Library of medium-resolution fiber optic echelle spectra of F, G, K, and M field dwarfs to giants stars

We present a library of Penn State Fiber Optic Echelle (FOE) observations of a sample of field stars with spectral types F to M and luminosity classes V to I. The spectral coverage is from 3800 AA to 10000 AA with nominal a resolving power 12000. These spectra include many of the spectral lines most widely used as optical and near-infrared indicators of chromospheric activity such as the Balmer lines (H_alpha, H_beta), Ca II H & K, Mg I b triplet, Na I D_{1} and D_{2}, He I D_{3}, and Ca II IRT lines. There are also a large number of photospheric lines, which can also be affected by chromospheric activity, and temperature sensitive photospheric features such as TiO bands. The spectra have been compiled with the goal of providing a set of standards observed at medium resolution. We have extensively used such data for the study of active chromosphere stars by applying a spectral subtraction technique. However, the data set presented here can also be utilized in a wide variety of ways ranging from radial velocity templates to study of variable stars and stellar population synthesis. This library can also be used for spectral classification purposes and determination of atmospheric parameters (T_eff, log{g}, [Fe/H]). A digital version of all the fully reduced spectra is available via ftp and the World Wide Web (WWW) in FITS format.Comment: Latex file with 17 pages, 4 figures. Full postscript (text and figures) available at http://www.ucm.es/info/Astrof/fgkmsl/FOEfgkmsl.html To be published in ApJ

Instrumental variables quantile regression for panel data with measurement errors

This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables estimator are studied for large N and T when Na/T ! 0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The estimator is applied to the problem of measurement errors in variables, which induces endogeneity and as a result bias in the model. We derive an approximation to the bias in the quantile regression fixed effects estimator in the presence of measurement error and show its connection to similar effects in standard least squares models. Monte Carlo simulations are conducted to evaluate the finite sample properties of the estimator in terms of bias and root mean squared error. Finally, the methods are applied to a model of firm investment. The results show interesting heterogeneity in the Tobin’s q and cash flow sensitivities of investment. In both cases, the sensitivities are monotonically increasing along the quantiles

How many nucleosynthesis processes exist at low metallicity?

Abundances of low-metallicity stars offer a unique opportunity to understand the contribution and conditions of the different processes that synthesize heavy elements. Many old, metal-poor stars show a robust abundance pattern for elements heavier than Ba, and a less robust pattern between Sr and Ag. Here we probe if two nucleosynthesis processes are sufficient to explain the stellar abundances at low metallicity, and we carry out a site independent approach to separate the contribution from these two processes or components to the total observationally derived abundances. Our approach provides a method to determine the contribution of each process to the production of elements such as Sr, Zr, Ba, and Eu. We explore the observed star-to-star abundance scatter as a function of metallicity that each process leads to. Moreover, we use the deduced abundance pattern of one of the nucleosynthesis components to constrain the astrophysical conditions of neutrino-driven winds from core-collapse supernovae.Comment: 13 pages, published in Ap