Do corporate taxes harm economic performance? Explaining distortions in R&D- and export-intensive UK firms

This paper analyzes the effects of corporate tax liability on firm-level total factor productivity (TFP) as the key driver of economic performance. This is a new dimension in the UK productivity puzzle that has not attracted attention so far. We use 6559 manufacturing firms over 2004–2011 to investigate whether higher levels of corporate tax affect the productivity catch-up process by reducing after-tax earnings that could alternatively be used for productivity-enhancing investment, particularly focusing on R&D- and export-intensive firms. Our key results are summarized as follows: first, higher levels of corporate taxation impact adversely on TFP and this finding is robust to different tax measures and insensitive to endogeneity bias; second, as R&D- and export-intensive firms tend to have relatively higher TFP growth, higher levels of tax liability as a share of earnings before interest and taxes decelerate TFP growth of these firms

Knowledge spillovers and output per worker: an industry-level analysis for OECD countries

This study analyzes the impact of knowledge spillovers on output per worker at the industry level using a primal production function approach. The article makes three different contributions to the international spillovers literature: (1) it identifies trade related spillovers under alternative assumptions regarding the information transferred through imports; (2) it explores the importance of horizontal and vertical foreign direct investment (FDI) in knowledge spillovers; and (3) it looks at how institutional factors determine the impact of FDI-related spillovers on productivity. The main findings of the study are: (1) international knowledge spillover is an important driver of industry output per worker, and the magnitude of this spillover effect varies with alternative assumptions about the information content embodied in imports, while high technology industries benefit significantly more from import-related knowledge spillovers; and (2) the gains from FDI spillovers are primarily horizontal, but when institutional factors are considered, countries with stronger protection of intellectual property rights and a high “ease of doing business” tend to experience a substantial increase in the effectiveness of both horizontal and vertical FDI-related spillover

Knowledge spillovers, absorptive capacity and growth: an industry-level analysis for OECD countries

Given the decline in growth momentum in the manufacturing sector in many OECD countries, the role of knowledge-based capital has emerged as a key driver for sustained growth. While empirical studies on estimating knowledge spillovers have usually been undertaken at the country level, the spillover effects can be more definitive only if the analysis is conducted at the industry-level. The effectiveness of international spillovers is conditional on recipient country’s absorptive capacity and this is an important component of the spillover mechanism that has not attracted significant attention so far. This paper therefore assesses the effect of spillovers in driving per capita output growth taking into account the role of absorptive capacity. Our main findings are first, the confirmation of the robust positive relationship between human capital and output growth for 14 OECD countries at industry level. Second, the gains from international spillover are conditional to the level of human capital and the degree of protection of intellectual property rights. Third, countries that improve absorptive capacity can potentially increase gains from spillovers via either trade or FDI (including vertical FDI). Finally, significant heterogeneity is found between high and low-tech industries. The former group is more effective in absorbing spillovers while the latter has failed to reach the critical level of technological advancement in order to absorb foreign and domestic knowledge

Quantum bound states for a derivative nonlinear Schrodinger model and number theory

A derivative nonlinear Schrodinger model is shown to support localized N-body bound states for several ranges (called bands) of the coupling constant eta. The ranges of eta within each band can be completely determined using number theoretic concepts such as Farey sequences and continued fractions. For N > 2, the N-body bound states can have both positive and negative momentum. For eta > 0, bound states with positive momentum have positive binding energy, while states with negative momentum have negative binding energy.Comment: Revtex, 7 pages including 2 figures, to appear in Mod. Phys. Lett.

Detection of the high energy cut-off from the Seyfert 1.5 galaxy NGC 5273

We perform the NuSTAR and Swift/XRT joint energy spectral fitting of simultaneous observations from the broad-line Seyfert 1.5 galaxy NGC 5273. When fitted with the combination of an exponential cut-off power-law and a reflection model, a high energy cut-off is detected at 143$^{+96}_{-40}$ keV with 2-sigma significance. Existence of such cut-off is also consistent with the observed Comptonizing electron temperature when fitted with a Comptonization model independently. We observe a moderate hard X-ray variability of the source over the time-scale of ~12 years using INTEGRAL/ISGRI observations in the energy range of 20-100 keV. When the hard band count rate (6-20 keV) is plotted against the soft band count rate (3-6 keV), a hard offset is observed. Our results indicate that the cut-off energy may not correlate with the coronal X-ray luminosity in a simple manner. Similarities in parameters that describe coronal properties indicate that the coronal structure of NGC 5273 may be similar to that of the broad-line radio galaxy 3C 390.3 and another galaxy MCG-5-23-16 where the coronal plasma is dominated by electrons, rather than electron-positron pairs. Therefore, the coronal cooling is equally efficient to the heating mechanism keeping the cut-off energy at low even at the low accretion rate.Comment: 11 pages, 6 figures, 1 table, accepted for publication in MNRA

Semiparametric Bayesian analysis of gene-environment interactions with error in measurement of environmental covariates and missing genetic data

Case-control studies are widely used to detect geneenvironment interactions in the etiology of complex diseases. Many variables that are of interest to biomedical researchers are difficult to measure on an individual level, e.g. nutrient intake, cigarette smoking exposure, long-term toxic exposure. Measurement error causes bias in parameter estimates, thus masking key features of data and leading to loss of power and spurious/masked associations. We develop a Bayesian methodology for analysis of case-control studies for the case when measurement error is present in an environmental covariate and the genetic variable has missing data. This approach offers several advantages. It allows prior information to enter the model to make estimation and inference more precise. The environmental covariates measured exactly are modeled completely nonparametrically. Further, information about the probability of disease can be incorporated in the estimation procedure to improve quality of parameter estimates, what cannot be done in conventional case-control studies. A unique feature of the procedure under investigation is that the analysis is based on a pseudo-likelihood function therefore conventional Bayesian techniques may not be technically correct. We propose an approach using Markov Chain Monte Carlo sampling as well as a computationally simple method based on an asymptotic posterior distribution. Simulation experiments demonstrated that our method produced parameter estimates that are nearly unbiased even for small sample sizes. An application of our method is illustrated using a population-based case-control study of the association between calcium intake with the risk of colorectal adenoma development

Classical diffusion of N interacting particles in one dimension: General results and asymptotic laws

I consider the coupled one-dimensional diffusion of a cluster of N classical particles with contact repulsion. General expressions are given for the probability distributions, allowing to obtain the transport coefficients. In the limit of large N, and within a gaussian approximation, the diffusion constant is found to behave as N^{-1} for the central particle and as (\ln N)^{-1} for the edge ones. Absolute correlations between the edge particles increase as (\ln N)^{2}. The asymptotic one-body distribution is obtained and discussed in relation of the statistics of extreme events.Comment: 6 pages, 2 eps figure