Total factor productivity measurement with carbon reduction

2017 ◽  
Vol 24 (4) ◽  
pp. 575-592 ◽  
Author(s):  
Xiancun Hu ◽  
Chunlu Liu
Keyword(s):  
Total Factor Productivity ◽  
Construction Projects ◽  
Driving Forces ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Productivity Analysis ◽  
Factor Productivity ◽  
Productivity Measurement ◽  
Content Type ◽  
Carbon Reduction

Purpose The purpose of this paper is to present an approach for productivity measurement that considers both construction growth and carbon reduction. Design/methodology/approach The approach applied is a sequential Malmquist-Luenberger productivity analysis based on a directional distance function and sequential benchmark technology using the data envelopment analysis (DEA) technique. The sequential Malmquist-Luenberger productivity change index is decomposed into pure technical efficiency, scale efficiency, and technological change indices, in order to investigate the driving forces for productivity change. Findings The construction industries of the Australian states and territories were selected implement the new approach. The results indicate that construction growth and carbon reduction can be achieved simultaneously through the learning of techniques from benchmarks. Practical implications Current research on total factor productivity (TFP) in construction generally neglects carbon emissions. This does not accurately depict the nature of construction and therefore yields biased estimation results. TFP measurement should consider carbon reduction, which is beneficial for policymakers to promote sustainable productivity development in the construction industry. Originality/value The approach developed here is generic and enhances productivity and DEA research levels in construction. This research can be used to formulate policies for evaluating performance in worldwide construction projects, organizations and industries by considering undesirable outputs and desirable outputs simultaneously, and for promoting sustainable development in construction by identifying competitiveness factors.

Measuring total factor productivity change of microfinance institutions in India using Malmquist productivity index

2018 ◽  
Vol 12 (1) ◽  
pp. 105-130 ◽  
Author(s):  
Dilip Ambarkhane ◽  
Ardhendu Shekhar Singh ◽  
Bhama Venkataramani
Keyword(s):  
Total Factor Productivity ◽  
Financial Institutions ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Microfinance Institutions ◽  
Factor Productivity ◽  
Content Type ◽  
The Poor

PurposeMicrofinance institutions (MFIs) provide small loans and other financial services to the poor. These institutions are established for helping the poor to raise income levels and to reduce poverty. Recently, MFIs are required to reduce their dependence on grants and subsidies. Consequently, they face conflicting objectives of improving reach and profitability. These can be achieved by improving productivity. This paper aims to investigate productivity change in 21 major MFIs in India which are rated by Credit Rating and Information Services of India Limited in 2014.Design/methodology/approachThis paper attempts to examine total factor productivity change in 21 major Indian MFIs during the period from 2014 to 2016 using Malmquist productivity index. The inputs and outputs are selected considering objectives of outreach and financial sustainability. The authors have categorized MFIs in three categories, namely, large, medium and small, depending on asset size.FindingsIt is revealed that large MFIs are able to catch up with industry best practices by improving their systems and processes, but they need to improve scale efficiency. The Reserve Bank of India has recently initiated a policy of granting banking licenses to those financial institutions which have good outreach and are financially strong. It can be used for shortlisting MFIs before granting permission to operate as banks. The method can also be used for benchmarking them for productivity. It can also be replicated in other countries.Originality/valueIn India, MFIs are playing important role in economic development by providing microcredit to the poor. However, very few studies have been undertaken regarding productivity of MFIs in India. The present study intends to fill this gap. It will facilitate benchmarking of MFIs as competitive and sustainable financial institutions catering to the requirements of small borrowers.

scholarly journals Understanding the components of profitability and productivity change at the micro level

2019 ◽  
Vol 69 (5) ◽  
pp. 1061-1079 ◽  
Author(s):  
Bernd Andreas Wiech ◽  
Athanassios Kourouklis ◽  
James Johnston
Keyword(s):  
Total Factor Productivity ◽  
Scale Effects ◽  
Future Research ◽  
Productivity Change ◽  
Factor Productivity ◽  
Productivity Measurement ◽  
Firm Level ◽  
Content Type ◽  
Using Data ◽  
Productivity Indicators

Purpose The purpose of this paper is to present a refined framework providing clarity in terms of the components of profitability and productivity change from the perspective of the firm level. Design/methodology/approach The literature is analysed with a scoping study and a systematic literature review. Productivity measurement approaches are compared using data at the product level. Findings The definition of total factor productivity (TFP) in the literature negatively affects the accuracy of profitability and productivity measurement. In the usual case of a dynamic output mix, TFP change encompasses biasing output mix effects relating to profitability, but not to productivity change. Therefore, this paper defines changes of a ratio of output quantities to input quantities not as TFP change, but as quantitative profitability (QP) change. A framework is proposed decomposing profitability change into price recovery and QP change, whereas the latter comprises of valid productivity change (encompassing technological, technical efficiency and productivity-related scale effects) and output mix change (encompassing proportion, quality, output switching and profitability-related scale effects). Research limitations/implications Future research should include literature from the industrial organisation field of economics. The presented framework should be transferred to the standard production function framework used in economics. Practical implications The paper can help preventing faulty decision making or distrust due to the use of biased profitability or productivity indicators. TFP-based productivity indicators are unsuitable for most firms. To measure productivity meaningfully, firms should use adequate approaches (e.g. standard input- or adjusted total factor productivity-based ones). Originality/value The paper contributes to a more accurate performance measurement approach, as researchers and practitioners better understand the components of profitability and productivity change.

scholarly journals Total Factor Productivity Growth of Indian General Insurance Companies in the Recent Period: A Bootstrapped Approach

