Trade Agreements and Economic Growth

This paper studies the growth effects of regional trade agreements (RTAs), taking into account the WTO participation of RTA members. Assuming smaller preference margins of RTAs for WTO members than non-members, I show in a model a stronger growth effect of RTAs for non-WTO members than that for WTO members. Based on a comprehensive set of 270 RTAs and a large panel dataset covering 177 countries over the period of 1960-2007, the regression results show that RTAs promote growth for non-WTO members, while their growth effect is insignificantly different from zero for WTO members. This implies that the complementarity between the two approaches of trade liberalization in promoting economic growth is so far limited

GATT/WTO Promotes Trade Strongly: Sample Selection and Model Specification

Some recent empirical studies examine the impact of the GATT/WTO on trade. This paper investigates the sample selection bias and the gravity model specification issues in the literature. First, the GATT/WTO not only makes existing trading partners trade more at the intensive margin, but also creates new trading relationships at the extensive margin. Most existing papers exclude zero trade observations and hence ignore the extensive margin. Secondly, due to the violation of some maintained assumptions, the traditional log-linear gravity regressions fail to uncover the role of the GATT/WTO even at the intensive margin. Using a large bilateral panel dataset including zero trade flows and a more appropriate econometric method, this paper finds that the GATT/WTO has been very effective in promoting world trade at both the intensive and extensive margins

Testing Conflicting Political Economy Theories: Full-Fledged versus Partial-Scope Regional Trade Agreements

We apply a duration analysis to test the conflicting predictions of the median voter model and the lobbying model using panel data on regional trade agreement (RTA) formation. Our results show that the pro-labor prediction of the median voter model is supported by the full-fledged free trade areas and customs unions (FTAs/CUs), while the pro-capital prediction of the lobbying model is supported by the partial-scope preferential trade arrangements among developing countries. This finding holds better for the country pairs with more different capital-labor ratios as a result of the stronger distributional effects of RTAs. The support for the median voter model (lobbying model) is stronger when the two countries in a pair have left-oriented (right-oriented) governments. I also find stronger support for the median voter model for the subset of FTAs/CUs with service coverage and stronger support for the lobbying model for countries that place higher weight on political contribution

(WP 2014-02) Trade Volatility and the GATT/WTO: Does Membership Make a Difference?

Using bilateral trade data for 210 countries over the period 1948-2003, this paper attempts to shed some light on the relationship between WTO and members’ trade volatilities. We show that the trade among WTO members tends to be more stable than the trade outside the WTO, and there is strong evidence of interdependence of trade volatilities. The results show comovement of trade volatilities across all dyads in general, and much stronger comovement among WTO members than between WTO and non-WTO members. Such strong comovement implies that WTO member countries not only share the benefits of having an interdependent and more predictable trade system, but also share the risks of contagious world trade collapse as evidenced by the 2008 global financial crisis. In addition, we find that larger economies and countries covered by other types of integration agreements can do better in coping with such type of contagion

Free trade agreements and the consolidation of democracy

We study the relationship between participation in free trade agreements (FTAs) and the sustainability of democracy. Our model shows that FTAs can critically reduce the incentive of authoritarian groups to seek power by destroying protectionist rents, thus making democracies last longer. This gives governments in unstable democracies an extra motive to form FTAs. Hence, greater democratic instability induces governments to boost their FTA commitments. In a dataset with 116 countries over 1960-2007, we find robust support for these predictions. They help to rationalize the rapid simultaneous growth of regionalism and of worldwide democratization since the late 1980s

Digital Transformation of High Voltage Isolation Control and Monitoring System for HVE-400 Ion Implanter

HVE-400 ion implanter is special ion implantation equipment for semiconductor materials boron and phosphorus doping. The ion source and extraction deflection system are at high voltage platform, while the corresponding control system is at ground voltage position. The control signals and measurement signals of various parameters at the high-voltage end need to be transmitted between ground voltage and high voltage through optical fibers to isolate high voltage. Upgrading is carried out due to the aging of the optical fiber transmission control and monitoring system, which cannot work stably. The transformation replaces the original distributed single-point control method with an advanced distributed centralized control method, and integrates all control and monitoring functions into an industrial control computer for digital operation and display. In the computer software, two kinds of automatic calculation of ion mass number are designed. After upgrading, the implanter high-voltage platform control and monitoring system features digitalization, centralized control, high reliability, strong anti-interference, fast communication speed, and easy operation.Comment: 6 pages, 4 figures, 1 tabl

Numerical analysis of yield properties of closed-cell aluminum foam under multiaxial loads by 3D voronoi model

Metallic foam is a typical porous material whose yield surface is related to not only von Mises equivalent stress but also the hydrostatic pressure. It is essential to study the yield properties of closed-cell aluminum foam under complex loading conditions. However, because the current experimental technique may support only a few proportions of multiaxial loading, it is hard to learn the yield surface well especially for the tensile hydrostatic pressure. In this article, we explored a numerical method to learn the yield properties of aluminum foam, in which the meso structures of aluminum foam were simulated by 3D Voronoi method. In addition, the yield surface of aluminum foam was drawn successfully with the numerical method. The main works included: (1) In our numerical simulation, we tested the calculating parameters such as mass scaling, elements number, and loading velocity on simulation results and verified the homogeneity of the 3D Voronoi model firstly. Furthermore, the optimized calculating parameters were determined by considering both reliability and feasibility of the calculation. Homogeneity of 3D Voronoi model was checked by the compression behaviors of aluminum in different directions. (2) In order to overcome the difficulty to determine critical yield state of metallic foams under complex loads, we recommended criterion by setting a dimensionless plastic dissipation value to determine the onset yield state of the foam under multiaxial loads. The critical value of dimensionless plastic dissipation was deduced from the common criterion—0.2% plastic strain in uniaxial loading, and the effect of relative densities on critical values was analyzed. (3) Three normal stresses were applied on cubic aluminum foam proportionally to implement the proportional loading. The different loading proportional factors of the three normal stresses were set widely to insure the yield surface including enough data, such as the hydrostatic loads cover from minimum negative to maximum positive values; each proportion has three loading proportional factors. Further, effects of the relative density on yield surface were investigated

Data-driven approach for modeling Reynolds stress tensor with invariance preservation

The present study represents a data-driven turbulent model with Galilean invariance preservation based on machine learning algorithm. The fully connected neural network (FCNN) and tensor basis neural network (TBNN) [Ling et al. (2016)] are established. The models are trained based on five kinds of flow cases with Reynolds Averaged Navier-Stokes (RANS) and high-fidelity data. The mappings between two invariant sets, mean strain rate tensor and mean rotation rate tensor as well as additional consideration of invariants of turbulent kinetic energy gradients, and the Reynolds stress anisotropy tensor are trained. The prediction of the Reynolds stress anisotropy tensor is treated as user's defined RANS turbulent model with a modified turbulent kinetic energy transport equation. The results show that both FCNN and TBNN models can provide more accurate predictions of the anisotropy tensor and turbulent state in square duct flow and periodic flow cases compared to the RANS model. The machine learning based turbulent model with turbulent kinetic energy gradient related invariants can improve the prediction precision compared with only mean strain rate tensor and mean rotation rate tensor based models. The TBNN model is able to predict a better flow velocity profile compared with FCNN model due to a prior physical knowledge.Comment: 23 page