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soodoku/tariffs.ipynb

Last active April 3, 2025 17:29
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tariffs.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "2cf1c131-cf2e-4623-96c3-8945aeb972c5",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import numpy as np\n",
"\n",
"# Set display options\n",
"pd.set_option('display.max_rows', None)\n",
"pd.set_option('display.max_columns', None)\n",
"pd.set_option('display.width', None)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "eb140a82-37e4-440d-931f-2d84a2c5e2a0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Merged Dataframe:\n",
" country wb_tariff year wto_tariff year.1 unctad_tariff year.2 \\\n",
"0 Aruba 9.66 2021.0 NaN NaN 10.80 2021.0 \n",
"1 Afghanistan 5.63 2018.0 6.5 2018.0 6.49 2018.0 \n",
"2 Angola 11.33 2021.0 10.9 2021.0 8.40 2021.0 \n",
"3 Anguilla NaN NaN NaN NaN 13.14 2021.0 \n",
"4 Albania 1.13 2021.0 3.6 2021.0 0.78 2021.0 \n",
"\n",
" est_tariff_charged reciprocal_tariff \n",
"0 10 10 \n",
"1 49 10 \n",
"2 63 32 \n",
"3 10 10 \n",
"4 10 10 \n"
]
}
],
"source": [
"\n",
"# Read the first CSV\n",
"# Since the data format looks a bit unusual, we'll need to clean it up\n",
"df1 = pd.read_csv('wiki_tariffs.csv')\n",
"\n",
"# Read the second CSV\n",
"df2 = pd.read_csv('trump_tariffs.csv')\n",
"\n",
"# Function to clean percentage strings and convert to float\n",
"def clean_percentage(val):\n",
" if isinstance(val, str) and '%' in val:\n",
" return float(val.replace('%', ''))\n",
" elif isinstance(val, str) and val == '*EU member*':\n",
" return np.nan\n",
" else:\n",
" return val\n",
"\n",
"# Clean up the first dataframe\n",
"for col in df1.columns:\n",
" if 'tariff' in col.lower():\n",
" df1[col] = df1[col].apply(clean_percentage)\n",
"\n",
"# Clean up the second dataframe\n",
"for col in df2.columns:\n",
" if 'tariff' in col.lower():\n",
" df2[col] = df2[col].apply(clean_percentage)\n",
"\n",
"# Perform an inner join on country\n",
"merged_df = pd.merge(df1, df2, left_on='country', right_on='country', how='inner')\n",
"# Display the merged dataframe\n",
"print(\"Merged Dataframe:\")\n",
"print(merged_df.head())"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "cd3384be-ae41-4f21-b513-678c252c78b5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['country', 'wb_tariff', 'year', 'wto_tariff', 'year.1', 'unctad_tariff',\n",
" 'year.2', 'est_tariff_charged', 'reciprocal_tariff'],\n",
" dtype='object')"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_df.columns"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "67773186-e9fb-4fb6-9a78-542ec2a626b9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Correlation Matrix:\n",
" wb_tariff wto_tariff unctad_tariff est_tariff_charged\n",
"wb_tariff 1.000000 0.687042 0.930968 -0.209010\n",
"wto_tariff 0.687042 1.000000 0.712645 -0.075520\n",
"unctad_tariff 0.930968 0.712645 1.000000 -0.196792\n",
"est_tariff_charged -0.209010 -0.075520 -0.196792 1.000000\n"
