Equilibrium Search and Tax Credit Reform

An empirical equilibrium job search model with wage posting is developed to analyze the labor market impact of UK tax reforms. The model allows for a rich characterization of the labor market, with hours responses, accurate representations of the tax and transfer system, and both worker and firm heterogeneity. The model is estimated with pre-reform longitudinal survey data using a semi-parametric estimation technique, and the impact of actual tax reform policies is simulated. The model predicts that the British Working Families’ Tax Credit and contemporaneous reforms increased employment, with equilibrium effects found to play a relatively minor role.Labour market equilibrium, job search, wage dispersion, unemployment, monopsony, incidence, tax credits

Employment, Hours of Work and the Optimal Taxation of Low Income Families

The optimal design of low income support is examined using a structural labour supply model. The approach incorporates unobserved heterogeneity, fixed costs of work, childcare costs and the detailed non-convexities of the tax and transfer system. The analysis considers purely Pareto improving reforms and also optimal design under social welfare functions with different degrees of inequality aversion. We explore the gains from tagging and also examine the case for the use of hours-contingent payments. Using the tax schedule for lone parents in the UK as our policy environment, the results point to a reformed non-linear tax schedule with tax credits only optimal for low earners. The results also suggest a welfare improving role for tagging according to child age and for hours-contingent payments, although the case for the latter is mitigated when hours cannot be monitored or recorded accurately by the tax authorities.childcare costs, low income support, taxation

Employment, hours of work and the optimal taxation of low income families

This paper examines the tax schedule for low income families with children. We take an optimal tax approach based on a structural labour supply model which incorporates unobserved heterogeneity, fixed costs of work, childcare costs and the detailed non-convexities of the tax and transfer system. The motivation is the British earned income tax credit reform (WFTC) and its interaction with the tax and transfer system for lone parents. Our analysis also examines the case for the use of hours-contingent payments. The results point to a tax schedule which depends on the age of children, with tax credits only optimal for low earners with school age children. The results also suggest a welfare improving role for hours-contingent payments although this is mitigated when hours cannot be monitored or recorded accurately by the tax authorities.

The Links between Income Distribution and Poverty Reduction in Britain

human development, aid, trade, security

Financial work incentives in Britain: comparisons over time and between family types

This paper reviews various techniques for quantifying financial incentives to work, shows how financial work incentives have changed across the population since 1979, and estimates how much of these changes are due to changes in the tax and benefit system.

Semi-automated detection of eagle nests: an application of very high-resolution image data and advanced image analyses to wildlife surveys

Very high-resolution (VHR) image data, including from unmanned aerial vehicle (UAV) platforms, are increasingly acquired for wildlife surveys. Animals or structures they build (e.g. nests) can be photointerpreted from these images, however, automated detection is required for more efficient surveys. We developed semi-automated analyses to map white-bellied sea eagle (Haliaeetus leucogaster) nests in VHR aerial photographs of the Houtman Abrolhos Islands, Western Australia, an important breeding site for many seabird species. Nest detection is complicated by high environmental heterogeneity at the scale of nests (~1–2 m), the presence of many features that resemble nests and the variability of nest size, shape and context. Finally, the rarity of nests limits the availability of training data. These challenges are not unique to wildlife surveys and we show how they can be overcome by an innovative integration of object-based image analyses (OBIA) and the powerful machine learning one-class classifier Maxent. Maxent classifications using features characterizing object texture, geometry and neighborhood, along with limited object color information, successfully identified over 90% of high quality nests (most weathered and unusually shaped nests were also detected, but at a slightly lower rate) and labeled <2% of objects as candidate nests. Although this overestimates the occurrence of nests, the results can be visually screened to rule out all but the most likely nests in a process that is simpler and more efficient than manual photointerpretation of the full image. Our study shows that semi-automated image analyses for wildlife surveys are achievable. Furthermore, the developed strategies have broad relevance to image processing applications that seek to detect rare features differing only subtly from a heterogeneous background, including remote sensing of archeological remains. We also highlight solutions to maximize the use of imperfect or uncalibrated image data, such as some UAV-based imagery and the growing body of VHR imagery available in Google Earth and other virtual globes

Nanosecond laser texturing for high friction applications

AbstractA nanosecond pulsed Nd:YAG fibre laser with wavelength of 1064nm was used to texture several different steels, including grade 304 stainless steel, grade 316 stainless steel, Cr–Mo–Al ‘nitriding’ steel and low alloy carbon steel, in order to generate surfaces with a high static friction coefficient. Such surfaces have applications, for example, in large engines to reduce the tightening forces required for a joint or to secure precision fittings easily. For the generation of high friction textures, a hexagonal arrangement of laser pulses was used with various pulse overlaps and pulse energies. Friction testing of the samples suggests that the pulse energy should be high (around 0.8mJ) and the laser pulse overlap should be higher than 50% in order to achieve a static friction coefficient of more than 0.5. It was also noted that laser processing increases the surface hardness of samples which appears to correlate with the increase in friction. Energy-Dispersive X-ray spectroscopy (EDX) measurements indicate that this hardness is caused by the formation of hard metal-oxides at the material surface

On the need to consider wood formation processes in global vegetation models and a suggested approach

Dynamic global vegetation models are key tools for interpreting and forecasting the responses of terrestrial ecosystems to climatic variation and other drivers. They estimate plant growth as the outcome of the supply of carbon through photosynthesis. However, growth is itself under direct control, and not simply controlled by the amount of available carbon. Therefore predictions by current photosynthesis driven models of large increases in future vegetation biomass due to increasing concentrations of atmospheric CO2 may be significant over-estimations. We describe how current understanding of wood formation can be used to reformulate global vegetation models, with potentially major implications for their behaviour

Neurocognitive and observational markers: prediction of autism spectrum disorder from infancy to mid-childhood

Background Prospective studies of infants at high familial risk for autism spectrum disorder (ASD) have identified a number of putative early markers that are associated with ASD outcome at 3 years of age. However, some diagnostic changes occur between toddlerhood and mid-childhood, which raises the question of whether infant markers remain associated with diagnosis into mid-childhood. Methods First, we tested whether infant neurocognitive markers (7-month neural response to eye gaze shifts and 14-month visual disengagement latencies) as well as an observational marker of emerging ASD behaviours (the Autism Observation Scale for Infants; AOSI) predicted ASD outcome in high-risk (HR) 7-year-olds with and without an ASD diagnosis (HR-ASD and HR-No ASD) and low risk (LR) controls. Second, we tested whether the neurocognitive markers offer predictive power over and above the AOSI. Results Both neurocognitive markers distinguished children with an ASD diagnosis at 7 years of age from those in the HR-No ASD and LR groups. Exploratory analysis suggested that neurocognitive markers may further differentiate stable versus lost/late diagnosis across the 3 to 7 year period, which will need to be tested in larger samples. At both 7 and 14 months, combining the neurocognitive marker with the AOSI offered a significantly improved model fit over the AOSI alone. Conclusions Infant neurocognitive markers relate to ASD in mid-childhood, improving predictive power over and above an early observational marker. The findings have implications for understanding the neurodevelopmental mechanisms that lead from risk to disorder and for identification of potential targets of pre-emptive intervention