Spillover Effects of Taxes on Government Debt: Spatial Panel Approach

2014 ◽  
Author(s):  
Katarzyna Kopczewska ◽  
Janusz Adam Kudda ◽  
Konrad Walczyk ◽  
Agata Agnieszka Kocia ◽  
Robert Kruszewski
Keyword(s):  
Government Debt ◽  
Spillover Effects ◽  
Spatial Panel

Spillover effects of taxes on government debt: a spatial panel approach

2016 ◽  
Vol 37 (3) ◽  
pp. 274-293 ◽  
Author(s):  
Katarzyna Kopczewska ◽  
Janusz Kudła ◽  
Konrad Walczyk ◽  
Robert Kruszewski ◽  
Agata Kocia
Keyword(s):  
Government Debt ◽  
Spillover Effects ◽  
Spatial Panel

scholarly journals The Effect of Manufacturing Agglomeration on Haze Pollution in China

2018 ◽  
Vol 15 (11) ◽  
pp. 2490 ◽  
Author(s):  
Jun Liu ◽  
Yuhui Zhao ◽  
Zhonghua Cheng ◽  
Huiming Zhang
Keyword(s):  
Industrial Structure ◽  
Spillover Effects ◽  
Eastern Region ◽  
Spatial Panel ◽  
Panel Model ◽  
Specific Analysis ◽  
Haze Pollution ◽  
Regional Haze ◽  
Spatial Panel Model ◽  
Development Levels

Based on panel data on 285 Chinese cities from 2003 to 2012, we use a dynamic spatial panel model to empirically analyze the effect of manufacturing agglomeration on haze pollution. The results show that when economic development levels, population, technological levels, industrial structure, transportation, foreign direct investment, and greening levels are stable, manufacturing agglomeration significantly aggravates haze pollution. However, region-specific analysis reveals that the effects of manufacturing agglomeration on inter-regional haze pollution depends on the region: the effect of manufacturing agglomeration on haze pollution is the largest in the Western region, followed by the Central region, and is the least in the Eastern region. Based on the above conclusions, we put forward several specific suggestions, such as giving full play to the technology and knowledge spillover effects of manufacturing agglomeration, guiding manufacturing agglomerations in a scientific and rational way, accelerating the transformation and upgrading of manufacturing industries in agglomeration regions.

scholarly journals A Framework for Spatiotemporal Analysis of Regional Economic Agglomeration Patterns

2018 ◽  
Vol 10 (8) ◽  
pp. 2800 ◽  
Author(s):  
Rui Jin ◽  
Jianya Gong ◽  
Min Deng ◽  
Yiliang Wan ◽  
Xuexi Yang
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Interaction Model ◽  
Spillover Effects ◽  
Spatiotemporal Pattern ◽  
Regional Economic ◽  
Spatial Panel ◽  
Economic Agglomeration ◽  
Spatial Panel Data

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.

scholarly journals ECO-INNOVATION PATHS: CONVERGENCE OR DIVERGENCE?

2020 ◽  
Vol 26 (6) ◽  
pp. 1213-1236 ◽  
Author(s):  
Agnieszka Karman ◽  
Arkadiusz Kijek ◽  
Tomasz Kijek
Keyword(s):  
Spillover Effects ◽  
Growth Patterns ◽  
Sustainable Growth ◽  
Spatial Panel ◽  
Panel Models ◽  
Environmental Objectives ◽  
The Absolute ◽  
Positive Spillovers ◽  
Spatial Panel Models

Eco-innovations comprise new or modified processes, techniques, practices, systems and products allowing environmental harms to be avoided or reduced. They are employed in order for specific social and environmental objectives to be achieved, hence their environmental, social, and institutional significance relating to the achievement of long-term sustainable growth patterns. As a consequence, eco-innovation has great amount of focus from many countries. Adding to the current literature which focuses mainly on the drivers and effects of eco-innovation in the context of developed and developing countries, this paper tries to find an answer to the question about the absolute β-convergence of eco-innovation. We also consider the spillover effects in the analyses. Our sample consists of 38 countries and relates to the years 2012−2017. We apply the spatial panel models to verify the research hypotheses. The results confirm that there is the absolute β-convergence in the sample countries. Moreover, we find evidence of positive spillovers of eco-innovation.

scholarly journals ON PRICE CO-MOVEMENT AND VOLATILITY SPILLOVER EFFECTS IN CHINA’S HOUSING MARKETS

2017 ◽  
Vol 21 (3) ◽  
pp. 240-255 ◽  
Author(s):  
Yingliang WENG ◽  
Pu GONG
Keyword(s):  
Housing Prices ◽  
Housing Price ◽  
Housing Markets ◽  
Spillover Effects ◽  
Volatility Spillover ◽  
Policy Makers ◽  
Chinese Cities ◽  
Spatial Panel ◽  
Volatility Spillovers ◽  
Spatial Panel Data

The soaring property prices in many Chinese cities have recently attracted increasing attention. This study uses the data on housing price indices from January 2005 to December 2014 in 10 large Chinese cities to analyze volatility spillover effects and to identify the determinants of price co-movement across the China’s regional housing markets. This research proposes a novel dynamic spatial panel data model that accounts for multivariate asymmetrical generalized autoregressive conditional heteroskedasticity components in disturbances to address these issues empirically. Results reveal that housing prices in cities are significantly influenced by population, income, mortgage rates, policy factors, and the national macroeconomic situation. The analysis further indicates that the housing returns of regions in China that are in close geographic and economic proximities exhibit strong co-movement and volatility spillovers. Evidence of significantly positive leverage effects in regional housing markets is also determined. This study’s findings have significant implications for academic researchers, financial experts, and policy makers.

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 A spatial econometric study on effects of fiscal and financial supports for agriculture in China

2013 ◽  
Vol 59 (No. 7) ◽  
pp. 315-332 ◽  
Author(s):  
G. Yuandong ◽  
W. Tao ◽  
Y. Wen ◽  
W. Xiaohua
Keyword(s):  
Economic Development ◽  
Rural Economy ◽  
Spillover Effects ◽  
Financial Policies ◽  
Spatial Econometric ◽  
Spatial Panel ◽  
Rural Economic Development ◽  
National Economic ◽  
Effective Assessment ◽  
Reform And Opening Up

Since the reform and opening-up, the disparity between Chinese rural economy and the overall national economic development has already become the key constraint for further development of the national economy. In order to increase the farmers’ income and to promote rural economic development, the efforts of China’s budgetary and financial policies to support agriculture have been strengthened year by year. However, it lacks an accurate and effective assessment to evaluate the effects of China’s fiscal and financial policies supports for agriculture. This paper proposes to estimate and measure the effects of China’s fiscal and financial supports for agriculture utilizing the Chinese provincial panel data on the basis of the latest spatial panel econometric method. The results show that since China intensified the fiscal and financial support in 2004, the direct effects of fiscal and financial supports for agriculture have improved, but the spatial spillover effects have turned from positive to negative.  

Sign in / Sign up

Export Citation Format

Share Document