]
}
],
"source": [
"tariff_cols = ['wb_tariff', 'wto_tariff', 'unctad_tariff', 'est_tariff_charged']\n",
"tariff_df = merged_df[tariff_cols]\n",
"\n",
"# Remove rows with NaN values\n",
"tariff_df = tariff_df.dropna()\n",
"\n",
"# Calculate correlations\n",
"correlation_matrix = tariff_df.corr()\n",
"print(\"Correlation Matrix:\")\n",
"print(correlation_matrix)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "b2ce288e-b1b4-4607-9c5a-168a96cf4eae",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 1000x800 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Correlations with Estimated Tariff Charged:\n",
"est_tariff_charged 1.000000\n",
"wto_tariff -0.075520\n",
"unctad_tariff -0.196792\n",
"wb_tariff -0.209010\n",
"Name: est_tariff_charged, dtype: float64\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1800x600 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"R-squared values with Est. Tariff Charged:\n",
"wb_tariff: 0.0437\n",
"wto_tariff: 0.0057\n",
"unctad_tariff: 0.0387\n"
]
}
],
"source": [
"# Create a heatmap visualization\n",
"plt.figure(figsize=(10, 8))\n",
"sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\", vmin=-1, vmax=1)\n",
"plt.title('Correlation Between Tariff Metrics')\n",
"plt.tight_layout()\n",
"plt.savefig('tariff_correlations.png')\n",
"plt.show()\n",
"\n",
"# Print correlations with est_tariff_charged specifically\n",
"est_tariff_corr = correlation_matrix['est_tariff_charged'].sort_values(ascending=False)\n",
"print(\"\\nCorrelations with Estimated Tariff Charged:\")\n",
"print(est_tariff_corr)\n",
"\n",
"# Create scatter plots for visual comparison\n",
"fig, axes = plt.subplots(1, 3, figsize=(18, 6))\n",
"\n",
"# Plot wb_tariff vs est_tariff_charged\n",
"axes[0].scatter(tariff_df['wb_tariff'], tariff_df['est_tariff_charged'])\n",
"axes[0].set_xlabel('World Bank Tariff (%)')\n",
"axes[0].set_ylabel('Estimated Tariff Charged (%)')\n",
"axes[0].set_title('WB Tariff vs Est. Tariff Charged')\n",
"\n",
"# Plot wto_tariff vs est_tariff_charged\n",
"axes[1].scatter(tariff_df['wto_tariff'], tariff_df['est_tariff_charged'])\n",
"axes[1].set_xlabel('WTO Tariff (%)')\n",
"axes[1].set_ylabel('Estimated Tariff Charged (%)')\n",
"axes[1].set_title('WTO Tariff vs Est. Tariff Charged')\n",
"\n",
"# Plot unctad_tariff vs est_tariff_charged\n",
"axes[2].scatter(tariff_df['unctad_tariff'], tariff_df['est_tariff_charged'])\n",
"axes[2].set_xlabel('UNCTAD Tariff (%)')\n",
"axes[2].set_ylabel('Estimated Tariff Charged (%)')\n",
"axes[2].set_title('UNCTAD Tariff vs Est. Tariff Charged')\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig('tariff_scatter_plots.png')\n",
"plt.show()\n",
"\n",
"# Calculate R-squared values\n",
"r_squared = {}\n",
"for col in ['wb_tariff', 'wto_tariff', 'unctad_tariff']:\n",
" r_squared[col] = correlation_matrix.loc[col, 'est_tariff_charged']**2\n",
"\n",
"print(\"\\nR-squared values with Est. Tariff Charged:\")\n",
"for col, val in r_squared.items():\n",
