Drivers of growth spillovers

随着我国城市化的快速发展，区域城市之间的联系逐渐加强，不同的扩张模式对城市间经济增长溢出效应会产生不同的影响。基于Capello模型，计算了京津冀城市群地区13个城市扩张带来的经济增长溢出效应，通过比较扇状扩张城市和轴向扩张城市得到和给出的城市增长溢出效应，研究了不同扩张类型城市溢出效应的差异，以及京津冀地区经济增长溢出效应的空间分布特征。结果表明，京津冀城市群地区城市间经济增长溢出效应明显，北京和天津给出的溢出效应远高于其他城市，扇状扩张城市比轴向扩张城市更有利于城市之间的增长效益溢出。京津冀地区已经形成了以北京、天津、廊坊和唐山为中心的核心区，石家庄、保定为核心的次级核心区，位于城市群边缘的城市与核心城市联系较弱，在未来的城市群发展中，可通过政策和规划优化城市形态，使城市空间形态更有利于城市经济发展。

This paper collects the data of 20 cities' regional gross domestic product (GDP) in Guangdong from 1979 to 2013 as basic to measure the spatial correlation of regional economic growth between cities by establishing the VAR models and depicts the characteristics of spatial correlation of regional economic growth in Guangdong through the Analytic Network Process.The results show that: (1) There exist 160 spatial correlation relationships between cities and the spatial correlation is stability and multiple.After modularization, 20 cities can be divided into four modules--the bidirectional spillover module, net spillover module, main beneficial module and net beneficial module.The spillover network structure of economic growth has obvious flattening feature.(2) Guangzhou and Shenzhen are the engines of the spatial spillover of economic growth in Guangdong.Shanwei and Shaoguan are the main sources of the growth energy.(3) The Pearl River Delta influences the spatial spillover of regional economic growth in peripheral areas prominently.Within the Pearl River Delta, Dongguan is the main beneficiary in this spillover effect.And Zhaoqing belongs to the net beneficial module, so fails to play a role of transferring the growth energy to other cities. (4) The differences of industrial structure between cities will have a negative effect on spatial correlation.And the differences in the degree of openness between cities will promote the spillover effect of regional economic growth significantly.

In this paper, we examine the dynamic interdependence via growth spillovers between financial cycle represented by real bank credit growth and business cycle as real GDP growth using dynamic spillover index of Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012). Using quarterly data on five SAARC (the South Asian Association for Regional Cooperation) countries over the period 1975Q4-2013Q4, the study reports following empirical regularities: First, there is a limited interdependence between business and financial cycles within SAARC nations. The pattern of dependence is almost homogeneous. Second, the results of across SAARC indicate that the magnitude of dynamic relationship is not as high as studies have reported in the case of other economic interests groups. Third, to credit-growth spillover, India appears to be the primary driver of economic and financial integrations followed by Bangladesh and Pakistan. Fourth, the spillover analysis between SAARC countries and China reveals that the directional interdependence is relatively higher than the SAARC alone. Among macroeconomic indicators, we find that government debt to GDP, inflation and interest rate are the primary determinants of credit growth spillover. Among financial development indicators, the number of mobile subscribers and number of bank branches as financial inclusion variables appears as significant determinants of credit growth spillover than the portfolio equity assets and remittances.

This paper examines real and financial linkages between Saudi Arabia and other GCC countries.Growth spillovers from Saudi Arabia to Bahrain are found to be sizeable and statistically significant, but those to other GCC countries are not found to be significant.Equity market movements in Saudi Arabia are found to have significant implications for other GCC countries, while there is no evidence of co-movements in bonds markets.These findings suggest some degree of interdependence among GCC countries.

This paper develops an extended Solow model by considering the time‐variant spillover effect of interregional economies. Instead of using fixed spatial distances among regions, the regions' temporal‐spatial distances are measured by constructing a database of train types and calculating the fastest region‐to‐region routes. We collect provincial economic data and railroads data over the period 2003–2012 in China to establish a dynamic temporal‐spatial panel model. The estimation results indicate significant temporal‐spatial externalities. Compared with classical spatial models, the temporal‐spatial model not only has a much better goodness‐of‐fit but also has consistent total effects, direct effects and indirect effects.

Bangladesh is an important member of the Bay of Bengal and the Andaman Sea (BoBAS) rim countries. The partners of growth in this region include traditional partners like eth USA, the UK and some newly emerging partners such as the European Union (EU), Germany, India and China. This article examines the pattern of growth dependence of Bangladesh vis-à-vis its 11 major trade, remittance, foreign aid and FDI partner countries by using vector autoregressive process (VAR) and annual data ranging from 1972 till 2015. Out of 11 partners selected in this study only three of them named the USA, India and Japan have significant growth spillover effect on the economy of Bangladesh. Most of the newly added countries in the list of partnership with Bangladesh are yet to offer any significant growth spillover effect. Only four and a half decade of exploration in economic interaction is not enough to yield sustained relationship be it trade, aid, remittance, foreign aid or FDI. A robustness check by using high frequency monthly data keeps the result intact. In all the three tests, we find that only Japan has two-way growth relationship with Bangladesh, which is trade and concessional loan-driven channel. Variance decomposition analysis identifies the USA, India (a member of BoBAS) and Japan as the prime driver of our growth counting around 32 per cent of the contribution whereas remaining 68 per cent originates from Bangladesh’s own soil.

