A Stochastic Frontier Analysis of Exporting Small and Medium Sized Enterprises in India

2016 ◽  
Vol 7 (3) ◽  
pp. 1-23
Author(s):  
Manoj Kumar
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Returns To Scale ◽  
Key Factors ◽  
Technical Inefficiency ◽  
Frontier Analysis ◽  
Efficiency Performance ◽  
Size Firm ◽  
Almost All

This study employs a stochastic frontier analysis (SFA) and technical inefficiency effects model to predict the technical efficiency of 3,168 Indian manufacturing and exporting SMEs, analyze their returns to scale and key factors impacting on their technical efficiency. Indian manufacturing and exporting SMEs extensively rely on labor rather than capital to increase their output, including almost all exporting SME groups, except those exporting to North & South America. The production of Indian manufacturing SMEs exporting to Oceania, however, has increasing returns to scale (1.1965). The inefficiency effects model reveals that firm size, firm age, foreign ownership, location and government assistance are firm-specific factors that significantly affect the technical inefficiency of production. Finally, evidence-based policies are also provided to facilitate improvement in the technical efficiency performance of Indian manufacturing and exporting SMEs.

scholarly journals Stochastic Frontier Analysis on Technical Efficiency of Strawberry Farming in Purbalingga Regency Indonesia

2020 ◽  
Vol 9 (2) ◽  
pp. 105
Author(s):  
Irene Kartika Eka Wijayanti, ◽  
Jamhari Jamhari, ◽  
Dwidjono, Hadi Darwanto ◽  
Any Suryantini
Keyword(s):  
Technical Efficiency ◽  
Formal Education ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Technical Inefficiency ◽  
Factors Affecting ◽  
Frontier Analysis ◽  
Central Java ◽  
Frontier Production Function ◽  
Central Java Province

The objective of this study is to determine technical efficiency and factors affecting technical inefficiency of strawberry farming in Purbalingga Regency. This study was conducted in Karangreja Subdistrict, Purbalingga Regency, Central Java Province. Purposive sampling method was utilized to select 100 farmers as the respondents. All of whom have been running their farm business for at least three years consecutively from 2015 to 2017. Stochastic frontier production function was applied to measure technical efficiency and factors affecting technical inefficiency. The findings show that strawberry farming in Purbalingga Regency, Central Java Province, is technically efficient with efficiency number varies between 26.50-99.40% and the average efficiency number of 77.80%. Furthermore, the results indicate that the farmers’ formal education and the number of household members significantly affect the technical efficiency of strawberry farming.

scholarly journals The Dynamics and Sources of Technical Efficiency of the Manufacturing Industries in Bangladesh

2020 ◽  
Author(s):  
Sheikh Jafar Emran ◽  
Md. Moniruzzaman
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Returns To Scale ◽  
Manufacturing Industries ◽  
Efficiency Gain ◽  
Firm Characteristics ◽  
Frontier Analysis ◽  
Textile And Apparel ◽  
Wooden Furniture

Abstract This paper aims to analyze the dynamics of technical production efficiency of the manufacturing sector in Bangladesh using the cross-sectional data collected under the Survey of Manufacturing Industries (SMI) conducted in 2006 and 2012. Based on the dynamics of mean efficiency scores among the industries derived using Stochastic Frontier Analysis(SFA) techniquewith Cobb-Douglas technology with half-normal distribution during the considered period three most efficiency gainer industries are ((i) Jute textile,(ii) Dying and bleaching of textiles, and(iii) Bidies respectively. On the other hand, under SFA specification with Translog production function top three efficiency gainers are (i) Jute textile,(ii) Bidies, and(iii) Fish, Crustaceans and Molluses respectively. Under constant returns to scale in Data Envelopment Analysis(DEA), based on the mean efficiency score top three efficiency gainers are(i) Fibre textile,(ii) Embroidery of textile and apparel, and(iii) Wooden furniture and fixture respectively while undervariable returns to scale top three gainers are(i) Fibre textile,(ii) Embroidery of textile and apparel, and(iii) Wooden furniture and fixture respectively. Whatever technique we employ, we find that most cases garments or garments related industries remain among top performers in terms of efficiency gain. This indicates that garments industries have improved significantly in terms of efficiency to survive in world competition. Moreover, our results suggest that firm characteristics, location factors as well as ownership features are more important jointly rather than individually to enhance efficiency. Locational and ownership characteristics jointly, in most cases, are also not so influential in pulling the efficiency measures up. However, the firm characteristics are very important in raising the technical efficiency of the firms, especially in case of stochastic frontier analysis. And firm characteristics shows stronger impacts in interaction with other locational and/or ownership characteristics.

