Technical change and superstar effects: evidence from the roll-out of television

"Superstar effects" generate large compensation differentials among similarly talented individuals. Are superstar effects amplified by technological innovations that extend the scale over which talent is deployed? I test this idea in the market for entertainers, using the roll-out of television as a natural experiment which provides clean variation in a scale-related technological change. The launch of a local TV station increases top entertainers' incomes, resulting in a twofold increase in top-percentile income share, while reducing employment and incomes of lower-level talents. These results show clear evidence of superstar effects and are inconsistent with canonical models of skill-biased technological change

The rise of TV shows how technological change can lead to superstar wages for some and low wages for most others

New technologies can open markets and amplify differences in talent to produce big differences in incomes. In new research, Felix Koenig looks at the effect of the introduction of television on entertainers' wages. He finds that in communities where television first launched, especially those with greater competition for talent, entertainers' salaries became much more unequally distributed. A small number of top earners benefited greatly, while demand declined for most workers

​SEED:​ ​Towards​ ​a​ ​Shared​ ​Evaluation​ ​Environment​ ​for​ ​Software-Defined-Networking Applications

Software-Defined-Networking (SDN) is an ongoing topic in the networking-community. Despite this, the evaluation of SDN-applications is still a nontrivial task. Researches need to study the evaluation environment as well as create fitting scenarios. This process is time consuming and error prone. Furthermore, the issue of reproducibility is gaining traction in the community as many publications are not reproducible. We present SEED, a Shared Evaluation Environment for SDN-applications. SEED separates applications, scenarios and simulators from each other. For this, it leverages the OpenFlow interface and introduces a description format for simulation scenarios. These scenarios are parsed by an adapter interface for three supported simulators. SEED aids researchers by enabling easy reuse of scenarios and by addressing simulators with a unified interface. Further, a clear experiment specification aids to simplify reproducibility

Importing inequality: immigration and the top 1 percent

In this paper we study the contribution of migrants to the rise in UK top incomes. Using administrative data on the universe of UK taxpayers we show migrants are over-represented at the top of the income distribution, with mi-grants twice as prevalent in the top 0.1% as anywhere in the bottom 97%. These high incomes are predominantly from labour, rather than capital, and migrants are concentrated in only a handful of industries, predominantly finance. Almost all (85%) of the growth in the UK top 1% income share over the past 20 years can be attributed to migration

Nodal phases in non-Hermitian wallpaper crystals

Symmetry and non-Hermiticity play pivotal roles in photonic lattices. While symmetries such as parity-time ($\mathcal{PT}$) symmetry have attracted ample attention, more intricate crystalline symmetries have been neglected in comparison. Here, we investigate the impact of the 17 wallpaper space groups of two-dimensional crystals on non-Hermitian band structures. We show that the non-trivial space group representations enforce degeneracies at high symmetry points and dictate their dispersion away from these points. In combination with either $\mathcal{T}$ or $\mathcal{PT}$, the symmorphic p4mm symmetry, as well as the non-symmorphic p2mg, p2gg, and p4gm symmetries, protect novel exceptional chains intersecting at the pertinent high symmetry points.Comment: 6 pages, 2 figure

Trust in hybrid human‐automated decision‐support

Research has examined trust in humans and trust in automated decision support. Although reflecting a likely realization of decision support in high‐risk tasks such as personnel selection, trust in hybrid human‐automation teams has thus far received limited attention. In two experiments (N1 = 170, N2 = 154) we compare trust, trustworthiness, and trusting behavior for different types of decision‐support (automated, human, hybrid) across two assessment contexts (personnel selection, bonus payments). We additionally examined a possible trust violation by presenting one group of participants a preselection that included predominantly male candidates, thus reflecting possible unfair bias. Whereas fully‐automated decisions were trusted less, results suggest that trust in hybrid decision support was similar to trust in human‐only support. Trust violations were not perceived differently based on the type of support. We discuss theoretical (e.g., trust in hybrid support) and practical implications (e.g., keeping humans in the loop to prevent negative reactions)