Upward and downward biases in the "double world GDP" estimates of the gains of open borders

Summary: I discuss recent estimates that open borders could double gross world product through increases to migrant productivity. Such a doubling would be extreme, but not out of the range of our experience: it would be equivalent to raising world per capita income to the level of Greece (U.S. levels would quadruple world product), or a couple decades of continued economic growth. However, it would require the great majority of the developing world to migrate. I discuss the migration levels required for the estimates, polling and historical data bearing on migration levels, and population and economic growth trends that affect the estimates. Over several decades, the impact estimates seem too high, requiring implausible quantities and rates of migration, although potential effects remain large. Over the longer term, boosts such as population growth in poor countries and increased education for second generation migrants increase the maximum potential of migration beyond doubling world output, but development in poor countries, changes in place premium, and other changes may reduce gains over time.

What portion of a boost to global GDP goes to the poor?

Summary: How should individuals compare the impact of donations made to the world's poorest with changes in overall economic activity which are not specifically targeted at the poor, but proportionally increase incomes worldwide? World income is on the order of 30 times income for GiveDirectly recipients, so the cost of generating a similar immediate boost in log income would also be about 30 times as great. Some industries are more evenly distributed across the world than others: an economic change that delivered equal absolute dollars gain to people around the world might only need to be a few times greater. I discuss some industries that may illustrate these poles and intermediate levels. Changes in foreign aid from dollars to rich countries appear less important than growth impacts on poor countries.

Cancer vs malaria: burden, treatment spending, R&D spending, R&D results

Summary: I compare the burden, treatment spending, and R&D spending for cancer and malaria worldwide. Cancer causes somewhat more than twice the DALY burden of malaria, but has almost 14 times the global R&D budget per DALY, and almost 60 times the global treatment budget per DALY. Funding for malaria, which is controlled by donors, has a much higher share dedicated to R&D than cancer spending. That R&D also seems to produce more results, indicating diminishing returns at work in medical R&D.

A glance at the United Kingdom's Department for International Development (DfID), and careers in government grantmaking

Summary: I take a quick glance at the financial statements of  the United Kingdom's foreign agency, the Department for International Development (DfID). The agency's portfolio includes many highly effective interventions, but likely has some room for improvement in its funding allocation and delivery. Its budget is more than $6.5 million per employee, suggesting that if an employee has at least a modest positive influence over DfID activities, then he or she could do more direct good there than by working in industry and donating to the most effective international health charities. I suggest looking more closely at this broader category, of careers in government grant allocation.

It's harder to favor a specific cause in more efficient charitable markets

Summary: People vary widely in their views on the relative importance of different causes, interventions, and charities. Those with strong idiosyncratic beliefs favoring one might expect they will have much greater impact by focusing on the favored cause. However, "smart money" which moves in pursuit of marginal returns, can mean that targeted support simply displaces flexible support, instead of adding to it. For example, attempts to favor one of GiveWell's recommended charities relative to others can easily be thwarted as GiveWell attends to room for more funding and diminishing returns in making its recommendations. Insofar as the effective altruist movement increases this dynamic, it will tend to link different causes and interventions together.

If big donors have much better opportunities than small donors, then small donors can go to Las Vegas, or Wall Street

Summary: For various reasons, donors giving large amounts may be able to achieve more per dollar with their donations, enjoying economies of scale. When this is true, small donors may be able to do more good by exchanging a donation for a lottery with a 1/n chance of delivering a donation n times as large. In practice, transaction costs and taxation mean the donation will be smaller, a cost which must be compared against scale economies. However, the use of randomization, casino gambling, derivatives, and other institutions can limit lottery costs to a modest factor, lowest when investments are used. So small donors who believe strong scale economies exist can take advantage of them.

Recent growth at Giving What We Can and GiveWell

Summary: For the last three years Giving What We Can's number of additional members each year has been fairly steady. The same was true of GiveWell's increases in number of donors and money moved (excluding Good Ventures) for 2010-2012. However, small donors to GiveWell have shown accelerated growth in 2013 following Peter Singer's TED talk, which may be reflected by large donors as the figures for the 2013 giving season become known.

Turning log-consumption into a [crude] measure of short-run human welfare

Summary: [This post is intended more as notes than for a general audience.] Many have praised log income as a good proxy for individual humans' welfare. While log income alone is useful for analyzing transfers within a fixed population, when spending can also change population (e.g. through saving lives, contraception, assistance for parents) log income must be supplemented to produce a measure that tracks welfare, e.g. with an estimate of the value of a life at a subsistence income compared to the value of a life at some higher income. I then take a first pass at global income distribution statistics in this light.