Linkpost for https://allegedwisdom.blogspot.com/2024/09/mortality-cost-of-taxation.html
Here are some interesting questions:
1) If Japan raises $1 billion by increasing taxes on investment income, how many people will die as a result?
2) If Kenya raises $1 billion with a bundle of sales taxes, how many people will die as a result?
3) If the USA raises $1 billion with a tariff on Chinese goods, how many people will die as a result?
(If it is not obvious to you that these numbers are all more than zero, consider the basic facts that poverty kills people, and taxes take money from people. I like telling people that cost-benefit analysis is how to do "primum non nocere" for public health policy.)
In a competent civilization, there would be an academic sub-discipline devoted to these Mortality Cost of Taxation (MCT) questions. University professors would research MCT methodology and develop MCT best practices, and there would be a neutral MCT agency in all G20 countries that estimated the mortality effect of every tax policy under consideration. Then people would estimate how many lives would be saved by spending the tax money, and compare. (In reality, they would use a metric like the DALY, to account for both quality and quantity of life lost, but I am focusing on deaths in this discussion to keep things simple and vivid.)
In the world we live in, this academic discipline only exists in my head (as far as I know, and I would love to learn otherwise), and I suck at it. The best answer I can give is:
1) Ask a taxation or tariff economist how much the policy will impact GDP.
2) Divide that number by the country's GNI per capita.
3) Divide that number by 100.
So, in Japan (GNI/cap $40k), every $4 million in economic impact will kill someone, and in Kenya (GNI/cap $2k), every $200,000 in economic impact will kill someone.
My answer assumes that all taxation is basically the same, and assumes that the MCT is roughly twice the Value of Statistical Life (VSL). This is the best I can do, and it probably isn't wrong by more than an order of magnitude.
VSL estimates come from looking at the wage differences between similar jobs with different occupational fatality rates, for example lumberjacks and gardeners. In the USA, for every $13 million or so in increased wages among we-assume-otherwise-identical jobs, one person dies on the job. In Kenya, many more people will die for $13M in increased wages.
If everyone responded to the tax increase by working a more dangerous job, then the VSL would be the correct estimate of the MCT. But this is obviously impossible at a societal level; the composition of jobs is roughly fixed and the tax change does not alter occupational safety standards.
If everyone was perfectly rational and made consistent tradeoffs between money and mortality risk, then the VSL would be the true estimate of the effects of people reducing their consumption in response to a tax increase. But we know that the all-cause mortality rate among people with dangerous professions is higher, so they cannot be turning their extra income into lower risk via consumption at the VSL rate.
For this reason, and for various other handwavey reasons I can't formally justify (e.g. budget constraints, short-run elasticities being lower, behavioral-economics effects, and vaguely gesturing at the literature on how people respond to income shocks), I assume that broad-based income loss from taxation or tariffs turns into mortality at roughly twice the VSL rate. Although I still use the VSL in all my work, because that is the current methodological standard and I can't cite anything better.
If you think you can do better, or know someone who has done better, or would like to collaborate to find ways to do better, please let me know.
PS Obviously the story becomes different with more targeted taxes. Taxing rich people causes less mortality (assuming that the tax incidence actually falls on them). Taxing harmful substances or things with negative externalities could have zero or even negative MCT, if it doesn't move much activity into a violent black market. I would assume that taxing positional goods causes roughly zero MCT, but there may be weird side effects I am not considering.
PPS It's a weird feeling to be so bad at something, and also the best in the world, because nobody else is even trying. I have looked, and can't find any discussion of this. Maybe I'm just missing it. But in all the discussion of VSLs and how to use them and how to derive them, nobody seems to justify the methodology by pointing to the harm of taxation, or to make the obvious point that taxation kills people so it would be nice to know if your policy is saving more lives than it kills.
I like the idea of measuring or anticipating the effects of a tax in units of deaths avoided/caused and quality of life gained/lost instead of in monetary terms. The monetary measurement of the impacts of a tax (the common approach among economists) can be quite a bad proxy for actual things we care about: saving and improving lives. There's actually a growing field of economics aiming to replace the GDP measure with quality of life measurements.
