Calculate Coefficient of Price-Related Bias (PRB)

Source: R/formulas.R, R/ci.R

PRB is an index of vertical equity that quantifies the relationship between ratios and assessed values as a percentage. In concrete terms, a PRB of 0.02 indicates that, on average, ratios increase by 2% whenever assessed values increase by 100 percent.

PRB is centered around 0 and has a generally accepted value of between -0.05 and 0.05, as defined in the IAAO Standard on Ratio Studies Section 9.2.7. Higher PRB values indicate progressivity in assessment, while negative values indicate regressivity.

NOTE: PRB is significantly less sensitive to outliers than PRD or COD.

prb(assessed, sale_price, na.rm = FALSE)

prb_ci(assessed, sale_price, alpha = 0.05, na.rm = FALSE)

prb_met(x)

Arguments

assessed

A numeric vector of assessed values. Must be the same length as sale_price.

sale_price

A numeric vector of sale prices. Must be the same length as assessed.

na.rm

Default FALSE. A boolean value indicating whether or not to remove NA values. If missing values are present but not removed the function will output NA.

alpha

Default 0.05. Numeric value indicating the confidence interval to return. 0.05 will return the 95% confidence interval.

x

Numeric vector of sales ratio statistic(s) to check against IAAO/Quintos standards.

Functions

  • prb(): Returns a numeric vector containing the PRB of the input vectors.

  • prb_ci(): Returns upper and lower CI as a named vector.

  • prb_met(): Returns TRUE when input PRB meets IAAO standards (between -0.05 and 0.05).

See also

Other formulas: cod(), mki(), prd()

Examples

# Calculate PRB
prb(ratios_sample$assessed, ratios_sample$sale_price)
#> [1] 0.002475787

# Calculate PRD confidence interval
prb_ci(ratios_sample$assessed, ratios_sample$sale_price)
#>       2.5 %      97.5 % 
#> -0.01404379  0.01899536