scholarly journals Decomposing total factor productivity of SMEs in agricultural sector in Aceh, Indonesia

2022 ◽  
Vol 951 (1) ◽  
pp. 012051
Author(s):  
M S A Majid ◽  
F Faisal ◽  
H Fahlevi ◽  
A Azhari ◽  
H Juliansyah

Abstract This study measures and decomposes the Total Factor Productivity (TFP) of the SMEs in the agricultural sector across 23 regencies/cities in Aceh province, Indonesia during the 2015-2019 period. Using Data Envelopment Analysis (DEA), the study found a low level of SMEs’ productivity during the study period. The SMEs in Aceh province recorded different levels of TFP. Overall, the SMEs’ TFP has slightly declined, contributed mainly by an increase in efficiency level and a decline in the technical efficiency change. These findings showed the importance of adopting advanced agricultural-related technologies and implementing good SMEs’ governance principles to further improve SMEs’ TFP. Finally, the government must prioritize promoting non-productive SMEs across the 23 regencies/districts in the province by offering sufficient financial aids and conducting professional managerial training programs.

2014 ◽  
Vol 16 (3) ◽  
pp. 277-308
Author(s):  
Ndari Surjaningsih ◽  
Bayu Panji Permono

This paper calculates and decomposes the Total Factor Productivity (TFP) for large and medium scale industry in Indonesia covering the period of 2000-2009. By using Data Envelopment Analysis (DEA)  method, the result shows there is a shift of the supporting factors on the growth of TFP on manufacturing sector within the 2 (two) sample period. In the period of 2000-2004, efficiency change becomes the main contributor on the growth of TFP. Whereas in the period of 2005-2009, technical change becomes the main supporting factor of TFP,however it goes along with the growth of negative efficiency change or the decline of the company’s catching-up effect ability to adapt with the more advance technology. The grouping of the sample across subsectors, technical change and also efficiency change shows the declining amount of manufacture industry with superior productivity. Furthermore, the number of low and weakening catching-up industry is increasing.  Keywords: Indonesian manufacturing, total factor productivity, technical change, efficiency change, economic scale change, Data Envelopment Analysis JEL Classification: L6, M11


Author(s):  
Sarang Monga ◽  
Rajesh K. Rana ◽  
Arun Pandit

Background: India is the largest producer as well as consumer of pulses in the world due to higher relance of their people on vegetarian sources of proteins, however, we have been dependent on import of pulses for meeting our demand for pulses over several decades. As a strategy to be self-reliant in pulses production two important initiatives were taken by the government of India viz. implementation of Accelerated Pulses Production Program (A3P) and inclusion of pulses in the National Food Security Mission (NFSM-Pulses) during 2010-11. Pigeon pea has tremendous medicinal and pharmacological properties and uses in addition to the good quality source of proteins. Significant improvement observed in production and productivity of pigeon pea after the A3P and NFSM-Pulses was questioned for its Total Factor Productivity (TFP) growth. Methods: This study was designed to assess impact of A3P and NFSM-Pulses on TFP of Pigeon pea in major Indian producing states. TFP was estimated with the help of Malmquist Productivity Index (MPI) using Data Envelopment Analysis Program (DEAP) version-2.1 in five states of India viz., Gujarat, Karnataka, MP, Maharashtra and UP which contribute more than three-fourth pigeon pea production in India. Result: TFP change in period-II (after A3P and NFSM-Pulses) was invariably higher than the TFP change in period-I (before the initiatives) in all the studied states. It indicates that these government initiatives contributed to the enhancement of production and productivity of pigeon pea with the support of better technology adoption rather than just led by higher use of inputs. 


2014 ◽  
Vol 16 (3) ◽  
pp. 259-288
Author(s):  
Ndari Surjaningsih ◽  
Bayu Panji Permono

This paper calculates and decomposes the Total Factor Productivity (TFP) for large and medium scale industry in Indonesia covering the period of 2000-2009. By using Data Envelopment Analysis (DEA)  method, the result shows there is a shift of the supporting factors on the growth of TFP on manufacturing sector within the 2 (two) sample period. In the period of 2000-2004, efficiency change becomes the main contributor on the growth of TFP. Whereas in the period of 2005-2009, technical change becomes the main supporting factor of TFP,however it goes along with the growth of negative efficiency change or the decline of the company’s catching-up effect ability to adapt with the more advance technology. The grouping of the sample across subsectors, technical change and also efficiency change shows the declining amount of manufacture industry with superior productivity. Furthermore, the number of low and weakening catching-up industry is increasing.  Keywords: Indonesian manufacturing, total factor productivity, technical change, efficiency change, economic scale change, Data Envelopment AnalysisJEL Classification: L6, M11


2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yennie Glorya Panjaitan ◽  
Edy Yusuf Agung Gunanto

Sektor pariwisata sebagai salah satu sektor yang diandalkan bagi penerimaan daerah maka pemerintah Provinsi Jawa Tengah dituntut untuk dapat menggali dan mengelola potensi wisata yang dimiliki. Penelitian ini bertujuan untuk menganilisis tingkat efisiensi dan produktivitas pada sektor pariwisata di Jawa Tengah antara tahun 2017 dan 2019 dengan sampel 35 Kabupaten/Kota. Analisis dilakukan dengan menggunakan konsep efisiensi yang didasarkan pada teori produksi, pengukuran nilai efisiensi dan produktivitas diperoleh menggunakan metode analisis Data Envelopment Analysis (DEA) dan Malmquist Productivity Index (MPI). Asumsi yang digunakan adalah variable return to scale (VRTS) dan model orientasi output (output oriented). Dengan variable input objek wisata, restoran dan rumah makan, biro perjalanan wisata dan jumlah hotel bintang serta melati. Variabel output dalam penelitian ini adalah wisatawan dan pendapatan sektor pariwisata. Hasil akhir penelitian menunjukkan bahwa terdapat 16 Kabupaten/Kota (45,8%) di tahun 2017, 18 Kabupaten/Kota (51,4%) di tahun 2019 yang mencapai efisiensi teknis penuh. Total Factor productivity change mengindikasikan bahwa 22 Kabupaten/Kota (62,8%) mendekati frontier baik pada frontier produksi maupun frontier efisiensi dan dari scale efficiency change mengindikasikan bahwa terdapat 17 Kabupaten/Kota (48,57%) mengalami perbaikan efisiensi teknis selama periode 2017 ke 2019.