2019 ◽  
Vol 11 (1-2) ◽  
pp. 59-80
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Private Sector ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Malmquist Index ◽  
American Economic Review ◽  
Productivity Index ◽  
Insurance Companies ◽  
Productivity Change ◽  
Productivity Analysis ◽  
Factor Productivity

This study estimates Malmquist index of total factor productivity change of 14 major general insurers in India over the period 2009–10 to 2016–17 over 7 annual windows. The study decomposes total factor productivity index into its constituent components, using several approaches including Färe et al. (1989, Productivity Developments in Swedish Hospitals: A Malmquist Output Index Approach. Carbondale: Department of Economics, Southern Illinois University; 1992, Journal of Productivity Analysis 3(1): 85–101), Färe et al. (1994, American Economic Review 84(1): 66–83), Ray and Desli (1997, American Economic Review 87(5): 1033–39) and Wheelock and Wilson (1999, Journal of Money, Credit and Banking 31(2): 212–23). Furthermore, the study uses bootstrap data envelopment analysis (DEA) method to obtain bias-corrected point and interval estimates of Malmquist index and its components. Finally, the study makes a comparison of productivity performance between public and private sector insurers. The results indicate a modest growth in total factor productivity during the period contributed mainly by efficiency changes. The private sector insurers performed better than the public sector in terms of productivity growth. The variations in productivity performance indicate that insurer scale of activity can affect their performance. JEL Classification: G-23, C-61, D-21

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.

Total factor productivity of the non-life insurers in India: Malmquist index with a new decomposition

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ashiq Mohd Ilyas ◽  
S. Rajasekaran
Keyword(s):  
Total Factor Productivity ◽  
Life Insurance ◽  
Economies Of Scale ◽  
Negative Impact ◽  
Malmquist Index ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Decomposition Approach ◽  
Content Type ◽  
Insurance Sector

PurposeThis paper aims to measure the change and the sources of change in total factor productivity (TFP) of the Indian non-life insurance sector over the period 2005–2016.Design/methodology/approachThis study employs the bootstrapped Malmquist index (MI) to assess the changes in the TFP and adopts a decomposition approach proposed by Balk and Zofío (2018). Moreover, it utilises truncated regression to identify the determinants of the TFP. In addition, it employs Wilcoxon-W test and t-test to scrutinise the difference between the state-owned and the private insurers in terms of variations in TFP and its various components.FindingsThe results divulge a miniature improvement in TFP of the insurance sector, which is primarily attributable to the improvement in scale efficiency (economies of scale). The results also reveal that there are no significant TFP differences across the ownership. However, private insurers have better scale efficiency and lower input-mix efficiency than state-owned insurers. In addition, the results unveil that size, diversification and reinsurance have a negative impact on the TFP, while age has a positive impact on it.Practical implicationsThe results may help the policymakers to frame new consolidation policies. Moreover, the findings may guide the decision-makers of the Indian non-life insurance companies to abate inefficiency and improve TFP.Originality/valueThis study estimates bias-corrected changes in TFP and efficiency in the non-life insurance sector. Moreover, it adopts an elaborated decomposition of the MI to identify the true sources of change in the TFP.

scholarly journals Decomposition of Total Factor Productivity Change in the U.S. Hog Industry

2008 ◽  
Vol 40 (01) ◽  
pp. 137-149 ◽  
Author(s):  
Nigel Key ◽  
William McBride ◽  
Roberto Mosheim
Keyword(s):  
Total Factor Productivity ◽  
Growth Rates ◽  
Farm Size ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Hog Industry ◽  
Frontier Analysis ◽  
Tfp Growth ◽  
The U.S

The U.S. hog industry has experienced dramatic structural changes and rapid increases in farm productivity. A stochastic frontier analysis is used to measure hog enterprise total factor productivity (TFP) growth between 1992 and 2004 and to decompose this growth into technical change and changes in technical efficiency, scale efficiency, and allocative efficiency. Productivity gains over the 12-year period are found to be explained almost entirely by technical progress and by improvements in scale efficiency. Differences in TFP growth rates in the Southeast and Heartland regions were found to be explained primarily by differences in farm size growth rates.

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.

Measurement of financial efficiency and productivity of Turkish Public Universities by using non-parametric methods

2019 ◽  
Vol 11 (4) ◽  
pp. 876-896
Author(s):  
Aslı Günay ◽  
Murat Ali Dulupçu
Keyword(s):  
Total Factor Productivity ◽  
Public Universities ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Financial Efficiency ◽  
Data Set ◽  
Content Type ◽  
Efficiency And Productivity

Purpose The purpose of this paper is to measure the financial efficiency and productivity of 23 public universities founded in 1992 in Turkey over the period between 2004 and 2013. The results obtained will provide managerial information and act as a guide to public universities’ administrations, in using their resources more effectively. Design/methodology/approach Data envelopment analysis is applied to assess the relative financial efficiency of these universities, while Malmquist total factor productivity index is used to measure the total factor productivity change concerning financial inputs of the universities. Findings The number of financially efficient universities and the number of universities showing an increase in their productivity according to their financial inputs change annually and both of them display a rough trend over the years. A decrease of about 5 percent in the financial productivity of the universities is observed which stems from a technological recession. Therefore, public universities in Turkey are not able to develop effective policies to diversify, increase and use their financial resources. Originality/value When the lack of studies within the literature measuring the financial efficiency of higher education institutions is taken into account, this study can fill a gap in this area. The analyses conducted here distinguish from existing studies on this subject with regards to the extent and diversity of financial data set and the measurement of both efficiency and productivity change of universities considering financial inputs concurrently.

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.

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