Kakwani Index

assesspy.ki(estimate: list[int] | list[float] | Series, sale_price: list[int] | list[float] | Series) → float

The Kakwani Index (KI) is a Gini-based measure to test for vertical equity in assessment. It first orders properties by sale price (ascending), then calculates the Gini coefficient for sale values and estimated values (while remaining ordered by sale price). The Kakwani Index is the difference between the coefficients: $Gini of Estimated Values - Gini of Sale Prices$.

For the Kakwani Index:

KI < 0 is regressive KI = 0 is vertical equity KI > 0 is progressive

Parameters:

• estimate (Array-like numeric values) – A list or pd.Series of estimated values. Must be the same length as sale_price.

• sale_price (Array-like numeric values) – A list or pd.Series of sale prices. Must be the same length as estimate.

Returns:

A single float value containing the PRB of the inputs.

Return type:

float

Example:

# Calculate KI:
import assesspy as ap

ap.ki(ap.ccao_sample().estimate, ap.ccao_sample().sale_price)