The study uses ASI data published by Central Statistical Organization, Government of India for the period 1980-1981 to 2007-2008 for the analysis. Findings The study finds that the rate of decline of the labour intensity is more pronounced in the case of labour-intensive industries than all the manufacturing industries. The results of GA method suggest that the TFPG of labour-intensive industries has declined continuously from the pre-reforms period to the post-reforms period. Similarly, LP method indicates a continuous decline in TFPG of labour-intensive manufacturing industries during the post-reforms period. Interestingly, the results of SPF method also corroborate the findings of earlier two methods at the aggregate level but vary at a certain degree at the disaggregated level. Originality/value This paper is useful in the context of India considering the importance given to labour-intensive industries by the present government in terms of reviving the sector and improving the productivity and output.

Deregulation, technical efficiency and production risk in rice farming: evidence from Zhejiang Province, China

2020 ◽  
Vol 12 (4) ◽  
pp. 605-622
Author(s):  
Juanli Wang ◽  
Xiaoli Etienne ◽  
Yongxi Ma
Keyword(s):  
Technical Efficiency ◽  
Performance Metrics ◽  
Production Performance ◽  
Land Market ◽  
Stochastic Production Frontier ◽  
Production Frontier ◽  
Technical Inefficiency ◽  
Production Risk ◽  
Content Type ◽  
Stochastic Production

PurposeThe purpose of this paper is to evaluate the technical efficiency and production risk in China's rice production and examine the effect of factor market reform on these two agricultural performance metrics.Design/methodology/approachUsing an unbalanced farm-level panel data with 2,193 observations on 329 rice farms from 2004 to 2016, the authors estimate a translog stochastic production frontier model that accounts for both technical inefficiency and production risk. A one-step procedure through the maximum likelihood method that combines the stochastic production frontier, technical inefficiency and production risk functions is used to circumvent the bias problem often found in the conventional two-step model.FindingsEstimation results show that both land and labor market reforms significantly improved the level of technical efficiency over the years, although the effect of land market deregulation is of a much higher magnitude compared to the latter. The land market reform, however, has also increased the risk of production. The authors further find that a higher proportion of hired labor in total labor cost helps lower production risk, while also acting to decrease technical efficiency. Additionally, agricultural subsidies not only increased the output variability but also lowered technical efficiencyOriginality/valueFirst, the authors evaluate the effect of market deregulation on technical efficiency and production risk under a stochastic frontier framework that simultaneously accounts for both production performance metrics, which is important from a statistical point of view. Further, the authors exploit both cross-sectional and time-series variations in a panel setting to more accurately estimate the technical inefficiency scores and production risk for individual farmers, and investigate how the exogenous land and labor market reforms influence these two production performance measures in China's rice farming. This is the first study in the literature to analyze these questions under a panel framework.

A generalized stochastic production frontier analysis of technical efficiency of rice farming

2016 ◽  
Vol 9 (2) ◽  
pp. 114-128 ◽  
Author(s):  
Aditi Bhattacharyya ◽  
Raju Mandal
Keyword(s):  
Technical Efficiency ◽  
Rice Production ◽  
Farm Households ◽  
Rice Farming ◽  
Stochastic Production Frontier ◽  
Production Frontier ◽  
Technical Inefficiency ◽  
Content Type ◽  
Farm Level ◽  
Stochastic Production

Purpose This paper aims to analyze farm-level technical inefficiency of rice farming in Assam, India, using a multiple-output generalized stochastic frontier framework. Design/methodology/approach Primary data for this study were collected in 2009-2010 from 310 farm-households in four non-contiguous districts of Dhubri, Morigaon, Dibrugarh and Cachar that are located in different agro-climatic regions of Assam. Based on a Cobb–Douglas production function for multiple rice varieties, the paper simultaneously estimates the generalized stochastic production frontier and examines effects of exogenous factors on farm-level technical inefficiency. Findings Results of this study show that the average technical inefficiency of farms is 8.5 per cent in the sample. Further, inefficiency is lower in the frequently flood prone areas, and availability of government support helps reduce such inefficiency as well. However, technical efficiency is higher for the Muslim farm-households, and it decreases with greater land fragmentation. The study also finds that the use of primitive technology like bullock reduces technical efficiency of rice farming. Originality/value This paper is based on a novel data set that has specially been collected to examine productivity and efficiency of rice cultivation in the flood plains of Assam that has not been studied before. Further, to the best of the authors’ knowledge, this paper is the first one to model rice production as a multiple-output stochastic production frontier and analyze technical efficiency of rice production accordingly.

