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Add overall aid descriptions Djibouti

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Marty Oehme 2022-09-07 18:01:29 +02:00
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_drivers-of-inequality-djibouti.qmd
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@ -151,6 +151,21 @@ fig.show()
Note: Values shown are for all Official Development Assistance flows valid under the OECD CRS data, split into the type of financing flow, calculated as constant currency (2020 corrected) USD millions.
Source: Author's elaboration based on OECD ODA CRS (2022).
The amount of Official Development Assistance to Djibouti has generally been increasing since 2011,
first steadily and, since 2017, more rapidly, as can be seen in @fig-dji-aid-financetype.
With just under 150m USD in assistance contributions 2011 and just over 320m USD at its peak in 2020,
Djibouti has received less overall ODA funds than the other countries surveyed in this study.
The primary type of development assistance provided are grants, with loans making up between half and one third of the absolute grant amount in USD between 2011 and 2020.
Grants have trended slowly upwards from just over 100m USD in 2011 to 135m in 2014,
before fluctuating around this level until 2017,
and finally increasing more significantly to over 200m USD in 2020.
Loans had a more significant jump earlier, from there relatively stagnant level of under 40m USD in 2014 to 80m USD in 2015,
with a similarly significant jump from 2018 to 2019,
before decreasing slightly again to just over 110m in 2020.
While largely comprising less than 10m USD until 2018,
other official flows (non-export credits) had a large increase to over 75m USD in 2019,
be decreasing almost as significantly again the following year.
```{python}
#| label: fig-dji-aid-donortype
#| fig-cap: "Total ODA for Djibouti per year, separated by donor type"
@ -178,24 +193,15 @@ fig.show()
Note: Values shown are for all Official Development Assistance flows valid under the OECD ODA data, split into bilateral development donor countries (dac) and multilateral donors (mlt), as constant currency (2020 corrected) USD millions.
Source: Author's elaboration based on OECD ODA CRS (2022).
```{python}
#| label: tbl-dji-aid-electricity
#| tbl-cap: "ODA for transmission and distribution of electric power in Djibouti per year, separated by financing type"
#| column: page
totals = df.loc[
((df['SECTOR'] == 23630) | (df['SECTOR'] == 23631)) & # Total
(df['CHANNEL'] == 100) &
(df['AMOUNTTYPE'] == 'D') &
((df['FLOW'] == 11) | (df['FLOW'] == 13)) & # Total
(df['FLOWTYPE'] == 112) &
(df['AIDTYPE'] == "100") # contains mixed int and string representations
]
electricityaid = totals[totals['DONOR'] < 20000] # drop all 'total' aggregations
The primary donor type of development assistance to Djibouti has been through bilateral donors for the majority of time between 2011 and 2020,
see @fig-dji-aid-donortype.
While bilateral contributions have been consistently around 100m USD,
multilateral contributions slowly increased from 45m USD in 2011 to just under 70m USD 2016.
This situation changed, however, with both types of contributions increasing more significantly in 2018 and 2019.
The multilateral contribution of 108m USD in 2019 is larger than the previous year's bilateral contributions (104m USD),
though those equally rose significantly to almost 160m USD in 2019.
While the bilateral contributions spiked in 2019 before falling to 130m USD the following year,
multilateral contributions kept increasing significantly to over 170m USD in 2020.
For the first time in 2020, then, multilateral contributions provided a significantly larger share of development assistance to Djibouti than bilateral contributions,
a trend which may move even further apart if bilateral contributions keep decreasing while multilateral ones increase.
el_grouped = electricityaid.groupby(['Year', 'Flow']).agg({'Value': ['sum']})
el_grouped.style.format(escape="latex")
el_grouped
```
Note: Values shown are for all Official Development Assistance flows valid under the OECD CRS data, split into the type of financing flow, calculated as constant currency (2020 corrected) USD millions. The category under analysis is Electric Power transmission and distribution (centralized grids) within the data.
Source: Author's elaboration based on OECD ODA CRS (2022).