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The international dollar (int’l dollar or intl dollar, symbols Int’l$., Intl$., Int$), also known as Geary–Khamis dollar (symbols G–K$ or GK$), is a hypothetical unit of currency that has the same purchasing power parity (PPP) that the U.S. dollar had in the United States at a given point in time.[1][2] It is mainly used in economics and financial statistics for various purposes, most notably to determine and compare the purchasing power parity and gross domestic product (GDP) of various countries and markets. The year 1990 or 2000 is often used as a benchmark year for comparisons that run through time. The unit is often abbreviated, e.g., 2000 US dollars or 2000 International$ (if the benchmark year is 2000).

It is based on the twin concepts of PPP of currencies and the international average prices of commodities. It shows how much a local currency unit is worth within the country’s borders. It is used to make comparisons both between countries and over time. For example, comparing the per capita GDP of various countries in international dollars, rather than based simply on exchange rates, provides a more valid measure to compare standards of living. It was proposed by Roy C. Geary in 1958 and developed by Salem Hanna Khamis between 1970 and 1982.

Figures expressed in international dollars cannot be converted to another country’s currency using current market exchange rates; instead, they must be converted using the country’s PPP exchange rate used in the study.

Exchange rate by country

According to the IMF, below is the implied PPP exchange rate of the international dollar to the local currencies of the following nations:

Country Exchange rate in 1985 Exchange rate in 2025[3]
Afghanistan 13.27
Albania 2.47 42.05
Algeria 2.45 42.58
Andorra 0.60
Angola 320.81
Antigua and Barbuda 1.85
Argentina 567.10
Armenia 148.16
Aruba 1.34
Australia 1.43
Austria 0.74
Azerbaijan 0.48
Bahamas 0.94
Bahrain 0.16
Bangladesh 30.91
Barbados 2.19
Belarus 0.92
Belgium 0.71
Belize 1.05
Benin 199.45
Bermuda
Bhutan 20.33
Bolivia 2.71
Bosnia and Herzegovina 0.72
Botswana 4.99
Brazil 2.55
Brunei 0.48
Bulgaria 0.43
Burkina Faso 213.78
Burundi 1420.00
Cape Verde 47.12
Cambodia 1350.00
Cameroon 199.28
Canada 1.16
Central African Republic 233.90
Chad 206.06
Chile 473.23
China 3.40
Colombia 1550.00
Comoros 191.21
Congo 1150.00
Congo-Brazzaville 214.06
Costa Rica 298.38
Croatia 0.47
Cuba
Cyprus 0.57
Czech Republic 12.96
Denmark 5.93
Djibouti 78.08
Dominica 1.37
Dominican Republic 23.86
Ecuador 0.43
Egypt 7.58
El Salvador 0.42
Equatorial Guinea 226.21
Eritrea
Estonia 0.61
Ethiopia 30.34
Fiji 0.90
Finland 0.75
France 0.65
Gabon 217.84
Gambia 17.71
Georgia 0.91
Germany 0.72
Ghana 4.75
Greece 0.53
Grenada 1.53
Guatemala 3.28
Guinea 3120.00
Guinea-Bissau 230.49
Guyana 69.06
Haiti 111.31
Honduras 11.90
Hong Kong 5.52
Hungary 187.45
Iceland 157.56
India 20.08
Indonesia 4720.00
Iran 171610.00
Iraq 491.17
Ireland 0.76
Israel 3.68
Italy 0.60
Ivory Coast 213.82
Jamaica 94.73
Japan 94.69
Jordan 0.30
Kazakhstan 170.82
Kenya 43.55
Kiribati 1.12
Kosovo 0.34
Kuwait 0.18
Kyrgyzstan 28.46
Laos 4770.00
Latvia 0.53
Lesotho 6.31
Liberia 0.46
Libya 1.84
Lithuania 0.5
Luxembourg 0.86
Macao 4.45
Madagascar 1390.00
Malawi 616.94
Malaysia 1.36
Maldives 7.92
Mali 198.63
Malta 0.56
Marshall Islands 1.09
Mauritania 11.74
Mauritius 17.92
Mexico 10.29
Micronesia 1.09
Moldova 7.48
Mongolia 1210.00
Montenegro 0.38
Morocco 3.92
Mozambique 23.65
Myanmar 625.04
Namibia 7.10
Nauru 1.90
Nepal 33.33
Netherlands 0.77
New Zealand 1.50
Nicaragua 12.51
Niger 206.53
Nigeria 194.96
North Korea
North Macedonia 19.32
Norway 8.80
Oman 0.18
Pakistan 67.54
Palau 1.02
Panama 0.45
Papua New Guinea 2.74
Paraguay 2650.00
Peru 1.83
Philippines 19.07
Poland 1.91
Portugal 0.57
Puerto Rico 0.77
Qatar 2.11
Romania 2.08
Russia 29.51
Rwanda 384.48
Saint Kitts and Nevis 1.69
Saint Lucia 1.35
Saint Vincent and the Grenadines 1.37
Samoa 2.01
San Marino 0.69
Sao Tome and Principe 13.77
Saudi Arabia 1.76
Senegal 206.67
Serbia 48.56
Seychelles 7.81
Sierra Leone 5340.00
Singapore 0.79
Slovakia 0.53
Slovenia 0.57
Solomon Islands 6.85
Somalia 0.40
South Africa 7.42
South Korea 787.88
South Sudan 1420.00
Spain 0.59
Sri Lanka
Sudan 989.32
Suriname 12.12
Swaziland 5.91
Sweden 8.31
Switzerland 0.94
Syria
Taiwan 13.65
Tajikistan 2.75
Tanzania 773.95
Thailand 10.09
Timor-Leste 0.29
Togo 198.30
Tonga 2.04
Trinidad and Tobago 3.39
Tunisia 0.92
Turkey 16.65
Turkmenistan 1.74
Tuvalu 1.47
Uganda 1260.00
Ukraine 12.86
United Arab Emirates 2.21
United Kingdom 0.67
United States 1.00
Uruguay 27.10
Uzbekistan 3670.00
Vanuatu 123.71
Venezuela 69.38
Vietnam 6990.00
Yemen 556.71
Zambia 7.56
Zimbabwe 10.31

