Belarus vs Sri Lanka: Value Added (Agriculture) — Value US$
Value Added (Agriculture) — Value US$ over time
- Belarus
- Sri Lanka
How they compare
Sri Lanka currently reports 5,738 million USD against 5,300 million USD in Belarus, a difference of 438 million USD.
That makes Sri Lanka's figure about 1.1 times Belarus's.
The two have swapped places 1 time across 7 shared years of data; in 2016 it was Sri Lanka ahead.
Belarus ranks 31st and Sri Lanka ranks 30th of 82 countries.
Sri Lanka has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Belarus | Sri Lanka | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 3,506 million USD | 5,233 million USD | 1,727 million USD | Sri Lanka |
| 2020s | 4,324 million USD | 5,831 million USD | 1,507 million USD | Sri Lanka |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher value added (agriculture) — value us$, Belarus or Sri Lanka?
- Sri Lanka, at 5,738 million USD against 5,300 million USD in Belarus as of 2023.
- What is the difference in value added (agriculture) — value us$ between Belarus and Sri Lanka?
- 438 million USD, with Sri Lanka ahead.
- How many years of comparable data are there for Belarus and Sri Lanka?
- 7 years are reported by both, from 2016 to 2022.
- How do Belarus and Sri Lanka rank globally for value added (agriculture) — value us$?
- Belarus ranks 31st and Sri Lanka ranks 30th of 82 countries.
- Where does this data come from?
- Food and Agriculture Organization of the United Nations, published as Value Added (Agriculture) — Value US$. 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).