Does a Diversified Crop Portfolio Make Farmers More Efficient? A Stochastic Production Frontier Analysis of Farm-level Data from Assam, India

2021 ◽  
pp. 097300522199758
Author(s):  
Raju Mandal ◽  
Shrabanti Maity
Keyword(s):  
Positive Impact ◽  
Northeast India ◽  
Government Support ◽  
Stochastic Production Frontier ◽  
Production Frontier ◽  
Frontier Analysis ◽  
Farm Level ◽  
Agriculture Sector ◽  
Level Data ◽  
Stochastic Production

The agriculture sector in India is beset with twin limitations of shrinking cultivable area and absence of major technological breakthroughs in the recent past. In such a situation, a judicious management of the farm in the form of adjustment in a crop portfolio can be quite useful to maximise output and minimise wastage of resources. This article seeks to examine whether a diversified crop portfolio makes the farmers more efficient using farm-level survey data collected from geographically diverse areas of Assam, a state in northeast India. The results of a stochastic production frontier analysis show that adoption of a diversified crop portfolio across crops and seasons makes the farmers more efficient in cultivation by helping them reduce weather-induced damages to crops and reap better returns from farming. This efficiency-enhancing effect of crop diversification is found to be heterogeneous among the regions. However, too much diversification reduces the efficiency of farmers. The results have important implications for Assam where floods cause extensive damage to crops every year. Moreover, access to extension services and government support are found to make the farmers more efficient. On the other hand, fixed-rent form of tenancy reduces efficiency of the farmers while household size has a positive impact on the same.

scholarly journals The Economics and Productivity of Organic versus Conventional U.S. Dairy Farms

2021 ◽  
pp. 1-19
Author(s):  
Richard F. Nehring ◽  
Jeffrey Gillespie ◽  
Catherine Greene ◽  
Jonathan Law
Keyword(s):  
United States ◽  
Returns To Scale ◽  
Dairy Farms ◽  
Stochastic Production Frontier ◽  
Production Frontier ◽  
Return On Assets ◽  
Input Distance Function ◽  
Technological Adoption ◽  
Stochastic Production ◽  
Certified Organic

Abstract United States certified organic and conventional dairy farms are compared on the basis of economic, financial, and technological measures using dairy data from the 2016 USDA Agricultural Resource Management Survey. A stochastic production frontier model using an input distance function framework is estimated for U.S. dairy farms to examine technical efficiency and returns to scale (RTS) of farms of both systems and by multiple size categories. Financial and economic measures such as net return on assets and input costs, as well as technological adoption measures are compared by system and size. For both systems, size is the major determinant of competitiveness based on selected measures of productivity and RTS.

What does the new 2011-12 IIP series tell about the Indian manufacturing sector?

2018 ◽  
Vol 11 (2) ◽  
pp. 90-106
Author(s):  
Radhika Pandey ◽  
Amey Sapre ◽  
Pramod Sinha
Keyword(s):  
Design Methodology ◽  
Manufacturing Sector ◽  
High Growth ◽  
Industrial Output ◽  
Content Type ◽  
Annual Survey ◽  
Two Measures ◽  
Indian Manufacturing Sector ◽  
Practical Implications

