Editorial note
This report was produced by Rethink Priorities between May and July 2023. The project was commissioned and supported by Open Philanthropy, which does not necessarily endorse our conclusions.
This report builds on a short investigation conducted by Open Philanthropy in 2022, which found that previous philanthropic work on road safety looked potentially cost-effective. This report extends that analysis through in-depth case studies, expert interviews, cost-effectiveness modeling, and research into risk factors, the funding landscape, and promising interventions.
We have tried to flag major sources of uncertainty in the report, and are open to revising our views based on new information or further research.
Key takeaways
Executive Summary
According to the 2019 Global Burden of Disease (GBD) study, there were about 1.2 million deaths due to road injuries in 2019. About 90% of these take place in LMICs, and the majority of those killed are between 15 - 50 years old. Additionally, WHO analysis and expert interviews indicate that road safety laws in many LMICs do not meet best-practice. While there is limited information about what risk factors contribute most to the road safety burden, or what laws are most important to pass, the available evidence points to speed on the roads as most risky, followed by drunk driving.
We conducted case studies of key time periods in China and Vietnam to better understand the relative impact of (philanthropically-funded) policy changes versus other factors. Our assessment of China is that we think Bloomberg’s implementing partners contributed minimally to the key drunk driving policy change in 2011, and we think it’s likely that this law was only one of many drivers to reduce burden. In contrast, we think laws were a more important driving force in Vietnam, and advocacy by Bloomberg, the Asia Injury Prevention Foundation and others significantly sped up their introduction. We did not find any sources that gave insight into drivers on a global scale.
Regarding future burden, it’s likely that this will follow trends in motorization. Self-driving cars may mitigate burden as they become more common; one source estimates they could constitute 20% of the global market by 2040, though we expect this to be lower in LMICs.
This report builds on a short unpublished investigation conducted by Open Philanthropy in 2022. A quick BOTEC from that report, based on an existing impact evaluation (Hendrie et al., 2021), suggested that Bloomberg’s road safety initiative might be quite cost-effective enough (ROI: ~1,100x). This report extends that analysis by reviewing Hendrie et al.’s estimates of lives saved, and comparing the authors’ estimates for China and Vietnam to data on road outcomes from multiple sources. For China, we found that while the data shows reduced fatalities after 2011, we could not link them specifically to fewer incidents of drunk driving. For Vietnam, quantitative evidence for the impact of the helmet laws was stronger than for the drunk driving laws. As can be seen in our BOTEC, this analysis led us to reduce the estimated effectiveness of policy changes by 40% - 80%.
In addition, we used our case studies to estimate specific speed up parameters for advocacy of 0.4 years in China and 3.8 years in Vietnam, versus the 10 years used previously. These changes significantly reduce our estimate of lives saved to 17% of Open Philanthropy’s previous estimate. If we use the same methodology as the previous estimate (i.e., divide this estimate by 259 million USD, the entirety of Bloomberg’s spending between 2007 - 2020), then the ROI drops to 148x. However, we propose to account for the risk of failure in a different way. If we take an estimate of relevant philanthropic spending on advocacy in China and Vietnam only (~6 million USD) and apply a “risk of failure” parameter to generalize from these successful cases to all potential advocacy, then our calculated ROI is 1,544x (corresponding to about $65 per DALY averted).
The experts we spoke to suggest that laws can change as a comprehensive package (when the existing law is very old), or as amendments that tackle one (or perhaps two) risk factors. They suggested that countries do learn from one another, through networks like ASEAN, but some experts seemed to suggest that most spillover happens when NGOs actively transplant successful campaigns or projects from one country to the next.
Regarding other, non-legislative road safety interventions, we highlight three possibilities that could be worth further research: advanced vehicle technologies, medians, and integrated transport systems.
We think it’s likely that cost-effective opportunities in road safety legislation remain. While multilateral development banks (MDBs) spend 1 billion per year on road safety, this seems to be primarily focused on assessing and building safer roads, and providing institutional support to governments (e.g., setting up crash data systems). Philanthropic funding is more limited, with Bloomberg spending 40 million USD per year, and a brief review of other organizations suggests annual funding from other sources is in the region of 25 million USD. Bloomberg’s focus on 10 countries (and primarily urban settings) means gaps remain elsewhere, and these aren’t being completely covered by other foundations or the United Nations, in part due to funding constraints.
Specifically, we think there are opportunities for grantmakers to support advocacy for better speeding legislation in Pakistan and Thailand (where urban speed limits are 80 - 90 km/h). Additionally, there may be scope for grantmaking to advocate for better enforcement of laws in Indonesia and Nigeria. None of these countries are currently supported by Bloomberg’s road safety program.
Why could this area be promising for grantmakers
- We think this topic is neglected: There are clear gaps between laws in LMICs and best practice, and legislative advocacy seems neglected in some places despite large amounts of funding for other elements of road safety (e.g., building roads).
- Our BOTEC suggests that advocacy is cost-effective enough to consider grantmaking.
- Our case study of Vietnam suggests advocacy can have an impact on this topic, and technical assistance provided by advocates can improve laws.
Why might grantmakers not want to fund this?
- The quality of the data on road outcomes seems limited. This has two implications:
- Our data deep dives were not conclusive about the impact of previous policy changes, even though Blair Turner (a consultant for the Global Road Safety Facility) suggested that crash and fatality data for Vietnam and China is generally perceived as good quality compared to other LMICs. This makes us less confident about the effectiveness of these laws.
- Poorer data quality means that tracking the impact of any grantmaking is likely to be difficult. Xiaojing Wang (Vital Strategies) also flagged that in some countries, the road safety data is considered sensitive and therefore difficult to access.
