Paying taxes: Time to complete a corporate income tax correction (weeks) (DB17-20 methodology) - Score by country
The score for time to complete with a corporate income tax correction benchmarks economies with respect to the regulatory best practice on the indicator. The score is indicated on a scale from 0 to 100, where 0 represents the worst regulatory performance and 100 the best regulatory performance, and is computed...
Countries reporting
162
Highest
100
Angola
Lowest
0
Afghanistan
Median
100
Years covered
5
2015–2019
Data points
905
What the numbers show
Paying taxes: Time to complete a corporate income tax correction (weeks) (DB17-20 methodology) - Score is currently reported for 162 countries. The highest value is 100 in Angola; the lowest is 0 in Afghanistan.
The median across all reporting countries is 100, and the mean is 81.5.
Paying taxes: Time to complete a corporate income tax correction: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Angola | 100 | 2019 | — | flat |
| 1 | Argentina | 100 | 2019 | — | flat |
| 1 | Armenia | 100 | 2019 | — | flat |
| 1 | Antigua and Barbuda | 100 | 2019 | — | flat |
| 1 | Australia | 100 | 2019 | — | flat |
| 1 | Austria | 100 | 2019 | — | flat |
| 1 | Azerbaijan | 100 | 2019 | — | flat |
| 1 | Belgium | 100 | 2019 | — | flat |
| 1 | Benin | 100 | 2019 | — | flat |
| 1 | Burkina Faso | 100 | 2019 | — | flat |
| 1 | Belarus | 100 | 2019 | — | flat |
| 1 | Bolivia, Plurinational State of | 100 | 2019 | — | flat |
| 1 | Barbados | 100 | 2019 | — | flat |
| 1 | Botswana | 100 | 2019 | — | flat |
| 1 | Chile | 100 | 2019 | — | flat |
| 1 | China | 100 | 2019 | — | flat |
| 1 | Côte d'Ivoire | 100 | 2019 | — | flat |
| 1 | Cameroon | 100 | 2019 | — | flat |
| 1 | Colombia | 100 | 2019 | — | flat |
| 1 | Cape Verde | 100 | 2019 | — | flat |
| 1 | Costa Rica | 100 | 2019 | — | flat |
| 1 | Cyprus | 100 | 2019 | — | flat |
| 1 | Czechia | 100 | 2019 | — | flat |
| 1 | Germany | 100 | 2019 | — | flat |
| 1 | Dominica | 100 | 2019 | — | flat |
| 1 | Algeria | 100 | 2019 | — | flat |
| 1 | Ecuador | 100 | 2019 | — | flat |
| 1 | Eritrea | 100 | 2019 | — | flat |
| 1 | Spain | 100 | 2019 | — | flat |
| 1 | Estonia | 100 | 2019 | — | flat |
| 1 | Ethiopia | 100 | 2019 | — | flat |
| 1 | Finland | 100 | 2019 | — | flat |
| 1 | Fiji | 100 | 2019 | — | flat |
| 1 | France | 100 | 2019 | — | flat |
| 1 | Georgia | 100 | 2019 | — | flat |
| 1 | Ghana | 100 | 2019 | — | flat |
| 1 | Gambia | 100 | 2019 | — | flat |
| 1 | Equatorial Guinea | 100 | 2019 | — | flat |
| 1 | Greece | 100 | 2019 | — | flat |
| 1 | Grenada | 100 | 2019 | — | flat |
| 1 | Hong Kong, China | 100 | 2019 | — | flat |
| 1 | Haiti | 100 | 2019 | — | flat |
| 1 | Hungary | 100 | 2019 | — | rising |
| 1 | Indonesia | 100 | 2019 | — | flat |
| 1 | India | 100 | 2019 | — | volatile |
