scholarly journals Spatial Interaction Spillover Effects between Digital Financial Technology and Urban Ecological Efficiency in China: An Empirical Study Based on Spatial Simultaneous Equations

2021 ◽  
Vol 18 (16) ◽  
pp. 8535
Author(s):  
Yaya Su ◽  
Zhenghui Li ◽  
Cunyi Yang
Keyword(s):  
Economic Growth ◽  
Spatial Interaction ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Simultaneous Equations ◽  
Ecological Efficiency ◽  
Core Component ◽  
Coordinated Development ◽  
Three Stage Least Squares ◽  
Financial Technology

As a core component of the digital economy, digital financial technology has a complex interactive and interdependent relationship with ecological efficiency. From the holistic spatial interaction perspective, this paper uses spatial simultaneous equations and generalized spatial three-stage least squares (GS3SLS) to analyze the spatial interaction spillovers between digital financial technology and urban ecological efficiency based on data from 284 Cities in China from 2008 to 2018. The results show that: (1) Digital financial technology and urban ecological efficiency promote each other, and the latter is relatively dominant. (2) Both digital financial technology and urban ecological efficiency have significant spatial spillover effects. (3) Digital financial technology in surrounding cities has a restraining effect on local ecological efficiency, and the improvement of ecological efficiency in surrounding cities has a siphon effect on local digital financial technology. (4) There is spatial and period heterogeneity in the intensity of the spatial interaction spillover effect between the two. With resources and environment increasingly becoming rigid constraints on economic growth, these findings help identify new drivers of regional ecological efficiency and promote the coordinated development of digital finance and green ecology.

Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

2021 ◽  
pp. 135481662110211
Author(s):  
Honghong Liu ◽  
Ye Xiao ◽  
Bin Wang ◽  
Dianting Wu
Keyword(s):  
Economic Growth ◽  
Spillover Effect ◽  
Tourism Development ◽  
Spillover Effects ◽  
Policy Implications ◽  
Long Term Effects ◽  
Spatial Spillover ◽  
Domestic Tourism ◽  
Inbound Tourism ◽  
Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

scholarly journals Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index

2021 ◽  
Vol 13 (14) ◽  
pp. 8032
Author(s):  
Chengzhuo Wu ◽  
Li Zhuo ◽  
Zhuo Chen ◽  
Haiyan Tao
Keyword(s):  
Influencing Factors ◽  
Information Flow ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Urban Agglomeration ◽  
Coordinated Development ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
Search Index ◽  
Spatial Spillover Effect

Cities in an urban agglomeration closely interact with each other through various flows. Information flow, as one of the important forms of urban interactions, is now increasingly indispensable with the fast development of informatics technology. Thanks to its timely, convenient, and spatially unconstrained transmission ability, information flow has obvious spillover effects, which may strengthen urban interaction and further promote urban coordinated development. Therefore, it is crucial to quantify the spatial spillover effect and influencing factors of information flows, especially at the urban agglomeration scale. However, the academic research on this topic is insufficient. We, therefore, developed a spatial interaction model of information flow (SIM-IF) based on the Baidu Search Index and used it to analyze the spillover effects and influencing factors of information flow in the three major urban agglomerations in China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in the period of 2014–2019. The results showed that the SIM-IF performed well in all three agglomerations. Quantitative analysis indicated that the BTH had the strongest spillover effect of information flow, followed by the YRD and the PRD. It was also found that the hierarchy of cities had the greatest impact on the spillover effects of information flow. This study may provide scientific basis for the information flow construction in urban agglomerations and benefit the coordinated development of cities.

scholarly journals The Spatial Interaction Effect of Environmental Regulation on Urban Innovation Capacity: Empirical Evidence from China

2021 ◽  
Vol 18 (9) ◽  
pp. 4470
Author(s):  
Ruomeng Zhou ◽  
Yunsheng Zhang ◽  
Xincai Gao
Keyword(s):  
Environmental Regulation ◽  
Industrial Development ◽  
Positive Impact ◽  
Spatial Interaction ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Spatial Spillover ◽  
Innovation Capacity ◽  
Spatial Spillover Effects ◽  
The Impact

