scholarly journals Positive effect of village debt on land transfer: Evidence from county-level panel data of village finance in Zhejiang Province

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255072
Author(s):  
Chunhui Ye ◽  
Suwen Zheng ◽  
Edward Gu
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Market Mechanism ◽  
Zhejiang Province ◽  
County Level ◽  
Rural Land ◽  
Multivariate Statistical ◽  
Agricultural Enterprises ◽  
Land Transfer ◽  
The Impact

The purpose of this paper is to examine the impact of village debt on land transfer. Based on the county-level panel data of village finance and land transfer in 90 counties and 4 economic development zones of Zhejiang Province from 2013 to 2017, this paper carried out multivariate statistical analysis and set a fixed effect model to control the endogenous influence of region and time. It found that village debt as a pressure may encourage village committees to promote rural land transfer, and then especially promote land flows into agricultural firms; as a mechanism, the burden of village organization’s transactional debt (historical debt and administrative debt) is the key to promoting the rural land flow to agricultural enterprises; through further analysis, it is found that the village committee seeks "win-win" opportunities by intervening in land circulation to ensure the rights and interests of farmers and to obtain village benefits from them. This paper finds that this kind of push effect has the threshold, the debt will play a significant role in promoting when the debt rate is between 4.65% and 7.9%. In addition, there is regional heterogeneity in the contribution of debt, which exists only in plain, non-coastal and high-dependence areas. The results of this paper verify the view that "community mechanism and market mechanism are embedded and supported each other in acquaintance society" in the theory of community governance. In practice, it provides a realistic basis for policy makers to implement the policy of encouraging farmland circulation and properly deal with the problem of village debt.

scholarly journals The Impact of Dividend Policy on Stock Price Volatility in Pakistan

2019 ◽  
Vol IV (I) ◽  
pp. 506-515
Author(s):  
Ziaullah Shah ◽  
Shehzad Khan ◽  
Muhammad Faizan Malik
Keyword(s):  
Panel Data ◽  
Stock Price ◽  
Dividend Policy ◽  
Price Volatility ◽  
Fixed Effect Model ◽  
Share Prices ◽  
Dividend Payments ◽  
Effect Model ◽  
Dividend Irrelevance ◽  
The Impact

The objective of this study is to inspect dividend policy influence on volatility of share prices. For investigation seven Non-financial segment/sectors have been selected. A sample of 137 firms who paid four dividend payments listed at PSX is analysed for the period of 2007-2017.Proxy for policy of dividend are earning per share, Payout ratio, dividend yield, while assets growth and firm size are taken as control variables. OLS regression model has been initially applied on panel data. The outcomes of fixed effect model are focused. Overall outcomes of the study confirmed that prices of stock is significantly influenced by policy of dividend and reject dividend irrelevance theory.

scholarly journals Research on the Impact of Environmental Regulation and Technology Innovation on the Quality of Economic Growth

2021 ◽  
Author(s):  
Qingyang Wu
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Environmental Regulation ◽  
Technological Innovation ◽  
Environmental Regulations ◽  
Threshold Model ◽  
Fixed Effect Model ◽  
Paper Test ◽  
The Impact

Abstract：This paper uses the balanced panel data from 29 provinces (autonomous regions and municipalities) in China for a total of 17 years from 2000 to 2016 as a research sample, and establishes an empirical model to examine the impact of environmental regulations and technological innovation on the quality of economic growth. Then this paper test technological innovation as a threshold variable, in which play a regulatory role. Taking the provincial balanced panel data as a research sample, a fixed effect model, a system GMM model, and a panel threshold model were established for empirical testing and the robustness test. Based on the empirical results, this article draws the following conclusions: from a national perspective, environmental regulations and technological innovation can significantly promote the quality of economic growth; from a regional perspective, there are regional differences in impact effects. Under the constraints of environmental regulations, the promotion effect of technological innovation on the quality of economic growth will be reduced; the impact of environmental regulation on the quality of economic growth will have a "threshold effect", and environmental regulation can significantly promote the quality of economic growth only after crossing the threshold and the threshold of technological innovation.

