Ecuador vs Peru: Arms exports

Arms exports: 2 million TIV in Ecuador in 2018 and 5 million TIV in Peru in 2004, by SIPRI estimates.

SIPRI trend-indicator values · SIPRI

EcuadorPeruWorld

Every year

SIPRI trend-indicator values · SIPRI

Year	Ecuador	Peru	World
2025	–	–	33.5 billion
2024	–	–	30.7 billion
2023	–	–	29.5 billion
2022	–	–	33.3 billion
2021	–	–	27.1 billion
2020	–	–	24.1 billion
2019	–	–	27 billion
2018	2 million	–	27.4 billion
2017	–	–	31.3 billion
2016	–	–	31.5 billion
2015	–	–	28.7 billion
2014	6 million	–	27.1 billion
2013	–	–	27.4 billion
2012	–	–	27.9 billion
2011	–	–	29.9 billion
2010	–	–	25.8 billion
2009	–	–	24.4 billion
2008	–	–	24.1 billion
2007	–	–	26.5 billion
2006	–	–	24.5 billion
2005	–	–	21.4 billion
2004	–	5 million	21.3 billion
2003	–	–	19.2 billion
2002	–	–	17.7 billion
2001	–	14 million	18.5 billion
2000	–	–	20.5 billion
1999	–	–	25.4 billion
1998	–	–	27.9 billion
1997	–	–	28.9 billion
1996	–	–	23.7 billion
1995	–	–	22.9 billion
1994	–	–	23 billion
1993	–	–	25.8 billion
1992	–	–	24.3 billion
1991	–	–	28.2 billion
1990	–	–	30.2 billion
1989	–	–	34.9 billion
1988	–	–	36.8 billion
1987	–	–	39.4 billion
1986	–	–	39 billion
1985	–	–	38.2 billion
1984	–	–	41.6 billion
1983	–	–	43.9 billion
1982	–	50 million	46.2 billion
1981	–	–	45.8 billion
1980	–	–	42.2 billion
1979	–	–	38.4 billion
1978	–	–	42.4 billion
1977	–	–	40 billion
1976	–	–	36 billion
1975	–	–	37.2 billion
1974	–	–	36.6 billion
1973	–	–	36.3 billion
1972	–	–	34.5 billion
1971	–	–	32.9 billion
1970	–	–	25.3 billion
1969	–	–	28.1 billion
1968	–	–	26.1 billion
1967	–	–	25.6 billion
1966	–	–	25.8 billion
1965	–	–	25.8 billion
1964	–	–	26.7 billion
1963	–	–	20.3 billion
1962	–	–	17.5 billion
1961	–	–	16.4 billion
1960	–	–	17.6 billion

Major weapons the country sent abroad, in SIPRI trend-indicator values (TIV): what the arms are worth as military capability, priced by their production cost, not what was paid.
Source: SIPRI Arms Transfers Database, via the World Bank.
The faint line is the world as a whole, as the same source counts it.

How the layers work, where their data comes from and what they can’t tell you: Countries through time