{"indicators":80,"indicators_tracked":1318,"domains":12,"countries":204,"forecast_countries":68,"providers":40,"providers_official":17,"providers_published":15,"providers_by_kind":{"commercial":13,"research":9,"official":17,"ai_estimate":1},"feeds":44,"feeds_current":41,"indicator_id_prefixes":43,"sources":40,"sources_definitions":{"providers":"Organisations whose data the pipeline ingests today: public institutions, research projects, companies and one AI model. Counted only when their rows are in the database. Values typed into our own code are not a provider.","providers_official":"Of those, public institutions: intergovernmental bodies, national statistics offices, central banks and other government agencies.","providers_published":"Providers behind at least one of the indicators a reader can open on the site.","feeds":"Datasets or API endpoints (one provider can have several) that have rows in the database. Foundation forecasting models are not feeds.","feeds_current":"Feeds whose pipeline job fetched data successfully in the last 14 days. Feeds whose job is not logged in pipeline_runs are not counted here.","indicator_id_prefixes":"How many different indicator-id prefixes the database holds. This is the number the site used to call 'sources'. It is a naming convention, not a count of institutions: several prefixes share one provider.","last_successful_fetch":"Newest pipeline_runs row of the feed's job with status success and at least one row fetched. A job that writes several feeds shares its timestamp."},"sources_registry":"/api/sources","data_points":1252213,"forecast_indicators":215,"forecast_series":5942,"horizon_years":10,"relationships":2578,"relationships_statistical":6884,"accuracy_pct":85.3,"error_reduction_vs_naive_pct":22.1,"median_skill_vs_naive_pct":6.7,"indicators_beating_naive":135,"indicators_evaluated":215,"interval80_coverage_pct":74.1,"monthly_forecast_indicators":105,"monthly_forecast_series":958,"monthly_error_reduction_vs_naive_pct":8.4,"monthly_interval80_coverage_pct":73.6,"models":["age_cohort_retention","arima","chronos2","chronos2_cov","demographic_drivers","drift","ets","global","global_share","imf_weo","macro","naive","tabpfn35","theta","timesfm25","timesfm3","timesfm3_cov"],"models_count":17,"last_data_update":"2026-10-19 07:30:28","last_model_run":"2026-10-19T06:10:22","evaluation":"Protocol v7.4. Evaluation fold B: history cut at the panel anchor minus 5 years, 5 years scored out of sample. The anchor is the newest year at least 50% of an indicator's country series reach, so one fast country cannot move the window for the rest. Selection fold A: history cut at the panel anchor minus 10 years, 5 years forecast. Used only to choose each indicator's mix of models and to size its interval. Its last target year is fold B's as-of year, so nothing chosen on A had seen B's outcomes. Interval widths come from fold A and the older windows anchor-15, anchor-20; published intervals add fold B. The headline accuracy is a 5-year out-of-sample test on history up to each indicator's as-of year, not a check on the published 10-year forecasts. Fold B also decides which v8 (driver-based) indicators are published, so the fold-B score of a published v8 indicator is a validation result, not an independent test (ml_v7/engine.py). The prospective forecast ledger is the independent test. Chronos-2 and TimesFM are pretrained by their vendors on public data that may already contain part of the history they are scored on. The local fit respects the as-of cut; the pretraining corpus is outside our control. Inputs are pseudo-real-time: today's revised data, not the vintage that was available in the as-of year. A revision published later can flatter or punish a model.","protocol_version":"v7.4","protocol_fold_a_horizon_years":5,"protocol_fold_b_horizon_years":5,"protocol_selection_text":"Selection fold A: history cut at the panel anchor minus 10 years, 5 years forecast. Used only to choose each indicator's mix of models and to size its interval. Its last target year is fold B's as-of year, so nothing chosen on A had seen B's outcomes.","protocol_evaluation_text":"Evaluation fold B: history cut at the panel anchor minus 5 years, 5 years scored out of sample. The anchor is the newest year at least 50% of an indicator's country series reach, so one fast country cannot move the window for the rest.","protocol_interval_text":"Interval widths come from fold A and the older windows anchor-15, anchor-20; published intervals add fold B.","protocol_headline_scope":"The headline accuracy is a 5-year out-of-sample test on history up to each indicator's as-of year, not