This paper applies a spatial econometric model to measure the impact of environmental regulation on urban innovation capacity from a spatial interaction perspective by using panel data from 41 cities in the Yangtze River Delta urban agglomeration from 2009 to 2018. The study findings are as follows: first, environmental regulation has a significant positive impact on urban innovation capacity and a significant positive spatial spillover effect; second, innovation capacity has significant positive spatial dependence; third, city informatization level, government expenditures on science and technology, city economic scale, and industrial development level all positively affect the innovation capacity of neighboring cities and all have positive spatial spillover effects on the innovation capacity of neighboring cities; and finally, city expansion reduces the innovation capacity of a city and has negative spatial spillover effects on the innovation capacity of neighboring cities.

scholarly journals Applying the Super-EBM Model and Spatial Durbin Model to Examining Total Factor Ecological Efficiency From a Multi-Dimensional Perspective: Evidence From China

2021 ◽  
Author(s):  
Li Chengyu ◽  
Zhang Yongmei ◽  
Zhang Shiqiang ◽  
Wang Jianmei
Keyword(s):  
Distribution Pattern ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Evaluation Framework ◽  
Ecological Efficiency ◽  
Spatial Durbin Model ◽  
Spatial Spillover ◽  
Distance Model ◽  
Resource Exhaustion ◽  
Hybrid Distance

Abstract Ecological efficiency mainly emphasizes the importance of balancing the relationship between natural resources,energy,ecological environment and economic growth, which has aroused widespread concern in the world.China's rapid economic development has inevitably accompanied by serious resource exhaustion,environmental pollution and ecological deterioration in the past several decades,which has brought huge challenges to China's sustainable development.Therefore, establishing the evaluation framework of total-factor ecological efficiency (TFEE) and identifying its driving force has great significance for improving China's sustainable development capabilities.Firstly, a ecological efficiency evaluation framework is established based on the theory of total factor analysis.Secondly,establishing the Super-efficient hybrid distance model consider undesirable output,and measuring the total-factor ecological efficiency of nationwide,30 provinces and four regions during the period 2003–2017.Finally, the spatial effect of total-factor ecological efficiency and its driving factor are examined by using a Spatial Durbin model. The empirical results show that: (1)The efficiency measurement results show that the TFEE of China overall and regional showed different degrees of decline during the study period.There are significant differences among 30 provinces and four regions.Beijing,Tianjin,Shanghai are efficient,and the other provinces has not been effective.The TFEE of four region's are not achieve effective,and shows the distribution pattern of the eastern > northeast > central > western .(2)Moran’s I index show that the TFEE in nationwide has a positive spatial autocorrelation,and showing a strong spatial agglomeration.However,the spatial distribution pattern of TFEE in China was unstable and easy to change;Moran scatter plot indicates that china's provincial TFEE has not only spatial dependence characteristics, but also spatial differences in spatial correlation.(3)Most factors are bound up with TFEE in various degree, in which, TP,JJ and HC play a positive in TFEE ,and IS,CITY, and EI play a negative role in TFEE. Furthermore,ER show U type of relationship with TFEE.GDP and FDI cannot have a significant impact on TFEE at this stage.(4)The spatial Durbin model results show that TFEE has significant spatial spillover effect, and the improvement of the TFEE of province will increase the this TFEE of neighboring provinces.And spatial spillover effects of TP,IS,JJ,CITY,and HC are confirmed can significant impact the improvement of TFEE in neighboring provinces.

