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