Customs-Related Transaction Costs, Firm Size and International Trade Intensity

Customs are generally perceived as a time-consuming impediment to international trade. However, few studies have empirically examined the determinants and the impact of this type of government-imposed transaction costs. This paper analyses the role of firm size as a determinant of customs-related transaction costs, as well as the effect of firm size on the relationship between these costs and the international trade intensity of firms. The results of this study indicate that customs-related transaction costs repress international trade activities of firms, even at low levels of these costs. The paper identifies transaction-related economies of scale, simplified customs procedures and advanced information and communication technology as main determinants of customs-related transaction costs. It is shown that when these factors are taken into account, firm size has no effect on customs-related transaction costs. Policy implications are considered for firm strategy and public policy.

Controlling the Shadow Trade

From tackling illicit flows of small arms to combating nuclear smuggling, the shadow trade has become a central target of attempts to control the means of violence. This article argues that much of this practice and literature is framed in unhelpful terms that posit two distinct worlds, an upperworld and underworld, that separates illicit flow networks from the familiar world of state security policy. This implies that the possibilities for controlling the shadow trade are limited or require expansive and expensive controls. The article then examines the formation of illicit flow networks, drawing on examples including narcotics, small arms, nuclear materials, nuclear technology, major conventional arms, dual use technologies, and chemical weapons precursors; and finds that state and hybrid actors rather than extensive private networks are constitutive of illicit networks in many ways. It concludes by reclaiming hope for controlling the means of violence in this hybridity.

Emerging asymmetric interactions between forage and predator fisheries impose management trade-offs

A size and trait-based marine community model was used to investigate interactions, with potential implications for yields, when a fishery targeting forage fish species (whose main adult diet is zooplankton) co-occurs with a fishery targeting larger-sized predator species. Predicted effects on the size structure of the fish community, growth and recruitment of fishes, and yield from the fisheries were used to identify management trade-offs among the different fisheries. Results showed that moderate fishing on forage fishes imposed only small effects on predator fisheries, whereas predator fisheries could enhance yield from forage fisheries under some circumstances.

Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.