The Cherenkov Telescope Array (CTA) is a new observatory for very high-energy (VHE) gamma rays. CTA has ambitions science goals, for which it is necessary to achieve full-sky coverage, to improve the sensitivity by about an order of magnitude, to span about four decades of energy, from a few tens of GeV to above 100 TeV with enhanced angular and energy resolutions over existing VHE gamma-ray observatories. An international collaboration has formed with more than 1000 members from 27 countries in Europe, Asia, Africa and North and South America. In 2010 the CTA Consortium completed a Design Study and started a three-year Preparatory Phase which leads to production readiness of CTA in 2014. In this paper we introduce the science goals and the concept of CTA, and provide an overview of the project. ?? 2013 Elsevier B.V. All rights reserved

This paper provides new evidence of occupational closure and rent-sharing in the labour market. In many labour market segments, occupational closure refers only to self-employed positions, but not to employees within these occupations. We study the relation of changes in entry regulation for firms and the corresponding economic consequences for employees within these firms. Based on bargaining theory, we argue that economic rents are shared with employees. In order to identify this 'indirect' channel of occupational closure, this paper uses a major reform in the German craft sector in 2004. This reform relaxes entry regulation into self-employment in more than half of the craft occupations. By using rich administrative data in a fixed-effects framework, we compare wages of employees in both markets pre-and postreform. We find that employees in the reformed market are negatively affected after the reform. This proves the existence of former wage rents due to rent-sharing in closed market segments. This average wage effect, however, is not constant for all employees. If employees can make a credible threat to the employer to take advantage of deregulation and set up their own business, they can counteract the negative wage effects of the reform. As a consequence, our empirical results show that wages of young and skilled employees are less affected by the reform.

The identification of unconditional quantile treatment effects (QTE) has become increasingly popular within social sciences. However, current methods to identify unconditional QTEs of continuous treatment variables are incomplete. Contrary to popular belief, the unconditional quantile regression model introduced by Firpo, Fortin, and Lemieux (2009) does not identify QTE, while the propensity score framework of Firpo (2007) allows for only a binary treatment variable, and the generalized quantile regression model of Powell (2020) is unfeasible with high-dimensional fixed effects. This paper introduces a two-step approach to estimate unconditional QTEs where the treatment variable is first regressed on the control variables followed by a quantile regression of the outcome on the residualized treatment variable. Unlike much of the literature on quantile regression, this two-step residualized quantile regression framework is easy to understand, computationally fast, and can include high-dimensional fixed effects.

People’s occupations are strongly related to multiple dimensions of inequality, such as inequalities in wages, health, autonomy, or risk of temporary employment. The theories and mechanisms linking occupations to these inequalities are subject to debate. We review the recent evidence on the relationship between occupations and inequality and discuss the following four overarching theoretical perspectives: occupations and skills, occupations and tasks, occupations and institutions, and occupations and culture. We show that each perspective has strong implications for how scholars conceptualize occupations and which occupational characteristics are seen as relevant when explaining inequalities. Building on this, we review and critically examine the relevant theories related to and the mechanisms of the relationship between occupation and wage inequality, as an example. We conclude that there is sound empirical knowledge available on the relationships between occupations and inequality; however, some of the mechanisms are still unclear.

The unconditional quantile regression (UQR) model – which has gained increasing popularity in the 2010s and is regularly applied in top-rated academic journals within sociology and other disciplines – is poorly understood and frequently misinterpreted. The main reason for its increased popularity is that the UQR model seemingly tackles an issue with the traditional conditional quantile regression (CQR) model: the interpretation of coefficients as quantile treatment effects changes whenever control variables are included. However, the UQR model was not developed to solve this issue but to study influences on quantile values of the overall outcome distribution. This paper clarifies the crucial conceptual distinction between influences on overall distributions, which we term population-level influences, and individual-level quantile treatment effects. Further, we use data simulations to illustrate that various classes of quantile regression models may, in some instances, give entirely different conclusions (to different questions). The conceptual and empirical distinctions between various quantile regression models underline the need to match the correct quantile regression model to the specific research questions. We conclude the paper with some practical guidelines for researchers.