Smooth matter and source size in microlensing simulations of gravitationally lensed quasars

Several gravitationally lensed quasars are observed with anomalous magnifications in pairs of images that straddle a critical curve. Simple theoretical arguments suggest that the magnification of these images should be approximately equivalent, whereas one image is observed to be significantly demagnified. Microlensing provides a possible explanation for this discrepancy. There are two key parameters when modelling this effect. The first, the fraction of smooth matter in the lens at the image positions, has been explored by Schechter and Wambsganss (2002). They have shown that the anomalous flux ratio observed in the lensed quasar MG 0414+0534 is a priori a factor of 5 more likely if the assumed smooth matter content in the lens model is increased from 0% to 93%. The second parameter, the size of the emission region, is explored in this paper, and shown to be more significant. We find that the broadening of the magnification probability distributions due to smooth matter content is washed out for source sizes that are predicted by standard models for quasars. We apply our model to the anomalous lensed quasar MG 0414+0534, and find a 95% upper limit of 2.62 x 10^(16) h^(-1/2) (M/Msun)^(1/2) cm on the radius of the I-band emission region. The smooth matter percentage in the lens is unconstrained.Comment: 6 pages, 6 figures. To be published in MNRA

Do R&D Tax Credits Work? Evidence from a Panel of Countries 1979-1997

This paper examines the impact of fiscal incentives on the level of R&D investment. An econometric model of R&D investment is estimated using a new panel of data on tax changes and R&D spending in nine OECD countries over a 19-year period (1979–1997). We find evidence that tax incentives are effective in increasing R&D intensity. This is true even after allowing for permanent country-specific characteristics, world macro shocks and other policy influences. We estimate that a 10% fall in the cost of R&D stimulates just over a 1% rise in the level of R&D in the short-run, and just under a 10% rise in R&D in the long-run.tax credits, R&D, panel data, tax competition

A note on the Hybrid Soil Moisture Deficit Model v2.0

peer-reviewedThe Hybrid Soil Moisture Deficit (HSMD) model has been used for a wide range of applications, including modelling of grassland productivity and utilisation, assessment of agricultural management opportunities such as slurry spreading, predicting nutrient emissions to the environment and risks of pathogen transfer to water. In the decade since its publication, various ad hoc modifications have been developed and the recent publication of the Irish Soil Information System has facilitated improved assessment of the spatial soil moisture dynamics. In this short note, we formally present a new version of the model (HSMD2.0), which includes two new soil drainage classes, as well as an optional module to account for the topographic wetness index at any location. In addition, we present a new Indicative Soil Drainage Map for Ireland, based on the Irish Soil Classification system, developed as part of the Irish Soil Information System

Weak lensing calibration of mass bias in the REFLEX+BCS X-ray galaxy cluster catalogue

The use of large, X-ray selected galaxy cluster catalogues for cosmological analyses requires a thorough understanding of the X-ray mass estimates. Weak gravitational lensing is an ideal method to shed light on such issues, due to its insensitivity to the cluster dynamical state. We perform a weak lensing calibration of 166 galaxy clusters from the REFLEX and BCS cluster catalogue and compare our results to the X-ray masses based on scaled luminosities from that catalogue. To interpret the weak lensing signal in terms of cluster masses, we compare the lensing signal to simple theoretical Navarro-Frenk-White models and to simulated cluster lensing profiles, including complications such as cluster substructure, projected large-scale structure, and Eddington bias. We find evidence of underestimation in the X-ray masses, as expected, with $\langle M_{\mathrm{X}}/M_{\mathrm{WL}}\rangle = 0.75 \pm 0.07$ stat. $\pm 0.05$ sys. for our best-fit model. The biases in cosmological parameters in a typical cluster abundance measurement that ignores this mass bias will typically exceed the statistical errors.Comment: 13 pages, 5 figures. Revised to address referee comment

Competition and Innovation: An Inverted U Relationship

This paper investigates the relationship between product market competition (PMC) and innovation. A growth model is developed in which competition may increase the incremental profit from innovating; on the other hand, competition may also reduce innovation incentives for laggards. There are four key predictions. First, the relationship between product market competition (PMC) and innovation is an inverted U-shape. Second, the equilibrium degree of technological neck-and-neckness' among firms should decrease with PMC. Third, the higher the average degree of neck-and-neckness' in an industry, the steeper the inverted-U relationship. Fourth, firms may innovate more if subject to higher debt-pressure, especially at lower levels of PMC. We confront these predictions with data on UK firms' patenting activity at the US patenting office. They are found to accord well with observed behavior.

Competition and innovation: an inverted U relationship

This paper investigates the relationship between product market competition (PMC) and innovation. A Schumpeterian growth model is developed in which firms innovate ѳtep-by-stepҬ and where both technological leaders and their followers engage in R&D activities. In this model, competition may increase the incremental profit from innovating; on the other hand, competition may also reduce innovation incentives for laggards. This model generates four main predictions which we test empirically. First, the relationship between product market competition (PMC) and innovation is an inverted U-shape: the escape competition effect dominates for low initial levels of competition, whereas the Schumpeterian effect dominates at higher levels of competition. Second, the equilibrium degree of technological Ѯeck-and-neckness' among firms should decrease with PMC. Third, the higher the average degree of Ѯeck-and-neckness' in an industry, the steeper the inverted-U relationship between PMC and innovation in that industry. Fourth, firms may innovate more if subject to higher debt-pressure, especially at lower levels of PMC. We confront these four predictions with a new panel data set on UK firms' patenting activity at the US patenting office. The inverted U relationship, the neck and neck, and the debt pressure predictions are found to accord well with observed behavior in the data.