Fiscal Decentralisation, Provincial Economic Growth and Spillover Effects: A Spatial Panel Data Analysis

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 743-760
Author(s):  
Qasim Raza ◽  
Hafsa Hina
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Spatial Dependence ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Provincial Government ◽  
Data Set ◽  
Spatial Panel ◽  
Fiscal Decentralisation ◽  
Spatial Panel Data

This study examines the spatial dependence, direct and indirect effects of fiscal decentralisation on the provincial economic growth of Pakistan. Due to spatial dependence, spatial econometric technique is applied on the augmented growth of Mankiw, et al. (1992) by incorporating the fiscal decentralisation variable in the theoretical framework. The empirical analysis is based on the spatial panel data set, which is used from 1990 to 2011 of provinces. Model is selected on basis of specific to general and general to specific approach, and decided two-way fixed effects Spatial Durbin model (SDM) is appropriate for our data. We have estimated the SDM by maximum likelihood (bias corrected and random effect) estimation technique, otherwise, if we applied OLS and ignore the spillover effect which makes our estimated parameters biased and inconsistent. Results show that revenue decentralisation has positive, while expenditure decentralisation has negative effect to provincial economic growth. Spillover effects are found to be significant in case of revenue decentralisation and insignificant in case of expenditure. Negative and insignificant spillover effect of expenditure decentralisation is due to weak institutions, lack of intra governmental competition, and absence of political vision which may increase the level of corruption and less accountability. On the basis of econometric analysis, it may be suggested that federal government should transfer the resources to provinces as determined in the 18th amendment, and it is the responsibility of provincial government to train their officials in the area of professional ethics, technical and administrative skills by different programmes. JEL Classification: C31, C33, H3, H50 Keywords: Fiscal Decentralisation, Spatial Econometrics, Revenue, Expenditure

scholarly journals Study of the Spillover Effect on Sport to Chinese Regional Economic Development

2019 ◽  
Vol 10 (5) ◽  
pp. 487
Author(s):  
Huijun Jiang ◽  
Myeong Cheol Choi ◽  
Xinke Leng
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Data Model ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Regional Economic Growth ◽  
Panel Data Model ◽  
Regional Economic ◽  
Incentive Effect

Sports development can lead to the emergence of external economies, which forms part of the spillover effects on regional economic growth under certain conditions. This study uses a sample of 31 provinces in China from 2008–2012 to construct a panel data model to examine the role of sports development in the regional economic growth in the C-D function. The results indicate that sports development indeed brings a good incentive effect to the economy in all areas, which suggests a spillover effect of Chinese sports development that stimulates regional economic growth, but this spillover effect reflects a greater difference between different regions. Overall, Hebei, Jiangxi, Henan, Hubei, Hunan, and Sichuan have the highest coefficient of sports investment on economy, but Jilin is relatively weak.

scholarly journals Regression Models for Spatial Data: An Example from Gross Domestic Regional Bruto in Province Central Java

2017 ◽  
Vol 18 (2) ◽  
pp. 213
Author(s):  
Abdul Karim ◽  
Akhmad Faturohman ◽  
Suhartono Suhartono ◽  
Dedy Dwi Prastyo ◽  
Budi Manfaat
Keyword(s):  
Economic Growth ◽  
Spatial Data ◽  
Spatial Modeling ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Error Model ◽  
Transportation Infrastructure ◽  
Spatial Error ◽  
Central Java ◽  
Transportation Infrastructures

The important role of a region's transportation infrastructure strongly affects the economic growth of the region and tends to affect the surrounding areas. The effect is called spillover effect. The aim of the research was to recognize the direct effect and spillover effect (indirect) of transportation infrastructure on the economic growth in Central Java. To identify the spillover effects, it is necessary to recognize the different characteristics of each region which have the implications on the various transportation infrastructures at each region in Central Java. Therefore, the spatial modeling was conducted. In this study, the spatial modeling employed was Spatial Durbin Error Model (SDEM). The SDEM is another form of Spatial Error Model (SEM). It does not allow for lag effects of endogenous variables, but it allows for spatial error and spatial lag on exogenous variables in which it simplifies the interpretations on direct effects and spillover effect. According to SDEM estimates, the transportation infrastructures at the districts/municipalities in Central Java had no significant effect on the outputs at each region where the infrastructures were located and their neighboring districts/cities

