Global macro

The section at /global/ asks six questions about the world economy, with India always in view: is it growing or slowing; where is inflation heading; what are central banks doing and how tight is money; how much debt is there and is credit stretched; external balances and the dollar; commodities and trade. The overview (/global/) is a board of fourteen economies on ten measures. Each question has its own page, which ends with what it means for India. /global/fred/ is the catalogue of every FRED series we publish. /world/ (world stock markets) is separate.

Code: pipeline/tipsheet/compute/global_questions.py, publish/global_questions.py, step steps/global_questions.py (needs macro and bis). The older global bundles below are built by compute/global_macro.py, global_cycle.py, global_stress.py, bis.py and fred_catalogue.py, and are unchanged.

Bundles: macro/global/q/* (27 files, the largest about 65 KB). Each series bundle has one column per economy, named by its lower-case BIS code (in, us, xm for the euro area, cn, jp, gb, kr, id, br, mx, za, tr, au, ca) plus aggregates (g20, g7, oecd) where the source has them; meta.area_labels names every column.

The economies

India and the 13 peers the BIS pages already use: the US, the euro area, the UK, Japan, China, Korea, Indonesia, Brazil, South Africa, Mexico, Turkey, Australia and Canada. Turkey is kept in every table and on the board but left off shared-scale figures, because its inflation (above 80% at times) and policy rate would flatten every other panel. Each figure says so.

Sources, by question

Why India and the US use their own statistics

• India’s GDP. The OECD seasonally adjusts India’s quarterly GDP; MoSPI publishes no adjusted series. The two y/y rates differ by up to 0.9 pp a quarter (2026-Q2: OECD 8.10, MoSPI 7.82; 13 quarters on the 2022-23 base, mean difference 0.03 pp). We use MoSPI’s, the figure India’s statistics office publishes. The OECD’s is kept in the bundle as in_oecd_sa and drawn beside it on the growth page.
• The US’s GDP. OECD figures lag BEA’s annual revision: in October 2026 the OECD still had the pre-September vintage, 2026-Q2 2.19% against BEA’s 2.68%. Between 2000 and 2025-Q3 the two agree within 0.34 pp.
• India’s CPI. For years the OECD’s India CPI followed a different index from MoSPI’s all-India CPI: the two y/y rates differ by up to 5.6 pp (May 2019). We use MoSPI’s, linked across base years; the OECD’s is kept as in_oecd.
• India’s policy rate. BIS’s India series lags RBI by weeks (its last observation was June 2026 when this was built). We use RBI’s repo rate at month end where the pipeline has it, and BIS before; BIS’s is kept as in_bis.

Rules

• Dates: every value is dated by the first day of the period it describes (2026-04-01 = Q2 2026).
• Year-on-year changes compare the same month or quarter a year earlier; if that period is missing, the change is missing.
• Real policy rate = policy rate at month end minus CPI inflation for the same month. It is backward-looking: expected inflation is not available across countries.
• Peer median: the median of the other economies, India and Turkey excluded, only in months when at least half report.
• Reserves in months of imports: reserves at month end divided by one-twelfth of imports of goods and services in the latest full calendar year before the month (World Bank). Using the year before avoids look-ahead.
• India’s trade: rolling 12-month sums, only where all twelve months are reported. They start with the twelve months to March 2007, because the IMF’s import totals for India are incomplete before 2006 (US$ 110 bn in the year to March 2006, against 149 bn in the Commerce Ministry’s data).
• Partner shares: each partner’s share of India’s exports (or imports) over the latest 12 months, and the change on the 12 months before; partners are the top eight by value, ISO 3166 codes.

The board and its percentiles

Each cell of the overview board is the latest reading of one measure for one economy, and its percentile in that economy’s own history since January 2000: the share of readings since then at or below today’s, from 0 to 100. A percentile is left blank when a series has under eight years of history since 2000 (Australia’s monthly CPI, for example, starts in 2025).

The tint follows the percentile: blue above 50, red below, stronger towards the extremes, pale near the middle. It says only how unusual a reading is for that economy, not whether it is good or bad; each column says what “high” means (a high real policy rate is tight money, a high real exchange rate a dear currency). Percentiles use only the history up to the latest reading, so there is no look-ahead, but they are descriptive, not forecasts.

The ten measures: real GDP growth, the OECD leading indicator, CPI inflation, the policy rate, the real policy rate, the BIS credit gap, the private debt service ratio, real house prices (% y/y), the BIS real effective exchange rate and the current account (% of GDP, annual). The euro area has no OECD leading indicator, no BIS debt service ratio and is not in our World Bank pull, so those three cells are empty.

