Technical Efficiency Analysis of China’s Agricultural Industry: A Stochastic Frontier Model with Panel Data

2017 ◽  
pp. 454-463 ◽  
Author(s):  
Ji Ma ◽  
Jianxu Liu ◽  
Songsak Sriboonchitta
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Stochastic Frontier ◽  
Efficiency Analysis ◽  
Stochastic Frontier Model ◽  
Agricultural Industry

scholarly journals Estimation of technical efficiency of black cumin (Nigella sativa L.) farming in northwest Ethiopia: a stochastic frontier approach

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Abebe Birara Dessie ◽  
Tadie Mirie Abate ◽  
Betelhem Tsedalu Adane ◽  
Tiru Tesfa ◽  
Shegaw Getu
Keyword(s):  
Technical Efficiency ◽  
Nigella Sativa ◽  
Stochastic Frontier ◽  
Market Price ◽  
Northwest Ethiopia ◽  
Flowering Plant ◽  
Yield Potential ◽  
Stochastic Frontier Model ◽  
Black Cumin ◽  
The Mean

Abstract Ethiopia is one of the east African countries which produce and exports various spices to other countries. Black cumin (Nigella sativa L.) is an important stiff annual flowering plant which mainly grows by producers for its seeds. An increasing demand of black cumin seed and oil in local, national and international market for medicinal, consumption and commercial purpose makes the best alternative crop for small holder farmers in Ethiopia. In spite of its importance, not much has been done to improve its production and productivity in Ethiopia. Therefore, this research was designed to examining efficiency variations and factors influencing technical inefficiency levels of producers on black cumin production in northwest Ethiopia. Primary data were collected using a semi-structured questionnaire administered on 188 black cumin producers selected using systematic random sampling technique. Moreover, various data analysis methods such as descriptive statistics and stochastic frontier model were used for analyzing the data. The empirical result obtained by applying maximum likelihood estimate of stochastic frontier model revealed that seed (p < 0.01) labor (p < 0.05), chemical (p < 0.01) and land (p < 0.05) were significant input variables in determining black cumin production. The mean technical efficiency level of black cumin producer was generally low, about 53.1%. The mean value of actual yield, potential yield and yield gap was 3.131, 5.832 and 2.701 quintals, respectively. Moreover, the result of stochastic frontier model together with the inefficiency parameters revealed that market price of black cumin (p < 0.01) and access of extension service (p < 0.1) were significant variables and positively influenced the efficiency levels of black cumin producers. Whereas age of producers (p < 0.05) and distance to farm plot (p < 0.01) negatively influenced the technical efficiency levels of black cumin producers. Therefore, the study recommends that adoption of latest agricultural technologies; development of institutions, agricultural extension services and infrastructure are advisable to improve the efficiency and commercial value of black cumin production.

Technical efficiency and its determinants in the Indian textile garments industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdulla ◽  
Shiv Kumar
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Textile Industry ◽  
Small And Medium Enterprises ◽  
Stochastic Frontier ◽  
Efficiency Score ◽  
Value Chains ◽  
Small Scale ◽  
Content Type ◽  
Medium Enterprises

