This is a technical post, only of interest to people doing policy analysis. Much of it was originally written in response to a Facebook post related to Effective Altruism Policy Analytics, and I am reposting it here so it is in a more permanent place that I can link to.
One of the group members posted a link to the following paper:
and asked me if we should consider using this method.
Briefly, well-being analysis is an attempt to measure the costs and benefits of a policy using a direct measure of human happiness or well-being, instead of using dollar values. My response was divided into two sections:
Well-being analysis in any form is not currently useful for people submitting policy comments:
1) Any comment that relied on a well-being analysis would likely be summarily dismissed. As the paper states, regulatory agencies are required by law to do cost-benefit analysis, and that is what they understand. They do not understand this new alien thing, have no way of judging its quality, and have no incentive to care about it.
2) The language of policy right now is monetary costs and benefits. We will influence policy by speaking the language currently used, and speaking it well. Lojban might be a better language than English, but it would be folly to submit comments in it.
3) There is a good chance that in 30 years, an overall framework like this will replace cost-benefit analysis and be required by law. This does not make it useful to us. 30 years ago, cost-benefit analysis was a bizarre fringe thing that nobody cared about and that would not affect policy in any way.
Well-bring analysis as presented in the paper has serious flaws:
4) Their example analysis dramatically undervalues monetary costs. They claim that "If that same individual's income decreased from $100,000 to $36,700, she would lose 0.11 WBUs" on a scale of 1 to 10. By comparison, "Unemployed individuals suffer a loss of 0.83 WBUs per year during the time that they remain unemployed." However, we know that people who have lost their jobs routinely choose to remain unemployed rather than settle for jobs that pay less than what they earned before.
4a) The data they use to determine well-being will systematically undervalue money, because they do a regression that separately counts the effects of money and health. Treating money and health as separate and exogenous is a grave error. Money and health are heavily correlated because money buys health. Most of what rich people do with their money is to rearrange their lives so they will be healthier and safer. When you take away money, health goes down. Their data on the 'well-being effect of income' is just the residual effect of money after 'correcting' for all the things that the money bought.
5) To a first approximation, the well-being analysis they present is just a way to ignore the compliance costs of any regulation that does not cause observable layoffs. Widespread use of this system in its current form would encourage a horde of very expensive regulations. Given how cheap it is for individuals to purchase lives with money, this is a huge problem. If 0.001% of the compliance costs of the EPA regulation they support would have otherwise gone to effective charities, the regulation has reduced well-being.
6) According to this analysis methodology in its current form, job losses dominate any consideration of economic efficiency, technological growth, or cheaper, better goods. Consistent use of it to analyze policies would result in support of policies that enforced stagnation on an economy, preventing almost any kind of innovation that had the potential to cause layoffs unless that innovation had an immediate and obvious health or safety benefit. Specifically, a "Ban computers" policy analyzed 40 years ago would probably score highly on a well-being analysis.
I do hope that, at some point in the future, all government actions will be evaluated on how they are expected to affect the well-being of all people, measured directly. Money is an imperfect measurement of how things affect well-being, because different people value money differently and a lot of important goods are hard to put money values on.
But right now, measuring things by their monetary impact, and the health and life impacts converted to their monetary values, is the best we can do. There is simply far more data available on money than there is on direct well-being measurements, and an imperfect system you can actually use is better than a theoretically ideal system that cannot be implemented.
But right now, measuring things by their monetary impact, and the health and life impacts converted to their monetary values, is the best we can do. There is simply far more data available on money than there is on direct well-being measurements, and an imperfect system you can actually use is better than a theoretically ideal system that cannot be implemented.
Also, money is a much better measurement tool than most people realize. The money cost of doing a thing is a signal that includes a very good estimate of most of the resources consumed by that thing. Pollution and other externalities often make the money price of a thing an underestimate of its true cost, but in a competitive market it is rare for a money price to overestimate the cost of a thing. Whenever you think something should be cheap, but it costs a lot, that almost certainly means that you are missing something important. Regulators tend to miss important side effects and assume that things will be cheaper than they really are, because they only look sat narrow technical effects without considering larger impacts. Measuring the monetary impacts of a rule can correct for this.
However, as more research on well-being accumulates, and we get more data on how things affect quality of life, and we develop a better understanding of the complicated chains of causality that dominate all human interactions including the economy, we will probably move toward some kind of well-being analysis. The monetary costs and benefits will become a subset of the analysis. But it will likely take decades to get to that point.
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