scholarly journals MEASURING THE TECHNICAL EFFICIENCY AND THE RATE OF CHANGE IN THE TFP FOR FARMS RAIN-FED WHEAT IN THE REGION IN LIGHT OF DIFFERING SIZE AREA

2016 ◽  
Vol 47 (6) ◽  
Author(s):  
Rijib & Jbara
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Malmquist Index ◽  
Rate Of Change ◽  
Scale Efficiency ◽  
Total Production ◽  
Factor Productivity ◽  
Compound Fertilizer ◽  
The Subject ◽  
The Impact

This study deals with the subject of measuring the impact of variation of wheat planted area categories in the region rain-fed on the technical efficiency and the rate of change in( TFPch),The basic preliminary data was obtained from field resources by relying on a stratified random sample of wheat farmers in Sulaimaniyah region including 225 farms  production during 2013-2014 season , It has been measurement of technical and Scale  efficiency in light of change and stability of the total revenue according to the production function variables using (Area ,the amount of seeds ,compound fertilizer, urea fertilizer , pesticides , machinery work , manual work ) it turns out that the average technical efficiency for the first, second ,third ,forth ,and fifth class of the cultivated areas reached around( 82% , 76% ,70%, 53%,and 72 %) respectively recording a total average of 72% for the farms included in the studied sample . The numbers of farms achieving the optimum technical efficiency were (25, 3, 11, 21 and 15) for the five categories respectively.As far as the change in the total factor productivity (TFPch)in the farms subject to the study (using the Malmquist index of productivity) the result has indicated that the change in total production stood at an average of 1.39 , and the farms in which a positive change in the total factor productivity (TFPch) was 92 farms representing 41% of the total number of the farms included in the study , a negative (TFPch) was recorded in 83 farms representing 37% of the total number of the farms included in the study .

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 Measuring the Impact of Extreme Weather Phenomena on Total Factor Productivity of General Cropping Farms in East Anglia

2018 ◽  
Vol 3 (1) ◽  
pp. 1-22
Author(s):  
Yiorgos Gadanakis ◽  
Francisco Jose Areal
Keyword(s):  
Climate Change ◽  
Total Factor Productivity ◽  
Malmquist Index ◽  
Efficiency Score ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Time Data ◽  
East Anglia ◽  
Business Survey ◽  
The Impact

One of the main challenges of climate change on agriculture in UK is how to adapt to the potential changes to the availability of water. Changes in rainfall distribution may potentially lead to an increase in drought frequency, magnitude and duration. In this research a Data Envelopment Analysis (DEA) and a Malmquist Index (MI) are combined with a double bootstrap methodology to measure changes in Total Factor Productivity of general cropping farms in East Anglia. More specifically, the DEA technique was used to measure the year by year efficiency score for the farms in the sample and the MI and its components used to derive information on productivity over time. Data for the input – output models was obtained from the Farm Business Survey. Climate change is taken into consideration by using data for water cost as a proxy indicator of water consumption per farm. Results reveal changes in total, technical and scale efficiency and provide information on how the 2011 drought affect the TFP of the farms in the sample.

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.

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 Cost Efficiency and Total Factor Productivity: An Empirical Analysis of Pakistan’s Insurance Sector

2016 ◽  
Vol 21 (1) ◽  
pp. 123-150
Author(s):  
Uzma Noreen ◽  
Shabbir Ahmad
Keyword(s):  
Total Factor Productivity ◽  
Malmquist Index ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Innovative Technology ◽  
Average Score ◽  
Factor Productivity ◽  
Tobit Regression ◽  
Insurance Sector ◽  
The Impact

This study uses data envelopment analysis and the Malmquist index to examine the impact of financial sector reforms on the efficiency and productivity of Pakistan’s insurance sector over the period 2000–09. Our results indicate that the sector is cost-inefficient, with an average score of 58 percent – an outcome of the inappropriate use of inputs. The Malmquist productivity index performs better, indicating an improvement in total factor productivity of about 3 percent on average. The second-stage Tobit regression analysis shows that large firms are relatively inefficient from an allocative perspective as they are unable to equate the marginal product of inputs with their factor prices. Furthermore, the results demonstrate that private firms are more efficient than public firms in the nonlife insurance sector. The empirical findings suggest that a more competitive environment, diversified products and innovative technology could improve the productivity of insurance firms in Pakistan.

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 Influence of the Evolution of Marine Industry Structure on the Green Total Factor Productivity of Marine Economy

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1108
Author(s):  
Xinyi Wei ◽  
Qiuguang Hu ◽  
Weiteng Shen ◽  
Jintao Ma
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Government Intervention ◽  
Malmquist Index ◽  
Marine Ecology ◽  
Advanced Technology ◽  
Factor Productivity ◽  
Marine Economy ◽  
Low Efficiency ◽  
The Impact

The 14th five-year plan emphasizes the importance of marine ecology and environmental protection, and the green concept is incorporated into the high-quality development system of the marine economy. This research used the data of 11 coastal provinces and cities in China from 2006 to 2016, based on the super-efficiency slack-based measure model and global Malmquist index model. The objective was to calculate the green total factor productivity (GTFP) of the marine economy, to study the impact of the evolution of the marine industrial structure on marine economic GTFP. The study found the following: (1) in general, the upgrade of marine industrial structure promoted the growth of marine economic GTFP and presented an inverted “U” trend of initially promoting and then suppressing. Spatially, only the advancement and rationalization of industrial structure in the Yellow and Bohai Sea regions inhibited the growth of marine economic GTFP. In terms of time, the advanced marine industrial structure promoted the growth of GTFP from 2006 to 2010, whereas that of industrial structure inhibited the growth of GTFP from 2011 to 2016. (2) The GTFP of the marine economy showed an increasing trend, but the conversion rate of production technology is low. Falling into the “efficiency trap” of highly advanced technology input and low-efficiency technology output should be avoided. (3) Affected by the mismatch of regional resources or industrial structure, government intervention showed an “opposite” mechanism in areas with different marine economic strengths. Government intervention in areas with higher marine economic strength was conducive to GTFP growth, whereas government intervention in areas with weaker marine economic strength would hinder GTFP growth.

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.

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