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

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

2018 ◽  
Vol 10 (8) ◽  
pp. 2800 ◽  
Author(s):  
Rui Jin ◽  
Jianya Gong ◽  
Min Deng ◽  
Yiliang Wan ◽  
Xuexi Yang

Understanding regional economic agglomeration patterns is critical for sustainable economic development, urban planning and proper utilization of regional resources. Taking Guangdong Province of China as the study area, this paper introduces a comprehensive research framework for analyzing regional economic agglomeration patterns and understanding their spatiotemporal characteristics. First, convergence and autocorrelation methods are applied to understand the economic spatial patterns. Then, the intercity spatial interaction model (ISIM) is proposed to measure the strength of interplay among cities, and social network analysis (SNA) based on the ISIM is utilized, which is designed to reveal the network characteristics of economic agglomerations. Finally, we perform a spatial panel data analysis to comprehensively interpret the influences of regional economic agglomerations. The results indicate that from 2001 to 2016, the economy in Guangdong showed a double-core/peripheral pattern of convergence, with strengthened intercity interactions. The strength and external spillover effects of Guangzhou and Shenzhen enhanced, while Foshan and Dongguan had relatively strong absorptive abilities. Moreover, expanding regional communication and cooperation is key to enhancing vigorous economic agglomerations and regional network ties in Guangdong by spatial panel data analysis. Our results show that this is a suitable method of reflecting regional economic agglomeration process and its spatiotemporal pattern.


Author(s):  
Junwei Ma ◽  
Jianhua Wang ◽  
Philip Szmedra

Environmental productivity comprehensively measures economic growth and environmental quality. Environmental innovation is considered to be the key to solving economic and environmental problems. Therefore, discussing the impact of environmental innovation on environmental productivity will reveal its economic and environmental effects. This paper measures environmental productivity by value added per unit of pollution emissions (four types of emissions are used) using panel data of 10 Chinese urban agglomerations from 2003 to 2016 to analyze the spatial correlation of environmental productivity, and constructs a spatial panel data model to empirically test the impact of environmental innovation on environmental productivity. It was found that environmental productivity measured by value added per unit of carbon dioxide emissions (gross domestic product (GDP)/CO2) had a significant positive spatial spillover effect, and measured by value added per unit of sulfur dioxide emissions (GDP/SO2), smoke (dust) emissions (GDP/SDE), and industrial sewage emissions (GDP/IS) had a significant negative spatial spillover effect. Environmental innovation has a significant negative inhibitory effect on environmental productivity measured by GDP/SDE and GDP/IS, but no obvious effect measured by GDP/CO2 and GDP/SO2. Control variables such as economic development level, industrial agglomeration, foreign direct investment, and endowment structure factor also show significant differences in environmental productivity measured by value added per unit of pollution emissions. In addition, there are significant differences in direct effects of explanatory variables on environmental productivity of local regions and indirect effects on neighboring regions. These differences are also related to the types of pollution emissions. Therefore, policymakers should set different policies for different types of pollution and encourage different types of environmental innovation, so as to achieve reduced pollution emissions and improved environmental productivity.


2018 ◽  
Vol 63 (02) ◽  
pp. 447-464 ◽  
Author(s):  
LING XIONG ◽  
SHAOZHOU QI

Using the panel data of 30 provinces in China between 1997 and 2011, we employed the extended STIRPAT model and spatial panel econometrics methods to investigate the relationship between financial development and carbon emissions and test the influence of financial development as well as other factors on provincial carbon emissions per capita among Chinese provinces. The estimation results show that: (i) spatial spillover effects play a role in provincial carbon emissions in China; and (ii) the sum of technical effect and structure effect of financial development surpass its’ sum of direct effect and wealth effect in China, which suggests that financial development reduces carbon emissions per capita. China should pay more attention to the integration of green finance policy and environmental regulation, and establish appropriate mechanisms to strengthen inter-provincial interaction and coordinated development.


2015 ◽  
Vol 56 (1) ◽  
pp. 1-31 ◽  
Author(s):  
Guilherme Mendes Resende ◽  
Alexandre Xavier Ywata de Carvalho ◽  
Patrícia Alessandra Morita Sakowski ◽  
Túlio Antonio Cravo

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