scholarly journals Analisis Efisiensi Usahatani Padi di Jawa dan Luar Jawa, Kajian Prospek Peningkatan Produksi Padi Nasional

2021 ◽  
Vol 9 (2) ◽  
pp. 143-153
Author(s):  
Rivani Hilalullaily ◽  
Nunung Kusnadi ◽  
Dwi Rachmina
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Agricultural Land ◽  
Stochastic Frontier ◽  
Rice Production ◽  
Frontier Analysis ◽  
Production Factors ◽  
Rice Consumption ◽  
Farmer Education ◽  
Almost All

Rice can grow in almost all of the islands in Indonesia, but 57 per cent of it was produced in Java, which is less than 10 per cent of the national area in Indonesia. To anticipate the increasing need for rice consumption, it is important to study the prospects for increasing national rice production, especially by utilizing the potential of agricultural land outside Java island. The purpose of this study was to identify the prospects for the development of national rice, especially outside Java island, from the perspective of rice production factors and technical efficiency at the farm level. Using stochastic frontier analysis, the translog production function showed that the increasing use of inputs (land, seeds, fertilizers, pesticides) will not significantly increase rice production both in Java and outside Java island (inelastic). Technical efficiency analysis indicated that rice production in Java and outside Java island was 28 and 39 per cent below its frontier, respectively.  Further analysis showed that irrigation, land status, farmer groups, and farmer education were significantly improved technical efficiency. This study concluded that the potential to increase rice production by increasing technical efficiency outside of Java island was greater than in Java island. However, increasing the efficiency of rice production outside Java may be constrained by the availability of irrigated agricultural land. To significantly increase national rice production both in Java and outside Java island, a breakthrough in new rice production technology is needed.

scholarly journals Are Our Export-Oriented Industries Technically More Efficient?

2015 ◽  
Vol 54 (2) ◽  
pp. 97-121
Author(s):  
Tariq Mahmood ◽  
Ejaz Ghani ◽  
Musleh Ud Din .
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Returns To Scale ◽  
Manufacturing Industries ◽  
Data Envelopment ◽  
Frontier Analysis ◽  
Analysis Technique ◽  
Control Apparatus

This paper makes a comparison of technical efficiency scores between groups of exporting and non-exporting industries. Using data from Census of Manufacturing Industries in Pakistan (2005-06), technical efficiency scores of 102 large scale manufacturing industries are estimated. Stochastic Frontier Analysis as well as Data Envelopment Analysis technique are used to estimate technical efficiency scores. In Stochastic Frontier Analysis Translog and Cobb-Douglass Production Functions are specified, whereas in Data Envelopment Analysis technique, efficiency scores are computed under the assumptions of Constant Returns to Scale as well as Variable Returns to Scale. Industries showing high technical efficiency include Tobacco Products, Refined Petroleum Products, Carpets and Rugs, and Meat and Meat Products. Industries showing low technical efficiency include Refractory Ceramic Products, Electricity Distribution and Control Apparatus, Fish and Fish Products, Basic Precious Metals and Aluminum and its Products. Comparison of mean efficiency scores between exporting and non-exporting industries does not indicate any significant difference between efficiency scores across types of industries. JEL Classification: D24, L6, O14, F14 Keywords: Manufacturing Industries, Technical Efficiency, Stochastic Frontier Analysis, Data Envelopment Analysis, International Trade

scholarly journals Technical Efficiency of Smallholder Tomato Production in Semi-Urban Farms in Cameroon: A Stochastic Frontier Production Approach

2017 ◽  
Vol 7 (4) ◽  
pp. 27 ◽  
Author(s):  
Martin Paul Jr. Tabe-Ojong ◽  
Ernest L. Molua
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Smallholder Farmers ◽  
Research Question ◽  
Stochastic Frontier ◽  
Negative Influence ◽  
Farm Size ◽  
Primary Data ◽  
Tomato Production ◽  
Frontier Analysis

Agriculture is the mainstay of Cameroon’s economy as it serves the purposes of food, livelihood and employment. Nevertheless, the country’s agriculture is plagued by low productivity and inefficiency in production. One of the main reasons for low productivity is the inability of farmers to fully exploit available technologies and production techniques. An important research question that comes to mind is, what are the major factors that hinder the technical efficiency of smallholder farmers? This study thus aimed to determine the level of technical efficiency in the production of tomato in smallholder farms, relying on primary data collected using a structured survey instrument administered to 80 tomato farmers in the Buea municipality of Cameroon. Data was analyzed using descriptive statistics and a stochastic frontier analysis method in the Cobb-Douglas production function. The STATA.14 software was used to obtain both stochastic frontier estimates and the determinants of technical efficiency. The results indicate that farmers are not fully technically efficient with a mean technical efficiency score of 0.68 with one farmer operating on the frontier. The study also revealed that most of the farmers irrespective of the size of the holdings have shown technical inefficiency problems. The older farmers were observed with the best measures of technical efficiency. Education, age and the adoption and practice of agronomic techniques had a positive and significant influence on technical efficiency while the nearest distance to the extension agent had a rather negative influence on technical efficiency. The input-output relationship showed that the area of tomato cultivation and the quantity of improved seed used were positive and significantly related to output at the 5% level of probability. As a result, it is recommended that farmers should increase their farm size, use of improved seeds and the adoption and practice of novel techniques in production. More emphasis should be placed on extension agents as they have a significant role to play in terms of improving and augmenting farmers’ education and information base through on farm demonstrations and result oriented workshops as all this will ensure increased production and productivity thereby increasing technical efficiency and achieving food self-sufficiency.

