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Transportation, Economic Growth and Spillover
Effects: The Conclusion Based on the Spatial Econometric Model
Angang Hu, Shenglong Liu,
Front. Econ. China. 2010, 5 (2): 169-186.
https://doi.org/10.1007/s11459-010-0009-0
This paper tests the external spillover effects of the transportation on China’s economic growth from the theoretical and the empirical perspectives. Based on a logarithm production model, this study first proves the existence of the positive externality in the transportation. After that, the authors collect the data of the 28 provinces in China from 1985 to 2006, and use a relatively advanced spatial econometric method to test the positive externality. After constructing a spatial econometric model, the authors use the Maximum Likelihood (ML) method to estimate this model. According to the theoretical model and the empirical results, this article reaches the following conclusion: (1) The positive externalities in the transportation do exist; (2) From 1985 to 2006, the transportation contributed 24.8 billion yuan to China’s GDP every year: in this 24.8 billion yuan, 19.6 billion comes from the direct contribution and the rest 5.2 billion comes from the external spillover effects; (3) The summation of the direct contribution and the external spillover effects to the economic growth is on average 13.8% every year.
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Do Environmental Regulations Influence the Competitiveness
of Pollution-Intensive Products?
Yang Lu ,
Front. Econ. China. 2010, 5 (2): 276-298.
https://doi.org/10.1007/s11459-010-0014-3
According to “Pollution Haven Effect”, in order to circumvent stringent environment standards, polluting industries in developed countries will be chosen to locate into developing countries; another way is that developed countries increase imports of pollution-intensive products instead of producing by their own, both of which can contribute to the changes of comparative advantages in the past 30 years. Since 1990s, many scholars have paid special attention on whether environmental regulations affect the trade patterns or not, but the conclusions are ambiguous. This paper, based on the Heckscher-Ohlin-Vanek (HOV) model and using 95 and 42 countries sample data in year of 2005, is an empirical analysis which shows that: (1) according to the estimated results based on the “environmental governance” index calculated by CIESIN, environmental regulations do not change the comparative advantages of five types of pollutionintensive goods; (2) On the other hand, when the per capita income is considered as an endogenous indicator of environmental regulation, environmental regulation will significantly promote the comparative advantages in chemical products, iron and steel products and paper products, though environmental regulations do not take any influence on non-metallic minerals products and non-ferrous metals products. I think that appropriate level of environmental regulation can promote a comparative advantage in pollution-intensive goods.
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Microeconomic Analysis on the Growth of Trade
Volume in China: 1978–2007
Fuxiang Wu , Zhibiao Liu ,
Front. Econ. China. 2010, 5 (2): 299-324.
https://doi.org/10.1007/s11459-010-0015-2
The gravity equation is usually employed by researchers in the field of international trade to explain the growth of a country’s imports and exports volume, especially the manufactured goods. But in China, variables in the model, such as exchange rate, tariff, transportation cost, and spatial distance etc., are not sufficient to explain the riddle of China’s growth in trade volume. In fact, this growth in China’s trade volume is owing to the disintegration of production in the process of economic globalization, to the multinational corporations’ (MNC) vertical outsourcing of their manufacturing processes and procedures, and to the timely readjustment of Chinese enterprises on their strategies of participating in the international intra-product specialization. In this paper we establish an equilibrium model of intra-product specialization dominated by MNCs, and do some empirical tests on the growth in trade volume in China by using the variables including technological conditions of trade, similarity of economies, policy conditions of trade, disintegration of production and level of per capita capital equipment. The empirical results support our basic judgments.
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