Georgia vs Peru: Gross National Income — Value US$ per capita
Gross National Income — Value US$ per capita over time
- Georgia
- Peru
How they compare
Georgia currently reports 7,487 USD against 7,370 USD in Peru, a difference of 117 USD.
The two have swapped places 1 time across 33 shared years of data; in 1991 it was Peru ahead.
Georgia ranks 106th and Peru ranks 107th of 195 countries.
Peru has averaged higher in every one of the 4 decades both report.
Head to head by decade
| Decade | Georgia | Peru | Difference | Ahead |
|---|---|---|---|---|
| 1990s | 763.29 USD | 1,846 USD | 1,083 USD | Peru |
| 2000s | 1,757 USD | 2,658 USD | 901.31 USD | Peru |
| 2010s | 4,150 USD | 6,082 USD | 1,932 USD | Peru |
| 2020s | 5,574 USD | 6,626 USD | 1,051 USD | Peru |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher gross national income — value us$ per capita, Georgia or Peru?
- Georgia, at 7,487 USD against 7,370 USD in Peru as of 2023.
- What is the difference in gross national income — value us$ per capita between Georgia and Peru?
- 117 USD, with Georgia ahead.
- How many years of comparable data are there for Georgia and Peru?
- 33 years are reported by both, from 1991 to 2023.
- How do Georgia and Peru rank globally for gross national income — value us$ per capita?
- Georgia ranks 106th and Peru ranks 107th of 195 countries.
- Where does this data come from?
- Food and Agriculture Organization of the United Nations, published as Gross National Income — Value US$ per capita. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The FAOSTAT Macro Indicators database provides a selection of country-level macro indicators relating to total economy (Gross Domestic Product, Gross Fixed Capital Formation); agriculture activity; agriculture, forestry and fishing activity; total manufacturing activity; manufacturing of food products and beverages activity; manufacturing activity of tobacco products; and manufacturing activity of food, beverage and tobacco products.It releases time series for a selection of National Accounts variables, including gross domestic product, gross fixed capital formation, industry-level value added and gross output. The database also proposes additional indicators such as gross domestic product per capita, year-on-year growth rates and measures of industry contribution to gross domestic product. All data relating to Gross Domestic Product, Gross Fixed Capital Formation, agriculture, forestry and fishing activity, and to total manufacturing activity originates from the United Nations Statistics Division (UNSD) National Accounts Estimates of Main Aggregates database, which consists of a complete and consistent set of time series of the main National Accounts aggregates of all UN Members States and other territories in the world for which National Accounts information is available. The UNSD database's content is based on the countries' official National Accounts data reported to UNSD through the annual National Accounts Questionnaire, supplemented with data estimates for any years and countries with incomplete or inconsistent information (See http://unstats.un.org/unsd/snaama/Introduction.asp). Data series relating to the sub-industry Agriculture activity are obtained from the UNSD national accounts Official Country Data databases while series on the Manufacturing activity of food and beverages products, manufacturing activity of tobacco products and manufacturing activity of food, beverages and tobacco products originates from the United Nations Industrial Development Organization (UNIDO) INDSTAT2 database. In order to ensure that sub-industry series are consistent in levels with National Accounts based series, which is needed to support comparability across industries (agriculture vs. agro-industry and sub-industries), UNIDO originating series are rescaled on UNSD National Accounts Estimates of Main Aggregates data series (See Section 17.5 for a more detailed description of the data processing steps).