Statistical Interpolation Method of Turbulent Phase Screen

A relative displacement between the grid points of optical fields and those of phase screens may occur in the simulation of light propagation through the turbulent atmosphere. A statistical interpolator is proposed to solve this problem in this paper. It is evaluated by the phase structure function and numerical experiments of light propagation through atmospheric turbulence with/without adaptive optics (AO) and it is also compared with the well-known linear interpolator under the same condition. Results of the phase structure function show that the statistical interpolator is more accurate in comparison with the linear one, especially in the high frequency region. More importantly, the long-exposure results of light propagation through the turbulent atmosphere with/without AO also show that the statistical interpolator is more accurate and reliable than the linear one. (C) 2009 Optical Society of America.

Can the change in the composition of the US GDP explain the Great Moderation? A test via oil price shocks

The paper investigates whether the growing GDP share of the services sector can contribute to explain the great moderation in the US. We identify and analyze three oil price shocks and use a SVAR analysis to measure their economic impact on the US economy at both the aggregate and the sectoral level. We find mixed support for the explanation of the great moderation in terms of shrinking oil shock volatilities and observe that increases (decreases) in oil shock volatilities are contrasted by a weakening (strengthening) in their transmission mechanism. Across sectors, services are the least affected by any oil shock. As the contribution of services to the GDP volatility increases over time, we conclude that a composition effect contributed to moderate the conditional volatility to oil shocks of the US GDP.