Purpose This paper aims to discuss the changes in the new 2011-12 base year series of the Index of Industrial Production (IIP) to determine whether the new series has improved the understanding of the growth in the manufacturing sector. Design/methodology/approach This paper develops a simple framework to separately estimate the contribution of value- and volume-based commodities in the growth of the manufacturing index. The authors present a case study by analysing the growth performance of IIP drugs and pharmaceuticals sector by comparing it with real net sales of a common sample of firms in this segment. Findings The authors find that growth in value-based commodities contributes significantly in moving the index in either direction, and that high growth in value-based commodities coincides with periods of low inflation. On comparability, using real net sales as an alternate indicator of industrial output for the pharmaceuticals sector, the authors find that IIP and real net sales show contrasting trends, thereby raising issues of reliability. The authors also find that the IIP shows a disconnect with growth rates from Annual Survey of Industries for several industries. Practical implications The divergence between two measures of industrial activity raises crucial questions on the representativeness of the IIP. Originality/value The study builds a framework to separately estimate the contribution of value- and volume-based commodities in the growth of the manufacturing index.

Cultural traits influencing the adoption of new ways of workings

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amitesh Singh Parihar ◽  
Vinita Sinha
Keyword(s):  
Design Methodology ◽  
Driving Forces ◽  
Manufacturing Industries ◽  
Survey Questionnaire ◽  
Content Type ◽  
New Ways Of Working ◽  
One Step ◽  
Cultural Traits ◽  
The Individual ◽  
Practical Implications

Purpose The purpose of this paper is to identify the strengths and areas of improvement for taking organizations one step ahead in terms of adopting digitalization, analytics and governance. Also, the paper aims to identify the organizational cultural traits that influence the adoption of digitization and technology, analytics and governance. Design/methodology/approach A quantitative analysis of survey questionnaire collected from working professionals of various manufacturing industries to find out the driving traits and the restraining traits and to propose which is dominating. Sector: manufacturing, sample: working professionals across functions and sample size: 80–100 people. Findings This research suggests the cultural traits that influence the adoption of digitization and technology, analytics and governance in any organization. Practical implications As organizations explore new ways of working, their organizational culture and employee perspective would play an important role in prioritizing the interventions. This research aims to suggest a strategy to strengthen the driving forces and/or weaken the restraining forces. Originality/value There are various papers available on the individual topics but the uniqueness of this paper is that it represents all three factors in a single research and their influencers.

scholarly journals Influence of Big Data in managing cyber assets

2019 ◽  
Vol 9 (4) ◽  
pp. 503-514
Author(s):  
Amit Mitra ◽  
Kamran Munir
Keyword(s):  
Big Data ◽  
Asset Management ◽  
Design Methodology ◽  
Insurance Industry ◽  
Manufacturing Industries ◽  
Time Data ◽  
Content Type ◽  
Innovative Leadership ◽  
Data Flows ◽  
Desk Research

Purpose Today, Big Data plays an imperative role in the creation, maintenance and loss of cyber assets of organisations. Research in connection to Big Data and cyber asset management is embryonic. Using evidence, the purpose of this paper is to argue that asset management in the context of Big Data is punctuated by a variety of vulnerabilities that can only be estimated when characteristics of such assets like being intangible are adequately accounted for. Design/methodology/approach Evidence for the study has been drawn from interviews of leaders of digital transformation projects in three organisations that are within the insurance industry, natural gas and oil, and manufacturing industries. Findings By examining the extant literature, the authors traced the type of influence that Big Data has over asset management within organisations. In a context defined by variability and volume of data, it is unlikely that the authors will be going back to restricting data flows. The focus now for asset managing organisations would be to improve semantic processors to deal with the vast array of data in variable formats. Research limitations/implications Data used as evidence for the study are based on interviews, as well as desk research. The use of real-time data along with the use of quantitative analysis could lead to insights that have hitherto eluded the research community. Originality/value There is a serious dearth of the research in the context of innovative leadership in dealing with a threatened asset management space. Interpreting creative initiatives to deal with a variety of risks to data assets has clear value for a variety of audiences.

Sign in / Sign up

Export Citation Format

Share Document