scholarly journals Research on Spillover Effect of Urbanization on Rural Land Transfer Based on the SDM Model of Intelligent Computing

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Fucheng Yang ◽  
Guoyong Liu
Keyword(s):  
Panel Data ◽  
Spatial Heterogeneity ◽  
Spatial Correlation ◽  
Spillover Effect ◽  
Rural Land ◽  
Spatial Agglomeration ◽  
Intelligent Computing ◽  
Land Transfer ◽  
Southern Xinjiang

In order to explore the spillover effect of urbanization on rural land transfer, this paper uses the panel data of various regions and cities in Xinjiang from 2008 to 2018. Moran's I method is used to test and analyze the spatial correlation between urbanization and farmland transfer. Intelligent computing SDM is used to analyze the spillover effect of urbanization on farmland transfer. The results show that there is spatial correlation between farmland transfers in Xinjiang. There is spatial heterogeneity in the spatial agglomeration of urbanization and farmland transfer in northern and southern Xinjiang. The content of this paper can provide some reference and ideas for follow-up research.

scholarly journals The Impact of Target Price Policy on Cotton Cultivation: Analysis of County-Level Panel Data from China

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 988
Author(s):  
Wei Wang ◽  
Chongmei Zhang ◽  
Jiahao Song ◽  
Dingde Xu
Keyword(s):  
Panel Data ◽  
Price Policy ◽  
Policy Implications ◽  
County Level ◽  
Cotton Production ◽  
Target Price ◽  
Subsidy Policy ◽  
Price Subsidy ◽  
The Future ◽  
The Impact

China is an important cotton production area in the world. Since 2014, China has implemented a cotton target price subsidy policy in Xinjiang for 7 years. As the policy implementation time has lengthened, some deep-seated problems have started to emerge. Therefore, it is necessary to summarize and evaluate to clarify the future policy direction of the cotton target price subsidy policy. Based on county-level panel data of Xinjiang and Shandong from 2011 to 2018, this paper used the Propensity Score Matching—Difference in Difference method to analyze the impact of the implementation of cotton target price subsidy policy on cotton planting in Xinjiang. The results showed that: (1) after the implementation of the cotton target price subsidy policy, cotton production was stimulated by the transition, cotton producers’ enthusiasm for cotton production was higher, cotton production increased rapidly, and the yield per unit area decreased, indicating that there was a 'bubble' in cotton cultivation. (2) The target price subsidy policy mainly achieves the expansion of the cotton planting scale by reducing the area of competitive crops. In view of the above research conclusions, this paper further explains its policy implications. It is proposed that the future cotton target price level should be formulated to fully consider the comparative benefits between different crops, to restrict the subjects that enjoy subsidies and the upper limit of subsidies, and strictly implement the concept of green development; it is necessary to guide cotton production out of ecologically vulnerable areas.

scholarly journals Determinants of Financial Performance of Nepalese Commercial Banks: Evidence from Panel Data Approach

2020 ◽  
Vol 32 (2) ◽  
pp. 45-59
Author(s):  
Purna Man Shrestha
Keyword(s):  
Panel Data ◽  
Financial Performance ◽  
Commercial Banks ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Lagrangian Multiplier ◽  
Effect Model ◽  
Specific Factors ◽  
The Impact ◽  
Bank Specific Factors

