scholarly journals The application of data envelopment analysis based Malmquist total factor productivity index: Empirical evidence in Turkish banking sector

2013 ◽  
Vol 60 (2) ◽  
pp. 139-159 ◽  
Author(s):  
Benli Keskin ◽  
Suleyman Degirmen
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Banking Sector ◽  
Group Analysis ◽  
Sustainable Growth ◽  
Policy Implications ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Performance Comparisons

The objective of this study is to measure the total factor productivity and the changes in components of the total factor productivity generated by the banks in Turkish Banking Sector (TBS) during the period of 2004-2009. Based on these measurements, we quantify the production efficiency of the banks. To that end, the total factor productivity is taken as an initial point, and various performance comparisons are made both within the specified three sub-groups and among all deposit banks in TBS. Within the context of performance measurement, we use input and output variables to test technical efficiency index, which represents a combination of change in technical efficiency and in technology, and to test a change in total factor productivity index which comprises a change in pure technical efficiency and scale efficiency. In the calculation of these indexes, Malmquist total factor productivity index method is employed. Computed indexes provide us with the opportunity to make performance comparisons in order to assess which group and bank have comparatively highest performance among the groups and banks included in this study. When we consider the effects of 2007-2008 global crises on Turkish economy, notably on TBS, calculating the performance change ratio for previous periods or estimating the same for the following periods becomes vital in terms of enduringly changing and developing banks. The growing competition in TBS forces banks to attach more importance to productivity factor for sustainable growth purposes. In this regard, Malmquist total factor productivity index gives us the opportunity to quantify the changes in total factor productivity over the years. Accordingly, this study applies group analysis to determine which group is working efficiently. To do this, Malmquist total factor productivity index requires the use of panel data and depicts efficiency changes by years, representing crucial information for us to produce policy implications. In brief, the test results obtained by this study indicate that the foreign banks, thanks to positive changes in their technology, technical efficiency and total factor productivity, are more effective than other private and state banking groups.

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 A Study on the Efficiency of Tourism Poverty Alleviation in Ethnic Regions Based on the Staged DEA Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Jianchun Yang ◽  
Ying Wu ◽  
Jialian Wang ◽  
Chengcheng Wan ◽  
Qian Wu
Keyword(s):  
Ethnic Minority ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Poverty Alleviation ◽  
Malmquist Index ◽  
Great Difficulty ◽  
Local Economy ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Two Stages

Poverty alleviation through tourism is an important way for China to achieve targeted poverty alleviation and win the battle of poverty alleviation. As a region with deep poverty and great difficulty in poverty alleviation, whether tourism development has injected key impetus into ethnic minority areas needs to be tested by both qualitative analysis and quantitative measurement. This paper takes eight ethnic provinces (regions) in China as an example to conduct an empirical study. Based on the Data Envelopment Analysis (DEA)-BCC model and Malmquist index, it evaluates the tourism investment and tourism poverty alleviation efficiency of the ethnic regions in the two stages of tourism poverty alleviation, and analyzes them by classification. The results of the study show: (1) The pure technical efficiency in the first stage is relatively high, but the total factor productivity of each region is declining; (2) The pure technical efficiency in the second stage is also relatively high, but the scale efficiency is low, and the change rate of total factor productivity of the provinces in China has increased significantly; (3) The “double high” type includes Guangxi, Inner Mongolia, and Guizhou, and the “double low” type includes Qinghai, Yunnan, Tibet, Xinjiang, and Ningxia. The results of the study generally show that tourism poverty alleviation has brought about the improvement of the living standards of residents and the development of local economy, but the efficiency of tourism poverty alleviation needs to be improved. On this basis, the article puts forward corresponding improvement measures, in order to further help the ethnic minority areas get rid of poverty in a comprehensive way by promoting the efficient and sustainable development of tourism.

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 Does Low-Carbon City Construction Improve Total Factor Productivity? Evidence from a Quasi-Natural Experiment in China

2021 ◽  
Vol 18 (22) ◽  
pp. 11974
Author(s):  
Hongfeng Zhang ◽  
Lu Huang ◽  
Yan Zhu ◽  
Hongyun Si ◽  
Xu He
Keyword(s):  
Economic Development ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Progress ◽  
Scale Efficiency ◽  
Eastern Region ◽  
Low Carbon ◽  
Factor Productivity ◽  
City Construction ◽  
Low Carbon City