" print(f\"{col}: {val:.4f}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6b771a17-f7fc-4d2f-8ef3-e41ee0acd074",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.11 (Data Science)",
"language": "python",
"name": "py311ds"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Raw
trump_tariffs.csv
country est_tariff_charged reciprocal_tariff
xMaldives 10 10
Tajikistan 10 10
Cabo Verde 10 10
Burundi 10 10
Guadeloupe 10 10
Bhutan 10 10
Martinique 10 10
Tonga 10 10
Mauritania 10 10
Dominica 10 10
Micronesia 10 10
Gambia 10 10
French Guiana 10 10
Christmas Island 10 10
Andorra 10 10
Central African Republic 10 10
Solomon Islands 10 10
Mayotte 10 10
Anguilla 10 10
Cocos (Keeling) Islands 10 10
Eritrea 10 10
Cook Islands 10 10
South Sudan 10 10
Comoros 10 10
Kiribati 10 10
São Tomé and Príncipe 10 10
Norfolk Island 58 29
Gibraltar 10 10
Tuvalu 10 10
British Indian Ocean Territory 10 10
Tokelau 10 10
Guinea-Bissau 10 10
Svalbard and Jan Mayen 10 10
Heard and McDonald Islands 10 10
Reunion 73 37
Papua New Guinea 15 10
Malawi 34 17
Liberia 10 10
British Virgin Islands 10 10
Afghanistan 49 10
Zimbabwe 35 18
Benin 10 10
Barbados 10 10
Monaco 10 10
Syria 81 41
Uzbekistan 10 10
Republic of the Congo 10 10
Djibouti 10 10
French Polynesia 10 10
Cayman Islands 10 10
Kosovo 10 10
Curaçao 10 10
Vanuatu 44 22
Rwanda 10 10
Sierra Leone 10 10
Mongolia 10 10
San Marino 10 10
Antigua and Barbuda 10 10
Bermuda 10 10
Eswatini (Swaziland) 10 10
Marshall Islands 10 10
Saint Pierre and Miquelon 99 50
Saint Kitts and Nevis 10 10
Turkmenistan 10 10
Grenada 10 10
Sudan 10 10
Turks and Caicos Islands 10 10
Aruba 10 10
Montenegro 10 10
Saint Helena 15 10
Kyrgyzstan 10 10
Yemen 10 10
Saint Vincent and the Grenadines 10 10
Niger 10 10
Saint Lucia 10 10
Nauru 59 30
Equatorial Guinea 25 13
Iran 10 10
Libya 61 31
Samoa 10 10
Guinea 10 10
Timor-Leste 10 10
Montserrat 10 10
Chad 26 13
Mali 10 10
Algeria 59 30
Oman 10 10
Uruguay 10 10
Bahamas 10 10
Lesotho 99 50
Ukraine 10 10
Bahrain 10 10
Qatar 10 10
Mauritius 80 40
Fiji 63 32
Iceland 10 10
Kenya 10 10
Liechtenstein 73 37
Guyana 76 38
Haiti 10 10
Bosnia and Herzegovina 70 35
Nigeria 27 14
Namibia 42 21
Brunei 47 24
Bolivia 20 10
Panama 10 10
Venezuela 29 15
North Macedonia 65 33
Ethiopia 10 10
Ghana 17 10
Moldova 61 31
Angola 63 32
Democratic Republic of the Congo 22 11
Jamaica 10 10
Mozambique 31 16
Paraguay 10 10
Zambia 33 17
Lebanon 10 10
Tanzania 10 10
Iraq 78 39
Georgia 10 10
Senegal 10 10
Azerbaijan 10 10
Cameroon 22 11
Uganda 20 10
Albania 10 10
Armenia 10 10
Nepal 10 10
Sint Maarten 10 10
Falkland Islands 82 41
Gabon 10 10
Kuwait 10 10
Togo 10 10
Suriname 10 10
Belize 10 10
China 67 34
European Union 39 20
Vietnam 90 46
Taiwan 64 32
Japan 46 24
India 52 26
South Korea 50 25
Thailand 72 36
Switzerland 61 31
Indonesia 64 32
Malaysia 47 24
Cambodia 97 49
United Kingdom 10 10
South Africa 60 30
Brazil 10 10
Bangladesh 74 37
Singapore 10 10
Israel 33 17
Philippines 34 17
Chile 10 10
Australia 10 10
Pakistan 58 29
Turkey 10 10
Sri Lanka 88 44
Colombia 10 10
Peru 10 10
