A research on the construction material export and energy consumptions using the gravity model

This paper applies a gravity model to estimate the relationships between energy consumptions and many kinds of construction material export over the period 1992-2009 in China. The empirical result shows that energy consumptions have a significant and positive influence on the construction material export of China.

Estimating the gravity model without gravity using panel data

This article examines the effects of zero trade on the estimation of the gravity model using both simulated and real data with a panel structure, which is different from the more conventional cross-sectional structure. We begin by showing that the usual log-linear estimation method can result in highly deceptive inference when some observations are zero. As an alternative approach, we suggest using the poisson fixed effects estimator. This approach eliminates the problems of zero trade, controls for heterogeneity across countries, and is shown to perform well in small samples.

The home-market effect and bilateral trade patterns: a reexamination of the evidence

This paper finds that the evidence for the home market effect (HME) found by Hanson and Xiang (AER, 2004) is sensitive to the way the dependent and the independent variables are constructed. Second, we also find that the HME evidence goes away when we estimate their difference-in-difference gravity model on a truncated sample of positive trade flows. With Eaton–Tamura–Tobit, Heckman, and Helpman–Melitz–Rubinstein estimation of the gravity equation using Hanson and Xiang's data, we are unable to find any evidence for the HME. Finally, the HME evidence is also absent for a sample of Canadian provinces' exports to U.S. states. All of our results, taken together, do not reject the existence of the HME in general but rather suggest that the HME results found by Hanson and Xiang may not be robust.

Mapping Co2 emission from commuting in regional Australia : greater Geelong case study

Commuting to work is one of the most important and regular routines of urban transportation. From a geographic perspective, the length of people's commute is influenced, to some degree, by the spatial separation of their home and workplace and the transport infrastructure. The rise of car ownership in Australia has been accompanied by a considerable decrease of public transport use. Increased personal mobility has fuelled the trend of decentralised housing development, mostly without a clear planning for local employment, or alternative means of transportation. As a result, the urban patterns of regional Australia is formed by a complex network of a multitude of small towns, scattered in relatively large areas, which are totally dependent and polarized by few medium and large cities. Such hierarchical and dispersed geographical structure implies significant carbon dioxide emissions from transportation. Transport sector accounts for 14% of Australia's net greenhouse gas emissions, and without further policy action, they are projected to continue to increase. The aim of this paper is to demonstrate the importance of incorporating urban climate understanding and knowledge into urban planning processes in order to develop cities that are more sustainable. A GIS-based gravity model is employed to examine the travel patterns related to hierarchical and geographical urban region networks, and the derived total carbon emissions, using the Greater Geelong region as a case study. The new challenges presented by climate change bring with them opportunities. In order to fully reach the very challenging targets of carbon reduction in Australia an integrated and strategic vision for urban and regional planning is necessary.