scholarly journals Global Malmquist indices of productivity change in Egyptian wheat production

2017 ◽  
Vol 15 (2) ◽  
pp. e0111
Author(s):  
Yahia H. Elasraag ◽  
Silverio Alarcón
Keyword(s):  
Total Factor Productivity ◽  
Technical Change ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Parametric Approach ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Wheat Production ◽  
Time Period ◽  
Malmquist Indices

This study aims to measure the total factor productivity of the main governorates of wheat production in Egypt during the time period 1990-2012 and decompose it into technical change, efficiency change and scale change. We used Global Malmquist TFP index as a non-parametric approach. The results indicated that the contribution of technical change component is more important than the efficiency change component. In fact technical change rose, 25.7%, while efficiency change presented a little decline, 3.7%. The decomposition of efficiency change indicated that the main problem of wheat production in Egypt was scale efficiency that worsened by 5.5%.

Productivity Analysis of Coal-fired Thermal Power Plants in India Using Malmquist Index Approach

2019 ◽  
Vol 21 (6) ◽  
pp. 1338-1353
Author(s):  
Amritpal Singh Dhillon ◽  
Hardik Vachharajani
Keyword(s):  
Total Factor Productivity ◽  
Power Plants ◽  
Thermal Power ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Tfp Growth

The sustainable socio-economic growth of any country depends on the availability of adequate and reliable power at reasonable rates. This is even true in case of a rapidly developing country like India where coal-based power plants account for the majority of electricity generation. Making use of data envelopment analysis (DEA) and Malmquist productivity index (MPI), this study analyses the productivity change of coal-fired power plants during 2002–2012. Productivity change is further decomposed into technical efficiency change (EFFCH), technological change (TECHCH), scale efficiency change (SECH), pure technical change (PECH) and total factor productivity change (TFPCH). The study revealed that 0.70 per cent of average annual total factor productivity (TFP) growth was witnessed from 2002–2003 to 2011–2012 indicating overall progress. The contribution of TECHCH in TFP growth is positive, that is, 1.3 per cent per annum. It demonstrates that expansion of the efficient frontier. However, there was a decrease in technical EFFCH of −0.6 per cent per year, indicating the adverse sign of progress. Plants in the central sector achieved maximum growth of 4.6 per cent annually. A total of 54.05 per cent of plants have recorded negative TFP growth. Power plants between 500 and 999 MW achieved the highest operational performances in all indices except SECH.

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 Measurement of Total Factor Productivity in Commercial Airlines Sector using Malmquist Index and Data Envelopment Model

2020 ◽  
Vol 8 (6) ◽  
pp. 2168-2173
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Year 2013

This study attempts to measure productivity change of Airlines companies in private and public sector in India for a period of four years (2011-2016). In this study the nature and productivity change is probed using the Malmquist Productivity Index. This index has the constituents which are used to measure the performance in terms of change in Scale Efficiency, change in Technical Efficiency, change in Technological Change and Total Factor Productivity. The paper compares efficiencies for the companies in public and private commercial airlines sector in India. Five Airlines companies are included in the study. The research includes Total Annual Income as an output variable and Total Expenditure, Employee Compensation, Sales & Distribution Expenditure and Marketing expenses as Input variables. A panel data with 30 observations has been used for analysis. The panel data is used to arrive to MPI estimates, with a total of five commercial airlines companies in India. The Total Factor Productivity change in the airlines sector depends upon the change in the efficiency and productivity of the companies. From the study it is evident that the Total Factor Productivity change has not changed significantly over the last six years for all the companies under study. The Technical Efficiency was the highest in the year 2013-14 which then dropped in the subsequent year. The Total Factor Productivity change is mainly due to change in scale efficiency of the companies since the pure efficiency has shown no significant change during the period under study. The Total Factor Efficiency dropped by almost 50% in the case of Air India in the year 2015-16. This drop is attributed to the deterioration in the technical efficiency of the company. The overall Total Factor Productivity of Air India is the highest. This can be attributed to positive change in the company’s Technical Efficiency especially in the year 2013-14. It is evident that all the airlines companies under study have not emphasized on improving scale efficiency as well as pure efficiency. These companies can improve their overall productivity by bringing in efficiency in the scale of operations as well as focus on improving efficiency on factors other than scale of operations. The commercial airlines companies in India need to improve their scale efficiency and pure efficiency to improve their total factor productivity.

