2 Presenting the puzzle and challenge: Our ineffective giving

Overview of research Question/Problem: Why don’t people give in an evidence-based way?

For an introduction to the field of effective altruism, see this article from effectivealtruism.org

Also see here for an introductory resource list for effective altruism, including articles on the key ideas of the movement, as well as books, podcasts and videos.

When faced with the “girl drowning in the pond” we are willing to sacrifice substantial wealth to save a life. However, most people don’t make large donations to the very poor, in spite of evidence suggesting that lives can be saved for less than 10,000 USD. This is not for lack of generosity. There is a strong case that most donations go to charities that improve well-being far less per-dollar than others.

As Burum, Nowak, and Hoffman (2020) state:

“We donate billions of dollars to charities each year, yet much of our giving is ineffective. Why are we motivated to give, but not motivated to give effectively?”

References supporting this claim are given below.

This raises two related questions:

1. “Why don’t we give more to the most effective charities and to those most in need?” and

2. “Why are we not more efficient with our giving choices?”

To address this, we must understand what drives giving choices, and how people react to the presentation of charity-effectiveness information.

Note that these two questions are not identical: the first asks about the amounts given to the most needy charities, and the second about the choice of charities conditional on giving.

2.1 Motivation and descriptives

Individual donors, governments and firms demonstrate substantial generosity (e.g., UK charity represents 0.5-1% of GDP, US charity around 2% of GDP).

However, most donations go towards charities that are worthwhile but improve human well-being far less per dollar than basic medical interventions in poor countries, such as antimalarial bednets (see Givewell.org). Even within the same category, more can be achieved for less: e.g. while it costs around USD 50,000 to provide a blind person a guide dog, the equivalent amount could cure 500 people of blindness if it was spent on surgery to prevent blindness from trachoma (burton2009global?; macaskillDoingGoodBetter2015?).

Social science, biology and philosophy present a range of potential theoretical explanations of how values, preferences, and biases drive this ‘inefficient altruism.’ However, evidence (e.g., for ‘availability bias,’ or for ‘scope insensitivity’) comes largely from small-scale experiments in domains outside of charitable-giving. It is difficult to distinguish robust, credible findings from one-off results that are vulnerable to hype, p-hacking and publication bias (echoing the ‘replication crisis’ in experimental social science (shrout2018psychology?)). Given the limited, scattered findings, we do not have a definitive picture of which factors substantially impact ‘effective giving and support for policies that reduce extreme poverty.’ (We give a review of papers surveying this evidence below)

A plain-language summary of key points, without references (unfold):

Charities’ impact differs by an order of magnitude: Some charities are much more effective at saving/improving lives (and achieving other goals such as those involving animals and the environment) than others are. While it is difficult to gain precise estimate on the measures such as “cost of a life saved” there is strong evidence that there are orders of magnitude difference between different categories of charities and different interventions within these categories.

There are some very effective lifesaving charities: Some interventions seem likely to save or vastly improve individual lives at a cost in the range of USD 2000 - USD 10,000. When people are asked whether they would be willing to spend this amount or even a vastly larger amount to save a life in other contexts they typically will agree to do so.

There are two related and largely unresolved puzzles:

  1. Why are people not more generous with the most highly effective causes? and

  2. When they give to charity why do they not choose more effective charities?

There is some evidence on this but it is far from definitive. We do not expect there to be only a single answer to these questions; there may be a set of beliefs, biases, preferences, and underlying circumstances driving this. We would like to understand which of these are robustly supported by the evidence, and will have a sense of how important each of these are in terms of the magnitude of driving and absence of effective giving. There has been only a limited amount of research into this and it has not been systematic, coordinated, nor heavily funded.

We seek to understand because we believe that there is potential to change attitudes, beliefs, and actions (primarily charitable giving, but also political and voting behaviour and workplace/career choices). Different charitable appeals, information interventions and approaches may substantially change peoples charity choices. We see potential for changing the “domain” of causes chosen (e.g., international versus US domestic) as well as the effectiveness of the charities chosen within these categories. (However, we have some disagreement over the relative potential for either of these.)

Our main ‘policy’ audience includes both effective nonprofit organisations and ‘effective altruists.’ The EA movement is highly-motivated, growing, and gaining funding. However, it represents a niche audience: the ‘hyper-analytic but morally-scrupulous.’ EA organisations have focused on identifying effective causes and career paths, but have pursued neither extensive outreach nor ‘market research’ on a larger audience (see Charity Science, Gates Foundation/Ideas42).

