World Bank GovTech Dataset (October 2022) extraction for GTMI question

File: WBG_GovTech Dataset_Oct2022.xlsx

Sheet Stats relevant fields: Economy, Code, Reg (region), Borr (borrower type).

Filter used for countries in Africa that borrowed only from IBRD: Reg=AFR and Borr=IBRD.

Filtered countries count: 9

Filtered country rows (from Stats):

Angola | Code=AGO | Reg=AFR | Borr=IBRD

Botswana | Code=BWA | Reg=AFR | Borr=IBRD

Equatorial Guinea | Code=GNQ | Reg=AFR | Borr=IBRD

Eswatini | Code=SWZ | Reg=AFR | Borr=IBRD

Gabon | Code=GAB | Reg=AFR | Borr=IBRD

Mauritius | Code=MUS | Reg=AFR | Borr=IBRD

Namibia | Code=NAM | Reg=AFR | Borr=IBRD

Seychelles | Code=SYC | Reg=AFR | Borr=IBRD

South Africa | Code=ZAF | Reg=AFR | Borr=IBRD

 

2020 GovTech Enablers Index (GTEI) values from sheet CG_GTMI_Data (Year=2020, columns Economy/Code/GTEI):

Angola | Code=AGO | GTEI_2020=0.379951

Botswana | Code=BWA | GTEI_2020=0.330272

Equatorial Guinea | Code=GNQ | GTEI_2020=0.087348

Eswatini | Code=SWZ | GTEI_2020=0.226807

Gabon | Code=GAB | GTEI_2020=0.295597

Mauritius | Code=MUS | GTEI_2020=0.504043

Namibia | Code=NAM | GTEI_2020=0.261226

Seychelles | Code=SYC | GTEI_2020=0.337639

South Africa | Code=ZAF | GTEI_2020=0.842993