scholarly journals TOTAL FACTOR PRODUCTIVITY CHANGE IN THE REIT INDUSTRY: THE CASE OF MALAYSIAN REITS DURING AND POST GLOBAL FINANCIAL CRISIS

2019 ◽  
Vol 17 (9) ◽  
Author(s):  
Nor Nazihah Chuweni ◽  
Ihsan Isik ◽  
Andrea Blake
Keyword(s):  
Real Estate ◽  
Technological Change ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Change ◽  
Parametric Approach ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Real Estate Investment ◽  
Non Parametric

The paper examined productivity changes for the Malaysian Real Estate Investment Trust (M-REITs) using a non-parametric approach of Malmquist Productivity Index (MPI) of Data Envelopment Analysis (MPI-DEA). Data was attained from M-REIT annual reports, Thomson Reuters Datastream and Osiris via Bureau Van Dijk for 2007-2015. The non-parametric approach of MPI-DEA examined the Total Factor Productivity Change (TFPCH), Technological Change (TECHCH), Efficiency Change (EFFCH), Pure Technical Efficiency Change (PEFFCH) and Scale Efficiency Change (SECH) indices. On average, the M-REIT industry has faced 14.91% of productivity regress during 2007-2015 period, comprising 49.90% of efficiency increase and 33.40% technological regress. The decomposition of the productivity change index suggests that Malaysian REIT productivity changes were mainly due to efficiency change rather than technological change. These findings could help M-REIT managers to formulate ways to enhance their REIT productivity. The findings are also applicable tosimilar Shariah compliant real estate investment or socially responsible investment.

scholarly journals Total Factor Productivity (TFP) Industri Tekstil dan Produk Tekstil (TPT) di Indonesia Tahun 2005-2009

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Henny Kurniawaty
Keyword(s):  
Total Factor Productivity ◽  
Technical Change ◽  
Textile Industry ◽  
Average Rate ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Firm Level ◽  
Average Growth ◽  
High Productivity

The Textile Industry and Product (TPT) are one of industry which has export orient and has market target or has huge role in creating PDB of non oil and natural gas manufacture industry. The main aspect to solve the work of TPT industry sector those are the efficiency, high productivity, and the technology progress. This study counts the growth of Total Factor Productivity (TFP) in industry of TPT in Indonesia at the year 2005 to 2009 by using panel data firm level. The growth count of TFP used method of Stochastic Analysis Frontier (SFA) with 2 models those are Cobb Douglas and Translog’s model. The development of TFP is decomposed within 3 components those are technical eficiency change, technical change, and scale efficiency change. The average growth rate of TFP in industry of TPT in Indonesia is as 2%. The major establishment componen of growth formation of TFP is technical change, in which the average rate is over 1%, while the average technical eficiency change is as 1%. It shows that the efficiency is stable or it does not change from time to time and for the average rate scale efficiency change is very tinny, it is under 1%. The influence of wage to the growth of TFP is very tinny; besides, the foreign property influences the growth of TFP in industry of TPT in Indonesia. 

scholarly journals Dynamic Analysis of Total Factor Productivity (TFP) of Traditional Chinese Medicine (TCM) Hospitals in Hubei Province from 2013 to 2019

2021 ◽  
Vol 292 ◽  
pp. 02069
Author(s):  
Tang Cheng ◽  
MA Jun ◽  
Chen Li
Keyword(s):  
Total Factor Productivity ◽  
Malmquist Index ◽  
Hubei Province ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Index Method ◽  
Mean Values ◽  
The Mean

