## ch1data — dataset overview

## Source details

**Canonical URL:** [ch1data — dataset overview](https://www.imf.org/-/media/files/publications/gfsr/2023/april/data/ch1data.xlsx)

## Other formats

- [Markdown version](/-/media/files/publications/gfsr/2023/april/data/ch1data.xlsx.md)
- [Structured JSON version](/-/media/files/publications/gfsr/2023/april/data/ch1data.xlsx.json)

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### Dataset contents and structure
- XLSX workbook with multiple worksheets corresponding to figures in chapter 1 (worksheet names such as "Figure 1.2", "Figure 1.3.", "Figure 1.4.", etc.).
- Worksheet rowCount examples: 31, 73, 26, 79, 71, 61, 37, 85, 43, 134, 62, 41, 155, 153, 110, 95, 94, 2367, 943, 100, 5898, 943, 57, 5896, and others; some worksheets have rowCount 0.
- Many worksheets have mixed content: titles, axis labels, dates, and numeric series. Columns in sample rows are often sparse or unlabeled in the extracted sample.

### Major themes (worksheet-level)
- Credit market and bank capital structure (Figure 1.2).
- US money markets and Federal Reserve facilities (Figure 1.3).
- European funding stress, excess liquidity, and TLTROs (Figure 1.4).
- Bank lending standards and contributing factors (Figure 1.5).
- Securities holdings and valuation impacts on bank CET1 (Figure 1.7).
- Nonbank financial intermedaries (NBFIs) vulnerabilities and insurer asset composition (Figure 1.8).
- Financial conditions indexes across regions (Figure 1.9).
- US equity and bond market decompositions (Figure 1.10).
- Emerging market financial market developments and capital flows (Figures 1.13, 1.23).
- Quantitative tightening and additional government bond supply (Figures 1.19, 1.20).
- Corporate debt risk and firm-level interest coverage-based debt-at-risk (Figure 1.28).
- Residential and commercial real estate developments and vulnerabilities (Figures 1.29, 1.31).
- Extensive country- and sector-level time series throughout chapter-1 figures (many worksheets contain quarterly or monthly date series).