a check on the published 10-year forecasts.","protocol_caveats":"Fold B also decides which v8 (driver-based) indicators are published, so the fold-B score of a published v8 indicator is a validation result, not an independent test (ml_v7/engine.py). The prospective forecast ledger is the independent test. Chronos-2 and TimesFM are pretrained by their vendors on public data that may already contain part of the history they are scored on. The local fit respects the as-of cut; the pretraining corpus is outside our control. Inputs are pseudo-real-time: today's revised data, not the vintage that was available in the as-of year. A revision published later can flatter or punish a model.","reliability_threshold_pct":15,"reliability_min_series":3,"reliability_high":47,"reliability_moderate":88,"reliability_experimental":80,"reliability_evaluated":215,"reliability_high_median_error_reduction_pct":38.9,"reliability_high_by_domain":{"economy":{"high":22,"total":94},"demographics":{"high":8,"total":10},"work":{"high":5,"total":31},"health":{"high":4,"total":13},"technology":{"high":3,"total":7},"real_estate":{"high":1,"total":7},"energy":{"high":1,"total":16},"education":{"high":1,"total":3},"housing":{"high":1,"total":1},"environment":{"high":1,"total":4},"other":{"high":0,"total":22},"food":{"high":0,"total":2},"geopolitics":{"high":0,"total":4},"crime":{"high":0,"total":1}},"reliability_strong_single_series":26,"monthly_reliability_high":13,"monthly_reliability_moderate":62,"monthly_reliability_experimental":30,"monthly_reliability_evaluated":105,"monthly_reliability_high_median_error_reduction_pct":19.6,"reliability_basis":"skill on the latest 5-year holdout vs a 'no change' forecast; high = errors at least 15% smaller on 3+ series; never high when the data stopped arriving","reliability_stale_capped":3,"monthly_reliability_stale_capped":0,"stale_indicators":1067,"stale_graded_indicators":["fao.food_price_index","fred.cb_rate.BRA","fred.cb_rate.CAN","fred.cb_rate.CZE","fred.cb_rate.DNK","fred.cb_rate.HUN","fred.cb_rate.IDN","fred.cb_rate.IND","fred.cb_rate.JPN","fred.cb_rate.POL","fred.cb_rate.RUS","fred.cb_rate.ZAF","gapminder.life_expectancy_female","un.maternal_mortality_ratio","un.poverty_rate_intl","un.primary_completion_rate","un.renewable_energy_share","wb.cpi_yoy_monthly","wb.education_spending_gdp","wb.gini_coefficient","wb.government_debt_gdp","wb.health_spending_gdp","wb.out_of_pocket_health_spending","wb.rd_spending_gdp","wb.renewable_energy_pct","wb.researchers_per_million","who.life_expectancy_both","who.life_expectancy_male","who.uhc_coverage_index"],"freshness_rule":"stale = newest observation older than 4 months (monthly), 9 (quarterly), 36 (annual), 2 (daily/weekly) on at least half of the 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t_observation":"2016-01-01","age_months":129},{"country_iso3":"IRN","last_observation":"2016-01-01","age_months":129},{"country_iso3":"CAN","last_observation":"2017-01-01","age_months":117},{"country_iso3":"JPN","last_observation":"2017-01-01","age_months":117},{"country_iso3":"VEN","last_observation":"2017-01-01","age_months":117},{"country_iso3":"CHL","last_observation":"2018-01-01","age_months":105},{"country_iso3":"UGA","last_observation":"2018-01-01","age_months":105},{"country_iso3":"AUS","last_observation":"2019-01-01","age_months":93},{"country_iso3":"PHL","last_observation":"2019-01-01","age_months":93},{"country_iso3":"TZA","last_observation":"2020-01-01","age_months":81},{"country_iso3":"PAK","last_observation":"2021-01-01","age_months":69},{"country_iso3":"SGP","last_observation":"2021-01-01","age_months":69},{"country_iso3":"USA","last_observation":"2021-01-01","age_months":69},{"country_iso3":"IND","last_observation":"2022-01-01","age_months":57},{"country_iso3":"ISR","last_observation":"2022-01-01","age_months":57},{"country_iso3":"PER","last_observation":"2022-01-01","age_months":57},{"country_iso3":"VNM","last_observation":"2023-01-01","age_months":45}],"wb.trade_balance_usd":[{"country_iso3":"NGA","last_observation":"1960-01-01","age_months":801},{"country_iso3":"ARE","last_observation":"2023-01-01","age_months":45}],"wb.trade_pct_gdp":[{"country_iso3":"NGA","last_observation":"1960-01-01","age_months":801},{"country_iso3":"ARE","last_observation":"2023-01-01","age_months":45}],"wb.unemployment_rate":[{"country_iso3":"UKR","last_observation":"2021-01-01","age_months":69}],"wb.youth_unemployment":[{"country_iso3":"UKR","last_observation":"2021-01-01","age_months":69}]},"series_freshness_rule":"a country series is stale on the same thresholds as the indicator rule, judged on its own newest observation"}