| 1 | Ireland | 100 | 2019 | — | flat |
| 1 | Iceland | 100 | 2019 | — | flat |
| 1 | Israel | 100 | 2019 | — | flat |
| 1 | Italy | 100 | 2019 | — | flat |
| 1 | Japan | 100 | 2019 | — | flat |
| 1 | Kazakhstan | 100 | 2019 | — | flat |
| 1 | Saint Kitts and Nevis | 100 | 2019 | — | flat |
| 1 | Republic of Korea | 100 | 2019 | — | flat |
| 1 | Liberia | 100 | 2019 | — | flat |
| 1 | Sri Lanka | 100 | 2019 | — | flat |
| 1 | Lithuania | 100 | 2019 | — | flat |
| 1 | Latvia | 100 | 2019 | — | flat |
| 1 | Morocco | 100 | 2019 | — | flat |
| 1 | Republic of Moldova | 100 | 2019 | — | flat |
| 1 | Maldives | 100 | 2019 | — | flat |
| 1 | Mongolia | 100 | 2019 | — | flat |
| 1 | Mauritius | 100 | 2019 | — | flat |
| 1 | Namibia | 100 | 2019 | — | flat |
| 1 | Nigeria | 100 | 2019 | — | flat |
| 1 | Nicaragua | 100 | 2019 | — | flat |
| 1 | New Zealand | 100 | 2019 | — | flat |
| 1 | Oman | 100 | 2019 | — | flat |
| 1 | Philippines | 100 | 2019 | — | flat |
| 1 | Papua New Guinea | 100 | 2019 | — | flat |
| 1 | Portugal | 100 | 2019 | — | flat |
| 1 | Paraguay | 100 | 2019 | — | flat |
| 1 | Romania | 100 | 2019 | — | flat |
| 1 | Senegal | 100 | 2019 | — | flat |
| 1 | Solomon Islands | 100 | 2019 | — | flat |
| 1 | Sierra Leone | 100 | 2019 | — | flat |
| 1 | El Salvador | 100 | 2019 | — | volatile |
| 1 | Serbia | 100 | 2019 | — | flat |
| 1 | South Sudan | 100 | 2019 | — | flat |
| 1 | Sao Tome and Principe | 100 | 2019 | — | flat |
| 1 | Suriname | 100 | 2019 | — | flat |
| 1 | Slovakia | 100 | 2019 | — | flat |
| 1 | Sweden | 100 | 2019 | — | flat |
| 1 | Eswatini | 100 | 2019 | — | flat |
| 1 | Seychelles | 100 | 2019 | — | flat |
| 1 | Syrian Arab Republic | 100 | 2019 | — | flat |
| 1 | Thailand | 100 | 2019 | — | volatile |
| 1 | Tunisia | 100 | 2019 | — | volatile |
| 1 | Türkiye | 100 | 2019 | — | flat |
| 1 | Tanzania, United Republic of | 100 | 2019 | — | flat |
| 1 | Ukraine | 100 | 2019 | — | flat |
| 1 | Uruguay | 100 | 2019 | — | flat |
| 1 | United States of America | 100 | 2019 | — | flat |
| 1 | Uzbekistan | 100 | 2019 | — | flat |
| 1 | Viet Nam | 100 | 2019 | — | flat |
| 1 | Samoa | 100 | 2019 | — | flat |
| 1 | Yemen | 100 | 2019 | — | flat |
| 1 | Zambia | 100 | 2019 | — | flat |
| 1 | Zimbabwe | 100 | 2019 | — | flat |
| 1 | Taiwan, China | 100 | 2019 | — | flat |
| 100 | Libya | 98.66 | 2019 | — | flat |
| 101 | Myanmar | 97.77 | 2019 | — | flat |
| 102 | Guinea-Bissau | 94.2 | 2019 | — | flat |
| 103 | Bhutan | 93.75 | 2019 | — | flat |
| 104 | Netherlands | 93.3 | 2019 | — | flat |
| 105 | Denmark | 91.07 | 2019 | — | flat |
| 106 | Luxembourg | 86.61 | 2019 | — | flat |
| 107 | Belize | 84.38 | 2019 | — | flat |
| 108 | Kyrgyzstan | 83.48 | 2019 | — | flat |
| 109 | Lesotho | 82.59 | 2019 | — | flat |
| 110 | Sudan | 80.8 | 2019 | — | flat |
