Do the most productive firms become exporters? Application of a test for the case of Portugal

Using a longitudinal database (1996-2003) at the plant level, this article aims to shed light on the proposition that most productive domestic firms self-select to export markets. Self-selection and learning by exporting are two non-mutually-exclusive theses that attempt to explain the high correlation between firms’ international trade involvement and their superior performance relative to domestic firms. In general, we find evidence of a self-selection to exports. However, there is significant heterogeneity of sales destinations, firm import status before exporting,and the specificities of the sectors firms belong to.

The dark side of DEMMON: what is behind the scene in engineering large-scale wireless sensor networks

Most research work on WSNs has focused on protocols or on specific applications. There is a clear lack of easy/ready-to-use WSN technologies and tools for planning, implementing, testing and commissioning WSN systems in an integrated fashion. While there exists a plethora of papers about network planning and deployment methodologies, to the best of our knowledge none of them helps the designer to match coverage requirements with network performance evaluation. In this paper we aim at filling this gap by presenting an unified toolset, i.e., a framework able to provide a global picture of the system, from the network deployment planning to system test and validation. This toolset has been designed to back up the EMMON WSN system architecture for large-scale, dense, real-time embedded monitoring. It includes network deployment planning, worst-case analysis and dimensioning, protocol simulation and automatic remote programming and hardware testing tools. This toolset has been paramount to validate the system architecture through DEMMON1, the first EMMON demonstrator, i.e., a 300+ node test-bed, which is, to the best of our knowledge, the largest single-site WSN test-bed in Europe to date.