Purpose This paper aims to examine technical efficiency and its determinants in Indian textile garments industry in post-agreement on textiles and clothing regime and evaluate the technical efficiency among micro, small and medium enterprises (MSMEs) firms. Design/methodology/approach This study uses unbalanced panel data for the period 2005–2010 to 2015–2016. The stochastic frontier function is used to estimate technical efficiency and its determinants. Findings The results show that the overall ecosystem of textile garments’ value chains could be improved to enhance the technical efficiency thereof. The result also reveals that small-scale firms have the highest technical efficiency scores, and medium-scale firms have the least technical efficiency score among all the categories of MSMEs. Research limitations/implications The textile garments industry needs to define its innovation strategies, as these strategies lead to different results that can be achieved only through the management of resources dedicated to the generation and implementation of innovations. Practical implications This study has shown that to offset India’s cost disadvantage in the international markets, there is a need to develop an ecosystem of textile manufacturing and value chains, eliminate the inverted duty structure (where inputs are taxed at a higher rate than the final product) and switch over from shuttle looms toward shuttle-less looms. This would unleash the potential of textile and garments industry and make it globally competitive and technically efficient. Further, there will be an alignment with the ease of doing business with an appropriate mix of policy, technology, institution, infrastructure, information and services. Originality/value Using frontier production function takes stochastic context into account for the dynamic character of technical efficiency and its components. Most of the past studies have assessed technical efficiency at the aggregate level using three-digit National Industrial Classification (NIC) or four-digit NIC code. An analysis at higher levels of aggregation masks the variation in technical efficiency. This study used five-digit NIC data to measure the firm-specific technical efficiency of the textile industry. According to the authors’ knowledge, this study is the first of its kind in the Indian textile industry using stochastic frontier approach and panel data. Further, it also looks at the contribution of different determinants in technical efficiency to the firms.

Stochastic Frontier Model Approach of Technical Efficiency for Paddy Farming in Odisha

2020 ◽  
pp. 1135-1140
Author(s):  
Priyabrata Bhoi ◽  
Deepak Kumar Swain ◽  
Subhadra Mishra ◽  
Debahuti Mishra ◽  
Gour Hari Santra ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier ◽  
Stochastic Frontier Model ◽  
Model Approach

scholarly journals Labour efficiency in construction industry in Europe based on frontier methods: data envelopment analysis and stochastic frontier analysis

2017 ◽  
Vol 23 (6) ◽  
pp. 787-795 ◽  
Author(s):  
Joanicjusz NAZARKO ◽  
Ewa CHODAKOWSKA
Keyword(s):  
Data Envelopment Analysis ◽  
Construction Industry ◽  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Efficiency Analysis ◽  
European Countries ◽  
Personnel Cost ◽  
Data Envelopment ◽  
Frontier Analysis

The primary problems pertaining to productivity or – more precisely – efficiency are: how to define it and how to measure it. This article studies technical efficiency in Stochastic Frontier Analysis (SFA) – the input-oriented frontier model – in the construction industry and compares it with Data Envelopment Analysis (DEA) results. The models ex­plored in this paper were constructed on the basis of two outputs and personnel cost as an input. The research sample consisted of European countries. The aim was to determine whether there are substantial differences in estimation of ef­ficiency derived from those two alternative frontier approaches. The comparison of results according to the models may translate into higher reliability of the undertaken labour efficiency analysis in construction and its conclusions. Although the results are not characterized by high compatibility, the conducted analysis indicated the most attractive countries taking into account labour cost to profit and turnover ratios of enterprises. One of the determinants which should not be ignored when analysing the labour efficiency is the level of development of a country; however, it is not the sole factor affecting the efficiency of the sector.

scholarly journals Determinants and Differences of Grain Production Efficiency Between Main and Non-Main Producing Area in China

2019 ◽  
Vol 11 (19) ◽  
pp. 5225
Author(s):  
Furong Chen ◽  
Yifu Zhao
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Production Function ◽  
Production Efficiency ◽  
Stochastic Frontier ◽  
Grain Production ◽  
Marginal Productivity ◽  
Rural Labor ◽  
Stochastic Frontier Production Function ◽  
Frontier Production Function

This paper investigated the determinants, especially labor transformation, and differences of technical efficiency between main and non-main grain-producing area in China based on a panel data from 30 provinces in the period of 2001–2017. Stochastic frontier production function was used to estimate the level of technical efficiency and the marginal productivity of different inputs. The estimated results showed that land is the most important factor to improve China’s grain output, followed by fertilizers, labor, and machinery inputs. There was a significant 4.6 percent gap of production efficiency between main and non-main producing provinces. Influence of rural labor transformation was confirmed to be positive to improve technical efficiency.

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