Spatially resolved observations of warm ionized gas and feedback in local ULIRGs

We present VLT/VIMOS-IFU emission-line spectroscopy of a volume limited sample of 18 southern ULIRGs selected with z<0.09 and dec<10. By covering a wide range of ULIRG types, this dataset provides an important set of templates for comparison with high-redshift galaxies. We employed an automated Gaussian line fitting program to decompose the emission line profiles of Halpha, [NII], [SII], and [OI] into individual components, and chart the Halpha kinematics, and the ionized gas excitations and densities. 11/18 of our galaxies show evidence for outflowing warm ionized gas with speeds between 500 and a few 1000 km/s, with the fastest outflows associated with systems that contain an AGN. Our spatially resolved spectroscopy has allowed us to map the outflows, and in some cases determine for the first time to which nucleus the wind is associated. In three of our targets we find line components with widths >2000 km/s over spatially extended regions in both the recombination and forbidden lines; in two of these three, they are associated with a known Sy2 nucleus. Eight galaxies have clear rotating gaseous disks, and for these we measure rotation velocities, virial masses, and calculate Toomre Q parameters. We find radial gradients in the emission line ratios in a significant number of systems in our study. We attribute these gradients to changes in ionizing radiation field strength, most likely due to an increasing contribution of shocks with radius. We conclude with a detailed discussion of the results for each individual system, with reference to the existing literature. Our observations demonstrate that the complexity of the kinematics and gas properties in ULIRGs can only be disentangled with high sensitivity, spatially resolved IFU observations. Many of our targets are ideal candidates for future high spatial resolution follow-up observations.Comment: 44 pages, 8 figures, 3 tables, accepted to MNRA

Essays in Asset Pricing and Applied Micro-Economics

In the first chapter, Christian Goulding and I present a model of asset prices with recursive preferences and the simple consumption growth dynamics of Mehra and Prescott (1985) but relax the assumption that preference parameters are constant over time. We show that rare, temporary, and plausible fluctuations in the elasticity of inter-temporal substitution (EIS) and risk aversion (RA) can quantitatively explain numerous regularities in U.S. asset prices including: the equity premium and risk-free rate puzzles, excess return and consumption growth predictability, a counter-cyclical risk premium and an upward-sloping real yield curve. A novel implication is that time-varying EIS is more important than time-varying RA for explaining many of these regularities, suggesting a new source of risk in investors\u27 ability to plan their consumption over long horizons. In addition, our model can accommodate a behavioral interpretation of psychological factors (e.g. fear) that drive fluctuations in asset prices beyond traditional risk factors. The second chapter is an empirical study of the value of star college athletes. Collegiate athletes in the U.S. are not allowed to be paid directly for their athletic ability. Under the current regulations imposed by the NCAA, any compensation beyond scholarships and grant-in-aid to cover some basic living expenses is forbidden. This artificial constraint on athletes\u27 wages, when university athletic programs are generating significant revenues, has sparked much recent debate over the compensation of college athletes. To help inform this debate, I quantify the value of a NCAA Division 1 FBS (Football Bowl Subdivision) star football and NCAA Division 1 star basketball players by estimating their marginal revenue product using a novel dataset of individual player and team performance statistics and publicly available athletic program revenue data. I find that a star college football player is worth up to $1.2-$2.1 million while star college basketball players are worth up to $655,000-$1.1 million a year. Interestingly, I also find evidence suggesting that a college recruiter\u27s ability to identify revenue generating star players is limited and that the marginal revenue product of star college players declines as the team\u27s media coverage increases