Monetary Policy Under Uncertainty in Micro-Founded Macroeconometric Models

We use a micro-founded macroeconometric modeling framework to investigate the design of monetary policy when the central bank faces uncertainty about the true structure of the economy. We apply Bayesian methods to estimate the parameters of the baseline specification using postwar U.S. data, and then determine the policy under commitment that maximizes household welfare. We find that the performance of the optimal policy is closely matched by a simple operational rule that focuses solely on stabilizing nominal wage inflation. Furthermore, this simple wage stabilization rule is remarkably robust to uncertainty about the model parameters and to various assumptions regarding the nature and incidence of the innovations. However, the characteristics of optimal policy are very sensitive to the specification of the wage contracting mechanism, thereby highlighting the importance of additional research regarding the structure of labor markets and wage determination.

The performance of forecast-based monetary policy rules under model uncertainty

We investigate the performance of forecast-based monetary policy rules using five macroeconomic models that reflect a wide range of views on aggregate dynamics. We identify the key characteristics of rules that are robust to model uncertainty: such rules respond to the one-year ahead inflation forecast and to the current output gap, and incorporate a substantial degree of policy inertia. In contrast, rules with longer forecast horizons are less robust and are prone to generating indeterminacy. In light of these results, we identify a robust benchmark rule that performs very well in all five models over a wide range of policy preferences JEL Classification: E31, E52, E58, E61

Structure and Mobility through Capillary Electrophoresis

Through the modification of capillary coating procedures electroosmotic flow was controlled without altering the buffer properties. Aqueous buffers of differing ionic strengths were utilized in order to develop a better understanding of the surface properties of nanocrystalline lattices known as quantum dots. Secondary determination of nanocrystal surface properties was determined through the use of a zetasizer. Non-aqueous buffers were utilized in order to determine the effect of the coating on aseparation of hydrophobic, biologically relevant fatty acids. A dynamic capillary surface coat was compared to a successive multiple ionic layer (SMIL) polymeric coat in reguards to resolution and stability. The SMIL coat was further modified to improve resolution in non-aqueous analysis of fatty acids. Laser induced fluorescence detection was utilized for detection of fluorescently tagged fatty acids. The labeling reaction was studied in order to determine the low concentration limit of the labeling reaction. This reaction was then utilized to label an extraction of free fatty acids from bovine omentum. The electrophoretic technique was utilized to separate the extract to identify fatty acid composition

Temporal-adaptive Euler/Navier-Stokes algorithm for unsteady aerodynamic analysis of airfoils using unstructured dynamic meshes

A temporal adaptive algorithm for the time-integration of the two-dimensional Euler or Navier-Stokes equations is presented. The flow solver involves an upwind flux-split spatial discretization for the convective terms and central differencing for the shear-stress and heat flux terms on an unstructured mesh of triangles. The temporal adaptive algorithm is a time-accurate integration procedure which allows flows with high spatial and temporal gradients to be computed efficiently by advancing each grid cell near its maximum allowable time step. Results indicate that an appreciable computational savings can be achieved for both inviscid and viscous unsteady airfoil problems using unstructured meshes without degrading spatial or temporal accuracy

Hinode EUV Imaging Spectrometer Observations of Solar Active Region Dynamics

The EUV Imaging Spectrometer (EIS) on the Hinode satellite is capable of measuring emission line center positions for Gaussian line profiles to a fraction of a spectral pixel, resulting in relative solar Doppler-shift measurements with an accuracy of less than a km/s for strong lines. We show an example of the application of that capability to an active region sit-and-stare observation in which the EIS slit is placed at one location on the Sun and many exposures are taken while the spacecraft tracking keeps the same solar location within the slit. For the active region examined (NOAA 10930), we find that significant intensity and Doppler-shift fluctuations as a function of time are present at a number of locations. These fluctuations appear to be similar to those observed in high-temperature emission lines with other space-borne spectroscopic instruments. With its increased sensitivity over earlier spectrometers and its ability to image many emission lines simultaneously, EIS should provide significant new constraints on Doppler-shift oscillations in the corona.Comment: 7 Pages, 7 figure