Ballotpedia completes research into public-sector union membership


Our research project analyzing public-sector union membership, finances, and political spending is complete. We will be sharing our key findings with you in upcoming editions of our weekly newsletter, Union Station. This week, let’s turn our attention to membership totals.
 
Methodology: Because it is all but impossible to collect comprehensive data on public-sector union membership, we took a more narrowly tailored approach: identifying the most prominent public-sector unions in each state and tallying their memberships. For more information on our methodology, including a discussion of existing research and various challenges involved in collecting data, please see the article linked at the bottom of this post.
 
Summary of findings: We collected data for 228 unions nationwide, averaging about five in each state. We identified these unions based on media reports, consultation with experts on the ground, and our own research efforts (e.g., identifying unions by amount of political spending). Aggregate membership in these 228 unions is 5,654,109.
 
The following states had the five highest public-sector union membership numbers:
 
  • California: 811,483 members belonging to six large unions—approximately 14 percent of the nationwide total.
  • New York: 808,669 members belonging to five unions—14 percent of the nationwide total.
  • Illinois: 342,518 members belonging to five unions—6 percent of the nationwide total.
  • New Jersey: 324,750 members belonging to four unions—6 percent of the nationwide total.
  • Pennsylvania: 324,411 members belonging to five unions—6 percent of the nationwide total.
 
Public-sector union membership in those five states is 2,611,831, accounting for about 46 percent of the nationwide total. Meanwhile, membership in the 25 states rounding out the bottom of our list is 664,180, representing about 12 percent of the nationwide total.
 
For a complete breakdown of our membership data, including links to state-specific data sets, see the article linked below.