Low-carbon city construction (LCC) is an important strategy for countries desiring to improve environmental quality, realize cleaner production, and achieve sustainable development. Low-carbon cities have attracted widespread attention for their attempts to coordinate the relationship between environmental protection and economic development. Using the panel data from 2006 to 2017 of prefecture-level cities in China, this study applied the difference-in-differences (DID) method to analyze the effects of LCC on the total factor productivity (TFP) of the cities and its possible transmission mechanism. The results show significantly positive effects on TFP, but the effects on each component of TFP are different. Although the LCC has promoted technical progress and scale efficiency, it has inhibited technical efficiency. The accuracy of the results has been confirmed by several robustness tests. Mechanism analysis showed that the pilot policy of low-carbon cities has promoted technical progress and scale efficiency by technological innovation and the upgrading of industrial structure, but resource mismatches among enterprises have been the main reason for reduced technical efficiency. Regional heterogeneity analysis showed that the effects on TFP in the eastern region have been more significant than in the central and western regions. In the eastern region, they have promoted technical progress, while in the central and western regions, they have promoted technical progress and scale efficiency but hindered technical efficiency. This paper presents our findings for the effects of LCC on economic development and provides insightful policy implications for the improvement of technical efficiency in low-carbon cities.

scholarly journals EVALUATION OF REGIONAL DEVELOPMENT WITH BANKING AND FINANCE DATA

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Bilge MEYDAN ◽  
Aydin ULUCAN ◽  
Kazim Baris ATICI
Keyword(s):  
Regional Development ◽  
Total Factor Productivity ◽  
Banking Sector ◽  
Productivity Index ◽  
Factor Productivity ◽  
Output Factor ◽  
Development Index ◽  
Banking And Finance ◽  
Development Levels ◽  
Sector Data

This research aims to measure the change of provincial development levels of Turkey’s 81 provinces through banking sector data. The applied methodology is the Malmquist Total Factor Productivity Index (MTFPI). We perform the analysis based on two models. The main difference between models relies on handling the factor associated with ‘loans’. The first approach sees the loans as an output factor, which is based on the idea that loans indicate investment and therefore development. In the second model, we take the loans as an input factor, which represents the idea that loans indicate debt and therefore they should be minimized. We evaluate the findings with respect to geographical classification and the province development index.

scholarly journals Technical Efficiency and Technical Change in Africa: The Role of Money from the Diasporas

2018 ◽  
Vol 10 (7) ◽  
pp. 177
Author(s):  
Gloria Clarissa O. Dzeha ◽  
Joshua Yindenaba Abor ◽  
Festus Ebo Turkson ◽  
Elikplimi Komla Agbloyor
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Seemingly Unrelated Regression ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Factor Productivity ◽  
Unrelated Regression ◽  
The Relationship

Based on evidence from the literature that the relationship between remittances and total factor productivity (TFP) is inconclusive, we employ the non-parametric Malmquist productivity index - Data Envelope Analysis to decompose total factor productivity (TFP) into technical change and technical efficiency and further investigate the effect of remittances on the technical change and technical efficiency. We employ the Seemingly Unrelated Regression estimation (SUR) technique in a panel of twenty-three African remittance recipient countries across a twenty-three-year period (1990-2013). We show that remittances received by households have a positive and significant impact on technical efficiency but no significant on technical change (innovativeness). We further show that remittances received by skilled labour is significant to technical efficiency but has a lowering effect on technical efficiency.

Measurement and determinants of total factor productivity: evidence from Indian banking industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Biswabhusan Bhuyan ◽  
Subhamitra Patra ◽  
Ranjan Kumar Bhuian
Keyword(s):  
Total Factor Productivity ◽  
Economies Of Scale ◽  
Banking Sector ◽  
Value Added ◽  
Productivity Index ◽  
Annual Data ◽  
Fiscal Deficit ◽  
Factor Productivity ◽  
Content Type ◽  
Frontier Analysis

PurposeThe purpose of this study is to measure the level of total factor productivity of the Indian banking sector and to identify both the bank-specific and macroeconomic determinants of the total factor productivity after the global subprime mortgage crisis.Design/methodology/approachThe research sample consists of 61 commercial banks including 21 public sector banks, 18 private sector banks and 22 foreign banks. The annual data is collected from the website of Reserve Bank of India from 2008 to 2019. The authors employed the non-parametric DEA approach to estimate Malmquist total factor productivity index for each bank as well as across different ownership groups. The panel data estimation technique was used to identify the determinants of total factor productivity.FindingsThe results suggested that an increase in the technological shift raised the bank's productivity above the optimal frontier. Among the bank-specific determinants, the bank size and bank diversifications are significantly declining productivity, whereas credit-deposit ratio and return on asset significantly increasing productivity. Among the macro-specific determinants, inflation, growth rate and fiscal deficit ratio negatively affect productivity, whereas capital formation to the GVA ratio boosts the level of productivity.Research limitations/implicationsThe authors have used intermediate method to select the inputs and outputs as per the suitability to the context. However, the disaggregate level such as state and district level analysis can be done using production and value-added approaches to explore the regional variations of the banking performance. Furthermore, the parametric methods such as stochastic frontier analysis can be used to examine banking performance, which the authors left for the future research.Practical implicationsThis study suggested that banks should increase the economies of scale of their total assets and focus on the interest-earning activity. The banks need to proactively operate the business policy by following the changing path of inflation. The banks need to reduce their rate of fiscal-deficit to the GVA with the purpose to boost their level of productivity.Originality/valueThe study provides an important implication for bankers and policymakers in terms of heightening the banking performance during the period of dynamic economic events.