Objectives: To study the changes of TFP in TCM hospitals in Hubei Province from 2013 to 2019, so as to provide policy basis for improving service efficiency and promoting the development of TCM. Methods: The statistical reports of 90 public TCM hospitals in Hubei Province from 2013 to 2019 were collected using the Hubei Provincial Comprehensive Statistical Information System for TCM, and the TFP of TCM hospitals were dynamically analysed using the DEA-Malmquist index method. Results: From 2013 to 2019, the Total Factor Productivity Change (TFPCH) index of TCM Hospitals in Hubei Province increased by 0.8%; the Efficiency Change (EFFCH) index increased by 0.5%; the Technical Change (TECH) index increased by 0.3%; the Pure Efficiency Change (PECH) index increased by 0.2% and the Scale Efficiency Change (SECH) index increased by 0.4%. The mean values of the TFPCH index in the eastern, central, and western regions of Hubei Province were 1.001, 1.011, and 1.013, respectively, and the mean values of that in the secondary and tertiary hospitals were 1.004 and 1.024, respectively. Conclusions: The TFP of TCM hospitals in Hubei Province tends to improve on the whole. There are differences in the TFPCH index of TCM hospitals in different regions and levels. The stage development characteristics of core cities play a leading role and are worth learning.

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 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 Distinction between Informal and Unorganized Sector: A Study of Total Factor Productivity Growth for Manufacturing Sector in India

2011 ◽  
Vol 3 (5) ◽  
pp. 296-310
Author(s):  
Indrajit Bairagya
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Informal Sector ◽  
Productivity Growth ◽  
Manufacturing Sector ◽  
Total Factor Productivity Growth ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Unorganized Sector

Since its very onset, the concept and definition of the informal sector has been a subject of debate both at the national and international levels. Existing literature uses the terms ‘informal sector’ and ‘unorganized sector’ interchangeably. However, in India, the characteristics of enterprises in the informal and non-informal unorganized manufacturing sectors are different and, thus, it is not justifiable to consider the informal and unorganized sector interchangeably for the manufacturing sector. Thus, the objective of this paper is to test the hypothesis on whether or not the total factor productivity growth (TFPG) of the informal manufacturing sector is different from the non-informal unorganized manufacturing sector. TFPG is decomposed into technical efficiency change and technological change. Later, technical efficiency change is further decomposed by pure efficiency change and scale efficiency change. Results show that the average TFPG of the non-informal sector is higher than the informal sector. The informal sector heavily concentrates in own account small enterprises, whereas the non-informal unorganized sector concentrates only in directory manufacturing enterprises (DME). Due to large in size, DME avails the advantages of economies of scale, which, in turn, helps the units for more growth in terms of total factor productivity growth. The main reason for productivity decrease of the enterprises, besides technology regress and the lack of adequate investments, is the limitation of activities and scale along with the optimal allocation of resources. This study provides a basis on how policies can be designed for enhancing the total factor productivity growth of the informal sector.

scholarly journals Measuring Productivity and Efficiency of Traditional Chinese Medicine Hospitals from 2009 to 2016: A Bootstrap-Data Envelopment Analysis

2021 ◽  
Author(s):  
Xinliang Liu ◽  
Rui Chen ◽  
Shaopeng Wu ◽  
Jian Wang ◽  
Jianan Li ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Total Factor Productivity ◽  
High Efficiency ◽  
Low Cost ◽  
Statistical Significance ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Average Growth

Abstract Objective: It was to estimate the productivity and efficiency of Traditional Chinese Medicine (TCM) hospitals to provide empirical evidence for hospital managers and policy-makers to improve the management and quality of TCM service.Methods: The data of the individual tertiary public TCM hospitals were collected from official Yearbooks of Traditional Chinese Medicine of China (2010-2017). Bootstrap-Malmquist-DEA was employed to measure the productivity and efficiency (2009-2016). SPSS23.0 was used to conduct the descriptive analysis of the input and output indicators. R3.2.1 was applied to calculate the productivity and efficiency with FEAR package. The statistical significance was set at P < 0.05.Results: The annual average growth rates of each indicator were 6.61% (health professionals), 8.15% (actual open beds), 7.08% (outpatients and inpatients) and 12.50% (discharged patients) respectively from 2009 to 2016. Except the total factor productivity change (TFPC) between 2014 and 2015, more than half of the TCM hospitals had TFPC scores over 1.000. The overall annual geo-mean TFPC score was 1.0379.Conclusions: The overall annual rate of the TFPC of the tertiary public TCM hospitals was slightly increased. The technological progress was the main driver to improve the total factor productivity. The decreased technical efficiency was more affected by the decreased scale efficiency. The TCM hospitals need to pay attention to the development and innovation of the TCM technology, thereby improving the competitiveness. The TCM hospitals managers should pursuit the high quality, high efficiency and low cost of the TCM services.

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