optpolicy_main.OptimalPolicy.winners_losers

OptimalPolicy.winners_losers(data_df, welfare_df, welfare_reference_df: int = 0, outpath: None = None, title: str = '')

Compare the winners and loser.

k-means is used to cluster groups of individuals that are similar in gains and losses from two user-provided allocations. The groups are described by the policy scores as well as the decision, protected, and materially relevant variables.

Parameters

• data_df (Dataframe) – Variables used for descriptions.

• welfare_df (DataFrame) – Welfare of the allocations.

• welfare_reference_df (DataFrame, optional) – Welfare of the reference allocation. The default is 0.

• outpath (String or None, optional) – Path used to save the outputs.

• title (String, optional) – Title used in the statistics. The default is ‘’.

Returns

results_dict – Contains the results. This dictionary has the following structure: ‘data_plus_cluster_number_df’ : DataFrame

Cluster number (‘cluster_no’) is added to data_df.

’outpath’Path

Location of directory in which output is saved.

Return type

Dictionary.