Evaluation analysis on industrial green total factor productivity and energy transition policy in resource-based region

2021 ◽  
pp. 0958305X2110054
Author(s):  
Yaozu Xue
Keyword(s):  
Environmental Pollution ◽  
Total Factor Productivity ◽  
Pollution Control ◽  
Energy Transition ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Shanxi Province ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Positive Effect

Based on the input-output panel data of industrial sectors of Shanxi Province, which is the only province-wide resource-based region in China, this paper uses the non-parametric DEA model and the Malmquist productivity index to construct the DEA-Malmquist model for evaluation analysis of the green total factor productivity (GTFP) and its decomposition value of the sub-sector, and then through fixed effect panel regression model studies the ways of energy transition of the SDG’s. The results show that the technological progress index has the greatest contribution to the growth of GTFP, while the scale efficiency index has the lowest contribution. And the amount of investment in environmental pollution control has a significant positive relationship with the GTFP of the three major polluting industries in Shanxi. Among them, investment in environmental pollution control has the greatest positive effect on the GTFP of light polluting industries characterized by high technology, high added value and low emissions; investment in environmental pollution control has the largest positive effect on the GTFP of heavy polluting industries with heavy chemical industry and pollution-intensive industries; investment in environmental pollution control has the weakest positive effect on the GTFP of the medium polluting industries that manufacture life service products and some heavy industrial products. Based on these results, the paper puts forward effective policy for the energy transition of resource-based regions.

scholarly journals MALMQUIST INDICES OF PRE- AND POST-DEREGULATION PRODUCTIVITY, EFFICIENCY AND TECHNOLOGICAL CHANGE IN THE SINGAPOREAN BANKING SECTOR

2010 ◽  
Vol 55 (04) ◽  
pp. 599-618 ◽  
Author(s):  
BOON L. LEE ◽  
ANDREW C. WORTHINGTON ◽  
WAI HO LEONG
Keyword(s):  
Technological Change ◽  
Global Economy ◽  
Banking Sector ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Efficiency Improvement ◽  
Factor Productivity ◽  
Malmquist Indices ◽  
Foreign Competitors

By the end of the 1990s, the Singaporean government had recognised the need to open up its banking sector so as to remain competitive in the global economy. The Monetary Authority of Singapore (MAS) thus began deregulation of the banking sector in 1999 to strengthen the competitiveness of local banks relative to their foreign competitors through mergers. This paper employs a nonparametric Malmquist productivity index to provide measure of productivity, technological change and efficiency gains over the period 1995–2005. The findings reveal some total factor productivity growth associated with deregulation and scale efficiency improvement largely from mergers amongst the local banks.

scholarly journals An Empirical Study on the Growth of Agricultural Green Total Factor Productivity in the Huanghuai River Economic Zone by Big Data Computing

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Yanan Zhang ◽  
Jinghong Wei ◽  
Ying Wang ◽  
Sang-Bing Tsai
Keyword(s):  
Economic Development ◽  
Carbon Cycle ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Carbon Sink ◽  
Green Economy ◽  
Productivity Index ◽  
Factor Productivity ◽  
Productivity Level ◽  
Economic Zone

Facing the new form and situation of the Huaihe Economic Zone, it is of great significance to analyze the sources of growth and the intrinsic mechanism of the green total factor productivity of its economic-ecological system, to grasp the spatial and temporal characteristics of green total factor productivity, and to study the influence of each factor on green total factor productivity to achieve sustainable economic development in the Huaihe Economic Zone. Based on the clarification of economic growth theory, green economy theory, carbon cycle theory, and green total factor productivity theory, this paper identifies and discusses the limitation that the existing research literature often ignores the endogenous role of carbon sinks when measuring green total factor productivity. Then, the green total factor productivity of Huaihe Economic Zone based on carbon cycle from 2004 to 2017 is measured using the superefficient nonradial SBM model. Combined with the GML productivity index, it is decomposed into technical progress and technical efficiency and analyzed in comparison with the green total factor productivity without considering ecological purification capacity (carbon sink) from the perspective of time and space. Finally, the spatial Durbin model is used to analyze the effects of seven variables, including the level of economic development, environmental regulation, R&D level, and openness to the outside world, on green total factor productivity in the Huaihe Economic Zone, and to analyze the direct and indirect effects of each variable on green total factor productivity. TFP based on expected output carbon sink and GDP overall outperforms TFP based on expected output GDP only, mainly because the growth of technical efficiency is underestimated when carbon sink is not considered. Technical efficiency and technological progress are equally important for the growth of TFP in an eco-economic perspective. It is of great practical significance for both the comprehensive understanding of the green total factor productivity level and the improvement path of the ecosystem and the coordinated and sustainable development of the Huaihe Economic Zone.

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