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Administrative Overhead Ratio

Source: R/get-expenses-admin-ratio.R
get_expenses_admin_ratio.Rd

Share of total expenses devoted to management and general administration.

Formula:

aer = management_expenses / total_expenses

Definitional Range

Bounded [0, 1]. In combination with program and fundraising ratios, all three sum to 1.0 by construction. The empirical range for most nonprofits is approximately [0.05, 0.35].

Benchmarks and rules of thumb

  • Charity Navigator targets management and general expenses at or below 15% of total expenses for a favorable score.

  • Values below 5% may indicate underinvestment in governance systems.

Calculated For: 990 filers only.

Usage

get_expenses_admin_ratio( df,
  mgmt_expenses  = "F9_09_EXP_TOT_MGMT",
  total_expenses = "F9_09_EXP_TOT_TOT",
  winsorize = 0.98 ,
  range     = "zo",
  sanitize  = TRUE,
  summarize = FALSE )

Arguments

df

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

mgmt_expenses

Management and general expenses.

total_expenses

Total functional expenses.

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:

- `expenses_admin`   - administrative overhead ratio (raw)
- `expenses_admin_w` - winsorized version
- `expenses_admin_z` - standardized z-score (based on winsorized values)
- `expenses_admin_p` - percentile rank (1-100)

Details

Primary uses and key insights

The administrative overhead ratio measures what fraction of total expenses is devoted to management and general administration - the governance, compliance, financial management, and executive functions of the organization. It is the management component of the broader overhead ratio (get_overhead_ratio()), which adds fundraising expenses.

A high administrative ratio may indicate organizational complexity, compliance burden, or inefficiency; a very low ratio may indicate underinvestment in governance and financial systems. The appropriate level depends heavily on organizational size and mission type.

Formula variations and their sources

Management and general expenses (Part IX line 25C) / total functional expenses (line 25A). This is the most common operationalization. An alternative includes unallocated costs or uses a broader definition of overhead, but the Part IX column breakdown (program, management, fundraising) is the standard basis.

Canonical citations

  • Lecy, J.D. & Searing, E.A. (2015). Anatomy of the nonprofit starvation cycle. Nonprofit and Voluntary Sector Quarterly, 44(3), 539-563.

  • Overhead Myth Campaign (GuideStar, BBB Wise Giving, Charity Navigator, 2013).

  • Nunnenkamp, P. & Ohler, H. (2012). Throwing foreign aid at HIV/AIDS in developing countries: Missing the target? World Development, 40(10), 1978-1994. - Uses administrative ratios in cross-organizational comparisons.

Variables used:

  • F9_09_EXP_TOT_MGMT: Management and general expenses (mgmt_expenses)

  • F9_09_EXP_TOT_TOT: Total functional expenses (total_expenses)

Examples

library( fiscal )
data( dat10k )

d <- get_expenses_admin_ratio( df = dat10k )
#>    :: Total expenses equal to zero :: 77 case(s) replaced with NaN
head( d[ , c( "expenses_admin", "expenses_admin_w", "expenses_admin_z", "expenses_admin_p" ) ] )
#>    expenses_admin expenses_admin_w expenses_admin_z expenses_admin_p
#>             <num>            <num>            <num>            <int>
#> 1:             NA               NA               NA               NA
#> 2:      0.1384701        0.1384701       0.08996751               64
#> 3:      0.1315314        0.1315314       0.03150629               62
#> 4:             NA               NA               NA               NA
#> 5:      1.0000000        1.0000000      10.84640410               99
#> 6:             NA               NA               NA               NA