2.1.1 Descriptives of giving (US, international) and how 'ineffective' it is.

Who does give effectively? Potential global welfare gains to changing ‘where we give.’ Who does give effectively?

Fitz/Kagan: Understanding Effective Givers:

In this study we attempt to understand who is predisposed towards effective giving. After providing a description of the effective giving movement, we measure support for effective giving and measure a wide range of personality traits and demographics that may predict support for effective giving. We briefly define the EA movement as an important force “we” (economists, psychologists) need to discuss.

Some references (WIP): - General giving statistics: (meerGenerosityIncomeWealth2020?), (rooneyDynamicsAmericanGiving2019?) - Various references at IUPIU; see also Osili, Weipking, Bekkers work

  • Sources of data: PSID, GVUSA, GINPS, [add the list here], Giving USA: The Annual Report on Philanthropy (raw data?), Study of High Net Worth Philanthropy

2.2 (Lack of) previous synthesis on this

While there have been some relevant prior reviews ((loewensteinScarecrowTinMan2007?), introduction to Berman et al. (2018), Baron and Szymanska (2011)),

There has also been some unpublished or non-academic work: ‘Behavior and Charitable Giving’ (Ideas42, 2016), ‘Charitable Fundraising And Smart Giving’ (Gertler, 2015), and ‘The Psychology of Effective Altruism’ (Miller, 2016, slides only).

The current project uniquely combines

  1. A focus on effectiveness,

  2. considering ‘choices among charities’ as well as in isolation,

  3. incorporating recent work and developments from the ‘EA movement,’

  4. a rigorous, sceptical approach to evidence, and

  5. advancing a research agenda while building tools that promote robust evidence.

Ideas42: “We did not find many field-based, experimental studies on the factors that encourage people to choose thoughtfully among charities or to plan ahead to give.”


Note: (greenhalghSystematicReviewBarriers2020?) performed ‘a systematic review of the barriers to and facilitators of the use of evidence by philanthropists when determining which charities (including health charities or programmes) to funds’ using PRISMA guidelines.

19 Feb 2021, DR: I am looking into this in more detail. My impression is that their approach is distinct. They seem not to focus on psychological barriers, they focus more on large philanthropists and foundations, and they put greater weight on qualitative work and self-reports than we do here.

I intend to look more closely at how they identified these studies, how they eliminated studies from consideration, and why many of the studies we discuss in the current project were not found or were excluded.

2.2.1 Effectiveness-specific work

Comparison of outlines: unfold

Gertler, "Charitable Fundraising and Smart Giving"

  • Substantial motivation
  • A broad picture of the evidence on what motivates and can be used to giving in general
  • “Strategies for Effective Charities” (pp 48-59) is most relevant to the current project


(Baron and Szymanska 2011) (chapter)

  • Introduction (with problem/puzzle)

  • Possible Nonutilitarian Heuristics

Evaluability (focus on attributes easy to evaluate e.g., > efficiency/overhead)

“instead, what is more evaluable than the lives saved per dollar of contribution is the operating cost per dollar”

  • Average vs. Marginal Benefit, Diversification, Prominence, Parochialism

  • Identifiability, Voluntary Versus Tax

  • Experiments

  • Waste, Average Cost

  • Diversification,

  • Unequal Efficiency; Unequal Efficiency, Several Projects Versus One

  • Nationalism

  • Forced Charity

  • Discussion: Utilitarian Models of Altruism, Maximize Total Utility, Limited Self-Sacrifice, Limited Altruism, Moral Education, Implications

2.3 Definitions - “Efficiency” versus impact

Consider: The measures used are relevant to how we consider issues such as charity ‘quality ratings’ and ‘overhead aversion.’

Reference: Steinberg & Morris, 2010 wrote about marginal vs average effectiveness.

It is important to define the concept of talking about. What, precisely, is this ‘effectiveness’ or ‘impact’ of a charity we are focusing on? It is not trivial to get this right and there are some delicate and hotly debated questions even within the EA movement. Nonetheless, I sketch the basic idea in the math below.

Aside: ’but what about uncertainty?

Thanks to Jason Schukraft for bringing up this point.

* This discussion abstracts away from issues of empirical uncertainty. We obviously cannot be certain state of the world ‘with or without’ one’s charitable giving. This we cannot be certain about the impact of a particular charitable gift. I aim to return to this issue in later sections.

For the sake of the discussion below, we might assume that either:

  • donors essentially only care about the expected value consequences of their choices or
  • to the extent that their is uncertainty over the ‘impact’ of donations and interventions, this uncertainty is similar across causes.


\(G_j\): The total donations given to charity \(j\) during some interval; i.e., the charity’s income.

