Total Factor Productivity Change in Commercial Banking Industry in India and Pakistan

2004 ◽  
Author(s):  
Ali Ataullah ◽  
J. Barry Howcroft
Keyword(s):  
Total Factor Productivity ◽  
Banking Industry ◽  
Commercial Banking ◽  
Productivity Change ◽  
Factor Productivity

scholarly journals Industry Efficiency and Total Factor Productivity Growth under Resources and Environmental Constraint in China

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Feng Tao ◽  
Ling Li ◽  
X. H. Xia
Keyword(s):  
Energy Consumption ◽  
Total Factor Productivity ◽  
Environmental Efficiency ◽  
Pollutant Emissions ◽  
Productivity Index ◽  
Productivity Change ◽  
Factor Productivity ◽  
Energy And Environment ◽  
Capital Labor Ratio ◽  
Investment Capital

The growth of China's industry has been seriously depending on energy and environment. This paper attempts to apply the directional distance function and the Luenberger productivity index to measure the environmental efficiency, environmental total factor productivity, and its components at the level of subindustry in China over the period from 1999 to 2009 while considering energy consumption and emission of pollutants. This paper also empirically examines the determinants of efficiency and productivity change. The major findings are as follows. Firstly, the main sources of environmental inefficiency of China's industry are the inefficiency of gross industrial output value, the excessive energy consumption, and pollutant emissions. Secondly, the highest growth rate of environmental total factor productivity among the three industrial categories is manufacturing, followed by mining, and production and supply of electricity, gas, and water. Thirdly, foreign direct investment, capital-labor ratio, ownership structure, energy consumption structure, and environmental regulation have varying degrees of effects on the environmental efficiency and environmental total factor productivity.

scholarly journals KOMPARASI EFISIENSI & PRODUKTIVITAS PERUSAHAAN ASURANSI JIWA KONVENSIONAL DAN SYARIAH DI INDONESIA PADA TAHUN 2014 – 2017, DENGAN PENDEKATAN DEA & INDEKS MALMQUIST

2020 ◽  
Vol 6 (9) ◽  
pp. 1877
Author(s):  
Oky Suryoaji ◽  
Eko Fajar Cahyono
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Malmquist Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Constant Return

Tujuan penelitian ini adalah untuk mengetahui tingkat efisiensi dan produktivitas perusahaan asuransi jiwa antara konvensional dan syariah (baik Unit Usaha Syariah maupun Full Fledge) periode 2014 – 2017. Penelitian ini menggunakan pendekatan kuantitatif dengan metode non parametrik DEA (Data Envelopment Analysis) yang dilandaskan dengan asumsi CRS (Constant Return to Scale) dan VRS (Variable Return to Scale) dan Indeks Malmquist asumsi TFPC (Total Factor Productivity Change) dengan diolah menggunakan aplikasi DEAP Versi 2.1. Variabel yang digunakan meliputi Total Aset, Beban, Klaim, Premi/Dana Tabrru’, dan Pendapatan. Subjek yang digunakan dalam penelitian ini sebanyak 29 perusahaan asuransi jiwa syariah yang terdiri 10 perusahaan asuransi jiwa syariah dan 19 perusahaan asuransi jiwa konvensional. Hasil penelitian menunjukkan bahwa rata-rata perusahaan asuransi jiwa konvensional dan syariah belum mencapai efisien (CRS) dan rata-rata TFPC perusahaan asuransi jiwa konvensional sudah mencapai produktivitas sementara syariah belum mencapai produktivitas.Keywords:Asuransi Jiwa Syariah, Efisiensi, Produktivitas, Data Envelopment Analysis (DEA), Constant Return to Scale (CRS), Variable Return to Scale (VRS), Malmquist Index (MI), Total Factor Productivity Change (TFPC)

scholarly journals Productivity Change of Microfinance Institutions in Bosnia and Herzegovina

2019 ◽  
Vol 14 (2) ◽  
pp. 23-33
Author(s):  
Velid Efendić ◽  
Nejra Hadžiahmetović
Keyword(s):  
Total Factor Productivity ◽  
Bosnia And Herzegovina ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Microfinance Institutions ◽  
Factor Productivity ◽  
Strategic Objectives ◽  
Average Decrease ◽  
Recent Financial Crisis

Abstract The main aim of this paper is to investigate the productivity changes of microfinance institutions (MFIs) in Bosnia and Herzegovina (BiH) during and after the recent financial crisis. The study covers the period starting from 2008 until 2015. Using the Malmquist Productivity Index (MPI) over the sample of 10 MFIs and a balanced panel dataset of 80 observations, this study explores technical and technological change as well as total factor productivity (TFP) change. The empirical findings indicate a decline in TFP in most of the analyzed periods with an average decrease of 2.5%. The study reveals an average technological decline in the industry of 1.7%, while technical efficiency change is recorded at the level of -0.8%. Overall, crisis efficiency recovery occurred during the period between 2009 and 2013. However, due to technological inefficiencies, average total factor productivity change remains negative. Hence, policy makers need to enhance the technological progress in order to meet their strategic objectives in BiH MFIs.

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

The Origins of Productivity Change and Economic Growth in China’s Cities between the Years 2001 and 2014

2018 ◽  
Vol 06 (02) ◽  
pp. 1850012
Author(s):  
Jiancui LIU ◽  
Shilin ZHENG
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Statistical Data ◽  
Physical Capital ◽  
Productivity Change ◽  
Factor Productivity ◽  
Transitional Processes ◽  
Second Tier ◽  
Theory Research ◽  
Factor Inputs

Total factor productivity represents not only the core of neo-classical growth theory research, but is also a key component in the understanding of the transitional processes of China from a factor-driven to an innovation-driven economy. In this paper, relying on 2000–2014 year statistical data, drawn from China’s four centrally administered and 283 provincial-level cities, the paper’s authors apply Cobb–Douglas production function methods to the calculation of urban total factor productivity rates of increase, and to changes in differing factor inputs, to show how, during the period of interest, involved changes impacted China’s economic growth. The analysis finds that: (1) between the years 2001 and 2005, changes in total factor productivity represented an important source of economic growth, but that after 2005 China’s economic growth clearly exhibited physical capital-driven features; (2) from 2012 onwards, influenced by resource-based and heavy chemical industries, the decrease in total factor productivity of China’s central region cities was the greatest (among the various areas), revealing an “extensive” aspect, and in 2014 the contribution rates of the region’s cities’ physical capital and total factor productivity were 127.77% and [Formula: see text]36.6%, respectively; (3) examining the cities based on their differing classifications, after 2012, the contribution rates of the fourth-tier cities’ total factor productivities underwent severe declines, while in China’s first- and second-tier cities the contribution rates of their total factor productivities exhibited signs of recovery.

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