ANALYSIS OF COMPETITIVENESS OF THE TOURISM SECTOR EAST JAVA PROVINCE (A TECHNICAL EFFICIENCY & CONVERGENCE APPROACH)

2020 ◽  
Vol 8 (6) ◽  
pp. 294-304
Author(s):  
Suparno Suparno
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
High Efficiency ◽  
Government Expenditure ◽  
Spillover Effect ◽  
Productive Efficiency ◽  
Factor Productivity ◽  
Significance Level ◽  
Tourism Sector ◽  
Low Efficiency

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.

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.

Does foreign direct investment spillover total factor productivity growth? A study of Indian drugs and pharmaceutical industry

2017 ◽  
Vol 24 (7) ◽  
pp. 1937-1955 ◽  
Author(s):  
Nitin Arora ◽  
Preeti Lohani
Keyword(s):  
Foreign Direct Investment ◽  
Pharmaceutical Industry ◽  
Total Factor Productivity ◽  
Direct Investment ◽  
Spillover Effect ◽  
Foreign Firms ◽  
Factor Productivity ◽  
Content Type ◽  
Domestic Firms ◽  
Tfp Growth

Purpose Foreign firms have certain advantages which may spillover to domestic firms in the form of improvements in total factor productivity (TFP) growth. The purpose of this paper is to empirically observe the presence of TFP spillovers of foreign direct investment (FDI) to domestic firms through analyzing source of TFP growth in Indian drugs and pharmaceutical industry. Design/methodology/approach This paper examines the sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry over the period 1999 to 2014. The data of 304 firms has been used for estimation of the growth rates of TFP and its sources under stochastic frontier analyses based Malmquist productivity index framework. For frontier estimation, the Wang and Ho (2010) model has been executed using translog form of production function. Findings The results show that there exists significant TFP spillover effect from the presence of foreign equity in drugs and pharmaceutical industry of India. The results also show that the major source of TFP fluctuations in the said industry is managerial efficiency that has been significantly affected by FDI spillover variables. In sum, the phenomenon of significant Intra-industry (horizontal) efficiency led productivity spillovers of FDI found valid in case of Indian drugs and pharmaceutical industry. Research limitations/implications The number of foreign firms is very less to imitate the significant impact of foreign investment on TFP growth of Indian pharmaceutical industry at aggregated level; and the Wang and Ho (2010) model is failing to capture direct impact of FDI on technological change under Malmquist framework. Practical implications Since, there exists dominance of domestic firms in Indian drugs and pharmaceutical industry, the planners should follow the policy which not only attract FDI but also benefit domestic firms; for example, developing modern infrastructure and institution which will further help domestic firms to absorb spillovers provided by the Multinational Corporations and also accelerate the growth and development of the economy. Social implications In no case, the foreign firms should dominate the market share otherwise the efficiency spillover effect will be negative and the domestic firms will be destroyed under the self-centric approach of foreign firms protected by the recent patent laws. Originality/value The study is a unique attempt to discuss the production structure and sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry with such a wide coverage of 304 firms over a period of 16 years under Wang and Ho (2010) model’s framework. The existing studies on TFP spillovers are using either a small sample size of firms or based upon traditional techniques of measuring spillover effects.

scholarly journals Construction of Spatiotemporal Difference Image of the Impact of Financial Structure on China’s Total Factor Productivity

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yong Yu
Keyword(s):  
Total Factor Productivity ◽  
Evaluation Method ◽  
Financial Structure ◽  
Model Verification ◽  
Factor Productivity ◽  
Analysis Model ◽  
Dea Model ◽  
Dea Analysis ◽  
Low Efficiency ◽  
The Impact

My country’s current research on the influencing factors of total factor productivity has problems such as single evaluation method, low efficiency, and poor overall level in terms of evaluation methods and evaluation efficiency. Based on this, this study divides the financial structure into three traditional sections, banking, securities, and insurance, and uses the DEA model to study the temporal and spatial differences of the financial structure’s influence on the total factor productivity of the four major political and economic regions of China’s eastern, western, central, and northeastern China. First, establish a DEA model based on data mining algorithms, combine financial data comparisons over the years, to achieve a quantitative analysis of the financial structure’s impact on China’s total factor productivity, calculate financial efficiency, and then combine the DEA analysis data model with the grey correlation method. Analyze its internal influence rules, and design experiments for model verification analysis. The results show that the DEA analysis model can realize 8 iterations of data on the impact of financial structure on China’s total factor productivity, and its evaluation accuracy can reach more than 96.2%.

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 Agricultural basic industry subjects productivity development examination in the region Trnava (SR) by adopting the Malmquist indexes

2010 ◽  
Vol 56 (No. 3) ◽  
pp. 108-115
Author(s):  
P. Bielik ◽  
D. Hupková ◽  
M. Vadovič ◽  
V. Benda
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Future Trend ◽  
Factor Productivity ◽  
Technological Changes ◽  
Efficiency Change ◽  
Basic Industry ◽  
Factors Influencing ◽  
Two Factors ◽  
Malmquist Indexes

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.

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