## Dataset overview

## Source details

**Canonical URL:** [Dataset overview](https://www.imf.org/-/media/files/publications/gfsr/2021/april/data/chapter3-data.xlsx)

## Other formats

- [Markdown version](/-/media/files/publications/gfsr/2021/april/data/chapter3-data.xlsx.md)
- [Structured JSON version](/-/media/files/publications/gfsr/2021/april/data/chapter3-data.xlsx.json)

---

### Dataset description
- Workbook name: "chapter3-data" containing worksheets related to the Global Financial Stability Report (GFSR) — Chapter 3. Commercial Real Estate.
- Worksheets present in the file: "GFSR Chapter 3 Apr. 2021", "Table of Contents", and multiple figure worksheets (examples: "Figure 3.1.", "Figure 3.2.", "Figure 3.3.", "Figure 3.4.", "Figure 3.5.", "Figure 3.6.", "Figure 3.7.", "Figure 3.8.", "Figure 3.9.", "Figure 3.10.", "Box 3.1. Figure", "Box 3.2. Figure", "Box 3.3. Figure").
- Row and column counts (sample):
  - "GFSR Chapter 3 Apr. 2021": rowCount 32, columnCount 10
  - "Table of Contents": rowCount 28, columnCount 12
  - "Figure 3.1.": rowCount 88, columnCount 23
  - "Figure 3.3.": rowCount 232, columnCount 37
  - "Figure 3.4.": rowCount 1568, columnCount 30
  - "Figure 3.5.": rowCount 2938, columnCount 32
  - "Figure 3.6.": rowCount 1090, columnCount 41
  - "Figure 3.7.": rowCount 60, columnCount 50
  - "Figure 3.8.": rowCount 64, columnCount 36
  - "Figure 3.9.": rowCount 116, columnCount 34
  - "Figure 3.10.": rowCount 117, columnCount 36
  - "Box 3.1. Figure": rowCount 118, columnCount 33
  - "Box 3.2. Figure": rowCount 118, columnCount 41
  - "Box 3.3. Figure": rowCount 118, columnCount 34

### Major themes and figure headings (as labeled in the workbook)
- "Figure 3.1. Developments in Global Corporate Real Estate Markets During the COVID-19 Crisis"
- "Figure 3.2. Commercial Real Estate Markets and Financial Stability: Channels of Transmission"
- "Figure 3.3. Corporate Real Estate Losses in Past Crises"
- "Figure 3.4. Commercial Real Estate Market Funding Structure"
- "Figure 3.5. Dynamics in Commercial Real Estate Financial Metrics Over the Past Two Decades"
- "Figure 3.6. Commercial Real Estate Price Misalignment"
- "Figure 3.7. Commercial Real Estate Prices and Real GDP Growth"
- "Figure 3.8. United States: Impact of an Adverse Commercial Real Estate Price Shock on Bank \nSoundness"
- "Figure 3.9. Impact of an Adverse Shock to Commercial Real Estate Prices on Corporate Investment"
- "Figure 3.10. Macroprudential Policies, Capital Flow Management Measures, and Downside Risks to Commercial Real Estate Prices"
- Box figures: "Figure 3.1.1. Commercial Real Estate Market Developments Across Cities During the COVID-19 Pandemic", "Figure 3.2.1. Trends and Developments in Cross-Border Commercial Real Estate (CRE) Investment Flows", "Figure 3.3.1. The US Commercial Mortgage-Backed Securities Market during the COVID-19 Crisis"

