Loss Exchange Ratio Database Project (LERD)

Citation: Long, Stephen B., Kathryn McNabb Cochran, and William Andrew Wagstaff. 2017. Codebook for the Loss Exchange Ratio Database Project (LERD), Version 1.0. Online: https://facultystaff.richmond.edu/~slong/LERD.html.

Abstract

This project fills a gap in existing data available for systematic analysis by scholars interested in war outcomes.  Several well-known data collection efforts, such as the Correlates of War project (COW) and the Peace Research Institute of Oslo (PRIO), provide data on total casualties for each combatant in interstate conflicts from 1816-2001, but none of the existing data sets provide information about who inflicted which casualties on whom.  In bilateral wars, this is a straightforward question, as the cause of any casualties is clearly the other combatant.  However, for the many multilateral wars in history, total casualty numbers do not give us any useful information about which states paid higher costs in the conflict relative to their gains and how states performed against each other. The LERD project provides directed casualties data and the resulting loss-exchange ratios (LERs) for all wars involving more than two combatants between 1816 and 1990. The files below are separated into those used for the first article employing the data set and those appropriate for other projects.

Replication Files for Cocrhan and Long (2017)

Cochran, Kathryn McNabb and Stephen B. Long, "Measuring Military Effectiveness: Calculating Loss-Exchange Ratios for Multilateral Wars, 1816-1990." International Interactions (forthcoming 2017).

Replication Data, Graphs, and Log Files

Complete Project Files

Data Zip File Includes:

  • Battles (All Sources). Do not use for analysis, as this file includes multiple entries for individual battles and would overweight well-reported battles.
  • Battles (Aggregated). Suitable for analysis, but does not include battles from wars involving only two combatant states.
  • Full Documentation. Includes complete coding records and original source quotations for all entries in Battles (All Sources).
  • Aggregation Code for Battles (Aggregated) data set.

For more information on LERD, please contact Stephen B. Long (slong@richmond.edu).

 

 

 

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