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This paper investigates the economic costs of rebalancing current account positions in the Euro area by means of internal devaluation. Internal devaluation relies on wage suppression the deficit countries. Based on an old Keynesian model we estimate a current account equation, a wage-Phillips curve and an Okun's Law equation. All estimations are carried out for a panel of twelve Euro area members. From the estimation results we calculate the output costs of reducing current account deficits. Greece, Ireland, Italy, Portugal and Spain (GIIPS) had, on average, current account deficits of 8.4% of GDP in 2007. To eliminate these current account deficits, a reduction of GPD by some 47% would be necessary. In principle there are two ways that trade imbalances could be resolved: deflationary adjustment in the deficit countries or inflationary adjustment in the surplus countries. Presently, the burden of adjustment is exclusively on the deficit countries. Our results indicate that the economic costs of this adjustment to those countries are equivalent to the output loss of the Great Depression. An adjustment of the surplus countries would increase growth and it would come with higher inflation, but it would allow rebalancing without a Great Depression in parts of Europe.

Abstract. This paper reports an experiment for stress recognition in human-computer interaction. Thirty-one healthy participants performed five stressful HCI tasks and their skin conductance signals were monitored. The selected tasks were most frequently listed as stressful by 15 typical computer users who were involved in pre-experiment interviews asking them to identify stressful cases of computer interaction. The collected skin conductance signals were analyzed using seven popular machine learning classifiers. The best stress recognition accuracy was achieved by the cubic support vector machine classifier both per task (on average 90.8 %) and for all tasks (Mean = 98.8 %, SD = 0.6 %). This very high accuracy demonstrates the potentials of using physiological signals for stress recognition in the context of typical HCI tasks. In addition, the results allow us to move on a first integration of the specific stress recognition mechanism in PhysiOBS, a previously-proposed software tool that supports researchers and practitioners in user emotional experience evaluation.

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