Automated Author ProfileMontenovo, Laura
Montenovo, Laura
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: 1.5 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This paper studies employment outcomes during the early stages of the COVID-19 pandemic across eight countries exhibiting different case levels and policy responses: the United States, Australia, France, Denmark, Italy, South Korea, Spain, and Sweden. While the proportion of people not-at-work increased in all countries, safety net policies seem to influence whether people remained employed-but-absent from work as opposed to becoming unemployed or leaving the labor force. We find large employment decreases among young workers and those who only have a high school degree, and increased labor market disparities in countries with the largest declines in employment. A variety of evidence suggests labor demand was a larger driver of employment declines than labor supply and that stringent social distancing policies reduce employment even in the absence of high case numbers. Job characteristics - the importance of face-to-face interactions and the ability to work remotely - were closely related to changes in labor market outcomes.
Authors
- Breunig, Robert ;
- Cheng, Wei ;
- Lee, Kyoung Hoon ;
- Montenovo, Laura ;
- Weinberg, Bruce ;
- Zhang, Yinjunjie
This paper studies employment outcomes during the early stages of the COVID-19 pandemic across eight countries exhibiting different case levels and policy responses: the United States, Australia, France, Denmark, Italy, South Korea, Spain, and Sweden. While the proportion of people not-at-work increased in all countries, safety net policies seem to influence whether people remained employed-but-absent from work as opposed to becoming unemployed or leaving the labor force. We find large employment decreases among young workers and those who only have a high school degree, and increased labor market disparities in countries with the largest declines in employment. A variety of evidence suggests labor demand was a larger driver of employment declines than labor supply and that stringent social distancing policies reduce employment even in the absence of high case numbers. Job characteristics - the importance of face-to-face interactions and the ability to work remotely - were closely related to changes in labor market outcomes.
Authors
- Breunig, Robert ;
- Cheng, Wei ;
- Lee, Kyoung Hoon ;
- Montenovo, Laura ;
- Weinberg, Bruce ;
- Zhang, Yinjunjie
This archive contains replication data and code for "TAre Charitable Donations and Volunteering Substitutes or Complements? New Evidence from Recent Tax Changes", published in the National Tax Journal.
Authors
- Montenovo, Laura