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Calculate Net Energy Burden (NEB)

Source: R/energy_ratios.R
neb_func.Rd

Calculates Net Energy Burden as the ratio of energy spending to gross income. Note: NEB is mathematically identical to Energy Burden (EB = S/G). The distinction is conceptual - "NEB" emphasizes that proper aggregation methodology should be used via Net Energy Return (Nh).

Usage

neb_func(g, s, se = NULL)

Arguments

g

Numeric vector of gross income values

s

Numeric vector of energy spending values

se

Optional numeric vector of effective energy spending (defaults to s)

Value

Numeric vector of Net Energy Burden values (identical to energy burden)

Details

Mathematical Identity: At the household level, NEB = EB = S/G.

For aggregation across households:

  • Individual household data: Use ner_func() first, then weighted.mean(nh), then convert back via neb = 1/(1+nh_mean). This uses arithmetic mean instead of harmonic mean, providing both computational simplicity and numerical stability.

  • Cohort data (pre-aggregated totals): Can use direct calculation sum(spending)/sum(income) which is equivalent to the Nh method.

  • Never use weighted.mean(neb) or weighted.mean(eb) - this introduces 1-5% error.

Why "NEB" vs "EB"? The "Net" terminology connects to the Nh (Net Energy Return) framework and reminds users to use proper aggregation. Mathematically identical, conceptually clarifying.

See also

ner_func() for the Net Energy Return calculation used in proper aggregation

energy_burden_func() for the mathematically identical calculation

Examples

# Individual household - NEB identical to EB
neb_func(50000, 3000)  # 0.06
#> [1] 0.06
energy_burden_func(50000, 3000)  # 0.06 (same)
#> [1] 0.06

# For aggregation - use Nh method (individual HH data)
incomes <- c(30000, 50000, 75000)
spending <- c(3000, 3500, 4000)
households <- c(100, 150, 200)

# CORRECT: Via Nh (arithmetic mean)
nh <- ner_func(incomes, spending)
nh_mean <- weighted.mean(nh, households)
neb_correct <- 1 / (1 + nh_mean)

# WRONG: Direct mean of NEB
neb_wrong <- weighted.mean(neb_func(incomes, spending), households)

# For cohort data (totals already aggregated)
total_income <- c(3000000, 7500000, 15000000)
total_spend <- c(300000, 525000, 750000)
neb_direct <- sum(total_spend) / sum(total_income)  # Simple and correct