### Selected sample numeric values (preserved exactly as in the dataset samples)
- Figure 1.2 (Banks Usage of AT1 Debt, sample row):
  - AT1 Index weight (%) for "Bank 1": 8.9721088
  - CET1: 0.14206383232106704
  - AT1: 0.023551268310110753
- Figure 1.3 (SOFR and FHLB Discount Note Rates; Daily Money Market Fund Flows, sample row 2023-01-03):
  - Date: 2023-01-03T00:00:00.000Z
  - SOFR: 0.14000000000000057
  - FHLB: -0.2649999999999997
  - Government money market fund flows (Billions): 11.551897468
  - Prime: 8.113218137999999
  - Treasury: 12.182178439999989
- Figure 1.4 (Jurisdiction Excess Liquidity vs. Outstanding TLTROs, sample rows):
  - LUX: Excess Liquidity 261.2944138511448; TLTRO 8.552340265334
  - CYP: Excess Liquidity 74.65572114394384; TLTRO 16.896807367915006
  - FIN: Excess Liquidity 52.31823817503914; TLTRO 10.515380387554446
  - BEL: Excess Liquidity 44.73867243114672; TLTRO 8.066966223652356
  - NLD: Excess Liquidity 37.969763493460356; TLTRO 5.602741354866233
- Figure 1.5 (Bank Lending Standards, sample dates and values):
  - Date: 2005-04-01T00:00:00.000Z; USA 1.9481002330504908; JPN -0.381783759264314; EUR -0.24537299998194007; EM 0.5080333646945459
  - US bank lending/quarter indicators in sample rows include values such as EU 2.7661835479495096 and UK -1.805480653501732 in other dated rows.
- Figure 1.6 (HTM and AFS Securities for All US Banks, sample dates):
  - Date: 2007-01-01T00:00:00.000Z; HTM 0.019762815857163375; AFS 0.180431618584021
  - Date: 2007-04-01T00:00:00.000Z; HTM 0.01759573398444476; AFS 0.1802729592500582
  - Date: 2007-07-01T00:00:00.000Z; HTM 0.018412066233373464; AFS 0.1746185970951676
  - Date: 2007-10-01T00:00:00.000Z; HTM 0.01650917355965017; AFS 0.16590920740068235
- Figure 1.7 (Banks’ Security Holdings and Estimated Impact to CET1 — selected region values):
  - UK total securities: 35.38524618441431; debt securities: 19.515028896991698
  - US CET1 impact samples (basis points): -480, -261.4539655069249, -21.060633411329825
  - Europe CET1 impact samples (basis points): -172.7226865569389, -48.31551974448316, 4.6122211992857105
- Figure 1.8 (Insurer portfolios — Level III assets and US insurers illiquid assets, sample percentiles):
  - 90th percentile (Level III share): 6.394531854905764; 2016 value: 16.838140914040913; 2021 value: 18.07980530679286
  - US insurers allocation sample (2014): Nontraditional Liabilities 2.993233495504446; Structured Credit 4.529677195418257; Private CMBS 3.0024297119055885; Private RMBS 1.9784796945505032; Mortgage Loans 6.8205484206872615; Other Illiquid Assets 8.39986115931968
- Figure 1.9 (IMF Staff Financial Conditions Index sample dates):
  - Date: 2019-03-29T00:00:00.000Z; United States -0.530512477075771; Euro area -0.261915887552439; Other advanced economies 0.3628317610399; China 0.204386075790875; Emerging markets excluding China 0.108842805135622
  - Date: 2019-06-28T00:00:00.000Z; United States -0.703261668537327; Euro area -0.342456118229495; Other advanced economies 0.273582888659102; China 0.169748505921937; Emerging markets excluding China 0.00728132641406181
- Figure 1.10 (S&P 500 decomposition sample):
  - Price returns 3.3022628816292476; Risk-free rate -2.759389165344295; Earnings -1.1207614696517654; Equity risk premia 7.182413516625307
- Figure 1.13 (Emerging Market Bank Equity Excess Returns — sample):
  - Latam Since SVB collapse 1.4447450853160257; YTD 1.5428241324094687
  - Asia Since SVB collapse -4.932653151173969; YTD 0.9719685381253289
  - EMEA Since SVB collapse -4.791248469592029; YTD -2.992004354198734
  - US Since SVB collapse -20.594337; YTD -14.272589658716782
- Figure 1.19 (Quantitative Tightening — US, sample rows):
  - 2013-Q1 Net issuance / changes in outstanding marketable debt: 287.66261032608963
  - 2013-Q1 Absorption by the Federal Reserve (negative = purchases): -137.60574210000004
  - 2013-Q1 Share of net issuance absorbed by the Fed (rolling 4-quarter avg, right scale): 11.99562559270116
  - 2023 original maturities projected to be run off by the Fed: <=2 years 136.14641945930788; >2-5 years 338.7826542572764; >5-10 years 134.0533837221321; >10-30 years 14.681078761283526
  - 2008Q4 US-chartered banks' holdings of US Treasury Securities: US banks' holdings of US Treasuries 56.362; Reserves of US banks 546.942; Share of US Treasury holdings in total US bank assets 0.4659052686841346; Share of US banks' Treasury holdings in total outstanding 0.7529557742351044
- Figure 1.20 (European government and gilt supply sample rows):