Nicaragua 36 18
Norway 30 15
Costa Rica 17 10
Jordan 40 20
Dominican Republic 10 10
United Arab Emirates 10 10
New Zealand 20 10
Argentina 10 10
Ecuador 12 10
Guatemala 10 10
Honduras 10 10
Madagascar 93 47
Myanmar (Burma) 88 44
Tunisia 55 28
Kazakhstan 54 27
Serbia 74 37
Egypt 10 10
Saudi Arabia 10 10
El Salvador 10 10
Côte d'Ivoire 41 21
Laos 95 48
Botswana 74 37
Trinidad and Tobago 12 10
Morocco 10 10
Raw
wiki_tariffs.csv
country wb_tariff year wto_tariff year unctad_tariff year
Aruba 9.66% 2021 10.80% 2021
Afghanistan 5.63% 2018 6.50% 2018 6.49% 2018
Angola 11.33% 2021 10.90% 2021 8.40% 2021
Anguilla 13.14% 2021
Albania 1.13% 2021 3.60% 2021 0.78% 2021
United Arab Emirates 2.63% 2021 4.80% 2021 3.09% 2021
Argentina 6.51% 2021 13.40% 2021 7.40% 2021
Armenia 3.61% 2021 6.30% 2021 3.54% 2021
Antigua and Barbuda 13.07% 2021 9.90% 2021 12.95% 2021
Australia 0.81% 2021 2.40% 2021 0.84% 2021
Austria 1.39% 2021 EU member 0.96% 2021
Azerbaijan 6.01% 2021 8.50% 2021 6.16% 2021
Burundi 8.53% 2021 12.80% 2021 5.78% 2021
Belgium 1.39% 2021 EU member 1.33% 2021
Benin 10.89% 2021 12.10% 2021 8.61% 2021
Burkina Faso 7.30% 2021 12.10% 2021 7.98% 2021
Bangladesh 10.95% 2021 14.00% 2021 13.11% 2021
Bulgaria 1.39% 2021 EU member 1.28% 2019
Bahrain 2.09% 2021 4.80% 2021 3.16% 2021
Bahamas 17.05% 2018 32.50% 2018 24.75% 2018
Bosnia and Herzegovina 2.80% 2021 6.40% 2021 2.15% 2021
Belarus 2.27% 2021 6.70% 2021 1.94% 2021
Belize 17.79% 2021 11.90% 2021 10.32% 2021
Bermuda 23.84% 2021 20.80% 2021
Bolivia 5.12% 2021 11.80% 2021 5.43% 2021
Brazil 7.76% 2021 13.30% 2021 8.79% 2021
Barbados 12.24% 2021 11.70% 2021 8.44% 2021
Brunei 0.02% 2021 0.30% 2021 0.03% 2021
Bhutan 3.33% 2021 9.70% 2021 3.09% 2021
Botswana 0.95% 2021 7.70% 2021 1.28% 2021
Central African Republic 16.44% 2017 18.00% 2017 16.21% 2017
Canada 2.35% 2021 4.00% 2021 1.63% 2021
Switzerland 1.40% 2021 5.60% 2021 0.18% 2021
Chile 0.43% 2021 6.00% 2021 0.45% 2021
China 2.31% 2021 7.50% 2021 2.12% 2021
Ivory Coast 7.63% 2021 12.10% 2021 8.82% 2021
Cameroon 15.46% 2019 18.20% 2019 13.75% 2019
Democratic Republic of the Congo 8.40% 2020 10.90% 2020 8.17% 2020
Republic of the Congo 11.55% 2015 9.91% 2015
Cook Islands 3.50% 2021 0.59% 2021
Colombia 2.58% 2021 5.80% 2021 2.68% 2021
Comoros 4.34% 2021 15.10% 2021 4.78% 2021
Cape Verde 9.96% 2021 10.20% 2021 8.33% 2021
Costa Rica 1.43% 2021 5.60% 2021 0.88% 2021
Cuba 8.91% 2021 4.40% 2021 10.18% 2021
Cayman Islands 20.39% 2021 19.42% 2021
Cyprus 1.39% 2021 EU member 1.46% 2021
Czech Republic 1.39% 2021 EU member 1.14% 2021
Germany 1.39% 2021 EU member 1.39% 2021
Djibouti 17.56% 2014 19.59% 2014
Dominica 7.84% 2020 10.70% 2020 9.93% 2020
Denmark 1.39% 2021 EU member 1.95% 2021
Dominican Republic 3.80% 2021 7.50% 2021 4.30% 2021
Algeria 10.29% 2021 19.00% 2021 10.25% 2021
Ecuador 4.63% 2021 11.20% 2021 5.05% 2021
Egypt 10.43% 2019 19.00% 2019 5.70% 2019
Eritrea 5.43% 2006 7.11% 2006
Spain 1.39% 2021 EU member 1.73% 2021
Estonia 1.39% 2021 EU member 2.10% 2021
