Thursday, March 2, 2017

The Story of a Lucky Economist

The career guide 80,000 Hours highly recommends getting an Economics PhD. I completely agree with their assessment. If you have an academic personality and a decent work ethic, and are lucky enough to be born with high analytical intelligence, there are few better options. If you identity as an Effective Altruist and want to make the world a better place, becoming an economist (and doing anything other than teach at a low-ranked school) is an excellent career choice for earning to give (collecting a good paycheck and giving a lot to charity) and, if you get lucky, can also be good for direct impact (personally making the world a better place.)

I got lucky. This is the story of my direct impact as an economist working for a US federal government agency. Please do not expect that this is likely to happen to you if you become an economist and start to work for a government. But something like it might happen.

Before I tell my story, I will tell the story of C, one of the veteran economists in our office. When she was interviewing me for the job and telling me about the work that they do, she told the story of her direct impact, which I will heavily paraphrase.

When the agency produces a regulation, they get scientists, lawyers, and policy experts together in a room to write the rule. If the team is well-managed and/or the economists are good at making friends, there will also be an economist in the room.

C was in the room when they were writing rules for irrigation water quality. There was some concern that pathogens in the irrigation water would contaminate the final food, so the room's consensus was that they would require all irrigation water to meet the same standards as drinking water. Then C started asking questions.

C: "Are we going to apply this rule to drip irrigation?"
Someone: "Yes, I don't see why not."
C: "Are we going to ban people from fertilizing plants with manure?"
Someone: "No, of course not, it is safe under the right conditions."
C: "So, you are writing a rule that would force people to put drinking water on manure?"

Everyone else looked at each other, and then realized that they should loosen the water quality standards under certain conditions.

C explained that one of our main jobs as agency economists was to think about the big picture and be the voice of 'common sense' in the room. It is surprisingly difficult to find people who can do this, and the 'PhD Economist' credential is a signal that you might be the kind of person who can escape groupthink and see neglected but important side effects and chains of causality.

This story was perhaps the highlight of her 20-year career in the agency. She probably saved farmers tens of millions of dollars, in total. In that one conversation, she repaid the country the value of her entire career's salary. This is what you can expect your direct impact to be as an agency economist: find ways to save people money and make life a little less difficult for them, while still accomplishing the mission of the agency. This is a good life and a noble calling, for those who think about efficiency and the big picture, and it is unreasonable to expect more.

I got more.

One day, the boss asked me to do a quick estimate of the costs and benefits of removing the GRAS (generally recognized as safe) status of PHOs (partially hydrogenated oils). You may know this as the 'trans fat ban'. Because this was technically just an exercise of existing authority and not a new regulation, it did not need an official economic analysis, but management thought it would be good to have some idea of the numbers before moving forward.

I did not know what to expect at first, but after I did the research, I found that the numbers would be huge. The costs would be measured in billions, and the lives saved would be measured in tens of thousands. There was very strong scientific evidence that trans fats are uniquely toxic among all commonly used food additives, and banning them would be the biggest public health action on decades. As a conservative estimate, they were killing eight Americans every day.

Once I realized this, I was consumed with a need to do everything I could to make the action publish as soon as possible, while making sure that it and my analysis would survive any legal challenge. I was shocked that few others in the agency realized how big and how important this was. Most of management just saw it as another thing on a big list of things that the agency was doing, and either did not know or care about the numbers involved. There was nothing I could do to push it out faster, aside from explaining the rule's huge positive effects to everyone who would find me credible, which I did. But talk like that is common in the agency, because everybody wants to push out their favorite regulation.

But I could make a real positive impact by making absolutely sure that I was not delaying the action. I studied the process, identified the likely times when things would stop because people were waiting for economic numbers, and prepared for those times. I made sure that all of my spreadsheets were flexible and complete enough to, with a few minutes' work, accept any variation in inputs and produce new output tables. I occasionally wrote several versions of the analysis ahead of time while waiting for management decisions, one for each plausible decision, so that I could turn it around in hours of being notified of the decision. When necessary, I worked lots of overtime to get things out the next day.