The impact of bank specific factors on the financial performance of Nepalese commercial banks is analyzed in this paper. The financial performance is measured by using return on assets (ROA). Similarly, managerial efficiency (ME), liquidity (LIQ), credit risk (CR), assets quality (AQ) and operational efficiency (OE) is used as proxy of bank specific factors. This study used panel data of 17 commercial banks for the period of 2010/11 to 2017/18. Breusch and Pagan Lagrangian multiplier test showed that Pooled Regression model is not appropriate and Hausman test concluded that Fixed Effect model is appropriate rather than Random Effect model. Using the Fixed Effect model; this study concludes that bank specific factors have significant impact on financial performance of Nepalese commercial banks. Finally, this study reveals that ME, AQ and OE have significant positive impact, and CR has negative impact on the financial performance of Nepalese commercial banks.  

scholarly journals Impact of Medical Professionals on Carbapenem-Resistant Pseudomonas Aeruginosa: Moderation Effect of Workload Based on the Panel Data in China

2020 ◽  
Author(s):  
Meng Han ◽  
Xinping Zhang
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Panel Data ◽  
Registered Nurses ◽  
Fixed Effect Model ◽  
Hierarchical Regression ◽  
Medical Professionals ◽  
Moderation Effect ◽  
Carbapenem Resistant ◽  
The Impact ◽  
The Relationship

Abstract Background: Antimicrobial resistance (AMR) causes serious increase in morbidity, mortality and costs, especially carbapenem-resistant Pseudomonas aeruginosa (CRPA). Medical professionals play an important role in tackling AMR. Available studies overlooked the impact of workload on medical professionals in the relationship between medical professionals and AMR. This study explored the relationship between medical professionals and CRPA rate and the moderation effect of medical professionals’ workload in this relationship. Methods: Based on provincial-level panel data in China, hierarchical regression analysis was used to explore moderation effect of workload on medical professionals and CRPA rate. Fixed-effect model was applied to estimate the moderation effect models. Medical professionals were measured by the numbers of physicians, registered nurses, pharmacists, clinical microbiologists per 1000 populations. Workload was measured by the number of daily visits of physicians. Results: The numbers of physicians, registered nurses, pharmacists and clinical technicians were significant negative with CRPA rate (Coef. = -0.889, -0.775,-1.176, -0.822; P= 0.003, 0.003, 0.011, 0.007, respectively). Workload had significant positive moderation effect between physicians, registered nurses, pharmacists, clinical technicians and CRPA rate (Coef.= 1.270, 1.400, 2.210, 1.634; P=0.004, 0.001, 0.035, 0.003, respectively). Conclusions: Increasing medical professionals may help curb CRPA. Measures to reduce medical professionals’ workload should be implemented to improve CRPA performance further.

scholarly journals Impact of Medical Professionals on Carbapenem-Resistant Pseudomonas Aeruginosa: Moderation Effect of Workload Based on the Panel Data in China

2019 ◽  
Author(s):  
Meng Han ◽  
Xinping Zhang
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Panel Data ◽  
Registered Nurses ◽  
Fixed Effect Model ◽  
Hierarchical Regression ◽  
Medical Professionals ◽  
Moderation Effect ◽  
Carbapenem Resistant ◽  
The Impact ◽  
The Relationship

Abstract Background: Antimicrobial resistance (AMR) causes serious increase in morbidity, mortality and costs, especially carbapenem-resistant Pseudomonas aeruginosa (CRPA). Medical professionals play an important role in tackling AMR. Available studies overlooked the impact of workload on medical professionals in the relationship between medical professionals and AMR. This study explored the relationship between medical professionals and CRPA rate and the moderation effect of medical professionals’ workload in this relationship from a macro perspective. Methods: Based on panel data in China, hierarchical regression analysis was used to explore moderation effect of workload on medical professionals and CRPA rate. Fixed-effect model was applied to estimate the moderation effect models. Medical professionals were measured by the numbers of physicians, registered nurses, pharmacists, clinical microbiologists per 1000 populations. Workload was measured by the number of daily visits of physicians. Results: The numbers of physicians, registered nurses, pharmacists and clinical technicians were significant negative with CRPA rate (Coef. = -0.889, -0.775,-1.176, -0.822; P= 0.003, 0.003, 0.011, 0.007, respectively). Workload had significant positive moderation effect between physicians, registered nurses, pharmacists, clinical technicians and CRPA rate (Coef.= 1.270, 1.400, 2.210, 1.634; P=0.004, 0.001, 0.035, 0.003, respectively). Conclusions: Increasing medical professionals may help curb CRPA. Measures to reduce medical professionals’ workload should be implemented to improve CRPA performance further.

