scholarly journals Technical efficiency and total factor productivity of rural banks in Ghana

2017 ◽  
Vol 5 (1) ◽  
pp. 1366088 ◽  
Author(s):  
Eric Fosu Oteng-Abayie ◽  
Goodness Aye

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.


2021 ◽  
Vol 12 ◽  
Author(s):  
Jianchun Yang ◽  
Ying Wu ◽  
Jialian Wang ◽  
Chengcheng Wan ◽  
Qian Wu

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.


2010 ◽  
Vol 56 (No. 3) ◽  
pp. 108-115
Author(s):  
P. Bielik ◽  
D. Hupková ◽  
M. Vadovič ◽  
V. Benda

Analysis of the productivity and efficiency development could be used to asses the trend and factors influencing this process. The main goal of this paper is estimation of the Total Factor Productivity (TFP) development of agricultural farms in the Trnava region in the period 2002–2006. Results of this analysis could be used to detect the trend in the TFP development. The results of the analysis confirmed there is no evident trend in the average TFP indicators. This could be explained by the variation of technical efficiency change and technological changes during this period. These two factors represent the components of the TFP indicator. According to the present development of the TFP indicator, it is not possible to unambiguously forecast the future trend.


2020 ◽  
Vol 8 (6) ◽  
pp. 294-304
Author(s):  
Suparno Suparno

This research analysis of tourism competitiveness is based on the very high disparity problem in the condition of the tourism sector in East Java Province. With a sample of 10 districts / cities and using investment data, tourist visits, population, government spending and tourism sector PDRB, it is produced that investment and tourist visits have a positive but not significant effect on tourism sector PDRB because due to the probability > 0.05. While the population and government expenditure have a positive and significant effect on the tourism sector PDRB due to the probability < 0.05. Fixed effect models that are formed are:PSP = 39485712 + 0.018 INV + 0.389 TOURIST + 22.304 POP + 0.065 GEX + e               To measure tourism competitiveness, it is used with technical efficiency and total factor productivity where it is produced: Sidoarjo Regency, Malang City and Surabaya City are regencies / cities that have the highest level of technical efficiency with a value of 100% technical efficiency. Whereas with the calculation of total factor productivity in Gresik Regency (21,350), Jember Regency (16,543) and Kediri Regency (15,650) are regencies / cities that have the highest productivity. Based on the calculation of technical efficiency and total factor productivity results are obtainedL1) High efficiency and productive, Jember Regency; (2) High efficiency and less productive, Sidoarjo Regency, Malang City and Surabaya City; (3) Low and productive efficiency, Kediri Regency, Lamongan Regency and Gresik Regency; and (4) Low efficiency and less productive, Banyuwangi Regency, Pasuruan Regency and Pasuruan City.               The spillover effect occurs in Pasuruan City, where the economy of Pasuruan City is affected by investments from Sidoarjo Regency and Surabaya City as indicated by the significance level of 0.051 Surabaya City investment and 0.048 for Sidoarjo Regency investment which means smaller and equal to 0.05.               The calculation of convergence shows that the average convergence of regencies / cities in East Java to leader regions over 15 years and 5 months means that districts / cities need an average of 15 years and 5 months to match the conditions of tourism in the city of Surabaya.


2011 ◽  
Vol 3 (5) ◽  
pp. 296-310
Author(s):  
Indrajit Bairagya

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.


Author(s):  
Hongfeng Zhang ◽  
Lu Huang ◽  
Yan Zhu ◽  
Hongyun Si ◽  
Xu He

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.


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