\(B_j(G_j)\): A function defining the beneficial outcome achieved by charity \(j\) with the total donations \(G_j\).

Here, we are referring to \(B_j(G_j)\) as (the improvement to) some ultimate outcome: Lives saved (i.e., deaths averted), quality adjusted life years (QALY) added, QALY weighted by age, Disease-adjusted (DALY), future happy lives generated, sentient suffering averted, etc.

As noted, there are disagreements over how and whether we should trade off among these outcomes. Issues such as population ethics, and the importance of sentience and experience — come to the fore. We will ignore these for now.

The important distinction here: \(B(G_j)\) does not refer to a simple intermediate ‘output’ such as ‘antimalarial nets provided’ nor ‘textbooks purchased.’ We are referring to the social outcome of ultimate value; an outcome that could be valued in and of itself.

This naturally takes into account both the ‘technical efficiency’ in terms of how many units of output can be produced per dollar, and the rate at which each unit of this output boosts the ultimate outcomes of interest.


The ‘production function’ is (perhaps tautologically) the product of two terms:

(Total or marginal) impact per dollar = output per dollar \(\times\) impact per output

This is obviously an oversimplification. To achieve the beneficial outcome the charity will require many intermediate inputs (or “outputs” as noted above), including ‘management’ and ‘careful targetting of programs.’ Some charities may be able to acquire these inputs at better prices than others, and some may also use a more efficient mix of inputs.


A donor may care about the ‘impact’ of her own donation; i.e., she may want to know the difference in outcomes that her donation achieves everything else equal. In other words, the difference in the ultimate outcome in a world with versus without her donation.

Small donor assumption: For a small donor (perhaps someone who donates less than USD 100,000), we may assume that this “rate of benefit” will be the same for both the first and the last dollar she donates.

See this talk/article from Owen Cotton-Barratt for more on some key economic effective altruist concepts, including heavy tailed distributions, diminishing marginal returns and comparative advantage

Thus we consider the marginal impact, as a simplification:

\(B_j^\prime (G_j)\) for the marginal donor.

I assert that \(B_j^\prime(G_j)\) is the quantity that GiveWell (and perhaps other EA charity raters) are attempting to measure.


We know (evidence cited in fold):

There is abundant evidence for this. Some links and references: Ord, T. (2013, March 12). “The moral imperative toward cost-effectiveness in global health. Center for Global Development.” Retrieved from www.cgdev.org/content/publications/detail/142701. Also “Your dollar goes farther overseas.” (2016). Retrieved from http://www.givewell.org/giving101/Your-dollar-goes-further-overseas

\(B_j^\prime(G_j)\) is much larger for the most impactful relative to the most popular charities.


Increased benefits could be achieved if donations were ‘’reallocated’’ towards more impactful charities. An individual who gains value from her giving through it’s impact alone would naturally donate to only the one charity that has the greatest marginal impact, the charity \(j\) with the greatest \(B_j'(G_j)\) term. If every donor is doing this, then as an ‘equilibrium’ result, every charity receiving positive donations should have the same last-dollar marginal impact. In maths:

\[\begin{equation} B_k^\prime(G_k) = B_j^\prime(G_j)\forall j,k s.t. G_j>0, G_k>0 \end{equation}\]

Caveats:

This assumes a single impact goal, essentially ‘cause neutrality.’

The idea that each donor gives only to a single charity essentially depends on the above ‘Small donor assumption.’ Still, allowing that the marginal-benefit-leading-charity may vary within the range of an individuals’ donation simply implies that they should allocate among multiple charities each up to the point that the last dollar given yields the same marginal benefit as the other charities, yielding the above result. We can imagine an equilibrium in which all donors give to multiple charities, with each of these charities being virtually “tied” in their marginal effectiveness.


But we do not seem to be doing this. Again: billions are given to charity, and these charities clearly have vastly different marginal impacts, even among those that seem to target very similar outcomes.

2.4 Why (under which models) is this a puzzle?

Does the set of facts mentioned above constitute a “puzzle” for our Economics and Psychology models… or are there obvious existing explanations? In Economic terms, are donors mysteriously ‘’leaving money on the table’’ or are they simply optimizing given their their preferences and constraints? What could explain this?

Economists love when we can say that something is officially a Puzzle. It is an achievement in itself to be the researcher who first discovered a Puzzle, even if we have no clue how to resolve it.

Aside on ‘Warm glow’… consider the contrast between models where people care about the impact of their gift versus models in which they care only about the ‘amount sacrificed’ (naive warm glow). Does impact map into the ‘good feeling’ from giving? Can it do so?