11,351 research outputs found

    Issues in the design and implentation of an R&D tax credit for the UK

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    R&D tax credits have become a popular policy tool for encouraging research and development (R&D) spending by business, with many countries offering subsidies of this form. The divergence between private and social rates of return to R&D expenditure by private firms provides one of the main justifications for government subsidies to R&D.2 In order to achieve the optimal level of R&D investment, government policy aims to bring private incentives in line with the social rate of return. An R&D tax credit does this by reducing the cost to the firm of doing R&D. Recent empirical evidence suggests that R&D tax credits are an effective instrument in stimulating additional R&D. However, in order to be desirable, a policy needs to be cost-effective and implementable. This Briefing Note reviews some of the major issues in the design and implementation of R&D tax credits. In Section 2, we briefly discuss the existing tax treatment of R&D in the UK. In particular, we outline the new Research and Development Allowance - which is an allowance for expenditure on plant, machinery and buildings for use in scientific research and which is available to firms of all sizes - and the tax credit for R&D that is available to small and medium-sized enterprises (SMEs). We then discuss, in Section 3, some of the main design features of tax credits that have been implemented in other countries. The discussion mainly concerns the question of how to target new or incremental R&D so as to keep down the total exchequer cost. We discuss problems that arise in defining incremental R&D and how these can be tackled. In Section 4, we provide estimates of the amount of new R&D and the exchequer cost that would be likely to result from implementing different designs of R&D tax credit in the UK. Section 5 concludes. Some technical details are dealt with in the Appendix

    Scaffolds and Generalized Integral Galois Module Structure

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    Let L/KL/K be a finite, totally ramified pp-extension of complete local fields with residue fields of characteristic p>0p > 0, and let AA be a KK-algebra acting on LL. We define the concept of an AA-scaffold on LL, thereby extending and refining the notion of a Galois scaffold considered in several previous papers, where L/KL/K was Galois and A=K[G]A=K[G] for G=Gal(L/K)G=\mathrm{Gal}(L/K). When a suitable AA-scaffold exists, we show how to answer questions generalizing those of classical integral Galois module theory. We give a necessary and sufficient condition, involving only numerical parameters, for a given fractional ideal to be free over its associated order in AA. We also show how to determine the number of generators required when it is not free, along with the embedding dimension of the associated order. In the Galois case, the numerical parameters are the ramification breaks associated with L/KL/K. We apply these results to biquadratic Galois extensions in characteristic 2, and to totally and weakly ramified Galois pp-extensions in characteristic pp. We also apply our results to the non-classical situation where L/KL/K is a finite primitive purely inseparable extension of arbitrary exponent that is acted on, via a higher derivation (but in many different ways), by the divided power KK-Hopf algebra.Comment: Further minor corrections and improvements to exposition. Reference [BE] updated. To appear in Ann. Inst. Fourier, Grenobl

    Ciproxifan, an H~3~ Receptor Antagonist, Improves Learning and Memory in the APP Mouse Model of Alzheimer's Disease

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    Mice that express the mutant form of the human amyloid precursor gene associated with early-onset familial Alzheimer's disease demonstrate memory deficits and amyloid plaques. We show here that ciproxifan, a prototypical antagonist of H~3~-type histamine receptors, alleviates two types of learning and memory impairments in such mice. These data support the idea that modulation of H~3~ receptors represents a viable therapeutic strategy in the treatment of Alzheimer's disease

    Competition and innovation: an inverted U relationship

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    This paper investigates the relationship between product market competition (PMC) and innovation. A Schumpeterian growth model is developed in which firms innovate ‘step-by-step’, 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 ‘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 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

    Competition and innovation: an inverted U relationship?

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    This paper investigates the relationship between product market competition and innovation. It uses the radical policy reforms in the UK as instruments for changes in product market competition, and finds a robust inverted-U relationship between competition and patenting. It then develops an endogenous growth model with step-by-step innovation that can deliver this inverted-U pattern. In this model, competition has an ambiguous effect on innovation. On the one hand, it discourages laggard firms from innovating, as it reduces their rents from catching up with the leaders in the same industry. On the other hand, it encourages neck-and-neck firms to innovate in order to escape competition with their rival. The inverted-U pattern results from the interplay between these two effects, together with the effect of competition on the equilibrium industry structure. The model generates two additional predictions: on the relationship between competition and the average technological distance between leaders and followers across industries; and on the relationship between the distance of an industry to its technological frontier and the steepness of the inverted-U. Both predictions are supported by the data

    Persistence of Regional Unemployment: Application of a Spatial Filtering Approach to Local Labour Markets in Germany

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    The geographical distribution and persistence of regional/local unemployment rates in heterogeneous economies (such as Germany) have been, in recent years, the subject of various theoretical and empirical studies. Several researchers have shown an interest in analysing the dynamic adjustment processes of unemployment and the average degree of dependence of the current unemployment rates or gross domestic product from the ones observed in the past. In this paper, we present a new econometric approach to the study of regional unemployment persistence, in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment. First, we propose an econometric procedure suggesting the use of spatial filtering techniques as a substitute for fixed effects in a panel estimation framework. The spatial filter computed here is a proxy for spatially distributed region-specific information (e.g., the endowment of natural resources, or the size of the ‘home market’) that is usually incorporated in the fixed effects parameters. The advantages of our proposed procedure are that the spatial filter, by incorporating region-specific information that generates spatial autocorrelation, frees up degrees of freedom, simultaneously corrects for time-stable spatial autocorrelation in the residuals, and provides insights about the spatial patterns in regional adjustment processes. We present several experiments in order to investigate the spatial pattern of the heterogeneous autoregressive parameters estimated for unemployment data for German NUTS-3 regions. We find widely heterogeneous but generally high persistence in regional unemployment rates.

    Parental engagement on student academic self-efficacy and educational attainment expectation for immigrant youth.

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    With the increase of immigration to the United States, immigrant children have a unique position in the education system. Immigrant parents influence their children through different academic engagement practices. It is important to understand how parents impact students\u27 academic experiences. Employing the Educational Longitudinal Study of 2002, statistical analyses evaluated a sample of 2,514 high school sophomore immigrant students. The impact of parental engagement on the dependent variables were also compared between native language groups to learn whether or not specific cultural engagement practices impact student self-efficacy and attainment expectation differently. Findings revealed that parental engagement impacts academic self-efficacy and educational attainment expectation. Native language group differences indicated that the impact of parental engagement on the dependent variables was often greater for the Asian groups than Spanish and English speaking immigrants. Educators can use the information gained from this study to help immigrant parents improve their children\u27s academic experiences

    Computational Studies of Small Molecule Activation in Catylsis and Green Chemistry

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    Thermal activation of rupture and slow crack growth in a model of homogenous brittle materials

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    Slow crack growth in a model of homogenous brittle elastic material is described as a thermal activation process where stress fluctuations allow to overcome a breaking threshold through a series of irreversible steps. We study the case of a single crack in a flat sheet for which analytical predictions can be made, and compare them with results from the equivalent problem of a 2D spring network. Good statistical agreement is obtained for the crack growth profile and final rupture time. The specific scaling of the energy barrier with stress intensity factor appears as a consequence of irreversibility. In addition, the model brings out a characteristic growth length whose physical meaning could be tested experimentally.Comment: To be published in : Europhysics Letter
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