Not my problem: Growth spillovers from uncoordinated land use policy

In this study, we investigate the different spillover levels of economic policy uncertainty (EPU) on the oil, gold, and stock markets in China. EPU has the highest levels of the growth and volatility spillover on the gold market, and EPU transmits the lowest levels of growth and volatility spillovers to the oil market. EPU receives the highest level of return spillover from the oil market and the lowest from the gold market. However, EPU receives a higher level of the volatility spillover from the gold and stock markets. Regarding growth spillover, EPU is the net spillover receiver from the oil market and the net spillover transmitter to the gold market. Regarding volatility spillover, EPU is a main spillover receiver from all three markets. All net spillovers from EPU to the oil, gold, and stock markets are time‐varying. The recent financial crisis exerts significant effects on the net spillovers of EPU on the three markets.

The purpose of this study is to analyse the simultaneous spatial relationship between economic growth and e-commerce as well as the spillover effect between the two variables in East Java at the beginning of the Covid-19 pandemic in 2020. To answer the research objectives, spatial simultaneous modeling is used with the Spatial Autoregressive Generalized Spatial Three Model. Stage Least Square (SAR-GS3SLS) using rook contiguity. Based on the results of the SAR-GS3SLS, it can be concluded that at the beginning of the Covid-19 pandemic in 2020 in East Java, economic growth and e-commerce were simultaneously spatially interconnected. Variables that affect East Java's economic growth are e-commerce activities, the number of villages that have Base Transceiver Stations (BTS) and the spatial lag of economic growth (ρ1) while the open unemployment rate (TPT) and the Gini ratio have no significant effect on growth. economy. Variables that affect e-commerce are economic growth, internet banking users, percentage of population who have cellphones, number of millennials, number of villages that have ATMs and spatial lag of e-commerce (ρ2) while the number of villages with 4G/LTE signals has no effect on e-commerce. commerce. Regencies/cities that provide the highest spillover of economic growth and e-commerce in East Java are Malang, Mojokerto and Madiun Regencies. The three districts were able to provide a positive net spillover.

This paper introduces “spatial effects” and “dynamic effects” to investigate the influences of economic growth and energy transition on cross‐country CO2 emissions movements within the European Union (EU). We apply the fixed‐effects dynamic spatial Durbin error model to empirically gauge the magnitude of the spatial impacts and dynamic impacts for a sample of 26 EU countries throughout 1990–2015. By analyzing the empirical results, we conclude that: (1) Compared with dynamic spatial Durbin error model, the traditional dynamic panel model over‐estimates the parameters because traditional regression methods only capture the direct impacts, and neglect the indirect impacts. (2) A significant positive spatial spillover of CO2 emissions from neighboring countries to the local country is recognized, justifying the use of our spatial model. (3) Economic growth has positive impacts on CO2 emissions, while the spatial effects of economic growth exert negative impacts. Moreover, the total effects of economic growth are positive in both short‐term and long‐term. (4) Although the spatial effects of renewable energy are not significant, renewable energy has negative influences on CO2 emissions. (5) The impacts and spatial effects of natural gas are positive; therefore, its total effects are positive in both short‐run and long‐run. Based on our finding, we provide several policy recommendations, such as the emphasize of cooperation with CO2 reduction policies, the promotion of green economy and renewable energy, and the substitution of natural gas in the future.

As urbanization has occurred without the attendant growth and development spillovers in underdeveloped nations including Ethiopia, the phenomenon brought undesirable social and economic consequences. This article investigates the relationship between urbanization and urban household income and housing problem. Structural equation modeling was used to run mediation analysis. Correlation and regression analyses were also carried out to measure the direction and magnitude of the effect of the independent variable on the dependent. Regression analysis results indicate the existence of a significant direct effect of urbanization on limitations in income generating capacity of citizens. This article recommends taking policy measures to include development agendas of small and medium towns into regional plans as they absorb the influx to large cities and can help migrants experience the challenging complex urban life step by step. In addition, a policy intervention in the area of land tenure system and real estate development is required before the housing problems gets worsened.

Growth and Learning Spillovers from International Markets: Empirical Evidence from Greek Firms

ABSTRACTFew studies empirically estimate the effects of metropolitan growth on nonmetropolitan communities at a national scale. This paper estimates the growth effects of 276 MSAs on population in 1,988 nonmetropolitan communities in the United States from 2000 to 2007. We estimate the distance for growth spillovers from MSAs to nonmetropolitan communities and test the assumption that a single MSA influences growth. We compare three methods of weighting cities’ influence: nearest city only, inverse‐distance, and relative commuting flow to multiple cities. We find the inverse‐distance approach provides slightly more reliable and theoretically supportable results than the traditional nearest city approach.

The Pan Pearl River Delta (PPRD) Regional Co‐operation Framework Agreement was signed in 2004. It aims to bring prosperity through partnership among nine Chinese Mainland provinces and China's two special administrative regions. In this paper, we use a dynamic panel data model to examine the economic growth of the PPRD economies from 1985 to 2009. Our analysis confirms the existence of regional growth spillover effects in the PPRD area. Our results also show that economic growth spillover effects of non‐PPRD regions on the PPRD regions are greater than those among the PPRD members themselves. These findings imply that economic integration between Chinese provinces has generated considerable spillover effects on regional growth. However, the anticipated benefits of the implementation of the PPRD agreement have not been realized thus far. Therefore, greater effort should be made to promote further economic integration among these members so that their local economies can benefit from the positive spillover effects.

Market Integration, Politics and Culture: The Spatial Reach of Markets in Hyper-Growth China