- There are reasons why Bloomberg is not working in some countries (e.g., security concerns, lack of legislative process), and trying to work in the gaps may lead grantmakers to fund opportunities that look promising but are actually intractable. While we’ve included what we know about Bloomberg’s choices not to fund some countries (e.g., Nigeria, Morocco) in our report, further insight may be hard to get.
Key uncertainties
- We highlight that speed is the most important factor to address to reduce the burden of injuries and deaths on the road, and therefore may have a higher ROI than our BOTEC indicates (as this is based on only drunk driving and motorcyclist protection). However, it may be that legislation to stop speeding is also more difficult to advocate for and introduce.
- This might be suggested by the fact that Bloomberg’s previous three phases have had limited success in passing effective laws for speeding.
- In contrast, Charity Entrepreneurship’s 2022 report on road safety reviews 84 cases of advocacy for road safety legislation, and estimates a 48% success rate across all kinds of risk factors. If we re-calculate for the subset of cases related to speeding, this suggests a 77% success rate. We don’t suggest updating too much based on these numbers (as we don’t know that the case selection is representative), but they suggest speeding might not be so different from other laws.
- Our approach to the BOTEC was informed by previous OP work that relied on Hendrie et al. (2021). As a result, we selected cases that were relevant to Hendrie et al. (2021), but we think there are open questions about how much these legislative changes in China/Vietnam 10+ years ago reflect opportunities that grantmakers might consider for grantmaking now. Our “risk of failure” parameter tries to adjust for this, but it is ultimately a crude way to do this.
- Our “risk of failure” parameter currently implies that about one in every four philanthropic attempts to change road safety policy succeeds. If we had more time to refine our estimate, we might more closely investigate the characteristics of Charity Entrepreneurship’s sample, and the extent to which a success in that sample is comparable to the successes in China and Vietnam which we review in this report.
Contributions and acknowledgments
Aisling Leow, Erin Braid, and Carmen van Schoubroeck were the main authors of this report. Erin Braid edited the client-facing version of the report to transform it into a public-facing report. Melanie Basnak reviewed and supervised this report. Thanks to Adam Papineau for copyediting, to Rachel Norman for assistance with publishing the report online, and to James Hu for formatting and graphing assistance. Further thanks to Nneka Henry, Blair Turner, Atsani Ariobowo, Kim Lua, Lulu Xue, Xiaojing Wang, Jimmy Tang, and Phong Le for taking the time to speak with us.
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This seems like a critical but unsupported claim in the report. Your 'Speedup backwards BOTEC' implicitly assumes there is literally zero cost to reducing speed limits - it just compares a BOTEC for lives saved vs the lobbying cost. But there clearly is a cost to lower speed limits: it takes longer for people to get to their destinations! Presumably you agree than a 10mph speed limit would be a disaster for the economy, and impose huge human suffering, by making everyone sit around driving all day, and leaving more distant locations totally unreachable. If so, you need some positive argument for why the speed limit reductions you propose are not merely quantitatively but qualitatively different, and I do not see what that argument could be.
Moreover, I suspect this cost could be quite large. I don't really understand your methodology - how much speed limits are falling to produce the 8% drop in fatalities - but lets try to use some totally made up illustrative numbers.
According to the first result on Google, Americans spend around an hour driving each day. If speed limits are reduced by 10%, and this is binding for 20% of the time people drive, that's a 2% reduction in speed, or about 1.2 minutes per day per person. Looking at the country most similar (in my subjective opinion) to the US in your table, Mexico, it suggests a DALY saving of 66,000 from speed limit reforms, vs a population of around 128m, or 365*24*60*66/128000/365 = 0.7 minutes per person per day.
These two numbers are extremely close, I think basically purely by chance. They are produced by a very ad hoc process and could easily be off by multiple orders of magnitude. It is quite possible that reducing speed limits is still a very desirable policy change, even after taking into account this cost. But I think they do suggest that we do need to do some work here. There is a reason people drive fast - to get places - and preventing them doing so is a real cost that we need to grapple with.
Part of the reason I wrote this comment is because I think this is an example of a broader issue in EA policy analysis - namely quite extreme paternalism that ascribes literally zero value in the CBA to people's desire, and their reasons for desiring, to do the thing we are considering banning. CEARCH were rightly criticized for their poor methodology when trying to account for this with a soda ban, but at least they tried to take this into account, and I want to make sure that 'implicitly treat coercion as zero cost by ignoring it' isn't the path of least social resistance for EA analysis.
Your broader point is a fair one, and I appreciate that you've raised it. This is generally hard to do, and speaks to a larger question about how to measure across different "benefits" - how do you measure freedom versus DALYs, or climate effects, or animal welfare. Of course that doesn't mean we shouldn't do it - with or without social resistance! Cross-cause work is something we'd like to do more at RP.
In the case you've mentioned above, I wonder if QALYs might be relevant. (This may be your point about quantitative vs qualitative). Your example calculations directly compare the 1.2 minutes of extra driving to 0.7 minutes of being alive. But how does the time driving compare to the additional time you would spend at your destination? I would imagine that the gap between those two states is smaller than "alive (at some average level of happiness) vs dead". As you note, the calculations are rough enough that it's hard to work out what the overall conclusion is, but I think we'd probably need to apply another factor to the 1.2 minutes to capture that the time spent in the car is unlikely to be worse than death.
Separately - and more as a point of interest - I wonder what would actually happen if speed limits were drastically reduced in the way that you mention. Yes, there would definitely be negative effects like you describe, but I think peoples' habits would also change so that they can avoid sitting around driving all day. (To clarify, I'm not in favour of such a drastic change, I just find it interesting to consider)