Ethiopia 12.66% 2021 17.00% 2021 12.76% 2021
Finland 1.39% 2021 EU member 1.35% 2021
Fiji 8.35% 2021 7.90% 2021 4.16% 2021
France 1.39% 2021 EU member 1.53% 2021
Federated States of Micronesia 5.10% 2021
Gabon 14.50% 2019 17.70% 2019 14.11% 2019
Georgia 0.34% 2021 1.40% 2021 0.03% 2021
Ghana 10.51% 2021 12.10% 2021 9.89% 2021
Guinea 12.26% 2021 12.10% 2021 11.29% 2021
Gambia 17.69% 2021 12.10% 2021 17.80% 2021
Guinea-Bissau 11.82% 2021 12.10% 2021 10.32% 2021
Equatorial Guinea 15.63% 2007 14.51% 2007
Greece 1.39% 2021 EU member 1.92% 2021
Grenada 10.79% 2019 11.00% 2019 9.07% 2019
Guatemala 1.72% 2021 5.60% 2021 1.77% 2021
Guyana 4.73% 2021 11.70% 2021 3.97% 2021
Hong Kong 0.00% 2021 0.00% 2021 0.00% 2021
Honduras 2.85% 2021 5.80% 2021 2.67% 2021
Croatia 1.39% 2021 EU member 1.57% 2021
Haiti 6.76% 2020 4.90% 2020 6.39% 2020
Hungary 1.39% 2021 EU member 1.04% 2021
Indonesia 1.83% 2021 8.10% 2021 1.61% 2021
India 5.87% 2021 18.30% 2021 6.04% 2021
Ireland 1.39% 2021 EU member 1.53% 2020
Iran 12.09% 2020 20.10% 2020 12.66% 2020
Iceland 1.51% 2021 3.10% 2021 0.00% 2021
Israel 2.88% 2021 3.60% 2021 2.13% 2021
Italy 1.39% 2021 EU member 1.63% 2021
Jamaica 8.61% 2021 8.60% 2021 9.13% 2021
Jordan 3.98% 2020 10.10% 2020 3.44% 2020
Japan 1.84% 2021 4.20% 2021 0.76% 2021
Kazakhstan 2.17% 2021 5.70% 2021 2.15% 2021
Kenya 9.30% 2021 13.20% 2021 7.27% 2021
Kyrgyzstan 3.01% 2021 6.50% 2021 2.94% 2021
Cambodia 5.37% 2021 10.20% 2021 6.20% 2021
Kiribati 0.00% 2021
Saint Kitts and Nevis 8.84% 2020 9.20% 2020 8.78% 2020
South Korea 4.85% 2021 13.60% 2021 1.09% 2021
Kuwait 2.85% 2021 4.70% 2021 3.16% 2021
Laos 1.12% 2021 8.60% 2021 1.21% 2021
Lebanon 2.83% 2020 6.00% 2020 2.36% 2020
Liberia 6.64% 2021 12.10% 2021 6.09% 2021
Libya 4.03% 2021 5.20% 2021 4.27% 2021
Saint Lucia 9.08% 2020 9.20% 2021 9.55% 2020
Sri Lanka 4.36% 2021 6.00% 2021 1.73% 2021
Lesotho 3.35% 2021 7.70% 2021 4.44% 2021
Lithuania 1.39% 2021 EU member 2.29% 2021
Luxembourg 1.39% 2021 EU member 1.47% 2021
Latvia 1.39% 2021 EU member 1.18% 2021
Macau 0.00% 2021 0.00% 2021 0.00% 2021
Morocco 4.23% 2021 14.20% 2021 2.91% 2021
Moldova 1.20% 2021 5.30% 2021 1.05% 2021
Madagascar 7.51% 2021 11.70% 2021 8.03% 2021
Maldives 10.55% 2021 11.40% 2021 11.25% 2021
Mexico 1.21% 2018 7.10% 2021 1.33% 2018
North Macedonia 2.38% 2021 6.70% 2021 1.10% 2021
Mali 7.88% 2021 12.10% 2021 7.35% 2021
Malta 1.39% 2021 EU member 2.09% 2019
Myanmar 1.04% 2021 6.50% 2021 0.95% 2021
Montenegro 3.19% 2021 3.70% 2021 1.24% 2021
Mongolia 5.28% 2021 5.20% 2021 4.69% 2021
Mozambique 4.19% 2021 10.30% 2021 4.37% 2021
Mauritania 8.32% 2021 12.00% 2021 10.03% 2021
Montserrat 11.61% 2021
Mauritius 1.27% 2021 0.80% 2021 0.86% 2021
Malawi 5.95% 2021 12.20% 2021 5.13% 2021
Malaysia 3.62% 2021 5.60% 2021 3.78% 2021
Namibia 1.32% 2021 7.70% 2021 1.05% 2021
Niger 8.46% 2021 12.10% 2021 7.76% 2021
Nigeria 12.20% 2021 12.10% 2021 12.30% 2021
Nicaragua 1.96% 2021 5.70% 2021 2.07% 2021
Netherlands 1.39% 2021 EU member 1.48% 2021
Norway 3.00% 2021 5.90% 2021 0.13% 2021