scholarly journals Impact of Logistics Development on Economic Growth: An Empirical Research from Guangdong Province in China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiaofei Li ◽  
Fen Chen
Keyword(s):  
Economic Growth ◽  
Spillover Effect ◽  
Guangdong Province ◽  
Spillover Effects ◽  
Entropy Method ◽  
Logistics Industry ◽  
Spatial Spillover ◽  
Comprehensive Development ◽  
Local Economic Growth ◽  
The Impact

This paper evaluates the impact of the development of the logistics industry on economic growth based on panel data of 21 cities in Guangdong Province in China from 2007 to 2019. Using the overall entropy method, the comprehensive development index of the logistics industry is constructed to capture the performance of the logistics industry. On this basis, by using Moran’s index, we measure the spatial agglomeration effect of the logistics industry. Furthermore, direct and spatial spillover effects are also obtained. The estimation results of the spatial Durbin model (SDM) reveal that the elasticity coefficient of the effect of the comprehensive development level of the logistics industry on economic growth is 0.2590, which is significant at the 1% level. In addition, the coefficient of the direct effect of the logistics industry on local economic growth is 0.4074, and the coefficient of the spatial spillover effect on the economic growth of the surrounding areas is 0.3596, which are both significant at the 1% level. These results indicate that the development of the logistics industry can not only improve local economic growth but also promote the economic growth of the surrounding regions.

Variations in economic growth across states in Malaysia: an exploratory analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yusniliyana Yusof ◽  
Kaliappa Kalirajan
Keyword(s):  
Economic Growth ◽  
Socioeconomic Development ◽  
Secondary Data ◽  
State Level ◽  
Bootstrap Sampling ◽  
Content Type ◽  
Estimation Techniques ◽  
Development Index ◽  
Three Stage Least Squares ◽  
Development Gap

PurposeThe study contributes to the aim of regional development policy in reducing regional disparities, by examining the spatial balance in socioeconomic development across the states of Malaysia based on composite development index (CDI). Besides, the study has attempted to understand the issues in the development gaps across Malaysian states by evaluating the factors that explain the variation in economic growthDesign/methodology/approachThis study uses three-stage least squares (3SLS) and bootstrap sampling and estimation techniques to examine the factors that explain the variations in the growth of development across the states in Malaysia. The analysis involves 13 states in Malaysia (Johor, Melaka, Negeri Sembilan, Pulau Pinang, Perak, Perlis, Selangor, Kedah, Kelantan, Pahang, Terengganu, Sabah and Sarawak) from 2005 to 2015.FindingsThe pattern in the spatial socioeconomic imbalance demonstrates a decreasing trend. However, the development index reveals that the performance of less developed states remained behind that of the developed states. The significant factors in explaining the variation in growth across the Malaysian states are relating to agriculture, manufacturing, human capital, population growth, Chinese ethnicity, institutional factors and natural resources.Research limitations/implicationsThe authors focused on Malaysian states over the period between 2005 and 2015. The authors encountered some limitations in obtaining relevant data such as international factors and technological change that might also explain the variation in economic growth as the data on these variables are not reported at the state level. Moreover, the data on GSDP by sector was only available from the year 2005. Second, the study is based on secondary data. Future studies might examine the factors that contribute to the development gap across Malaysian states through interviews or questionnaires and compare the findings with the existing results. Despite its limitations, this study contributes to the existing literature that emphasizes on spatial balance of socioeconomic in a developing country, focusing on Malaysian states.Practical implicationsThese findings provide guidance for policymakers by understanding key potential areas to reduce the disparity in economic growth across Malaysian states by understanding their impact on the growth.Originality/valueThis study employs different method of 3SLS and bootstrap sampling and estimation techniques in examining the factors that explain the variations in the growth of development across the states in Malaysia.

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