Automated Author ProfileMncube, Keaoleboga
University of Pretoria0000-0003-1652-3829
Mncube, Keaoleboga
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: 1.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The objective of the thesis is to analyse and understand the interaction between the banking sector and the economy in South Africa. To do so, we evaluate the historical evolution of productivity in the South African banking industry in chapter 2, by calculating a measure of productivity through a descriptive exercise. In chapter 3, we introduce labour dynamics of the banking industry by developing a model that links the productivity of the banking sector and macroeconomic outcomes. In chapter 4, we analyse how banking sector regulation affects the relationship between the banking sector and the macroeconomy and the contribution of banking sector regulation in determining efficiency of the sector.
Authors
- Mncube, Keaoleboga
The objective of the thesis is to analyse and understand the interaction between the banking sector and the economy in South Africa. To do so, we evaluate the historical evolution of productivity in the South African banking industry in chapter 2, by calculating a measure of productivity through a descriptive exercise. In chapter 3, we introduce labour dynamics of the banking industry by developing a model that links the productivity of the banking sector and macroeconomic outcomes. In chapter 4, we analyse how banking sector regulation affects the relationship between the banking sector and the macroeconomy and the contribution of banking sector regulation in determining efficiency of the sector.
Authors
- Mncube, Keaoleboga