Licences

• OECD, World Bank, FAO: CC BY 4.0, with attribution in every bundle.
• BIS: reused under its terms of permitted use, citing “Source: BIS”.
• IMF (reserves, trade): the Data bank’s contract records “derived with credit”. Only derived figures are published (changes, ratios, 12-month sums, shares), never the IMF’s raw levels. The IMF World Economic Outlook table stays held back pending the owner’s decision.
• FRED: each series’ publish_policy in the Data bank catalogue decides. Everything in macro/global/q/* from FRED is public domain or citation-only.
• India’s 10-year government bond yield is left out of the long-rate figure: Indian bond yields (FBIL/FIMMDA) are withheld site-wide by the owner’s decision of 2026-10-02, and the OECD’s India series is built from the same market.
• PMIs (S&P Global, ISM) are proprietary and not used; the OECD’s business confidence indicator is the open stand-in.

Gaps

• ECB and Bank of Japan balance sheets. The ECB’s weekly series has ISO-week periods the Data bank’s SDMX parser does not read, and FRED’s copies are not in the curated catalogue. Only the Fed’s balance sheet is shown.
• Output gaps: only in the IMF WEO (held) and the OECD Economic Outlook (not ingested).
• Freight rates: the Baltic Dry and container indices are proprietary; chokepoint transits (IMF PortWatch) stand in.
• Core CPI for China, Brazil and Indonesia, and harmonised unemployment for India, China, Brazil, Indonesia and South Africa, are not published by the OECD.

Checks (2026-10-03, on real data)

• Quarterly GDP: the OECD query returned 36 series, 7,566 rows, to 2026-Q2 for every economy (India from 1996-Q3). US y/y against BEA: within 0.34 pp from 2000 to 2025-Q3 (the gap is OECD’s older vintage).
• India’s trade against the Commerce Ministry (financial years): exports 437.3 against 437.4 and imports 721.2 against 720.2 (US$ bn, 2024-25); exports 437.7 against 437.1 and imports 672.9 against 678.2 (2023-24).
• Board: 140 cells, 137 filled (the euro area’s three empty cells), 135 with a percentile.
• Licence gate: clean on every macro/global/q/* bundle; India has no column in money/long_rates_m (tested).
• Statements on the pages about rankings and history (who ran a surplus every year, whose real exchange rate is steadiest, who is above the Basel threshold) are computed from the bundles at build time, not written by hand.

US rates, liquidity, inflation and the India link

These are the older macro/global/* bundles, still used across the site (the money, inflation, external and growth pages; the dossiers; the indicator pages).

Code: pipeline/tipsheet/compute/global_macro.py, publish/global_macro.py.

Bundles: macro/global/* (23 files, the largest about 89 KB). Each bundle’s meta carries its source, licence, unit, method and start dates.

Sources

• FRED, through the Data bank dataset fred_series (33 series, refreshed daily by the 06:00 fred update). For each series and date the latest fetch is used.

  What	FRED ids	Publisher	Starts
  Treasury yields	DGS3MO, DGS2, DGS10, DGS30	Federal Reserve H.15 / Treasury	1981, 1976, 1962, 1977
  Real yield, breakeven	DFII10, T10YIE	H.15 / Treasury	2003
  Fed balance sheet, TGA	WALCL, WDTGAL, WTREGEN	Federal Reserve H.4.1	2002-12-18
  Overnight reverse repo	RRPONTSYD	New York Fed	2003 (full-time facility from 2013-09-23)
  Broad dollar, USD/INR	DTWEXBGS, DEXINUS	Federal Reserve H.10	2006, 1973
  Brent, WTI	DCOILBRENTEU, DCOILWTICO	EIA	1987, 1986
  CPI, core CPI	CPIAUCNS, CPILFENS (CPIAUCSL kept as a check)	BLS	1913, 1957
  PCE, core PCE	PCEPI, PCEPILFE	BEA	1959
  Jobs	UNRATE, PAYEMS	BLS	1948, 1939
  Fed funds, M2	FEDFUNDS, M2SL	Federal Reserve H.15, H.6	1954, 1959
  Financial conditions	NFCI, STLFSI4	Chicago Fed, St Louis Fed	1971, 1993
  Equity risk (derived only)	SP500, VIXCLS	S&P Dow Jones Indices, Cboe	2016, 1990

• FPI flows, through the IndiaDataHub loader in compute/flows.py:

  • NSDL daily net investment in US dollars (equity, and the total of all instruments), from 2021.
  • RBI’s monthly portfolio investment in India (US$, balance-of-payments basis), from April 2000.

• IMF World Economic Outlook, through the Data bank dataset imf_datamapper: annual real GDP growth and average consumer-price inflation for the world, advanced and emerging groups, and nine economies.