scholarly journals Technical Efficiency and Small Scale Maize Producers in Mwanza Region: A Stochastic Frontier Analysis

2021 ◽  
Vol 9 (3) ◽  
Author(s):  
Mukole Kongolo
Keyword(s):  
Technical Efficiency ◽  
Best Practice ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Likelihood Estimation ◽  
Estimation Procedure ◽  
Farm Size ◽  
Small Scale ◽  
Maize Production ◽  
Frontier Analysis

This study measured technical efficiency and its determinants in maize production by small-scale producers in Mwanza region, using a stochastic frontier production function approach. A randomly selected sample of participants in the two districts was used. The Maximum Likelihood estimation procedure was followed to obtain the determinants of technical efficiency and technical efficiency levels of small-scale maize producers. The minimum and maximum values of technical efficiency were between 20% and 91%, indicating that the least practices of specific producer operates at a minimum level of 20%, while the best practice producers  operate  at 91% technical efficiency  level respectively. The summary results of the mean technical efficiency was 63%. The main determinants of technical efficiency were labour, farm size, producer’s experience, producer’s age, family size which were all positive and statistically significant. The findings suggest that the average efficiency of small-scale maize producers could be improved by 37% through better use of existing resources and technology. These findings highlight the need for action by government to assist small-scale maize producers improve efficiency.

scholarly journals Technical Efficiency among Pepper Farmers in Sarawak, Malaysia: A Stochastic Frontier Analysis

2020 ◽  
Vol 10 (3) ◽  
pp. 729-739
Author(s):  
Anita Rosli ◽  
Alias Radam ◽  
Khalid Abdul Rahim ◽  
Amin Mahir Abdullah
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Agricultural Practices ◽  
Piper Nigrum ◽  
Maximum Output ◽  
Full Time ◽  
Frontier Analysis ◽  
One Step ◽  
The Mean

This study aimed to estimate the technical efficiency among pepper (Piper nigrum. L) farmers in Sarawak, Malaysia, using Stochastic Frontier Analysis (SFA). SFA involves a one-step process that can estimate technical inefficacy factors simultaneously with the production frontier. 678 pepper farmers were involved in this study, and the data were collected from 2012 to 2013. The mean score for technical efficiency was 0.518, indicating that pepper farmers were not efficient. However, the inefficiency model showed that education level, membership in farmers’ association, full-time as a pepper farmer, attending courses and visiting sample farms were factors that significantly improved inefficiency. The major problem of pepper farming in Sarawak is poor agricultural practices where farmers do not fully utilize the available agricultural inputs to produce maximum output. Based on the findings, farmers must improve their knowledge and skills in pepper farming through agronomic education.

scholarly journals The trends in efficiency of Lithuanian dairy farms: a semiparametric approach

2015 ◽  
Vol 37 (2) ◽  
pp. 167-178 ◽  
Author(s):  
Tomas Baležentis ◽  
Tianxiang Li ◽  
Alvydas Baležentis
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Dairy Farms ◽  
Random Coefficients ◽  
Family Farms ◽  
Frontier Analysis ◽  
Semiparametric Approach ◽  
Farm Accountancy Data Network ◽  
Development Paths

This study aims at analysing the trends in efficiency of Lithuanian dairy farms and thus identifying the prospective development paths. The semiparametric approach based on nonparametric regression and Stochastic Frontier Analysis is applied for the analysis. The research relies on Farm Accountancy Data Network and covers family farms. The period of 2004–2011 is considered. In order to identify the underlying trends in dairy farming, we focus on such features as technical efficiency, partial elasticities, and elasticity of scale. The semiparametric approach yielded rather high efficiencies. Specifically, the average technical efficiency of 89% was observed. A decline in technical efficiency during 2004–2011 is present for both point estimates and associated bounds of the confidence interval. Analysis of the elasticity of scale implies that most of the farms could still increase their scale of operation. The obtained results were confirmed by a parametric random coefficients model.

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