Identifying hedonic models

Economic models for hedonic markets characterize the pricing of bundles of attributes and the demand and supply of these attributes under different assumptions about market structure, preferences and technology. (See Jan Tinbergen, 1956, Sherwin Rosen, 1974 and Dennis Epple, 1987, for contributions to this literature). While the theory is well formulated, and delivers some elegant analytical results, the empirical content of the model is under debate. It is widely believed that hedonic models fit in a single market are fundamentally underidentified and that any empirical content obtained from them is a consequence of arbitrary functional form assumptions. The problem of identification in hedonic models is a prototype for the identification problem in a variety of economic models in which agents sort on unobservable (to the economist) characteristics: models of monopoly pricing (Michael Mussa and Sherwin Rosen, 1978; Robert Wilson, 1993) and models for taxes and labor supply (James Heckman, 1974). Sorting is an essential feature of econometric models of social interactions. (See William Brock and Steven Durlauf, 2001). In this paper we address the sorting problem in hedonic models. Nesheim (2001) extends this analysis to a model with peer effects. In this paper we note that commonly used linearization strategies made to simplify estimation and justify the application of instrumental variables methods, produce identification problems. The hedonic model is generically nonlinear. It is the linearization of a fundamentally nonlinear model that produces the form of the identification problem that dominates discussion in the applied literature. Linearity is an arbitrary and misleading functional form when applied to empirical hedonic models. Our research establishes that even though sorting equilibrium in a single market implies no exclusion restrictions, the hedonic model is generically nonparametrically identified. Instrumental variables and transformation model methods identify economically relevant parameters even 1 without exclusion restrictions. Multimarket data, widely viewed as the most powerful source of identification, achieves this result only under implausible assumptions about why hedonic functions vary across markets

Taking the Easy Way Out: How the GED Testing Program Induces Students to Drop Out

We exploit an exogenous increase in General Educational Development (GED) testing requirements to determine whether raising the difficulty of the test causes students to finish high school rather than drop out and GED certify. We find that a six point decrease in GED pass rates induces a 1.3 point decline in overall dropout rates. The effect size is also much larger for older students and minorities. Finally, a natural experiment based on the late introduction of the GED in California reveals, that adopting the program increased the dropout rate by 3 points more relative to other states during the mid-1970s.GED, dropout

Rapid adaptive evolution of colour vision in the threespine stickleback radiation.

Vision is a sensory modality of fundamental importance for many animals, aiding in foraging, detection of predators and mate choice. Adaptation to local ambient light conditions is thought to be commonplace, and a match between spectral sensitivity and light spectrum is predicted. We use opsin gene expression to test for local adaptation and matching of spectral sensitivity in multiple independent lake populations of threespine stickleback populations derived since the last ice age from an ancestral marine form. We show that sensitivity across the visual spectrum is shifted repeatedly towards longer wavelengths in freshwater compared with the ancestral marine form. Laboratory rearing suggests that this shift is largely genetically based. Using a new metric, we found that the magnitude of shift in spectral sensitivity in each population corresponds strongly to the transition in the availability of different wavelengths of light between the marine and lake environments. We also found evidence of local adaptation by sympatric benthic and limnetic ecotypes to different light environments within lakes. Our findings indicate rapid parallel evolution of the visual system to altered light conditions. The changes have not, however, yielded a close matching of spectrum-wide sensitivity to wavelength availability, for reasons we discuss

The Discovery of an Active Galactic Nucleus in the Late-type Galaxy NGC 3621: Spitzer Spectroscopic Observations

We report the discovery of an Active Galactic Nucleus (AGN) in the nearby SAd galaxy NGC 3621 using Spitzer high spectral resolution observations. These observations reveal the presence of [NeV] 14 um and 24 um emission which is centrally concentrated and peaks at the position of the near-infrared nucleus. Using the [NeV] line luminosity, we estimate that the nuclear bolometric luminosity of the AGN is ~ 5 X 10^41 ergs s^-1, which corresponds based on the Eddington limit to a lower mass limit of the black hole of ~ 4 X 10^3 Msun. Using an order of magnitude estimate for the bulge mass based on the Hubble type of the galaxy, we find that this lower mass limit does not put a strain on the well-known relationship between the black hole mass and the host galaxy's stellar velocity dispersion established in predominantly early-type galaxies. Mutli-wavelength follow-up observations of NGC 3621 are required to obtain more precise estimates of the bulge mass, black hole mass, accretion rate, and nuclear bolometric luminosity. The discovery reported here adds to the growing evidence that a black hole can form and grow in a galaxy with no or minimal bulge.Comment: 5 pages, 7 figures, Accepted for publication in ApJ Letter

The Footprint of F-theory at the LHC

Recent work has shown that compactifications of F-theory provide a potentially attractive phenomenological scenario. The low energy characteristics of F-theory GUTs consist of a deformation away from a minimal gauge mediation scenario with a high messenger scale. The soft scalar masses of the theory are all shifted by a stringy effect which survives to low energies. This effect can range from 0 GeV up to ~ 500 GeV. In this paper we study potential collider signatures of F-theory GUTs, focussing in particular on ways to distinguish this class of models from other theories with an MSSM spectrum. To accomplish this, we have adapted the general footprint method developed recently for distinguishing broad classes of string vacua to the specific case of F-theory GUTs. We show that with only 5 fb^(-1) of simulated LHC data, it is possible to distinguish many mSUGRA models and low messenger scale gauge mediation models from F-theory GUTs. Moreover, we find that at 5 fb^(-1), the stringy deformation away from minimal gauge mediation produces observable consequences which can also be detected to a level of order ~ +/- 80 GeV. In this way, it is possible to distinguish between models with a large and small stringy deformation. At 50 fb^(-1), this improves to ~ +/- 10 GeV.Comment: 85 pages, 37 figure

Economic, Neurobiological and Behavioral Perspectives on Building America's Future Workforce

A growing proportion of the U.S. workforce will have been raised in disadvantaged environments that are associated with relatively high proportions of individuals with diminished cognitive and social skills. A cross-disciplinary examination of research in economics, developmental psychology, and neurobiology reveals a striking convergence on a set of common principles that account for the potent effects of early environment on the capacity for human skill development. Central to these principles are the findings that early experiences have a uniquely powerful influence on the development of cognitive and social skills, as well as on brain architecture and neurochemistry; that both skill development and brain maturation are hierarchical processes in which higher level functions depend on, and build on, lower level functions; and that the capacity for change in the foundations of human skill development and neural circuitry is highest earlier in life and decreases over time. These findings lead to the conclusion that the most efficient strategy for strengthening the future workforce, both economically and neurobiologically, and for improving its quality of life is to invest in the environments of disadvantaged children during the early childhood years.

Visualizing genetic constraints

Principal Components Analysis (PCA) is a common way to study the sources of variation in a high-dimensional data set. Typically, the leading principal components are used to understand the variation in the data or to reduce the dimension of the data for subsequent analysis. The remaining principal components are ignored since they explain little of the variation in the data. However, evolutionary biologists gain important insights from these low variation directions. Specifically, they are interested in directions of low genetic variability that are biologically interpretable. These directions are called genetic constraints and indicate directions in which a trait cannot evolve through selection. Here, we propose studying the subspace spanned by low variance principal components by determining vectors in this subspace that are simplest. Our method and accompanying graphical displays enhance the biologist's ability to visualize the subspace and identify interpretable directions of low genetic variability that align with simple directions.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS603 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org