Argentina

7 episodes between 1828 and 2016. Consecutive crisis years are merged into episodes (gaps of up to two years bridged); each links to its episode page.

• 1828–1857
• 1890–1893
• 1914
• 1930–1934
• 1951
• 1956–1975
• 1980–2016

Source: Global Macro Database 2026_06 | Reinhart-Rogoff (HBS BFFS) | Laeven & Valencia (2020, 2026) | Jordà-Schularick-Taylor Macrohistory Database | ECB/ESRB Financial Crises Database. License: non-commercial research (inherits GMD / JST); cite all five chronologies. Methodology

The crisis early-warning model (ews-1.0) scores Argentina from realized data only: features dated 2024 or earlier, no forecasts and no nowcasts. 6 of the model’s 7 features are observed here, and the score places Argentina in decile 10 of 10 among the 196 countries carrying a current row.

An early-warning score flags a macro-financial configuration that resembles past pre-crisis years; it is not a forecast for Argentina. At the published operating threshold (p ≥ 12.5%), the era-blocked out-of-sample backtest gives precision 16.9% and recall 25.7%: most flags did not precede an onset, and most onset years went unflagged.

Source: Jordà-Schularick-Taylor Macrohistory R6 | Laeven & Valencia (2026), IMF WP/26/94 | BIS credit-to-GDP gap and total credit (Data Portal) | Global Macro Database (release 2026_06). License: non-commercial research (inherits GMD / JST). Model ews-1.0, data vintage jst-r6(2020);lv-2026-wp2694(2023);bis-gap(2025-Q4);gmd-2026_06(cut2024). Methodology

Financial inclusion

How much of the adult population (age 15+) is inside the financial system, from the World Bank Global Findex 2025: account ownership, digital payments, and formal saving and borrowing. Findex is a survey run in waves, not annually, so each card is a wave sparkline with the latest reading and the change since the first wave available for Argentina.

Source: World Bank Global Findex Database 2025. License: CC BY 4.0. Survey waves; percent of adults age 15+. Methodology

Policy, shadow and exchange rates

The monetary-policy and currency backdrop from the BIS and Krippner: the observed central-bank policy rate from the BIS (latest reading and a 10-year monthly path), the Krippner shadow short rate as a month-end model estimate of monetary stance at the zero lower bound rather than an observed policy rate, and, where reported, the BIS real broad effective exchange rate (index, 2020 = 100; a rise is real appreciation). The BIS policy-rate set covers 48 economies and the euro area; its real broad EER covers 63 economies. Krippner is cited here for the shadow-rate estimate and should be read as a model-based stance gauge, not as the central bank's posted rate. No Krippner shadow-rate estimate is present for Argentina in this estate.

Source: BIS central bank policy rates | BIS effective exchange rates | Krippner shadow short rate estimates (LJK Limited). License: BIS series are free with "Source: BIS" attribution; Krippner shadow-rate estimates are cited as model estimates from LJK Limited and are not republished as bulk data. Methodology

How concentrated Argentina’s income and wealth are. Top shares come from WID.world on equal-split adults (each adult in a couple assigned half the couple’s total); income (a flow) and wealth (a stock) are shown as distinct measures and never combined into one figure. The Gini coefficients are survey-based, on a 0 (perfect equality) to 1 (maximal concentration) scale: the World Bank PIP survey Gini and, where covered, the OECD disposable-income (post-tax, post-transfer) Gini. Each reading shows its year and, where a cross-country distribution exists, where Argentina sits among reporting economies. WID extends its most recent years by extrapolation, so a latest reading is an estimate.

Source: WID.world (World Inequality Database) | World Bank Poverty and Inequality Platform | OECD Income Distribution Database. License: WID.world and OECD IDD: display-with-attribution (owner no-redistribution ruling); World Bank PIP: CC BY 4.0. Top shares on equal-split adults; recent WID years are extrapolated. Ginis are survey-based and measure a different object from the fiscal top shares. Methodology

Latest government debt 85.3% of GDP (2024, Central govt (IMF GDD)). Peak 155.4% in 2023. This is 4.6 points above the 80.7% median at which 2000+ sovereign crises began (a comparison, not a prediction).

Source: IMF Global Debt Database | IMF World Economic Outlook. License: IMF, free with "Source: IMF" attribution. Methodology

Reading this profile

• This page composes existing FinObservatory layers; it introduces no new data. Every figure is reproducible from the source cited in its section. See the methodology for the composition and each source’s coverage and staleness.
• The peer line on a card (“N economies report; median…”) places this country’s latest reading among every reporting economy’s own latest reading for the same indicator, under the same filters. Latest years differ where reporting lags. It is a descriptive position (a count and a median), not a score; for indicators where lower is safer, such as nonperforming loans, a high position is not a good one.
• The layers stop at different dates: the World Bank GFDD depth and soundness series end 2021 and the IMF Financial Development Index ends 2020, but the IMF FSI soundness panel is current (annual through 2024–2025 where reported); the Global Findex inclusion series are surveyed in waves and reach 2024; IMF debt runs to 2024; the Penn World Table runs 1950–2023; and the BIS statistics are the most current (credit through 2025, residential property to 2026Q1, and the policy rate and effective exchange rate into 2026 where reported). Krippner's month-end shadow short rate estimates, where this page has them, run 1995-01-31 to 2026-06-30 and are model estimates rather than observed policy rates. The external accounts reach 2025 (IMF balance-of-payments and reserves), 2024 (remittance inflows) and 2023 (capital-account openness). A quiet recent tail in one section can simply be where that source stops.
• Where a source has no reading for Argentina, the section says so in words instead of drawing a chart. A stated absence means the underlying dataset does not cover this country, not that the value is zero.