Licences

• Levels are published only for public-domain series. US federal government works (Federal Reserve Board, Treasury, BLS, BEA, EIA) are public domain. FRED’s notes for every published series carry no third-party copyright; this was checked series by series through the FRED API on 2026-10-01. The Chicago Fed and St Louis Fed indices carry no restriction in FRED’s notes and are published with attribution.
• Oil: EIA’s reuse page says its data are public domain. EIA presents Brent and WTI spot as its own series with no third-party restriction.
• S&P 500 and VIX are copyrighted (FRED’s notes name S&P Dow Jones Indices and Cboe). Only weekly returns, drawdown and the VIX’s percentile are published, never a level.
• IMF: published with attribution. The IMF’s data terms allow reuse with attribution. The Data bank’s source note says “personal-research use only”, which is stricter than the IMF’s own terms. The bundle says so, and the owner should confirm.

Method

• Spreads: 10y-2y and 10y-3m are computed from the constant-maturity yields on the same day.
• Net liquidity: Fed total assets minus the Treasury General Account minus overnight reverse repos, all at Wednesday levels, in US$ billion.
  • It is a market shorthand, not an official measure.
  • A second column uses the week-average TGA (WTREGEN), the variant most often quoted. The two differ by a median of $9.5 bn.
  • Holiday Wednesdays: ON RRP is taken from the last value within 6 days, because the previous overnight operation is still outstanding.
  • Before the standing facility (2013-09-23): a Wednesday with no operation counts as zero.
• US CPI inflation: year on year from the not-seasonally-adjusted CPI-U, which is how BLS reports its headline. PCE uses BEA’s seasonally adjusted index, as BEA reports it.
  • All year-on-year rates are by calendar month, so a missing month gives a null rather than a shifted comparison.
• Weekly views: weeks end on Friday.
  • Each column takes its last value in the week.
  • The row is dated by the latest actual observation, so no row is dated after its data.
  • The H.4.1 bundle keeps its Wednesday dates.
• India link (descriptive only):
  • Weekly, from 2021: weekly FPI net investment (US$ million), weekly changes in net liquidity, the US 10-year (bp) and the broad dollar (%).
    • z-scores are taken against the trailing 156 weeks (minimum 52).
    • Rolling 52-week correlations (minimum 40) are between weekly FPI equity flows and each change.
  • Monthly, from 2003: RBI’s monthly FPI against 12-month changes, with z-scores against the trailing 60 months, and 36-month rolling correlations with one-month changes.
  • Nothing uses future data.
• IMF table: five years around the build year. Years from the build year on are flagged as projections. India’s figures are on a fiscal-year basis in the WEO.

Checks (2026-10-01, on real data)

• 10y-2y: our spread equals FRED’s T10Y2Y exactly on 12,576 of 12,579 days since 1976. The three exceptions (1990-11-21, 1991-01-29, 1995-11-29) are off by 0.01–0.02 points.

• 10y-3m: our spread matches T10Y3M on all but 2 of 11,188 days (1991-01-29 and 1999-10-01, up to 0.10 points).

• Breakeven: T10YIE equals DGS10 minus DFII10 on all 5,940 days.

• CPI levels: FRED’s CPIAUCNS matches the BLS public API (series CUUR0000SA0) on all 31 months it returned, January 2024 to August 2026.

  • Year-on-year rates computed from BLS’s own levels match ours for March to August 2026: 3.26, 3.81, 4.25, 3.53, 3.36 and 3.40%.

• CPI against BLS headline prints: our headline and core rates round to the published figures every time:

  Month	Headline	Core
  Jun 2022	9.1
  Sep 2022	8.2	6.6
  Sep 2023	3.7	4.1
  Dec 2024	2.9	3.2
  Jan 2025	3.0	3.3

  The comparison is stored in the bundle meta. Seasonally adjusted rates differ from these by up to 0.14 points over the last five years.

• Fed balance sheet: it peaks at $8,965 bn on 2022-04-13, which agrees with the published H.4.1 peak.

• Published files: every macro/global file is parsed as strict JSON (no NaN or Infinity) at publish time, and is under 150 KB.

Caveats

• October 2025 CPI does not exist. BLS published none because of the federal shutdown, so that month and October 2026 have no year-on-year rate.

• The correlations between FPI flows and global drivers are weak and unstable:

  Window	Range
  Weekly, rolling 52 weeks	−0.40 to +0.35
  Monthly, rolling 36 months	−0.58 to +0.34

  Full-period weekly correlations are between −0.02 and −0.09. The strongest monthly link is with the dollar (−0.33 over 246 months). Read these as description, not cause.

• NSDL dates FPI trades one day after the exchanges. Weekly sums absorb most of the lag.

• The H.10 dollar and rupee rates lag. They are published weekly on Mondays, so the latest week can be missing. The rupee here is a New York noon rate; use macro/india for RBI/FBIL rates.

• S&P 500 history on FRED covers only 10 years. Its drawdown is measured from the highest close since 2016.

• Revisions: NFCI and STLFSI4 are revised back through history every week, and payrolls are revised for two months after release.