The overall storyline is closely related to the TED talk by Dr. Dilip Ratha. (Link here.) In his talk, Dr Ratha highlights trends in growing remittance worldwide and its impact on global economic growth –especially with respect to under developed and developing countries. This paper utilizes tables to analyze publicly available World Bank data using tableau and establish numerically some of the inferences highlighted by Dr Ratha.
Source of Data
The source data required for this exercise is based on the data repository published on the World Bank site.
The following datasheets have been used in the analysis
- Net official development assistance and official aid received (current US$) (See here)
- World Development indicators (see here)
- World Governance indicators (see here)
The above data downloaded from three sources shall be reorganized for suitable processing in Tableau. In any case, no new data has be added or modified. The following changes have been made.
- The current World Bank data has Countries as rows and as many columns as the number of years in consideration i.e. 1960-2013. This table needed to be unrolled to have one row for each year for every country. This exercise was done for the following parameters.
- Countries Master (including region and income groups)
- Remittance data in USD
- Remittance data as % of GDP
- World bank aid to each country
- Economic stability index for each country
- Poverty Ratios
- In some of the source data sheets, the same country was spelt differently (use of special characters, spelling etc.).The corrections have been made to establish and ensure correct cross references
- Some of the source data sheets has aggregated data at region levels. These were given country codes like countries. Since our analysis is entirely at country level, the regional data has been removed