EA Survey 2018 Series: How Long Do EAs Stay in EA?

byPeter_Hurford16d31st May 201915 comments

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Not everyone who joins the effective altruism community stays around forever. Some people value drift, some people leave altogether, and some people continue to do EA-aligned things but choose to withdraw from the community. Better understanding how and why people leave EA is important for assessing our overall community health and impact, but getting reliable data on this can be very hard to do.

As of Giving What We Can’s 2014 Impact Analysis, they had noted that 1.7% of members leave each year and an additional 4.7% of members “go silent” each year, meaning that GWWC has not been able to hear a response from them after two years (doing roughly annual check-ins), with a total number of people ceasing donations at 5.8%. This would suggest ~74% of people involved in GWWC remain involved after a five year time period.

This number forms a good starting point, but it is fairly out of date, having been collected five years ago. It also may not be representative of the overall EA community, since being an active part of EA is a high time cost but may not require any financial costs, whereas pledging to donate 10% has a high financial cost, but may not require much time cost beyond sending in a check and returning an email once a year or so.

To try to address this question from a different perspective, we try to use data from three EA surveys run in 2018, 2017, and 2015.


Longitudinal Data by Email Address

People who take the EA Survey each year can optionally give their email. If they do so, their email is securely encrypted and stored as a way to track whether they take the EA Survey in multiple years while preserving anonymity. As long as people give the same email each year, we can look at how many people who take prior surveys come back and take the survey again, showing they continue to remain part of the EA community.

We can look at this data in Table 1, where we see that of the people who took the survey in 2015, identified as EA, and gave their email address, 16% of them were still in the survey and using the same email address for the 2017 EA Survey, while 15% of them did so when taking the 2018 EA Survey three years later. 27% of people who gave their email address in the 2017 EA Survey came back for the 2018 EA Survey with the same email address.


Longitudinal Data by Comparing Samples

The above analysis is made difficult due to the possibility that people may come back in future surveys but decide not to give an email address or give a different address. Moreover, people may come back but have not given an email address in past years or any year. To try to track the population more holistically regardless of email address, we instead can try to compare populations.

Specifically, any EA who took the EA Survey in a particular year must have joined EA on that year or earlier. So we can then look at future EA Surveys and see when people stated they joined EA and compare that back to the original totals and see how that compares. This is what we see in Figure 1, which plots the number of people who took the EA Survey in each year on blue bars and then compares the number of people who in 2018 report joining EA in a particular year on the orange line. We can see that the orange line dips below the total number of respondents for the 2015 and 2014 EA Surveys, showing that a large number of people who must have joined EA in 2015 or earlier are no longer reporting that in future surveys, meaning they most likely dropped out of the EA movement or at least dropped out of the population of EAs that fills out the EA Survey.

This is more accurate than email tracking in that it captures more people (such as those who didn’t give an email or those who changed emails), but less accurate in that it is possible that people who state they joined EA earlier could still show up just on later surveys and offset people who dropped off, making the retention rate appear higher than it actually is.

We can see the data behind this graph in Table 2. This data suggests a retention rate around 60%.


Conclusion

Longitudinal EA Survey data potentially provides a new source of data on EA retention, tracking how people engage with the EA movement and how that changes over time. This data shows that roughly ~60% of EAs still stay around after 4-5 years. Data based on emails shows a much lower retention rate of ~16% after 4-5 years, but is likely less accurate due to people merely changing email addresses. The original GWWC data suggests a ~74% retention rate over the same time period, but is based on annualizing and extrapolating a single year trend which likely makes for an overestimate.

However, there is still a lot of room for interpretation - despite our best attempts to distribute the survey widely, the population of EAs may still be different from those who actively engage with the EA movement, and even those who actively engage with the movement may still fail to fill out the EA Survey. It’s also difficult to benchmark retention data when we don’t have comparative data for other movements to know what is normal.


Coda

This post is part of the supplementary posts for the EA Survey 2018 Series. The annual EA Survey is a project of Rethink Charity with analysis and commentary from researchers at Rethink Priorities.

This post was written by Peter Hurford with analysis by Peter Hurford and David Moss. Thanks to Tee Barnett and Marcus Davis for additional review and editing.

Previous articles in the EA Survey 2018 Series include:

I - Community Demographics & Characteristics

II - Distribution & Analysis Methodology

III - How do people get involved in EA?

IV - Subscribers and Identifiers

V - Donation Data

VI - Cause Selection

VII- Group Membership

VIII- Where People First Hear About EA and Influences on Involvement

IX- Geographic Differences in EA

X- Welcomingness- How Welcoming is EA?


Prior EA Surveys include:

The 2017 Survey of Effective Altruists

The 2015 Survey of Effective Altruists: Results and Analysis

The 2014 Survey of Effective Altruists: Results and Analysis


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