### Selected numeric excerpts and data points (preserved exactly as in the file)
- Date stamps appearing in workbook: "2021-04-01T00:00:00.000Z"
- Figure 3.3 (panel labels and sample values):
  - "COVID-19 crisis", 3.9
  - "Moody's CRE loans baseline", 9.2
  - Quarterly labels: "2001Q1", "2001Q2", "2001Q3"
  - Sample rates: 0.0112905, 0.0113335, 0.0075557
- Figure 3.4 (panel 1 and sample country rows):
  - Panel title: "1. Size of the CRE Market in Selected Economies, 2019 vs. 2010  (Percent)"
  - Example rows:
    - "AUS", "Australia", 17.744383049283506, 20.559854363424655
    - "AUT", "Austria", 9.030470395955119, 9.814730545343275
    - "BEL", "Belgium", 12.890518811723808, 11.005415032775703
    - "CAN", "Canada", 15.789653509828462, 19.880655018561292
  - Bank-size CRE exposure example (percent): "<$10 billion", 183.7, 42.7, 9.7; "$10-$100 billion", 165.1, 31.8, 12.6; ">$100 billion", 49.3, 8.7, 6.5
  - Note: "Note: Because of the data licensing agreement, the data series shown in panels 4, 5 and 6 of this figure are proprietary."
- Figure 3.5 (time series and sample metrics):
  - Panel label: "(Index, 2009=100)"
  - Year 2005 row: 2005, 86.85446, 96.04501, 108.2909, ... , 6.851733924628832, 6.2404399999999995, 5.218916290322585, 5.2071, 8.1124275, ... , 4.64593740535318, 3.281306667, 2.351594167, 3.4408833334999995
  - Year 2006 row: 2006, 95.90986, 101.0481, 106.4352, ... , 6.820501051452169, 6.2404399999999995, 5.218916290322585, 5.2071, 8.1124275, ... , 4.658946526932681, 3.339199999999999, 2.793484166999999, 3.555469999749999
  - Year 2007 row: 2007, 102.6125, 108.7119, 117.5049, ... , 6.789268178275506, 6.124630000000001, 5.218916290322585, 5.021402500000001, 8.1062975, ... , 4.671955648512181, 3.623176666999999, 3.4399508335, 3.815545833499999
- Figure 3.6 (misalignment decomposition and sample values):
  - Sample misalignment statistics: 9.876439564456668, 11.581330732454191, 4.085774198229572, 1.578151864180975, 7.36881723040807, -4.212513502046121
  - Decomposition components example: "Aggregate supply", "Aggregate demand", "Monetary policy", "Spread", "NOI growth", "Credit-to-GDP", "Broad money-to-GDP", "Capital flow-to-GDP", "Vacancy rate"
  - Time label: "T+0y"
- Figure 3.7 (correlations and impact estimates):
  - Interquartile/median sample values: "Interquartile range", "Median", and numeric examples: 1, -0.48, -0.26715, -0.69285; 1, -0.29, -0.0029000000000000137, -0.5771
- Figure 3.8 (US bank soundness impacts):
  - Sample metrics and values:
    - "CRE nonperforming loans ratio", 7.741981225867735
    - "CRE net loan charge-off rate", 2.5426300353792692
    - "Net revenues before provisioning", -11.99330280509841
    - "Total regulatory capital", -4.896348392907148
    - Bank group examples with zeros and small decimals e.g., 0, 0.00235107, 0.00265191, 0.00357037, 0.00370938
- Figure 3.9 (corporate holdings and investment effects):
  - "Average Real Estate Holdings by Nonfinancial Corporations, 2004−19" sample:
    - 2004, 39.60376, 44.20326
    - 2005, 37.99007, 43.82154
    - 2006, 36.77216, 44.17294
  - Investment effect examples: "Constrained", -21.913937, -26.98211, -22.468364, -20.756; "Unconstrained", -8.6202349, -20.727419, -17.894312, -20.756
- Figure 3.10 (policy impacts on downside risks to CRE prices):
  - Sample impact values (Percentage points and percentiles):
    - Panel 1 sample: 0.145, 0.0493, 0.24069999999999997
    - Panel 2 sample: 0.082, -0.028549999999999992, 0.19255
    - Panel 3 sample: 0.172, 0.07794999999999999, 0.26605
    - Panel 4 sample: 0.183, 0.05925000000000001, 0.30674999999999997
    - Additional rows: 0.249, 0.13679999999999998, 0.3612; 0.051, -0.15525, 0.25725; 0.194, 0.019100000000000034, 0.3689; 0.166, 0.09505000000000002, 0.23695
- Box 3.1. Figure (city-level CRE during COVID-19):
  - Panel values for containment/mobility/policy groups:
    - "Low containment stringency", -0.21573454
    - "High containment stringency", -0.86357892
    - "High workplace mobility", -0.40357112884521484
    - "Low workplace mobility", -0.9222745895385742
    - "High additional spending and \nforgone revenue", -0.3651916980743408
    - "High Fiscal Support", -0.09877532720565796
    - "Low Fiscal Support", -0.7175564765930176
- Box 3.2. Figure (cross-border CRE flows and synchronization):
  - Panel 1 regional sample yearly values (Billions of US dollars, left scale; percent, right scale): 2007, 58.091644089, 211.015480505, 52.459885916, 5.772471888, 0.660035963, 33.26210021972656
  - Country sample rows with percentages and dates: "ARG", 100, -100, "2000-01-01T00:00:00.000Z", -1.421266; "BGR", 69.84341430664062, -42.00836944580078, "2000-04-01T00:00:00.000Z", -1.696586; "BRA", 52.89872741699219, -27.261625289916992, "2000-07-01T00:00:00.000Z", -2.14962; "BWA", 100, -100, "2000-10-01T00:00:00.000Z", -0.9984489
- Box 3.3. Figure (US CMBS issuance monthly series, Feb–Nov 2020):
  - Time series examples:
    - "2020-02-01T00:00:00.000Z", 14.806142
    - "2020-03-01T00:00:00.000Z", 5.57145
    - "2020-04-01T00:00:00.000Z", 0.306414
    - "2020-05-01T00:00:00.000Z", 4.153945

### Usage notes and data characteristics (as labeled in the workbook)
- Several panels across figures include the note: "Because of the data licensing agreement, the data series shown in [specified panels] of this figure are proprietary."
- Data types present: text labels, percentages (explicit percent values notated as numeric decimals in many cells), indices (Index, 2009=100), quarterly and monthly timestamps (ISO 8601 format, e.g., "2001Q1", "2020-02-01T00:00:00.000Z"), cross-sectional country identifiers (ISO or short codes such as "AUS", "AUT", "CAN"), panel-level numeric series (many values given with full decimal precision).
- Numeric fidelity: all numeric values are preserved in the workbook with full precision (examples above reproduced exactly).

*Source: chapter3-data — https://www.imf.org/-/media/files/publications/gfsr/2021/april/data/chapter3-data.xlsx*

---


_Source: https://www.imf.org/-/media/files/publications/gfsr/2021/april/data/chapter3-data.xlsx_