2021 ◽  
Vol 3 (2) ◽  
pp. 223-248
Author(s):  
Smart Edward Amanfo

The increasing need for electricity access to drive economic growth, social development, poverty alleviation and environmental sustainability requires that efficient allocation of scarce and competing resources in the generation, transmission and distribution subsectors of the electricity sector is indispensable. This paper analyses total factor productivity growth in a single input multiple-output framework in Ghana. The technique applied is data-orientated nonparametric Data Envelopment Analysis using Win4Deap 2 software. Total Factor Productivity Change is evaluated through Malmquist Productivity Index (MPI), as well as technological change (TECHC) and efficiency change (EFFCH) using firm-level panel data. Sources of productivity growth comparison are made between Electricity Company of Ghana (ECG) and the Northern Electricity Distribution Company (NEDCO) for the periods 2000 to 2020. The results show TECHCH marginally declined at an average annual rate of 0.3% and drives the electric power distribution productivity regress in ECG and NEDCO from 2000 to 2020. Further, the results indicate stagnation in scale efficiency, pure efficiency and efficiency change when estimated over 20 years. At firm levels comparison, the study shows that the Northern Electricity Distribution Company recorded a productivity growth rate of 4.9%, mainly due to technical progress. However, the Electricity Company of Ghana experienced a slight deterioration of productivity performance due to a 5.3% decline in technical efficiency. The study offers several policy recommendations on how the underperforming firm can learn to improve efficiency and technical to reduce electricity transmission losses.


2019 ◽  
Vol 65 (No. 6) ◽  
pp. 249-258 ◽  
Author(s):  
Truc Linh Le ◽  
Pai-Po Lee ◽  
Ke Chung Peng ◽  
Rebecca H. Chung

This study assessed the change in productivity and environmental efficiency of agriculture for nine East Asian countries for the time period from 2002 to 2010. Data were collected and then analysed by data envelopment analysis (DEA) approaches, including Malmquist total factor productivity (TFP) index and slacks-based measure (SBM) with the consideration of undesirable outputs. The results showed that there existed relatively large differences in productivity growth and environmental performance in the agricultural sector between countries in the sample. Overall, the countries examined in the present study experienced a decline in TFP due to decreases in technical efficiency. Taiwan, Japan, and Korea were found to show growths in productivity and fully efficient environmental performances throughout the study period, while Thailand was identified as having the lowest environmental efficiency score. Therefore, agriculture production and operation models in Taiwan, Japan, and Korea could serve as good references for the other six countries.<br />


2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
K. Palanisami ◽  
C. R. Ranganathan

Total Factor Productivity (TFP) measures the growth in output which is not accounted for by inputs. Data Envelopment Analysis which forms the basis for the computation of Malmquist TFP index is used in this paper to study the performance of different river basins in Andhra Pradesh state, India. The results indicated that average technical efficiency of all the basins is only 66%. In all the basins there was a decline in growth of agricultural output during the first two decades, viz., 1979-1980 to 1988-1989 and it had picked in the last decade (1999-2000). All the river basins have TFP change greater than 1 indicating progress in agricultural productivity. Out of the 40 river basins, 14 river basins have technical efficiency change less than 1 indicating decline in TFP growth whereas all the basins have technical changes greater than 1 implying that there is shift in production frontier over years. In general, within the TFP, technical change contributed more than technical efficiency change. Looking at the future options for increasing the agricultural output in the river basins, it is important to focus on improving the TFP growth compared to increasing the quantities of physical inputs.


2019 ◽  
Vol 12 (1) ◽  
pp. 175 ◽  
Author(s):  
Zijing Liang ◽  
Yung-ho Chiu ◽  
Xinchun Li ◽  
Quan Guo ◽  
Yue Yun

Under the low-carbon background, with the aid of the Malmquist–Luenberger SBM (Slack-based Measure) model of unexpected output, the green total factor productivity (GTFP) of the logistics industry in Jiangsu Province, China, was measured and decomposed in this study based on the reality and experience of logistics industry development in 13 cities in three regions of Jiangsu Province in the years 2006–2018 by taking resource consumption into the input system and discharged pollutants into the output system. It is concluded that the environmental regulation (ER) has a significant positive effect on the growth of the GTFP of the logistics industry, and technological progress has become an important endogenous force that promotes the GTFP of the logistics industry in Jiangsu Province. On this basis, a dynamic GMM (Generalized method of moment) model and a Tobit model were constructed to further study the possible temporal and spatial effects of ER on the GTFP of the logistics industry. The research results reveal that the ER can exert both promoting and inhibitory effects on the GTFP of the logistics industry, and there is a temporal turning point for the effects. Besides, the effects notably differ spatially and temporally. Finally, some policies and advice for the green sustainable development of the logistics industry were proposed. For example, the government and enterprises should pay attention to the green and efficient development of the logistics industry and dynamically adjust the ER methods. They should consider the greening of both forward logistics links and reverse logistics system in the supply chain.


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