| 111 | Slovenia | 80.36 | 2019 | — | flat |
| 112 | Rwanda | 78.12 | 2019 | — | flat |
| 112 | Tajikistan | 78.12 | 2019 | — | flat |
| 114 | Niger | 75.89 | 2019 | — | flat |
| 115 | Tonga | 74.55 | 2019 | — | flat |
| 116 | Bulgaria | 74.11 | 2019 | — | flat |
| 117 | Saint Lucia | 72.77 | 2019 | — | flat |
| 118 | Switzerland | 72.32 | 2019 | — | flat |
| 119 | Bangladesh | 70.98 | 2019 | — | flat |
| 119 | Saint Vincent and the Grenadines | 70.98 | 2019 | — | flat |
| 121 | Mozambique | 70.09 | 2019 | — | flat |
| 122 | Guyana | 69.42 | 2019 | — | flat |
| 123 | Kiribati | 67.41 | 2019 | — | flat |
| 124 | Russian Federation | 65 | 2019 | — | flat |
| 125 | Uganda | 64.73 | 2019 | — | flat |
| 126 | Kosovo | 63.39 | 2019 | — | flat |
| 127 | Singapore | 59.82 | 2019 | — | flat |
| 128 | Kenya | 58.93 | 2019 | — | flat |
| 129 | Guatemala | 56.92 | 2019 | — | flat |
| 130 | San Marino | 56.7 | 2019 | — | flat |
| 131 | Albania | 54.02 | 2019 | — | flat |
| 132 | Bosnia and Herzegovina | 53.57 | 2019 | — | flat |
| 132 | Canada | 53.57 | 2019 | — | flat |
| 134 | Congo, Democratic Republic of the | 47.77 | 2019 | — | flat |
| 134 | Egypt | 47.77 | 2019 | — | flat |
| 136 | North Macedonia | 46.88 | 2019 | — | flat |
| 137 | Nepal | 44.2 | 2019 | — | flat |
| 138 | Poland | 43.3 | 2019 | — | flat |
| 139 | Dominican Republic | 42.86 | 2019 | — | flat |
| 139 | Iraq | 42.86 | 2019 | — | flat |
| 141 | Pakistan | 41.96 | 2019 | — | flat |
| 142 | Montenegro | 40.62 | 2019 | — | flat |
| 143 | Croatia | 36.61 | 2019 | — | flat |
| 144 | Burundi | 33.93 | 2019 | — | flat |
| 144 | Comoros | 33.93 | 2019 | — | flat |
| 144 | Honduras | 33.93 | 2019 | — | flat |
| 144 | Chad | 33.93 | 2019 | — | flat |
| 148 | Guinea | 27.23 | 2019 | — | flat |
| 149 | Djibouti | 25.45 | 2019 | — | flat |
| 150 | Togo | 24.55 | 2019 | — | flat |
| 151 | Lebanon | 21.43 | 2019 | — | flat |
| 152 | Central African Republic | 20.54 | 2019 | — | flat |
| 153 | Malaysia | 19.87 | 2019 | — | volatile |
| 154 | Congo | 13.39 | 2019 | — | flat |
| 155 | Mali | 12.95 | 2019 | — | flat |
| 155 | Malawi | 12.95 | 2019 | — | flat |
| 157 | Madagascar | 9.38 | 2019 | — | flat |
| 158 | Norway | 8.93 | 2019 | — | flat |
| 159 | Peru | 4.46 | 2019 | — | flat |
| 160 | South Africa | 1.34 | 2019 | — | flat |
| 161 | Lao People's Democratic Republic | 0.8929 | 2019 | — | flat |
| 162 | Afghanistan | 0 | 2019 | — | volatile |
About this data
The score for time to complete with a corporate income tax correction benchmarks economies with respect to the regulatory best practice on the indicator. The score is indicated on a scale from 0 to 100, where 0 represents the worst regulatory performance and 100 the best regulatory performance, and is computed based on the methodology in the DB17-20 studies.