Basically, I identified the times when I was on the critical path, and did everything possible to shorten the time on that critical path. I do not know how successful I was. But even if I got the rule out one week faster, I saved over 50 lives. And if my analysis and contributions made the rule 0.1% more likely to survive a court challenge, then I saved over 25 lives. Direct impact numbers can get scary large when dealing with major public health initiatives that cause a single-digit percentage change in the heart attack rates of a country of 300 million.

However, depending on how you choose to interpret the Value of a Statistical Life, my second direct impact may have actually saved more lives.

Congress had passed a law requiring the agency to pass several major new regulations. The agency scheduled the regulations, starting with the most important ones that they had the most knowledge of. For the rest, they gathered information and started talking to a lot of affected producers to figure out what to do. One part of this law was a mandate to write rules about a thing that no agency in the world had ever dealt with before, and this was scheduled to be last, after a lot of research and discussion.

However, a consumer group sued the agency to publish the regulations faster. The agency lost, and was handed a court-ordered deadline for all rules, including the novel rule.

I was pulled off all other projects and assigned to this rule full-time. There were about a dozen of us in the room writing the first draft over a period of about two weeks. People would propose ideas and ask me questions about likely effects. I would poke around on the Internet and/or our internal databases for about an hour, crunch some numbers, and then give them a rough estimate.

It quickly became apparent that, even though everyone was trying to write the rule to cause as little burden as possible, following our congressional mandate would cost a lot of money.

Most rules exempt very small businesses from most or all requirements. In past rules, 'very small business' was typically defined as having up to $250,000 to $1 million in annual sales. I suggested raising the 'very small business' threshold and gave a menu of options, with cost savings and market coverage for a variety of cutoffs from $1 million up to $50 million. I went that high not because I expected anyone to choose that option, but because I understand framing and anchoring.

The team chose a threshold of $10 million in annual sales, which would save about $150 million a year compared to a $1 million cutoff, and still cover over 97% of the market by sales volume. After working to find plausible legal and scientific reasons that agency lawyers could use to justify this precedent-breaking number in court if necessary, the team agreed to propose the change to management, and management agreed.

My understanding of the power-law distribution of firm sizes, and my ability to communicate its practical effects, had saved small businesses about $150 million a year in compliance costs.

The Value of a Statistical Life in the USA is about $10 million. People will, on average, spend about $10,000 to reduce their chances of dying by one in a thousand. By saving people $150 million a year in compliance costs, I gave them enough resources to invest in things that are expected to save 15 lives a year. Assuming that the rule lasts for about 30 years before being rewritten, I saved the statistical equivalent of 450 lives with a couple insights and a few days of work.

Of course, I also caused a small increase in the chance that a very unlikely but horrible thing would happen. The increased chance, multiplied by the base rate and the expected casualties and other economic costs, means that I caused the statistical equivalent of about 50 deaths by encouraging the team to exempt small producers. So I can 'only' claim about 400 lives saved on net.

I do not expect anything like this to happen again in my career. I was lucky enough to be in the right place at the right time, twice. Laws and regulations with that much impact only come along about once a decade on average. For the rest of my life, I will be doing much smaller things.

The main message of this story is that the direct impact of a government economist is extremely high-variance. Most of the time, you will do nothing to make the world better. Occasionally, you will do something that prevents a few million dollars from being wasted. And if you get very very lucky, you might do something that saves the statistical equivalent of hundreds of lives.

Technical Appendix for Effective Altruists

If you are a PhD economist working for the US federal government, you will typically start at GS-12 and quickly work your way up to GS-14 (currently about $120,000 a year in the DC area). Then you will stay at GS-14 for the rest of your career unless you work your way up to senior management. This is less than private industry and consulting, although not that much less when you consider the value of benefits, and is much less stressful and time-consuming. I have an excellent lifestyle, and earn enough to painlessly give over $30,000 a year to charity.

If you are the kind of person who wants to work 80 hours a week and make a name for yourself, earn lots of money, and/or have more direct impact, then I still recommend starting your career as an agency economist. Government work does not force you to work as hard as industry or academia just to stay afloat. You will have extra time and energy in your week, so you can, if you choose, use that time for self-directed career advancement and make your agency job an excellent springboard to many different high-flying careers. I personally have no plans of exercising this option, but I know many people who have. Some publish lots of papers, others network and get promoted in the government, and others leave for high-paying mid-career private-sector jobs.