Short description of Geary–Khamis system

This system is valuing the matrix of quantities using the international prices vector. The vector is obtained by averaging the national prices in the participating countries after their conversion into a common currency with PPP and weighing quantities. PPPs are obtained by averaging the shares of national and international prices in the participating countries, weighted by expenditure. International prices and PPPs are defined by a system of interrelated linear equations that need to be solved simultaneously. The GK method produces PPPs that are transitive and actual final expenditures that are additive.

Inflation adjusting

When comparing between countries and between years, the international dollar figures may be adjusted to compensate for inflation. In that case, the base year is chosen, and all figures will be expressed in constant international dollars for that specified base year. Researchers must understand which adjustments are reflected in the data (Marty Schmidt):

  • Population adjustments (In which case, figures represent per capita monies);
  • Currency exchange rate adjustments (In which case, figures will be expressed in one currency unit (typically US$, International $, € £ or ¥);
  • Purchasing power parity adjustments and/or average commodity prices (in which case, figures are typically expressed as International $);
  • Inflation adjustments (in which case, figures have been adjusted, based on changes in an inflation index such as the consumer price index, to represent currency for a “base” year, such as 2000).

Description of Geary–Khamis system

It is an iterative method based on the solution of (m + n) linear equations; a country’s currency is chosen as the reference monetary unit and set equal to 1, and all the values of the Purchasing Power Parities are initially set equal to 1, for example, and the system is solved, iterating until the PPP values converge. Suppose PPPj is the parity of the j-th currency with a currency called international dollars, which may reflect any currency; however, the US dollar is the most commonly used. Then the international price Pi is defined as an international average of the prices of the i-th commodity in various countries. Prices in these countries are expressed in their national currencies. The Geary–Khamis method solves this by using national prices after conversion into a common currency using the purchasing power parities (PPP). Hence, the international price, Pi of the i-th commodity, is defined as:

This equation implies that the international price of the i-th commodity is calculated by dividing the total output of the i-th commodity in all selected countries, converted into international dollars, using purchasing power parities, by the total quantity produced of the i-th commodity. The previous equation can be rewritten as follows:

This equation suggests that Pi is a weighted average of international prices pij after conversion into international dollars using PPPj. PPPj is by the Geary–Khamis system defined through this equation:

The numerator of the equation represents the total value of output in the j-th country expressed in national currency, and the denominator is the value of the j-th country’s output evaluated by repricing at international prices Pi in international dollars. Then PPPj gives the number of national currency units per international dollar.

Advantages

Geary–Khamis international dollar is widely used by foreign investors and institutions such as the IMF, FAO and World Bank. It has become so widely used because it has made it possible to compare living standards between countries. Thanks to the international dollar, they can see a more trustworthy economic situation in the country and decide whether to provide additional loans (or any other investments) to said country, or not. It also offers some comparison of purchasing power parities all around the world (developing countries tend to have higher PPPs). Some traders even use the Geary–Khamis method to determine if a country’s currency is undervalued or overvalued. Exchange rates are frequently used for comparing currencies; however, this approach does not reflect the real value of currency in said country. It is better to include PPP or the prices of goods in said country. International dollar solves this by taking into account exchange rates, PPP and average commodity prices. The Geary–Khamis method is the best method for comparisons of agricultural outputs.

See also

References

  1. ^ “International Dollar Geary-Khamis Defined, Examples Explained”. Business Case Web Site. 24 February 2016. Retrieved 13 April 2019.
  2. ^ “What is an “international dollar”?”. World Bank Data Help Desk. Retrieved 13 April 2019.
  3. ^ “World Economic Outlook”. imf.org. Retrieved 15 April 2026.