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Add overall aid contribution descriptions to Vietnam

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Marty Oehme 2022-09-07 15:16:35 +02:00
parent 039e676210
commit b1d6e141a6
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GPG key ID: B7538B8F50A1C800
1 changed files with 24 additions and 23 deletions
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_drivers-of-inequality-vietnam.qmd
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@ -199,13 +199,27 @@ financetotals_grouped = financetotals_grouped.reset_index(['Flow', 'Year'])
financetotals_grouped.columns = financetotals_grouped.columns.to_flat_index() financetotals_grouped.columns = financetotals_grouped.columns.to_flat_index()
financetotals_grouped.columns = ['Financetype', 'Year', 'Value'] financetotals_grouped.columns = ['Financetype', 'Year', 'Value']
fig = px.line(financetotals_grouped, x='Year', y='Value', color='Financetype', labels={"Value": "Development aid, in millions"}, markers=True, template="seaborn") fig = px.line(financetotals_grouped, x='Year', y='Value', color='Financetype', labels={"Value": "Development aid amount, in millions of USD"}, markers=True, template="seaborn")
fig.show() 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. 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). Source: Author's elaboration based on OECD ODA CRS (2022).
Official Development Assistance (ODA) to Vietnam reached its highest point in 2014 with almost 5bn USD but generally decreased in the intervening years, as can be seen in @fig-vnm-aid-financetype.
Decreasing continuously after 2014,
development assistance reached its lowest point of the last ten years in 2019 when it fell to just under 2.5bn USD,
before increasing slightly to just above 2.5bn USD in 2020.
Development aid to Vietnam is primarily driven by ODA loans instead of ODA grants.
While grants were just under 1bn USD in 2011 and decreased slightly over the following years to 600m USD in 2019,
decreasing loans were also the primary driver of the overall development aid contributions,
with the overall monetary curve closely following that of loan contributions.
Thus, while loans constituted almost triple the USD amount of grants to Vietnam in 2011,
this number even climbed to almost 5 times the amount in 2014,
before falling to just over 2.5 times the amount of USD in loans compared to grants in 2020.
A large share of development aid contributions to Vietnam are also made up from other official flows, non-export credits,
a share which started equal to the absolute grant amount of USD contributed, rose steeply in 2013 to double the amount and fell equally steeply back to its original level in 2019.
```{python} ```{python}
#| label: fig-vnm-aid-donortype #| label: fig-vnm-aid-donortype
#| fig-cap: "Total ODA for Vietnam per year, separated by donor type" #| fig-cap: "Total ODA for Vietnam per year, separated by donor type"
@ -233,28 +247,15 @@ 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. 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). Source: Author's elaboration based on OECD ODA CRS (2022).
```{python} Bilateral donor contributions make up the largest part of development aid contributions to Vietnam, as can be seen in @fig-vnm-aid-donortype.
#| label: tbl-vnm-aid-electricity Both bilateral and multilateral contributions increase from 2011 to 2014 and subsequently begin decreasing.
#| tbl-cap: "ODA for transmission and distribution of electric power in Vietnam per year, separated by financing type" While bilateral contributions do not increase in absolute amounts afterwards until 2020,
#| column: page multilateral contributions increase again from 2019 to 2020.
totals = df.loc[ Nevertheless, bilateral contributions are consistently higher than multilateral,
((df['SECTOR'] == 23630) | (df['SECTOR'] == 23631)) & # Total having around a 1.5 times higher share of absolute USD contribution,
(df['CHANNEL'] == 100) & though growing to just over 2 times the share in 2017,
(df['AMOUNTTYPE'] == 'D') & before quickly shrinking down to just 1.3 times the share of multilateral contributions in 2018.
((df['FLOW'] == 11) | (df['FLOW'] == 13)) & # Total This gap may close further in the future, with multilateral contributions being on an increase and bilateral contributions still decreasing.
(df['FLOWTYPE'] == 112) &
(df['AIDTYPE'] == "100") # contains mixed int and string representations
]
electricityaid = totals[totals['DONOR'] < 20000] # drop all 'total' aggregations
pd.options.display.float_format = "{:.2f}".format
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).
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