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Debt to Asset Ratio

Source: R/get-debt-assets-ratio.R
get_debt_assets_ratio.Rd

Proportion of total assets financed through liabilities.

Formula:

dar = total_liabilities / total_assets

Definitional Range

Theoretically bounded [0, 1] when net assets are positive: zero means no debt; one means liabilities equal total assets (zero net assets). Values above 1.0 occur when total liabilities exceed total assets, i.e., the organization has negative net assets (accumulated deficits exceed equity). This is a distress indicator but not uncommon in capital-intensive nonprofits (hospitals, housing) carrying large long-term debt.

Benchmarks and rules of thumb

  • Below 0.50: Generally considered financially stable.

  • 0.50-0.70: Moderate leverage; manageable but warrants monitoring.

  • Above 0.70: High leverage; common vulnerability threshold (Tuckman & Chang 1991).

  • Above 1.0: Negative net assets; acute financial risk.

Calculated For: 990 + 990EZ filers.

Usage

get_debt_assets_ratio( df,
  debt   = c( "F9_10_LIAB_TOT_EOY",  "F9_01_NAFB_LIAB_TOT_EOY"  ),
  assets = c( "F9_10_ASSET_TOT_EOY", "F9_01_NAFB_ASSET_TOT_EOY" ),
  winsorize = 0.98 ,
  range     = "zo",
  sanitize  = TRUE,
  summarize = FALSE )

Arguments

df

A data.frame containing the fields required for computing the metric.

debt

Total liabilities, EOY. Accepts one or two column names; if two are provided they are coalesced with the 990 value taking priority over 990EZ.

assets

Total assets, EOY. Accepts one or two column names.

winsorize

The winsorization value (between 0 and 1), defaults to 0.98, which winsorizes at the 1st and 99th percentiles.

range

Character string specifying the theoretical range of the ratio, used to set winsorization bounds. Default "zo". Options: "np" (negative to positive), "zp" (zero to positive), "zo" (zero to one), "nz" (negative to zero), or a custom "lo;hi" pair (e.g. "0;10").

sanitize

Logical (default TRUE). If TRUE, NA values in the financial input columns are imputed to zero before the ratio is computed, respecting form scope: Part X and VIII/IX fields (990 only) are imputed only for 990 filers; Part I summary fields (990 + 990EZ) are imputed for all filers. The returned dataframe always contains the original unmodified input columns.

summarize

Logical. If TRUE, prints a summary() of the results and plots density curves for all four output columns (raw, winsorized, z-score, percentile). Defaults to FALSE.

Value

Object of class data.frame: the original dataframe appended with four new columns:

- `debt_assets`   - debt to asset ratio (raw)
- `debt_assets_w` - winsorized version
- `debt_assets_z` - standardized z-score (based on winsorized values)
- `debt_assets_p` - percentile rank (1-100)

Details

Primary uses and key insights

The debt to asset ratio (also called the leverage ratio or debt ratio) measures what fraction of total assets is financed by liabilities rather than equity (net assets). It is the most fundamental solvency indicator in both commercial and nonprofit finance: a ratio approaching 1.0 means the organization is almost entirely debt-financed and has minimal equity cushion; a ratio near 0 means assets are almost entirely owned free of debt.

For nonprofits this ratio is particularly important because: (1) they cannot raise equity capital by issuing stock, so debt is the primary external financing mechanism; and (2) funders, lenders, and rating agencies commonly use this ratio to assess creditworthiness and organizational stability.

Formula variations and their sources

The commercial formula is identical: total liabilities / total assets. Nonprofit applications use the same ratio but may define "total liabilities" differently. This implementation uses the 990 Part X total liabilities (line 26B) or the Part I summary equivalent for 990EZ filers (line 26B), which includes all short- and long-term obligations reported on the balance sheet.

Some studies use only long-term debt in the numerator to focus on structural leverage rather than near-term obligations. The full liabilities version is used here as the most comprehensive and commonly cited measure.

Why this formula was chosen

Total liabilities / total assets is the most universally understood and reported leverage measure. Using total liabilities rather than a subset avoids definitional ambiguity about which obligations to include. The PZ scope (both 990 and 990EZ) maximizes coverage across all filing types.

Canonical citations

  • Tuckman, H.P. & Chang, C.F. (1991). A methodology for measuring the financial vulnerability of charitable nonprofit organizations. Nonprofit and Voluntary Sector Quarterly, 20(4), 445-460.

  • Greenlee, J.S. & Trussel, J.M. (2000). Predicting the financial vulnerability of charitable organizations. Nonprofit Management and Leadership, 11(2), 199-210.

  • Keating, E.K., Fischer, M., Gordon, T.P. & Greenlee, J. (2005). Assessing financial vulnerability in the nonprofit sector. Harvard Business School Working Paper 04-016.

Variables used:

  • F9_10_LIAB_TOT_EOY: Total liabilities, EOY (debt, 990)

  • F9_01_NAFB_LIAB_TOT_EOY: Total liabilities from Part I (debt, 990EZ fallback)

  • F9_10_ASSET_TOT_EOY: Total assets, EOY (assets, 990)

  • F9_01_NAFB_ASSET_TOT_EOY: Total assets from Part I (assets, 990EZ fallback)

Examples

library( fiscal )
data( dat10k )

d <- get_debt_assets_ratio( df = dat10k )
#>    :: Assets equal to zero :: 268 case(s) replaced with NaN
head( d[ , c( "debt_assets", "debt_assets_w", "debt_assets_z", "debt_assets_p" ) ] )
#>    debt_assets debt_assets_w debt_assets_z debt_assets_p
#>          <num>         <num>         <num>         <int>
#> 1:  0.00000000    0.00000000    -0.7663079             1
#> 2:  0.00000000    0.00000000    -0.7663079             1
#> 3:  0.02459776    0.02459776    -0.5728525            59
#> 4:  0.00000000    0.00000000    -0.7663079             1
#> 5:  0.48026395    0.48026395     1.1317288            88
#> 6:  0.00000000    0.00000000    -0.7663079             1