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Discussions of the international dimension of the global economic crisis have frequently focused on the build-up of large current account "imbalances" since the mid-1990s. This paper examines the extent to which the U.S. current account can be understood in a purely real open-economy DSGE model, were agents' perception of long-run growth evolves over time in response to changes in productivity. We first show that long-run growth forecasts based on
ltering actual productivity growth comove strongly with survey measures of expectations. Simulating the model, we
nd that including data on U.S. TFP growth and the world real interest rate can, under standard parametrizations of our model, explain the evolution of the U.S. current account quite closely. With household preference that allow positive labor supply e¤ects after favorable news of future income, we can also generate output movements in line with the data.
Due to an increasing awareness of the potential hazardousness of air pollutants, new laws, rules and guidelines have recently been implemented globally. In this respect, numerous studies have addressed traffic-related exposure to particulate matter using stationary technology so far. By contrast, only few studies used the advanced technology of mobile exposure analysis. The Mobile Air Quality Study (MAQS) addresses the issue of air pollutant exposure by combining advanced high-granularity spatial-temporal analysis with vehicle-mounted, person-mounted and roadside sensors. The MAQS-platform will be used by international collaborators in order 1) to assess air pollutant exposure in relation to road structure, 2) to assess air pollutant exposure in relation to traffic density, 3) to assess air pollutant exposure in relation to weather conditions, 4) to compare exposure within vehicles between front and back seat (children) positions, and 5) to evaluate "traffic zone"- exposure in relation to non-"traffic zone"-exposure. Primarily, the MAQS-platform will focus on particulate matter. With the establishment of advanced mobile analysis tools, it is planed to extend the analysis to other pollutants including including NO2, SO2, nanoparticles, and ozone.