scholarly journals Indonesia Industrial Productivity Growth: Evidence of Re-industrialization or De-industrialization?

2019 ◽  
Vol 27 (2) ◽  
pp. 108-118 ◽  
Author(s):  
Lilik Sugiharti ◽  
Rudi Purwono ◽  
Martha Ranggi Primanthi ◽  
Miguel Angel Padilla Esquivias
Keyword(s):  
Technical Efficiency ◽  
Productivity Growth ◽  
Technological Progress ◽  
Stochastic Frontier Analysis ◽  
Scale Effects ◽  
Stochastic Frontier ◽  
Output Growth ◽  
Firm Level ◽  
Frontier Analysis ◽  
Skill Intensity

This study employs a Stochastic Frontier Analysis to decompose Total Factor Productivity for the manufacturing corridor of Indonesia. Technological progress, technical efficiency change, and scale effects are captured at a firm level covering all Java provinces from 2007 to 2013. The period is of particular interest as it covers the efforts of re-industrialization under the Master Plan for Acceleration of Indonesian Economy (MP3EI) and the sharp increase-decrease in global demand and global prices. The study captures sources of productivity growth supporting/deterring output growth, differentiating across firm characteristics based on size (large and medium), technology intensity, skill intensity, location (province), and capital-output ratio employed in production. As firms differ in the five elements, productivity and efficiency performance also differ. This paper questions whether productivity growth is limited to conventional sources -input growth and technological progress-, or if manufacturing is managing some gains through non-conventional channels -technical efficiency and scale effects. The paper also questions the presence of patterns in productivity among group firms (characteristics), finding that firms which combine a low-tech level, a higher skill ratio, and are medium in scale reported TFP at least 70 % higher than the average firm. Combinations of firm size, technology, skills, and ratio output affect the performance. Cost analysis of factors of production is also carried out, finding that energy is canceling out possible gains in scale effects by rising disproportionately both in consumption and prices. TFP growth was found to be negative and falling, raising the possibility of a path towards de-industrialization.

scholarly journals GLOBAL SOURCING AND TECHNICAL EFFICIENCY – A FIRM-LEVEL STUDY ON THE ICT INDUSTRY IN SWEDEN

2017 ◽  
Vol 18 (5) ◽  
pp. 877-896 ◽  
Author(s):  
Martin ANDERSSON ◽  
Trudy-Ann STONE
Keyword(s):  
Technical Efficiency ◽  
Manufacturing Industry ◽  
Management Practices ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Efficient Production ◽  
Global Sourcing ◽  
Firm Level ◽  
Frontier Analysis ◽  
International Sourcing

We analyse the relationship between international sourcing, measured as imports of intermediate inputs, and the technical efficiency of firms in the information and communications technologies (ICT) manufacturing industry in Sweden. Using stochastic frontier analysis, we provide evidence that global sourcing improves firms’ capabilities to combine and re-combine inputs in productive ways, thereby increasing technical efficiency. We find a robust relationship between technical efficiency and international outsourcing. First, we find that firms that are deeply integrated into global sourcing networks are closer to their own production frontier. Second, firms that are engaged in international sourcing are also closer to the industry efficiency frontier. These findings are consistent with the argument that international sourcing stimulates firms’ capabilities by enabling them to identify and adopt higher quality inputs or more efficient production and management practices. These findings also suggest that the variety and extent of firms’ global sourcing networks constitute an important source of differences in efficiency levels among firms the ICT manufacturing industry.

scholarly journals EAST JAVA’S PRODUCTIVITY GROWTH: EVIDENCE OF INDUSTRIALIZATION OR DEINDUSTRIALIZATION IN THE JAVA ISLAND?

2021 ◽  
Vol 2 (2) ◽  
pp. 118-138
Author(s):  
Miguel Angel Esquivias Padilla
Keyword(s):  
Technical Efficiency ◽  
Technological Progress ◽  
Stochastic Frontier Analysis ◽  
Scale Effects ◽  
Medium Size ◽  
Energy Prices ◽  
Efficiency Change ◽  
Frontier Analysis ◽  
Human Skills ◽  
Better Than

This study estimates Technical Efficiency (TE) and Total Factor Productivity (TFP) to analyze the sources of growth in the province of East Java in Indonesia. Technological progress, technical efficiency change, and scale effects are estimated through a stochastic frontier analysis (SFA) to break up different sources of growth within manufacture. This study looks at patterns of output expansion by differentiating gains from conventional sources –input growth and technological progress- and non-conventional sources –technical efficiency change and scale effects-. Results are aggregated based on tech-intensity, firm size, capital to output ratio employed, and labor skills. It also compares East Java with the other five provinces in the Java Island, the manufacturing corridor of the country. As expected, manufacturing sector is growing through input growth effects and tech progress-conventional sources- but underperforming in productivity by having negative efficiency change and negative scale effects. Labor has the largest elasticity to output (0.436), capital and raw materials have a much lower elasticity, and energy has a large negative one (-3.097) also causing a sharp increase in the cost of production. Low-tech firms, higher skills, and medium in size perform 72% better than average (TFP). MLT firms with labor-intensive and medium-size firms perform 58% better than average. However, champion industries have lower skills, good access to materials, and are less intensive in energy use. Some features of firm performance are: firm with larger portions of human skills capture the largest TE and higher TP values; those under high skills report larger losses due to negative scale effects; labor-intensive firms have larger TFP (less efficient but less exposed to energy prices).

scholarly journals Technical Efficiency of Manufacturing Enterprises in Libya: A Stochastic Frontier Analysis

2013 ◽  
Vol 5 (2) ◽  
pp. 528-535
Author(s):  
Hodud Essmui ◽  
Madeline Berma ◽  
Faridah Bt. Shahadan ◽  
Shamshubarida Bt. Ramlee
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Manufacturing Firms ◽  
Firm Level ◽  
Frontier Analysis ◽  
Manufacturing Enterprises ◽  
Stochastic Frontier Production Function ◽  
Econometric Approach ◽  
Frontier Production Function

This paper examines the performance of manufacturing firms in Libya. Specifically, it evaluates firm level technical efficiency. The paper uses an econometric approach based on a stochastic frontier production function to analyze 207 firms from survey conducted from March to May 2013. The results from estimations reveal that technical efficiencies of Libyan manufacturing firms ranging from 37.77 percent to 95.27 percent, with an average of 71.27 percent. While, the percent of firms that considered technically efficient is only 17.87 percent of the total firms.

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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