Antidumping Petition: To File or Not To File

Given the “normal value†of a product as common knowledge in an import-competing market, the profitability of a home firm in filing an antidumping (AD) petition against its foreign rival is shown to depend on the marginal cost differential between the home and foreign firms. When the marginal cost differential is “significantly large,†the home firm's ability to put the foreign firm at the risk of an AD violation is limited. But when the marginal cost differential is “significantly small,†the home firm is able to increase its output and lower the price of the product below its normal value, putting the foreign firm in the situation of an illegal dumping. One interesting implication is that, relative to the case without an AD law, the home firm has a stronger incentive to undertake cost-reducing activities (e.g., R&D investment or the adoption of a more efficient technology) under the law.antidumping laws, antidumping duties, dumping margins

Inundation simulation for urban drainage basin with storm sewer system

Copyright © 2000 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Hydrology . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Hydrology Vol. 234 (2000), DOI: 10.1016/S0022-1694(00)00237-7An urban inundation model, combining a storm sewer model SWMM, two-dimensional (2D) diffusive overland-flow model and operations of pumping stations, has been developed to simulate inundation in urban areas caused by the surcharge of storm sewers and outlet pumping stations. The movement of water in the studied urban watershed is characterized by two components, namely, the storm sewer flow component and the surcharge-induced inundation component. SWMM is employed to solve the storm sewer flow component and to provide the surcharged flow hydrographs for surface runoff exceeding the capacity of the storm sewers. The 2D diffusive overland-flow model considering the non-inertia equation with Alternative Direction Explicit numerical scheme is then used to calculate the detailed inundation zones and depths due to the surcharged water on overland surface. Drainage by pumping stations at outlets of the storm sewer system has also been taken into consideration. The parameters of the model are calibrated and verified for discrete storms. The combined model is suitable for analysis of inundation on urban areas due to overflow of storm sewers and flooding caused by failure of pumping stations. Simulated results can be applied to establish flood-mitigation measures

Application of geographic weighted regression to establish flood-damage functions reflecting spatial variation

Flood damage functions are necessary to ensure comprehensive flood-risk management. This study attempts to establish a residential flood-damage function through interviewing the residents living in the region where flood disasters occur frequently. Keelung River basin, near Taipei Metropolitan in Taiwan was selected as study area. Flood damages are related to the flood depths, which are the most commonly considered factor in previously published work. Ordinary least squares (OLS) regression was used to construct the flood-damage function at the beginning. Analytical results indicate that flood depth is the significant variable, but the spatial pattern of the residuals shows that residuals exhibit spatial autocorrelation. The Geographically Weighted Regression (GWR) Model was then applied to modify the traditional regression model, which cannot capture spatial variations, and to reduce the problem of spatial autocorrelation. The R-square value was found to increase from 0.15 to 0.24, and the spatial autocorrelation in the residuals was no longer evident. A modified OLS model with a dummy variable to capture the spatial autocorrelation pattern was also proposed for future applications. In conclusion, the residential flood damage is determined by flood depth and zone, and the GWR model not only captures the spatial variations of the affecting factors, but also helps to discover the independent variable to modify the traditional regression model.Keywords: flood damage, flood depth, OLS, GWR, spatial autocorrelatio