Union President Turnover

April 02, 2024

Local unions are required to file information about their organization and finances every year to the Department of Labor’s Office of Management and Labor Standards (OLMS). These forms include information about the officers of the union.

We can use the information from these forms to make a measurement of how often the leadership of local union changes.

We would like to know the rate at which presidents of a local union turns over. We can approximate the rate of changes in presidents by counting the number of distinct last names that are listed for a president in a yearly filing divided by the number of yearly filings submitted by the union. In order to correct for biases we subtract one from both the top and the bottom.

$$\text{Turnover} \sim \frac{\text{Distinct names} - 1}{\text{Years} - 1}$$

If the the last name is very common, or if presidency passed from one relative to another, then our measure will underestimate turnover. If the filing has a misspelling of the president’s last name, then we will overestimate.

Generally, though, our measure seems to be a reasonable approximation of presidential turnover.

One way, we can check is to see if our measure performs as we would expect from the literature on local union democracy.

In J.C. Anderson’s 1979 article, “A Comparative Analysis of Local Union Democracy”, Anderson identified a number of factors that are correlated with measures of local union democracy. In particular, he found that larger unions and long-established unions tended to have less competitive elections for officers.

Competitive elections for union officers should have a strong relation with turnover of officers. Losing elections is one direct cause of turnover. Similarly the fear of losing, or unwillingness to fight a difficult campaign also lead incumbent officers to decide to not run again.

Union Size #

As expected, larger local unions do have lower turnover of presidents.

Age of Union #

And younger locals do have higher presidential turnover.

This chart only include locals started after December 1, 1970. The data from the OLMS does not include establishment data for local unions established before that date.

Conclusion

At least in aggregate, our measure of presidential turnover seems reasonable. All the relationships shown here are still substantial and statistically significant in a multiple regression analysis.

It could be further refined by stricter checking that a difference in last names means the person is different or the sharing of last names means the person is the same. Using first name and a fuzzy string distance to allow for some typos would be good next steps.

For modelling, logistic regression is likely the most appropriate choice. Every year would be a trial with a binary outcome of whether this years president is the same or different than last year. This modeling choice would handle different number of available years naturally. This modeling would also allow for year-varying features.

Suggestions #

From twitter, I got a number of really useful suggestions. Where the tweet was public or I have permission, I will cite the user.

First, someone rightfully pointed out that presidents can change while the faction in power remains the same. It could be really useful to compare the entire set of officers in one year to the entire set officer in the next. If many or all officers changed, that would be a much better signal that the union has meaningfully different leadership than if just the president changed. I think this idea could really improve the precision of the measure.

One way you could implement:

$$\frac{\text{Distinct Officer Names} - \text{Distinct Officer Positions}}{(\text{Years} - 1) \cdot \text{Distinct Officer Positions}}$$

This is still a bit mushy. Would not distinguish a pattern of officers change that has a high level of continuity

versus many years of complete continuity and then a sudden change.

Second, Dave Kamper suggested that turnover should correlate with:

• salary of president (I bet this correlates strongly with size of union)
• whether the local has paid staff
• the financial trajectory of the union
• the membership trajectory

Appendix #