A large part of the world’s wealth is invested through passively traded, index-following funds, and with good reason, relating to risk aversion. I provide an argument that applying a similar method to donating to charity may bring about better outcomes, given we incorporate effectiveness metrics into the selection criteria for the index.
1. Why Follow Indexes?
Do so because it very likely provides the optimal risk/benefit ratio. In the investment world it’s been a long debate whether active or passive trading will be more profitable. The common wisdom is “investing passively into the S&P 500 should beat almost all active traders in the long run, and it’s almost impossible to pick the ones that won’t.” Many fit this hypothesis to historical data, and it seems to be true for a large proportion of past moments in time when an investment could have been made - given you would have had the guts to wait “for the long run” to come.
Stock markets are samples from the world economy. People play two games at the same time on them.
The first game is to participate in the gains of the economy growing (as Adam Smith described it in The Wealth of Nations). That growth is often around 1-3% a year after we subtract inflation. So for the sake of thinking, just imagine a long-term average steady growth - a straight, slightly sloping line on a chart. This game is not zero sum. Investing into a passively traded, index-following fund is dedicating ourselves to this game exclusively. It’s called “buying the market”.
The second game is a zero sum game. It’s about to take more from the growing pool than others. It’s called “beating the market”. In fact, it’s just playing a poker variant with a very complex ruleset. This is what we hope for with active trading.
2. Not All Indexes Created Equal
Statistically speaking, indexes are sampling structures. The Dow Jones Industrial Average takes 30 companies from the USA. It weights these based on the price of a single stock. It’s a historical index, and given how many companies are in the USA, it just doesn’t provide a good, representative sample. The most famous example, the S&P 500 takes into account the 500 leading US companies. It’s weighted by market capitalization, which is equal to market price per common share multiplied by the number of common shares on the market. It’s providing a much better statistical sample of the economy. The MSCI ACWI Equal Weighted is a global index (ACWI stands for All Country World Index). It samples about 2700-2800 companies from both developed and emerging markets. “Equal Weighted” means every company has the weight of one. Some may argue it’s somewhat close to being a representative sample, taken from the world economy. It still filters out war zones and countries with high instability.
So indexes have sample size, filtering criteria, and weighting methodology. Indexes are rebalanced periodically, because weighting changes, and companies cross filtering criteria barriers from time to time. The closer the index is to being a representative sample, the more closely it follows the trajectory of the total economic growth. Some companies will do (much) better than the market average, some (much) worse. We don’t know which ones upfront, so our best bet is going for the market average.
3. Applying This to Charity
When we buy a stock, we make a bet in the hope of profit. Whenever we donate to charity, we make a bet in the hope of doing good. Some charities have been more cost effective than others. Some execute better. Some will have higher impact, some lower. We can investigate their past, and draw conclusions based on that. We may pick some by hand (like in active trading), or we may create a weighting structure based on the available insights from these charities’ past (their current “stock price”). But just as with profitable companies, we don’t know these charities’ future. So let’s draw some conclusions from the analogy of active and passive trading on stock markets!
First, we hope for an optimum: the most good done (this is our “profit”) with the least risk possible. This is very similar to investment. If we accept this, it looks plausible that “index-following” is superior to “hand picking” in the long run. We should focus on creating good indexes to follow.
For example, imagine an index consisting of the top 30 most cost effective charities across the world. We could rebalance this index every 6 or 12 months. We could have equal weights, or weight it by expenditure, or expenditure times a measure of cost effectiveness (seems analogous to market cap), or some other measures of results (may be hard to have that right).
Second, at some point in the process of improving the weighting structure of an index, we’ll hit the wall of diminishing returns. That’s the point when we should aim for bigger samples. Because we still have risks. Some charities will perform very well, but some will underperform. We already have a best practice to offset this kind of risk: make a charity portfolio of 500 charities instead of 30.
We could have an “S&P 500”, or even “MSCI ACWI EW” for charities. The cost of managing the latter might be too high (too much investigation might be needed for each rebalance), but the former seems relatively easy to compose. By doing so we would benefit from about 140 years of portfolio theory advancement, applied to doing good.
I disagree with this for two reasons. Index investing is, as you say, motivated by two things: risk aversion and market efficiency. But neither of those applies to donating to charity.
I think one could argue that creating an index across causes makes sense, because it allows for exposure on things that are hard to compare (eg, we are not perfect utilitarians). I think in practical terms, it would help EAs have some reference and an easy way to donate across causes. For example, one could create a fund that is indexed to the elicited preferences of the EA community, or to some group of experts. The closest I am aware of is what Giving What We Can do.
I think that would be more analogous to a mutual fund: you pick and choose the charities that look particularly good. That's what EA Funds do.
Here's how the above "risk aversion" would translate to charity: the risk is not financial loss, but donating to a charity that uses that donation in an inefficient way. So risk aversion in the above described context is not avoiding financial loss, but avoiding utility loss.
The problem with mutual funds in the for-profit domain is that those mostly underperform index funds. General market indexes select the N best-performing companies - like 500 out of tens of thousands. This would translate to charity as selecting the N best-performing" charities, measured in something like "delivered utility per dollar". So let's select the 500 most cost-efficient charities, out of tens of thousands.
The selection process is still the hand-picking part, and that's an unavoidable part of donating, as we need to find out which charities are cost-efficient (we don't have the market efficiency clue as you pointed out). What I'm arguing for is then to have a broad selection of the hand-picked ones, and to construct a weighting among them, based on their properties. There exists an optimal distribution of donations, and we're very unlikely to find it by hand-picking alone. The for-profit market analogy shows that using the right statistical methods for finding the distribution (among the selected) is very likely superior, and the broader the sample (again, among the selected), the better the results will be.
Mutual funds underperform in an environment where arbitrage exists and prices are at least close to efficient.
Indices don't select the "best performing" companies, they usually select the "biggest" companies. Here the analogy to the charity world breaks.