  - 2015 European government bond supply (euro bn left scale): Gross supply 2015: 906; Redemptions -646; Net ECB purchases -463; Net supply taking ECB QT/QE into consideration -203
  - 2015 Gilt supply (British pound bn right scale): Gross supply 2015: 16; Redemptions -457; Net ECB purchases 18.75; Net supply taking ECB QT/QE into consideration -457
- Figure 1.23 (Emerging Market Capital Flows, portfolio flow tracking sample):
  - 2022-01-31T00:00:00.000Z: Local currency bonds 8.613278280024005; Sovereign Hard Currency (net issuance) 8.300999999999998; Equities -0.17855900000000013
  - Probability density of outflows sample value: 0.21172641542830015 (and other quarterly values up to 0.41086492028222776 and 0.4059912770327639)
  - Capital flows at risk (5th percentile) sample series includes values like 1.9, 2, 2.1, 2.4, 2.2, 2.2, 2.2, 2.1, 2.5, 2.6, 2, 2, 1.9, 1.8, 1.9, 2, 2.3, 2.8, 3.2, 3.2, 2.8
- Figure 1.25 (Frontier Markets and LIC challenges sample):
  - "Public debt/GDP" sample (1999): Frontier 35.3555; EMBIG ex-Frontier 29.564
  - "Public debt/GDP" sample (2000): Frontier 50.317499999999995; EMBIG ex-Frontier 40.4485
  - Median interest/revenue sample 2002-03-15T00:00:00.000Z: 6.94462207443407; 25th 2.052497117419496; 75th 17.321600661286674
- Figure 1.26 (Chinese property and LGFV spreads sample):
  - Relatively low income LG debt sample: 26.94717519488501
  - Relatively high income LG debt sample: 188.88582298087087
  - LGFV spreads and other cells include numeric values and some "#N/A" errors in sample extraction
- Figure 1.28 (Corporate Debt Analysis: Debt at Risk, sample rows):
  - Small firms, 2Q22 share of debt with ICR <1: 0.7260519862174988; 1 to 4: 0.06547828018665314; >4: 0.20846974849700928
  - AE high-grade sample ICR and shock values: Earnings shock 2.9189529418945312, 11.681047058105468, -2.9189529418945312; Interest shock 6.595556259155273, 5.085490798950195, -6.595556259155273
- Figure 1.29 (Residential real estate sample):
  - Price-to-Income index 2000q1: 101.2499
  - Permits 2000q1: 164.9969
  - Mortgage cost index 2000q1: 170.8212
  - Distribution of year-over-year changes (2022:Q3) sample categories: <= -5% 18.18182 (Advanced Economies); other distribution bins and values shown in table rows
- Figure 1.30 (Household vulnerabilities sample):
  - Debt service ratio and exposures per country row examples: Australia 13.7 (Debt service ratio percent, 2022:Q2), Korea 13.4, Netherlands 13.4, Canada 13.1, Norway 12.6, Denmark 12.5
  - Country-level consumption effect sample: US country-level estimate (2015-03-31T00:00:00.000Z) 0.9301061158560584; average effect with low saving gap -0.3364452; average effect with high saving gap -0.1113758
- Figure 1.31 (Commercial real estate sample):
  - Net percentage of banks tightening standards for CRE loans sample (many quarterly values; example earliest sample in table: -20)
  - Date-specified CRE data examples: 2016-01-01T00:00:00.000Z commercial mortgage-backed securities option-adjusted spread BBB (right scale) 394; 2016-04-01T00:00:00.000Z 379
  - Country CRE share samples: SWE 57.63127920817993 and 60.41069280098259; DNK 49.31598374547501 and 39.68507643949933

### Data quality and extraction notes (from the provided sample)
- Some worksheets or sample rows contain placeholder cells, "#N/A", or "#VALUE!" errors where the extraction captured Excel errors.
- Several worksheets in the workbook have rowCount 0 (empty sheets) or columns omitted in the extraction sample.
- Dates are represented in ISO 8601 format (for example, 2018-01-31T00:00:00.000Z, 2005-04-01T00:00:00.000Z).
- Numeric precision in the extracted samples is high and must be preserved when using the dataset (examples include many values with many decimal places).
- The workbook mixes chart labels, axis descriptors, and underlying series rows. Users should map rows/columns carefully to the corresponding figure panels and chart axes when using the data.

### Policy recommendations and analysis contained in the dataset
- The workbook contains numeric series and figure data supporting chapter 1 figures; the dataset itself does not include textual policy recommendations within the sampled numeric rows. Any policy or analytical interpretation should be drawn from the corresponding chapter text using these figures as inputs.

_This overview is based solely on the provided ch1data workbook sample extraction._

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_Source: https://www.imf.org/-/media/files/publications/gfsr/2023/april/data/ch1data.xlsx_