Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions

With growing regional economic integration,transportation systems have become critical to regional development and economic vitality but vulnerable to disasters.However,the regional economic ripple effect of a disaster is difficult to quantify accurately,especially considering the cumulated influence of traffic disruptions.This study explored integrating transportation system analysis with economic modeling to capture the regional economic ripple effect.A state-of-the-art spatial computable general equilibrium model is leveraged to simulate the operation of the economic system,and the marginal rate of transport cost is introduced to reflect traffic network damage post-disaster.The model is applied to the 50-year return period flood in2020 in Hubei Province,China.The results show the following.First,when traffic disruption costs are considered,the total output loss of non-affected areas is 1.81 times than before,and non-negligible losses reach relatively remote zones of the country,such as the Northwest Comprehensive Economic Zone(36%of total ripple effects).Second,traffic disruptions have a significant hindering effect on regional trade activities,especially in the regional intermediate input—about three times more than before.The industries most sensitive to traffic disruptions were transportation,storage,and postal service(5 times),and processing and assembly manufacturing(4.4 times).Third,the longer the distance,the stronger traffic disruptions'impact on interregional intermediate inputs.Thus,increasing investment in transportation infrastructure significantly contributes to mitigating disaster ripple effects and accelerating the process of industrial recovery in affected areas.

Housing Markets in China and Policy Implications:Comovement or Ripple Effect

The overheated housing market has recently become a top priority of the Chinese authorities and whether the ripple effect exists is key to understanding this housing issue. The present paper uses a cointegration estimation technique for six first-tier Chinese cities during the 2003-2013 period to show that the comovements among housing prices in China are fully reflected in a long-run equilibrium. Using the Toda- Yamamoto causality test, the ripple effect is found to be characterized by a lead -lag relationship. More importantly, it is found that Beo＇ing is the main source of housing price appreciation in China, and should be targeted as the regulatory object to efficiently resolve the troubles in this increasingly high housing-price era.

Assessment on IT-based Technical Innovation of the Subordinate Company of the Corporation

Information technology （IT） is one of the most important means by which companies can win an advantaged position in drastically competed market. It has a positive effect on the advancement of the corporation＇s technical innovation. The application of IT can promote the communication among subordinates of a corporation or group, reduce explicit boundaries of the subordinates, and boost the ripple effect of technical innovation of the subordinates. Not only does any subordinate company within a corporation need to assess both technical and economic benefits brought to the corporation itself by technical innovation, but also it should thoroughly analyze how the ripple effect of technical innovation among subordinate companies plays a significant role in the boosting value of the corporation as a whole. In this paper, a scientific approach to assessing technical innovation of a subordinate company is proposed through analyzing the ripple effect of IT-based technical innovation on subordinate companies.

External Dependent Economy and Structural Real Estate Bubbles in China

This study explores the relationship between external dependent economic structure, surplus monetary liquidity and real estate bubbles in China. Employing monthly data from 28 Chinese provinces over the period 2004-2005, we test whether real estate bubbles are caused by structural surplus monetary liquidity, ccontrolling other possible factors. Our empirical findings show that the growth of private savings in the banking sector, as an index of surplus monetary liquidity, ferments real estate bubbles regardless of the different development level across the 28 provinces.