## Figure 1.27. China: Impact of Tightening Financial Conditions on Nonfinancial Firms

## Source details

**Canonical URL:** [Figure 1.27. China: Impact of Tightening Financial Conditions on Nonfinancial Firms](https://www.imf.org/-/media/files/publications/gfsr/2019/april/english/ch1data/charts/figure1-27.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/gfsr/2019/april/english/ch1data/charts/figure1-27.pdf.md)
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### Panel descriptions and metrics
- Panel 1: Increase in Nonfinancial Credit by Sector (Trillions of renminbi, percent).
  - "Data are based on sector allocations for bank-disclosed loans, corporate bonds, and trust company assets under management."
- Panel 2: Increase in Nonfinancial Corporate Credit from Nonbanks, by Sector (Trillions of renminbi).
  - "Data are based on corporate bonds and trust company assets under management."
- Panel 3: Average Bond Spreads for AAA-Rated Local Government SOE Issuers, Adjusted for Maturity, Three-Month Rolling Average (Basis points).
- Panel 4: Bond Market Net Issuance: Annualized Growth Rate by Sector and Grade (Percent).
  - "High grade is defined as AAA-rated firms (at origination), and low grade are firms rated AA+ or lower."
- Panel 5: Median Liabilities to EBITDA Ratio (Ratio).
  - "Panels 5 and 6 are based on a sample of 3,700 Chinese firms from the Capital IQ database. EBITDA = earnings before interest, tax, depreciation, and amortization; SOE = state-owned enterprises."
- Panel 6: Corporate Debt-at-Risk: Share of Debt of Firms with Interest Coverage Ratio <1 (Percent).
  - "Firm-level interest expense is estimated using the median cost of funding (interest expense divided by interest-bearing debt) from each sector grouping and time period."

### Key quantitative values shown in the figure (as labeled in source)
- Axis and tick values appearing in panels and charts:
  - 0, 6, 3, 9, 12, 15, 18
  - 0, 15, 10, 5, 20, 25, 30
  - –2, 0, –1, 2, 1, 4, 3, 5, 6, 7
  - 0, 20, 40, 60, 80, 100, 120, 140
  - 0, 10, 20, 30, 40, 50, 60, 70, 80
  - 0, 20, 40, 60, 80, 100, 120, 140, 2013 14 15 16 17 18:H1 (series labeling context)
  - 0, 5, 10, 15, 20, 25, 30, 35, 40
  - 2, 6, 10, 4, 8, 12, 14, 16, 18
- Time-period and regime labels appearing in the figure:
  - 2010 11 12 13 14 15 16 17 18:H1
  - 2014:Q4–16:Q3: Easing
  - 16:Q4–18:Q2: Tightening
  - 18:Q2–18:Q4: Easing
  - Date ticks shown: Mar. 2012; Jul. 12; Nov. 12; Mar. 13; Jul. 13; Nov. 13; Mar. 14; Jul. 14; Nov. 14; Mar. 15; Jul. 15; Nov. 15; Mar. 16; Jul. 16; Nov. 16; Mar. 17; Jul. 17; Nov. 17; Mar. 18; Jul. 18; Nov. 18

### Substantive findings and comparisons (text excerpts and figure inference)
- Overall lending patterns:
  - "Overall lending to property and infrastructure firms has been resilient ..."
  - "... while nonbank credit to firms in other sectors contracted in 2018."
- Borrowing conditions and market access:
  - "Among similarly rated issuers, infrastructure and property firms enjoy more favorable borrowing conditions ..."
  - "... with greater access to the bond market through the cycle, particularly for lower-rated firms."
- Leverage and risk concentration:
  - "However, property and infrastructure firms tend to be more leveraged ...... and have a larger weak tail of firms than in other sectors."
- Sample and estimation notes:
  - Panels 5 and 6 are based on a sample of 3,700 Chinese firms from the Capital IQ database.
  - In panel 6, firm-level interest expense is estimated using the median cost of funding (interest expense divided by interest-bearing debt) from each sector grouping and time period.

### Data sources (as listed in figure)
- CEIC; SNL Financial; S&P Global Market Intelligence; Captial IQ database; Wind Information Co; and IMF staff calculations.

*Figure 1.27. China: Impact of Tightening Financial Conditions on Nonfinancial Firms — source as provided in the figure.*

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_Source: https://www.imf.org/-/media/files/publications/gfsr/2019/april/english/ch1data/charts/figure1-27.pdf_