ultimatch: counterfactual matching

ultimatch implements various score and distance based matching methods, i.e. Nearest Neighbor, Radius, Coarsened Exact, Percentile Rank and Mahalanobis and Euclidean Distance Matching. It implements an efficient method for distance based matching preventing the inflationary increment of the runtime. Matched observations are marked individually allowing interactions between treated and counterfactuals. Different methods can be combined to improve the results and/or to impose external requirements on the matched. Among other control variables, it creates mandatory weights to provide balanced matching results, preventing distortions caused by skewed counterfactual candidate distributions, e.g. overabundance of candidates with the same score or within the same coarsened group. It can be used to identify geographic neighborhood relations.

Prerequisites

STATA

Getting started

• Copy ultimatch.ado and ultimatch.sthlp into your ADO file directory (typically c:\ado).
• Call the help file within STATA: help ultimatch.
• Copy the provided examples from the help document into do-files and run them.
• Adjust the templates in the examples to your needs until you you get the hang of it.

Version history

2021.02.02

• Distance-based matching now supports the draw option.
• Matching results can be reproduced with set seed.
• Fixed a bug in score-based matching regarding the combination of copy and single.

2020.05.19

• Small adjustments to the help file.

2020.03.06

• The reported means are displayed as rounded numbers (9th digit after the comma).

2020.01.22

• Optimized the calculation of the outside reference point for the hypersphere leeway algorithm.

2019.09.10

• Implemented Standardized Differences in Means (SDM) as additional similarity measurement.
• Non-Clustered standard errors are now robust.

2019.08.31

• Prevent the usage of the options limit and exp for Coarsened Exact matching.

2019.08.26

• Fixed a bug in Mahalanobis matching that caused partially greedy behavior in non-greedy mode.
• Included options euclid and mahalamobis to improve flexibility for distance matching.
• Included option full as sub-option to copy to enforce treated/counterfactual tuples.
• Included option radius to explicitly activate radius matching instead of the implicit activation before.
• Percentile Rank is now considered a general transformation instead of a separate matching method.
• ultimatch now supports radius matching for the distance-based matching method.
• Added an additional example.

2019.04.25 (ssc repository version)

• Initial version.

Author

• Thorsten Doherr - ZEW