Automated Author ProfileMobius, Markus M.
Mobius, Markus M.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
We decompose the beauty premium in an experimental labor market where "employers" determine wages of "workers" who perform a maze-solving task. This task requires a true skill which we show to be unaffected by physical attractiveness. We find a sizable beauty premium and can identify three transmission channels: (a) physically attractive workers are more confident and higher confidence increases wages; (b) for a given level of confidence, physically attractive workers are (wrongly) considered more able by employers; (c) controlling for worker confidence, physically attractive workers have oral skills (such as communication and social skills) that raise their wages when they interact with employers. Our methodology can be adopted to study the sources of discriminatory pay differentials in other settings.
Authors
- Mobius, Markus M. ;
- Rosenblat, Tanya S.
We decompose the beauty premium in an experimental labor market where "employers" determine wages of "workers" who perform a maze-solving task. This task requires a true skill which we show to be unaffected by physical attractiveness. We find a sizable beauty premium and can identify three transmission channels: (a) physically attractive workers are more confident and higher confidence increases wages; (b) for a given level of confidence, physically attractive workers are (wrongly) considered more able by employers; (c) controlling for worker confidence, physically attractive workers have oral skills (such as communication and social skills) that raise their wages when they interact with employers. Our methodology can be adopted to study the sources of discriminatory pay differentials in other settings.
Authors
- Mobius, Markus M. ;
- Rosenblat, Tanya S.