Immiserizing growth and the Metzler Paradox in the Ricardian Model

Conditions for the occurrence of immiserizing growth and the Metzler paradox are analysed in the Ricardian model when consumers in the foreign country have Leontief preferences while consumers in the home country have Cobb-Douglas preferences. By using specific functional forms, the conditions for the occurrence of the two paradoxes are defined in terms of the exogenous parameters of the model rather than endogenous variables such as the elasticity of demand for exports in the conditions of Bhagwati (1958) and Metzler (1949a and b). It is shown that the simultaneous occurrence of both paradoxical results is possible for some parameter values

Multilateral trade liberalisation, foreign direct investment and the volume of world trade

A paradox in international trade is that multilateral trade liberalisation has resulted in increases in both the volume of world trade and the amount of foreign direct investment (FDI). This note presents a Cournot duopoly model with two regions, each consisting of two countries, and with an inter-regional transport cost. It is shown that multilateral trade liberalisation may lead firms to switch from exporting to undertaking export-platform FDI when the interregional transport cost is high. Also, when the inter-regional transport cost is high, the switch to FDI leads to an increase in the volume of world trade in this industry

The optimality of optimal punishments in Cournot supergames

The result of Colombo and Labrecciosa (2006) that optimal punishments are inferior to Nash-reversion trigger strategies with decreasing marginal costs is due to the output when a firm deviates from the punishment path being allowed to become negative

Product differentiation, the volume of trade and profits under Cournot and Bertrand duopoly

This paper analyses how product differentiation affects the volume of trade under duopoly using Shubik-Levitan demand functions rather than the Bowley demand functions used by Bernhofen (2001). The Shubik-Levitan demand functions have the advantage that an increase in product differentiation does not increase the size of the market as happens with the Bowley demand functions. It is shown that the volume of trade in terms of quantities is decreasing in the degree of product differentiation when the trade cost is relatively low, but increasing in the degree of product differentiation when the trade cost is relatively high

Clustering Weblogs on the Basis of a Topic Detection Method

In recent years we have seen a vast increase in the volume of information published on weblog sites and also the creation of new web technologies where people discuss actual events. The need for automatic tools to organize this massive amount of information is clear, but the particular characteristics of weblogs such as shortness and overlapping vocabulary make this task difficult. In this work, we present a novel methodology to cluster weblog posts according to the topics discussed therein. This methodology is based on a generative probabilistic model in conjunction with a Self-Term Expansion methodology. We present our results which demonstrate a considerable improvement over the baseline

Reinforcement Learning Experiments and Benchmark for Solving Robotic Reaching Tasks

Reinforcement learning has shown great promise in robotics thanks to its ability to develop efficient robotic control procedures through self-training. In particular, reinforcement learning has been successfully applied to solving the reaching task with robotic arms. In this paper, we define a robust, reproducible and systematic experimental procedure to compare the performance of various model-free algorithms at solving this task. The policies are trained in simulation and are then transferred to a physical robotic manipulator. It is shown that augmenting the reward signal with the Hindsight Experience Replay exploration technique increases the average return of off-policy agents between 7 and 9 folds when the target position is initialised randomly at the beginning of each episode

rl_reach: Reproducible reinforcement learning experiments for robotic reaching tasks

rl_reach is publicly available at this URL: https://github.com/PierreExeter/rl_reach[EN] Training reinforcement learning agents at solving a given task is highly dependent on identifying optimal sets of hyperparameters and selecting suitable environment input/output configurations. This tedious process could be eased with a straightforward toolbox allowing its user to quickly compare different training parameter sets. We present rl_reach, a self-contained, open-source and easy-to-use software package designed to run reproducible reinforcement learning experiments for customisable robotic reaching tasks. rl_reach packs together training environments, agents, hyperparameter optimisation tools and policy evaluation scripts, allowing its users to quickly investigate and identify optimal training configurations. rl_reach is publicly available at this URL: https://github.com/PierreExeter/rl_reachSIEuropean Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713654

Implementation of an Online Database for Chemical Propulsion Systems

The Johns Hopkins University, Chemical Propulsion Information Analysis Center (CPIAC) has been working closely with NASA Goddard Space Flight Center (GSFC); NASA Marshall Space Flight Center (MSFC); the University of Alabama at Huntsville (UAH); The Johns Hopkins University, Applied Physics Laboratory (APL); and NASA Jet Propulsion Laboratory (JPL) to capture satellite and spacecraft propulsion system information for an online database tool. The Spacecraft Chemical Propulsion Database (SCPD) is a new online central repository containing general and detailed system and component information on a variety of spacecraft propulsion systems. This paper only uses data that have been approved for public release with unlimited distribution. The data, supporting documentation, and ability to produce reports on demand, enable a researcher using SCPD to compare spacecraft easily, generate information for trade studies and mass estimates, and learn from the experiences of others through what has already been done. This paper outlines the layout and advantages of SCPD, including a simple example application with a few chemical propulsion systems from various NASA spacecraft

Prototype/topic based Clustering Method for Weblogs

[EN] In the last 10 years, the information generated on weblog sites has increased exponentially, resulting in a clear need for intelligent approaches to analyse and organise this massive amount of information. In this work, we present a methodology to cluster weblog posts according to the topics discussed therein, which we derive by text analysis. We have called the methodology Prototype/Topic Based Clustering, an approach which is based on a generative probabilistic model in conjunction with a Self-Term Expansion methodology. The usage of the Self-Term Expansion methodology is to improve the representation of the data and the generative probabilistic model is employed to identify relevant topics discussed in the weblogs. We have modified the generative probabilistic model in order to exploit predefined initialisations of the model and have performed our experiments in narrow and wide domain subsets. The results of our approach have demonstrated a considerable improvement over the pre-defined baseline and alternative state of the art approaches, achieving an improvement of up to 20% in many cases. The experiments were performed on both narrow and wide domain datasets, with the latter showing better improvement. However in both cases, our results outperformed the baseline and state of the art algorithms.The work of the third author was carried out in the framework of the WIQ-EI IRSES project (Grant No. 269180) within the FP7 Marie Curie, the DIANA APPLICATIONS Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Perez-Tellez, F.; Cardiff, J.; Rosso, P.; Pinto Avendaño, DE. (2016). Prototype/topic based Clustering Method for Weblogs. Intelligent Data Analysis. 20(1):47-65. https://doi.org/10.3233/IDA-150793S476520