This article combines all available data to produce pretax and post-tax income inequality series in 26 European countries from 1980 to 2017. Our estimates are consistent with macroeconomic growth and comparable with US distributional national accounts. Inequality grew in nearly all European countries, but much less than in the US. Contrary to a widespread view, we demonstrate that Europe’s lower inequality levels cannot be explained by more equalizing tax and transfer systems. After accounting for indirect taxes and in-kind transfers, the US redistributes a greater share of national income to low-income groups than any European country. “Predistribution,” not “redistribution,” explains why Europe is less unequal than the United States. (JEL D31, E01, H23, H24, H50, I38)
Household surveys often fail to capture the top tail of income and wealth distributions, as evidenced by studies based on tax data. Yet to date there is no consensus on how to best reconcile both sources of information, given the multiple biases at play. This paper contributes a novel method, rooted in standard calibration theory, to directly confront the problem of survey non-response between survey micro-data and anonymous tax data under reasonable assumptions. Our key innovation is to endogenously determine a "merging point" between the datasets, above which we start to incorporate information from tax data into the survey, under the assumption that the rate of representativeness is constant, then decreasing with income. This is followed by a "reweighting" and a "replacing" step, which preserves the microdata structure of the original survey, assuming no re-ranking of observations. We illustrate our approach with simulations, which show that our method is robust to the existence of income misreporting, and performs better than alternative methods. We also apply it to real data from five countries, both developed and less developed, finding changes to the levels and trends in income inequality. We discuss several limits to our approach and suggest some guidelines for future research.
We define generalized Pareto curves as the curve of inverted Pareto coe cients b(p), where b(p) is the ratio between average income or wealth above rank p and the p-th quantile Q(p) (i.e. b(p) = E[X|X > Q(p)]/Q(p)). We use them to characterize entire distributions, including places like the top where power laws are a good description, and places further down where they are not. We develop a method to nonparametrically recover the entire distribution based on tabulated income or wealth data as is generally available from tax authorities, which produces smooth and realistic shapes of generalized Pareto curves. Using detailed tabulations from quasi-exhaustive tax data, we demonstrate the precision of our method both empirically and analytically. It gives better results than the most commonly used interpolation techniques. Finally, we use Pareto curves to identify recurring distributional patterns, and connect those findings to the existing literature that explains observed distributions by random growth models.
Abstract-Fibre Bragg Grating (FBG) sensors are expected to provide valuable data in extreme radiation environments associated with nuclear research reactors. However, when the fast neutron fluence reaches 10 18 to 10 19 n/cm², the radiation induced changes in the material density and refractive index may drastically bias the measurements. The present study evaluates the radiation effect on the FBG performances by comparing their properties before and after their exposure to fast neutron fluences exceeding 10 19 n/cm² (E > 1 MeV). We studied responses of FBGs manufactured by three different laboratories in the same single-mode optical fibre but using different inscription conditions. The Bragg wavelength and the reflectivity were measured before and after irradiation thanks to a dedicated mounting. For nearly all FBGs, the Bragg peak remains visible after the irradiation while the radiation-induced Bragg wavelength shifts (RI-BWS) vary from a few pm (equivalent temperature error < 1°C) to nearly 1 nm (~100°C error) depending of the FBG inscription conditions. Such high RI-BWSs can be explained by the huge refractive-index variation and compaction observed for bare fibre samples through other experimental techniques. Our results show that by using specific hardening techniques the FBG-based temperature measurements in a nuclear research reactor experiment may become feasible.
A generalized Pareto curve is defined as the curve of inverted Pareto coefficients b(p), where b(p) is the ratio between average income or wealth above rank p and the p-th quantile. We present this concept and show how it can be used to better estimate distributions, especially from tax tabulations. By providing a simple decomposition of top shares, we discuss how studying inverted Pareto coefficients can improve the understanding of inequality dynamics. We also show how it helps to better analyze wealth and income concentrations along the distribution, using data for France, Spain, the United States, and China.
The potential of sol–gel-based optical sensors is investigated for applications in the aerospace domain. To this aim, a low-cost and non-intrusive sol–gel sensor based on waveguides, arranged as a 2D matrix structure, is fabricated by UV photolithography for delamination and damage detection. Two different organic–inorganic sol–gels were selected to fabricate the photonic device: TiO2–SiO2 and ZrO2–SiO2, acting as the waveguide core and the cladding, respectively. A systematic study was performed to determine the manufacturing parameters controlling their properties. The results show that large surfaces can be functionalized via sol–gel methods using the direct laser-writing approach. The structures are characterized in terms of refractive index, and the guiding properties were investigated through simulations and experiments, indicating an excellent behavior regarding the light guidance in a straight waveguide or in the 2D matrix structure grid. Additionally, preliminary tests show that the presence of impact can be easily detected after damage through the induced optical losses on large surfaces. This proof of concept sensor is a promising tool for structural health monitoring. To achieve the ultimate goal, the integration of this photonic sensor will be later performed on aircraft wings.
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