Nepal 11.99% 2021 12.70% 2021 11.88% 2021
Nauru 14.07% 2021 12.90% 2021 13.35% 2021
New Zealand 0.86% 2021 1.90% 2021 0.90% 2021
Oman 2.00% 2021 5.60% 2021 2.18% 2021
Pakistan 9.03% 2021 11.20% 2021 11.14% 2021
Panama 6.43% 2021 5.10% 2021 4.42% 2021
Peru 0.65% 2021 2.40% 2021 0.79% 2021
Philippines 1.73% 2021 6.10% 2021 0.90% 2021
Palau 9.49% 2021 4.00% 2021 3.14% 2021
Papua New Guinea 3.58% 2021 4.20% 2021 2.23% 2021
Poland 1.39% 2021 EU member 1.85% 2021
Portugal 1.39% 2021 EU member 1.58% 2021
Paraguay 4.49% 2021 9.60% 2021 4.77% 2021
Palestine 2.18% 2017 0.83% 2017
French Polynesia 5.75% 2021 6.76% 2021
Qatar 3.53% 2021 5.10% 2021 3.78% 2021
Romania 1.39% 2021 EU member 1.17% 2021
Russia 4.17% 2021 6.60% 2021 3.80% 2021
Rwanda 11.97% 2021 12.40% 2021 6.59% 2021
Saudi Arabia 4.23% 2020 6.30% 2021 5.20% 2020
Sudan 0.00% 2021 21.60% 2021 0.00% 2021
Senegal 8.88% 2021 12.10% 2021 9.34% 2021
Singapore 0.00% 2021 0.00% 2021 0.00% 2021
Solomon Islands 14.31% 2021 9.90% 2021 8.80% 2021
Sierra Leone 14.22% 2021 12.10% 2021 12.45% 2021
El Salvador 1.88% 2021 6.00% 2021 2.04% 2021
San Marino 0.69% 2021
Serbia 1.72% 2021 7.40% 2021 1.62% 2021
São Tomé and Príncipe 9.97% 2019 9.90% 2019 10.58% 2019
Suriname 8.43% 2021 10.40% 2021 7.43% 2021
Slovakia 1.39% 2021 EU member 1.51% 2021
Slovenia 1.39% 2021 EU member 1.91% 2021
Sweden 1.39% 2021 EU member 1.51% 2021
Eswatini 2.14% 2021 7.70% 2021 2.77% 2021
Seychelles 1.07% 2021 2.40% 2021 0.14% 2021
Syria 9.21% 2020 10.80% 2020 9.03% 2020
Chad 16.36% 2016 16.06% 2016
Togo 10.73% 2021 12.10% 2021 10.36% 2021
Thailand 3.15% 2021 11.50% 2021 2.07% 2021
Tajikistan 2.31% 2021 8.00% 2021 3.58% 2021
Turkmenistan 2.88% 2002 1.13% 2002
Timor-Leste 2.53% 2021 2.50% 2021 2.52% 2021
Tonga 6.59% 2021 10.70% 2021 8.30% 2021
Trinidad and Tobago 8.87% 2021 8.30% 2021 5.06% 2021
Tunisia 9.35% 2016 9.10% 2016
Turkey 3.22% 2021 10.70% 2021 1.69% 2021
Tuvalu 2.43% 2017 1.27% 2017
Taiwan 6.60% 2021 1.31% 2021
Tanzania 8.67% 2021 13.10% 2021 6.05% 2021
Uganda 8.67% 2021 17.60% 2021 6.04% 2021
Ukraine 1.71% 2021 4.40% 2021 1.87% 2021
Uruguay 5.25% 2021 10.30% 2021 6.64% 2021
United Kingdom 0.72% 2021 3.90% 2021 0.64% 2021
United States 1.47% 2021 3.40% 2021 1.48% 2021
Uzbekistan 2.56% 2021 7.40% 2021 2.36% 2021
Saint Vincent and the Grenadines 9.06% 2021 10.00% 2021 9.27% 2021
Venezuela 13.61% 2021 13.80% 2021 15.27% 2021
Vietnam 1.17% 2021 9.60% 2021 0.85% 2021
Vanuatu 11.08% 2021 9.20% 2021 9.31% 2021
Wallis and Futuna 2.09% 2021
Samoa 10.38% 2020 11.30% 2021 9.03% 2020
Yemen 5.03% 2017 7.60% 2017 5.97% 2017
South Africa 4.46% 2021 7.80% 2021 4.79% 2021
Zambia 4.81% 2021 14.60% 2021 4.78% 2021
Zimbabwe 11.37% 2021 17.90% 2021 10.08% 2021
Low & middle income economies (WB) 4.28% 2017
Low-income economies (WB) 9.79% 2017
Middle-income economies (WB) —
Upper middle income economies (WB) 3.70% 2017
High-income economies (WB) 2.02% 2017
European Union 1.39% 2021 5.20% 2021 1.49% 2021
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