scholarly journals DINAMIKA TOTAL FACTOR PRODUCTIVITY INDUSTRI BESAR DAN SEDANG INDONESIA

2014 ◽  
Vol 16 (3) ◽  
pp. 277-308
Author(s):  
Ndari Surjaningsih ◽  
Bayu Panji Permono
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Manufacturing Sector ◽  
Jel Classification ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Catching Up ◽  
Using Data

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

scholarly journals THE DYNAMICS OF TOTAL FACTOR PRODUCTIVITY OFMEDIUM AND LARGE MANUFACTURING IN INDONESIA

2014 ◽  
Vol 16 (3) ◽  
pp. 259-288
Author(s):  
Ndari Surjaningsih ◽  
Bayu Panji Permono
Keyword(s):  
Total Factor Productivity ◽  
Technical Change ◽  
Manufacturing Sector ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Advance Technology ◽  
Catching Up ◽  
Manufacture Industry ◽  
Using Data

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

scholarly journals Growth in Agricultural Productivity and Its Components in Bangladeshi Regions (1987–2009): An Application of Bootstrapped Data Envelopment Analysis (DEA)

Economies ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 37 ◽  
Author(s):  
Mita Bagchi ◽  
Sanzidur Rahman ◽  
Yao Shunbo
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Technical Change ◽  
Bias Correction ◽  
Technological Progress ◽  
Agricultural Extension ◽  
Data Envelopment ◽  
Crop Diversification ◽  
Factor Productivity ◽  
Efficiency Change

The present study applies a bootstrapped data envelopment analysis (DEA) procedure to compute bias-corrected measures of agricultural total factor productivity (TFP) change and its components (technical change and technical efficiency change) using a panel data of 19 regions of Bangladesh covering a 23-year period (1987–2009), thereby overcoming the limitation of the lack of statistical inference of the conventional non-parametric DEA. Results revealed that overall productivity grew at a modest rate of 0.03%, mainly powered by technological progress at 0.03% and a negligible decline in technical efficiency at 0.004% with large disparities amongst regions. Six regions in the middle order shifted ranks with regard to TFP change following bias correction. The estimated confidence intervals demonstrated that many regions underwent either progress or regress in productivity performance over time. Investments in research and development (R&D), agricultural extension, and crop diversification are suggested to improve regional inequality and declining technical efficiency.

scholarly journals TOTAL FACTOR OF PRODUCTIVITY AND ITS COMPONENTS: EVIDENCE FROM CEMENT - AND ENERGY SECTORS OF PAKISTAN

2018 ◽  
Vol 9 (1) ◽  
pp. 55 ◽  
Author(s):  
Razzi Abbas Jafri ◽  
Shahbaz Khan ◽  
Muhammad Haroon Shah ◽  
Nida Baig
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Change ◽  
Annual Reports ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Financial Firms ◽  
Tfp Growth ◽  
Time Period ◽  
Dea Method

This study employs “Data Envelopment Analysis (DEA)” method to calculate the “Total Factor Productivity (TFP)” growth and its components of 19 non-financial firms from Cement and Energy sectors of Pakistan listed on ISE-100 Index during the time period 20052011. The research focuses on to identify the factors like, technical change and technical efficiency change tends to influence the TFP of cement -and energy sectors of Pakistan. We use hand collected data from the annual reports of these non-financial firms included in our sample. Results show that cement sector has an overall positive TFP growth of 9.7%, and energy sector has an overall TFP growth of 1.5% during the study period. The study may assist us to recognize the extent to which these components can affect the TFP of a sector, and will further help us to explore new ways to boost up the productivity of these sectors which in turn may be beneficial to move country towards a sustainable path.

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
Keyword(s):  
Total Factor Productivity ◽  
Agricultural Sector ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Managerial Training ◽  
Aceh Province ◽  
The Government ◽  
Using Data ◽  
Different Levels

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.

scholarly journals ANALISIS TINGKAT EFISIENSI SEKTOR PARIWISATA DI JAWA TENGAH TAHUN 2017 DAN 2019

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yennie Glorya Panjaitan ◽  
Edy Yusuf Agung Gunanto
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change

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.

scholarly journals Total Factor Productivity Growth of Ghanaian Electricity Distribution Utilities Using Data Envelopment Analysis and Malmquist Index (2000–2020)

2021 ◽  
Vol 3 (2) ◽  
pp. 223-248
Author(s):  
Smart Edward Amanfo
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Total Factor Productivity Growth ◽  
Malmquist Productivity Index ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Distribution Company

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.

Exploring the Changes of Carbon Emissions Performance Using Data Envelopment Analysis

2013 ◽  
Vol 291-294 ◽  
pp. 1433-1438
Author(s):  
Qin Liang Tan ◽  
Xing Ping Zhang ◽  
Yong Mei Wei
Keyword(s):  
Developing Countries ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Carbon Emissions ◽  
Technical Change ◽  
Driving Force ◽  
Data Envelopment ◽  
Efficiency Change ◽  
Using Data

This paper measures the carbon emissions efficiency by using data envelopment analysis. The gross domestic product and carbon emissions are the two outputs, and labor, energy consumption and capital stock are the three inputs in our DEA model. We decompose changes of carbon emissions performance into two contributors: the carbon emissions technical efficiency change and the carbon emissions technical change. For the developing countries mentioned in this paper as a whole, the empirical results indicate that the carbon emissions technical efficiency change is the contributor to carbon emissions performance increase, while the carbon emissions technique change is the component driving carbon emissions performance decrease during 1983-2003. However, the carbon emissions technical efficiency change is the contributor to carbon emissions performance decrease, while the carbon emissions technical change is the driving force to carbon emissions performance increase during 2003-2008.

Indian IT and ICT Industry: A Performance Analysis Using Data Envelopment Analysis and Malmquist Index

2007 ◽  
Vol 7 (2) ◽  
pp. 1850109 ◽  
Author(s):  
Somesh Mathur
Keyword(s):  
Data Envelopment Analysis ◽  
Data Base ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Malmquist Index ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Software Firms ◽  
The Common

The present study gives an account of IT and ICT infrastructure in India and points out the reasons for the boom in the IT exports and outsourcing business today and in times to come. The article analyzes the performances of the Indian IT industry by working out the technical efficiency of the software and telecommunication firms using the mathematical model of the Data Envelopment Analysis (DEA). The DEA is a non linear programming way of calculating technical efficiency of the decision making units. The study also examines the impact of various determinants on technical efficiency of software firms and net exports across the IT firms and further examines the determinants for new technology adoption by telecommunication industries, because the success of the software firms in terms of its exports is intertwined with the performance of telecommunication industry. The study uses a Malmquist index to estimate total factor productivity (TFP) change for the common set of software firms existing between 1996 and 2006 using a prowess data base. The total factor productivity is decomposed into efficiency change (catching up phenomena) and technical change (innovations) for the common set of software firms existing between 1996 and 2006 in India. At the end the study works out the performance of the Indian ICT sector in comparison with countries which are front runners using the DEA and global information technology report 2006 data base. The study will quantify the changes needed in the relatively good Indian ICT environment and ICT readiness to increase its ICT usage among individuals, business and government. The article confirms the improvements in productivity, efficiency, and technical change of the Indian Software industry from 1996 to 2006.

Impact of Determinants of Industrial Development on Employment and Wages in Indian Manufacturing

2020 ◽  
pp. 18-30
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Firm Level ◽  
Employment Level ◽  
The Impact ◽  
Level Performance

ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

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