Everything I have discussed is only relevant to agencies where economists are actually involved in making policy decisions or new regulations. There are some places in government that are just research shops, pushing out academic publications. Avoid them. Other places have economists churn out standard reports and analyses for people to use. I do not know how impactful this is, but it is probably still a good job.

I have been able to use my knowledge to help with Effective Altruism Policy Analytics, and to give advice to many people in the LW/EA community. If you have further questions, feel free to ask in the comments here or in another location. If you are seriously considering this career, I am available to talk. I am also available as a dissertation advisor for any EA-affiliated PhD students aiming for an agency career (having advisors outside your school is an excellent signal, and I have worked on government hiring committees and know what they look for in job market papers).

7 comments:

Anonymous said...

> My understanding of the power-law distribution of firm sizes, and my ability to communicate its practical effects, had saved small businesses about $150 million a year in compliance costs.

> The Value of a Statistical Life in the USA is about $10 million. People will, on average, spend about $10,000 to reduce their chances of dying by one in a thousand. By saving people $150 million a year in compliance costs, I gave them enough resources to invest in things that are expected to save 15 lives a year. Assuming that the rule lasts for about 30 years before being rewritten, I saved the statistical equivalent of 450 lives with a couple insights and a few days of work.

I am skeptical of this logic. Yes, you saved $150 million/year in compliance costs. But that is not saving 15 lives a year. (Or at least I am missing the justification for it.) The companies *could* have used that money "to invest in things that are expected to save 15 lives a year," but most likely they just gave it to the CEOs (not literally---I mean they spent it on something unrelated).

It seems like this logic says that saving a company $10 million, in whatever way you can, is equivalent to saving a life. Maybe you believe this, but it seems self-serving.

Ben

Anonymous said...

Second. It's just a way of valuing money- like saying he "produced the statistical equivalent of 3.8 tonnes of gold". That money could buy that much gold, but it won't. The actual number of lives he statistically saved is 450 times the fraction of money that is spent on "saving lives". That would be some long, complex series.

Add in that there is no such thing as saving lives, only extending them. The easiest way to calculate how many years he earned would probably be by comparing the annual gdp of countries vs life expectancy. If he increased the GDP by .00000001%, and each 10% increase in GDP adds another year of life to the average, for a population of 300 million he would have added 4 months spread over 300 million people.

But still, adding 4 months of life to someone elses life for a couple days work is pretty impressive.

Anonymous said...

Well minus the 50 lives he may have endangered directly by those actions

Anonymous said...

Doing the math, it comes out to a .0009% increase in GDP, corresponding to 13400 years of life, or 170 people's full lives.

Alleged Wisdom said...

Ben:

It is appropriate to equate $10 million to a life saved, for several reasons.

These were small businesses in rural areas. Thousands of businesses would have been affected. For some of them, compliance costs would have been the thing that put them out of business, which would create unemployment and devastate lives and communities. For others, rule compliance would have taken up time and resources that would have otherwise been spent on improving the product, paying workers and small business owners more, or just relaxing and enjoying life.

I agree that people often do not spend their time and money on risk reduction that extends their lives. They often instead spend the resources on things that improve their quality of life. They will do whichever makes the most sense for their situation. We know that people are indifferent between spending $10,000 to reduce their chances of dying by one in a thousand, and spending that money on something else. That must mean that the something else is worth as much to them as the chance of not dying.

So yes, technically, I did not save 400 lives. I gave the people of the USA utility (ie quality and/or quantity of life) equal to about 400 lives saved. (Most of the costs of the bad event were economic damages from a recession likely to be triggered by the event, so most of the 50 lives lost was also a conversion from money costs as well.)

As a general rule, whenever the government forces people to spend $10 million on something the government wants, it is taking away money that would otherwise give people the utility equivalent of saving a life. Even when the costs are a monetization of time spent on regulatory compliance, the logic still holds, because the government is forcing people to sacrifice some percentage of their life.

Lou said...

Hey Richard; I've read this before, but still enjoy looking at it because it shows me your dedication; even at your workplace, in what your core beliefs are.

Rob said...

Hi Ben,

I'd love to pick your brains about careers in economics - what's the best way to get in touch with you?

Best,

Rob