Endogenous R&D Investment and Market Structure: A Case Study of the Agricultural Biotechnology Industry

Over the past three decades, the agricultural biotechnology sector has been characterized by rapid innovation, market consolidation, and a more exhaustive definition of property rights. The industry attributes consistently identified by the literature and important to this analysis include: (i) endogenous sunk costs in the form of expenditures on R&D; (ii) seed and agricultural chemical technologies that potentially act as complements within firms and substitutes across firms; and (iii) property rights governing plant and seed varieties that have become more clearly defined since the 1970s. This paper adds to the stylized facts of the agricultural biotechnology industry to include the ability of firms to license technology, a phenomenon observed only recently in the market as licensing was previously precluded by high transactions costs and “anti-stacking” provisions. We extend Sutton's theoretical framework of endogenous sunk costs and market structure to incorporate the ability of firms to license technology under well-defined property rights, an observed characteristic not captured in previous analyses of the sector. Our model implies that technology licensing leads to lower levels of industry concentration then what would be found under Sutton's model, but that industry concentration remains bounded away from perfect competition as market size becomes large.licensing, market structure, R&D, agricultural biotechnology, Research and Development/Tech Change/Emerging Technologies, L22, L24, Q16,

First measurement of gravitational lensing by cosmic voids in SDSS

We report the first measurement of the diminutive lensing signal arising from matter underdensities associated with cosmic voids. While undetectable individually, by stacking the weak gravitational shear estimates around 901 voids detected in SDSS DR7 by Sutter et al. (2012a), we find substantial evidence for a depression of the lensing signal compared to the cosmic mean. This depression is most pronounced at the void radius, in agreement with analytical models of void matter profiles. Even with the largest void sample and imaging survey available today, we cannot put useful constraints on the radial dark-matter void profile. We invite independent investigations of our findings by releasing data and analysis code to the public at https://github.com/pmelchior/void-lensingComment: 6 pages, 5 figures, as accepted by MNRA

Syndemics and the PrEP Cascade: Results from a Sample of Young Latino Men Who Have Sex with Men.

Young Latino men who have sex with men (MSM) are a highly vulnerable population for HIV infection. Pre-exposure prophylaxis (PrEP) is a novel biomedical HIV prevention tool that may aid in reducing the disparity in HIV incidence among Latino MSM. However, PrEP use is disproportionally low among Latino MSM and, therefore, identifying barriers along the PrEP continuum of care (the "PrEP cascade") would provide insight into how to best deploy PrEP interventions. Syndemics theory is a prominent framework employed in HIV prevention; however, to date, no known studies have applied this theory to PrEP. Thus, the aim of the current study was to explore the association between syndemics and the PrEP cascade, including the degree to which psychosocial and structural syndemic constructs are related to the PrEP cascade. Participants were 151 young Latino MSM (M age = 24 years; SD = 3) residing in San Diego, California, who completed a battery of online self-report measures. Results indicated high levels of syndemic indicators and varying levels of engagement across the PrEP cascade. As syndemic indicators increased, the odds of engagement across the PrEP cascade were significantly lowered. Psychosocial and structural syndemic factors accounted for unique variance in the PrEP cascade. Results highlight the need for combination interventions that address both psychosocial and structural barriers to PrEP use and persistence among young Latino MSM

Cross-correlation Weak Lensing of SDSS galaxy Clusters II: Cluster Density Profiles and the Mass--Richness Relation

We interpret and model the statistical weak lensing measurements around 130,000 groups and clusters of galaxies in the Sloan Digital Sky Survey presented by Sheldon et al. 2007 (Paper I). We present non-parametric inversions of the 2D shear profiles to the mean 3D cluster density and mass profiles in bins of both optical richness and cluster i-band luminosity. We correct the inferred 3D profiles for systematic effects, including non-linear shear and the fact that cluster halos are not all precisely centered on their brightest galaxies. We also model the measured cluster shear profile as a sum of contributions from the brightest central galaxy, the cluster dark matter halo, and neighboring halos. We infer the relations between mean cluster virial mass and optical richness and luminosity over two orders of magnitude in cluster mass; the virial mass at fixed richness or luminosity is determined with a precision of 13% including both statistical and systematic errors. We also constrain the halo concentration parameter and halo bias as a function of cluster mass; both are in good agreement with predictions of LCDM models. The methods employed here will be applicable to deeper, wide-area optical surveys that aim to constrain the nature of the dark energy, such as the Dark Energy Survey, the Large Synoptic Survey Telescope and space-based surveys

Photometric Redshift Probability Distributions for Galaxies in the SDSS DR8

We present redshift probability distributions for galaxies in the SDSS DR8 imaging data. We used the nearest-neighbor weighting algorithm presented in Lima et al. 2008 and Cunha et al. 2009 to derive the ensemble redshift distribution N(z), and individual redshift probability distributions P(z) for galaxies with r < 21.8. As part of this technique, we calculated weights for a set of training galaxies with known redshifts such that their density distribution in five dimensional color-magnitude space was proportional to that of the photometry-only sample, producing a nearly fair sample in that space. We then estimated the ensemble N(z) of the photometric sample by constructing a weighted histogram of the training set redshifts. We derived P(z) s for individual objects using the same technique, but limiting to training set objects from the local color-magnitude space around each photometric object. Using the P(z) for each galaxy, rather than an ensemble N(z), can reduce the statistical error in measurements that depend on the redshifts of individual galaxies. The spectroscopic training sample is substantially larger than that used for the DR7 release, and the newly added PRIMUS catalog is now the most important training set used in this analysis by a wide margin. We expect the primary source of error in the N(z) reconstruction is sample variance: the training sets are drawn from relatively small volumes of space. Using simulations we estimated the uncertainty in N(z) at a given redshift is 10-15%. The uncertainty on calculations incorporating N(z) or P(z) depends on how they are used; we discuss the case of weak lensing measurements. The P(z) catalog is publicly available from the SDSS website.Comment: 29 pages, 9 figures, single colum