I understand your causal mechanism to be as follows: (1) taxation reduces people's income, (2) having less income makes working risky jobs financially more attractive, (3) this causes more people to die. While this sounds plausible, I see quite a few problems with the approach that you're suggesting, which I'll cover below. (I won't go in-depth into the calculation you used since you already mentioned that it's not accurate and I assume the point of your post is to advocate for starting a subdiscipline of economics, rather than providing a method for calculation.)
Use of VSL estimates
VSL estimates are intended be used to understand how people value small reductions in risk, not to predict the outcome of increased wages on deaths. Greater risk leads to higher pay, but higher pay doesn't lead to this increase in deaths per se. For example, demand for risky jobs like firefighters isn't very elastic (the number of firefighters society needs is more or less fixed), and even if that wasn't the case, less qualified or experienced people may enter the field. I wouldn't use the VSL for this purpose since the methods used to calculate it don't establish this causal link.
Not a lot of people die in workplace accidents
I don't think people taking riskier jobs, as the VSL approach would assume, is the primary negative impact of taxation. Rather, I think reducing people's spendable income makes them less likely to buy healthy food, less likely to live in air-conditioned or heated houses, and less likely to be able to afford medical bills. Only a very small number of people actually die in accidents - let alone workplace accidents. So if we want to know the mortality effect of a tax, it would be more interesting to research questions such as: what is the effect of this tax on cardiovascular health (e.g. unable to buy healthy food) or lung health (e.g. air pollution).
Taxation is used to reduce mortality
Interestingly, having low income, low wealth, low education, and low social status are very strong determinants of early mortality. This is exactly what taxation is trying to tackle. If we take the data for my country (The Netherlands), for example, we see that more than half of all public spending goes to healthcare and social security, and another 12% goes to education. In short, taxation is mostly used to make healthcare affordable or to alleviate social determinants of mortality.
So no, I don't think we can assume that taxation kills people.
People in poverty are mostly exempt from taxes
Looking at distributive effects is probably really important here. I can imagine that taxing people to the point that they enter poverty (as you suggested) makes things a lot worse for them. Most countries have some type of tax-free threshold under which you don't have to pay income taxes. Low incomes are only taxed relatively little. Some taxes, like VAT on food, fall disproportionately on the poor since they spend a larger share of their income on food.
So, theoretically it's possible that taxation causes poverty, and poverty causes deaths. But if we look at the top causes of global poverty, we see that poverty is mostly caused by things we can tackle by spending tax money: on safety nets and food programmes to stop hunger, on healthcare systems to improve access, on sanitation and clean water to improve hygiene and save time, on education to give kids a prosperous future, on infrastructure so that people can get to work, on creating jobs...
Summary
In summary, I'm in favour of researching the effects of taxation and public spending on mortality, but I expect the sign on most taxes to be negative (i.e. reducing mortality), at least when the tax incidence is not on people in poverty and public funds are spent on sensible projects. I think the method based on the VSL is probably not appropriate, but your proposal to have a government consider the effects of mortality makes sense since we can probably make a good guesstimate of the effects of a tax or government programme on social determinants of mortality.
I have a table here showing the difference between a country with low taxes (United States) and a country with high taxes (Sweden). What I want to say with the table is that people who are unemployed have much more money in Sweden compared to the US. Also, in Sweden the taxes are making the costs lower for elderly care, child care, education, health care, medicine and so on. So even if the taxes are higher, you probably have better access to health care, medicine and financial aid in Sweden even if you are living on a minimum income. Because of the redistribution of money, taxes are giving money to people in poverty.
Income tax for people earning below 50 000 USD: 10-12 %.
Income tax for people earning over 50 000 USD: 22-37 %.
Income tax for people earning below 50 000 USD: 31 %.
Income tax for people earning over 50 000 USD: 51 %.
Value-added tax on goods and services: None.
Instead some states have sales tax on around 6 %.
Net childcare costs for a couple with average wage: 32 %.
Cost for one year in college: Over 9 000 USD / year.
Net childcare costs for a couple with average wage: 5 %.
Cost for one year in college: None, you get money for that.
Diabetes prevalence: 10.7 %.
Epipen cost: 600-700 USD.
Diabetes prevalence: 5.1 %.
Epipen cost: 40 USD (if your medical expenses exceeeds 300 dollars a year, you get your medicine for free).