scholarly journals Disasters and Domestic Tourist Arrivals in Indonesia in 2013-2017

2021 ◽  
Vol 8 (10) ◽  
pp. 465-477
Author(s):  
Alla Asmara ◽  
Annisa Hafizhah Uzdah
Keyword(s):  
Panel Data ◽  
Descriptive Analysis ◽  
Fixed Effect Model ◽  
Jel Classification ◽  
Population Number ◽  
Classification Code ◽  
Tourism Sector ◽  
Increasing Trend ◽  
The Impact ◽  
Domestic Tourist

The tourism sector is the leading sector in Indonesia's economic development in the future. One of the potential demand for Indonesia tourism sector comes from domestic tourist arrivals who show an increasing trend each year. On the other hand, the number of disasters in Indonesia in the last 10 years also showed an increasing trend. Starting from this phenomenon, the purpose of this study is to analyze the impact of disasters on domestic tourist arrivals in Indonesia. The analytical method used is descriptive analysis and panel data with Fixed Effect Model (FEM) approach. In this study, natural disasters were proxied through frequency of disasters and the number of fatalities. The results of the analysis indicate that frequency of disasters and the number of fatalities have a negative effect on the domestic tourist arrivals. However, only the number of fatalities has a statistically significant effect. Economic variables which also have a significant effect on domestic tourist arrivals are GRDP/capita, CPI, population, number of hotel rooms and accessibility. All of these variables have a positive effect on domestic tourist arrivals. Keywords: Disasters, panel data, tourism, domestic tourist JEL Classification code: Z38; O20; R58.

A Research on Rural Land Transfer System

2011 ◽  
Vol 211-212 ◽  
pp. 1216-1220
Author(s):  
Yu Xian Zheng ◽  
Shi Zhu Liu ◽  
Liu Juan Xu
Keyword(s):  
Logistic Regression ◽  
Zhejiang Province ◽  
Model Construction ◽  
Transfer System ◽  
Rural Land ◽  
Land Transfer ◽  
New Period ◽  
The New Period

In the new period of development of agriculture in China, as an important production element, rural land transfer has been a trend in the market. We first investigate some villagers in Qingyuan County of Zhejiang Province and use the collected data for model construction and fitting by logistic regression. Then we analyze the factors that affect farmers’ demand of joining specialized cooperatives and give some suggestions.

scholarly journals The Impact of Air Quality on Population Migration

2020 ◽  
Vol 15 (2) ◽  
pp. 23-32
Author(s):  
Ke Wang ◽  
◽  
Yiwei Wang ◽  
Chun-Ping Chang
Keyword(s):  
Air Quality ◽  
Panel Data ◽  
Negative Impact ◽  
Fixed Effect Model ◽  
Education Level ◽  
Population Migration ◽  
Control Factors ◽  
Effect Model ◽  
Per Capita ◽  
The Impact

Based on annual panel data of OECD countries from 1995 to 2014, this paper analyzes the impact of air quality (including per capita CO2, PM2.5, and SO emissions) on the immigrant population through a panel fixed-effect model, while employing control factors such as GDP, unemployment rate, and education level. Overall, we provide evidence that air quality is a key determinant of immigration in the selected countries, and in particular the host country’s emissions have a negative impact on immigrants. Greater emissions imply fewer immigrants, while fewer emissions denote more immigrants. Our findings provide countries with a way to more accurately estimate migrant inflow and offer an idea for OECD members on how to attract immigrants via an improvement in environmental quality.

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