Constraining the Scatter in the Mass-Richness Relation of maxBCG Clusters With Weak Lensing and X-ray Data

We measure the logarithmic scatter in mass at fixed richness for clusters in the maxBCG cluster catalog, an optically selected cluster sample drawn from SDSS imaging data. Our measurement is achieved by demanding consistency between available weak lensing and X-ray measurements of the maxBCG clusters, and the X-ray luminosity--mass relation inferred from the 400d X-ray cluster survey, a flux limited X-ray cluster survey. We find \sigma_{\ln M|N_{200}}=0.45^{+0.20}_{-0.18} (95% CL) at N_{200} ~ 40, where N_{200} is the number of red sequence galaxies in a cluster. As a byproduct of our analysis, we also obtain a constraint on the correlation coefficient between \ln Lx and \ln M at fixed richness, which is best expressed as a lower limit, r_{L,M|N} >= 0.85 (95% CL). This is the first observational constraint placed on a correlation coefficient involving two different cluster mass tracers. We use our results to produce a state of the art estimate of the halo mass function at z=0.23 -- the median redshift of the maxBCG cluster sample -- and find that it is consistent with the WMAP5 cosmology. Both the mass function data and its covariance matrix are presented.Comment: 14 pages, 6 figures, submitted to Ap

Cosmological Constraints from Galaxy Clustering and the Mass-to-Number Ratio of Galaxy Clusters

We place constraints on the average density (Omega_m) and clustering amplitude (sigma_8) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, w_p, and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our w_p measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct non-linear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both w_p and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when Omega_m or sigma_8 is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, even though this technique does not use abundance information. Using w_p and M/N alone, we find Omega_m^0.5*sigma_8=0.465+/-0.026, with individual constraints of Omega_m=0.29+/-0.03 and sigma_8=0.85+/-0.06. Combined with current CMB data, these constraints are Omega_m=0.290+/-0.016 and sigma_8=0.826+/-0.020. All errors are 1-sigma. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy surveys.Comment: 23 pages, submitted to Ap

Self calibration of gravitational shear-galaxy intrinsic ellipticity correlation in weak lensing surveys

The galaxy intrinsic alignment is a severe challenge to precision cosmic shear measurement. We propose to self-calibrate the induced gravitational shear-galaxy intrinsic ellipticity correlation (the GI correlation, \citealt{Hirata04b}) in weak lensing surveys with photometric redshift measurement. (1) We propose a method to extract the intrinsic ellipticity-galaxy density cross correlation (I-g) from the galaxy ellipticity-density measurement in the same redshift bin. (2) We also find a generic scaling relation to convert the extracted I-g correlation to the demanded GI correlation. We perform concept study under simplified conditions and demonstrate its capability to significantly reduce the GI contamination. We discuss the impact of various complexities on the two key ingredients of the self-calibration technique, namely the method to extract the I-g correlation and the scaling relation between the I-g and the GI correlation. We expect none of them is likely able to completely invalidate the proposed self-calibration technique.Comment: 14 pages, 4 figures. Heavily expanded version. No changes in major results and conclusions. Accepted to Ap

Variation in local population size predicts social network structure in wild songbirds

1. The structure of animal societies is a key determinant of many ecological and evolutionary processes. Yet, we know relatively little about the factors and mechanisms that underpin detailed social structure. 2. Among other factors, social structure can be influenced by habitat configuration. By shaping animal movement decisions, heterogeneity in habitat features, such as vegetation and the availability of resources, can influence the spatiotemporal distribution of individuals and subsequently key socioecological properties such as the local population size and density. Differences in local population size and density can impact opportunities for social associations and may thus drive substantial variation in local social structure. 3. Here, we investigated spatiotemporal variation in population size at 65 distinct locations in a small songbird, the great tit (Parus major), and its effect on social network structure. We first explored the within-location consistency of population size from weekly samples and whether the observed variation in local population size was predicted by the underlying habitat configuration. Next, we created social networks from the birds’ foraging associations at each location for each week and examined if local population size affected social structure. 4. We show that population size is highly repeatable within locations across weeks and years and that some of the observed variation in local population size was predicted by the underlying habitat, with locations closer to the forest edge having on average larger population sizes. Further, we show that local population size affected social structure inferred by four global network metrics. Using simple simulations, we then reveal that much of the observed social structure is shaped by social processes. Across different population sizes, the birds’ social structure was largely explained by their preference to forage in flocks. In addition, over and above effects of social foraging, social preferences between birds (i.e. social relationships) shaped certain network features such as the extent of realized social connections. 5. Our findings thus suggest that individual social decisions substantially contribute to shaping certain social network features over-and-above effects of population size alone

Precision Measurements of the Cluster Red Sequence using an Error Corrected Gaussian Mixture Model

The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment.Comment: 33 pages, 14 Figures; A typo in Eq.A11 is fixed. The C++/Python codes for ECGMM can be downloaded from: https://sites.google.com/site/jiangangecgmm