Bill Simmon’s masterful 754-page The Book of Basketball (2010) is a deep reflection on how to assess individual performance in a team sport. One of the big debates in the sport is whether Wilt Chamberlain or Bill Russell was the greatest basketball player of their generation.
There is no question that Wilt is the king of scoring. He scored 100 points in a single game, a feat no one has come close to matching. In the history of the NBA a single player has scored more than 60 points only 67 times and Wilt accounts for almost half, 32, of those.
Bill Russell won championships. The Boston Celtics won 11 championships with Russell in the 13 seasons he played. (Michael Jordan, who Bill Simmons in 2010 thought was the greatest player of all time, won 6 championships in 15 seasons). His collegiate team, the University of San Francisco, won the NCAA championship twice with Bill Russell in 1955 and 1956—and has never won since. Russell’s teams played Chamberlain’s teams 142 times and the head to head was 84 wins for Russell’s teams versus 58 for Chamberlain’s.
The debate about whether it is more important to have good individual statistics or be a team player that contributes to overall victory is hugely important in development today.
Development (and economic development) arose as an independent field with decolonization and the “proliferation of sovereigns” after World War II. We could date “development” from the founding of the Bretton Woods institutions in 1944, or Indonesia’s independence in 1945 and India’s and Pakistan’s in 1947 signaling the inevitable end of colonialization, or the UN Declaration of Human Rights in 1948, or Truman’s Point Four plan in 1949. Clearly by 1950 a “development era” was underway with a self-conscious group of individuals working in many disciplines and in many multi-national and regional organizations and in newly sovereign national governments to promote development. This global movement is “team development.”
Was team development a success? Well, on (practically) every objective indicator of human well-being the 60 years of the development era (1950–2010) has seen more progress in developing countries than all of previous human history combined.
Take schooling. In 1950 the average adult in the developing world had two years of schooling. If say there are roughly 5040 years of “human civilization,” this is 84 60-year periods. It took 84 60-year periods to get to 2 years of schooling and then one 60-year period to add five years to that total and reach an average of 7 years of schooling. Development era progress was 210 times faster than the historical average.
Take life expectancy. If we take Bronze and Iron Age life expectancy at birth to be about 26 (Wikipedia’s guesstimate) then the gain from the Iron Age to 1950 is 22 years to 48 and the gain from 1950 to 2010 is another 22 years. So progress in the development era was 84 times faster.
Take output per person. The historical Maddison data on output per capita suggest the lowest demographically sustainable income is around $400 (in 1990 Geary-Khamis PPP dollars). In those units 1950 world income was $2104, a gain over the long-run historical minimum of $1704. In 2010 global income was $7814. The gain in the development era was 281 times faster than the typical 60-year period of human history.
What is true of income is also true of any measure of income poverty—massive falls in headcount rates of poverty in the development era at any poverty line.
While harder to measure, this orders-of-magnitude more rapid progress is almost certainly true for a whole variety of other indicators. People are better nourished. More people live under democratic regimes. Basic equality of treatment across race, ethnicity, gender, caste has made enormous progress. Human rights are far more widely acknowledged and respected. Violence, both inter-state and inter-personal, costs less lives per capita.
The world facing the typical human being in the developing world is night and day a better place after 60 years of the development era. The objectives of team development were stated clearly, early, and often, and progress on those goals has been 100 times faster in the development era.
So, along come the green eye shade guys in 1966 and say “Yes, Mr. Russell we understand that the Boston Celtics have won 9 of the last 10 NBA Championships. Yes, we understand that is team success almost unprecedented in the history of any sport, not just basketball. But we cannot causally attribute that success to your individual performance. In 1966 Wilt Chamberlain had 33.5 points per game compared to your 12.9 and out rebounded you 24.6 to 22.8 per game.” How can we be sure you are contributing if it isn’t in the individual statistics? How can we be sure your teammates aren’t just better than his teammates?”
We reach the perils of partial attribution. What if the available statistics for individuals are biased towards some easily measurable elements of the game, like scoring, and away from other, equally valuable elements, like playing defense and preventing the other team from scoring. And what if the available statistics for individual scoring don’t take into account whether a player took a shot he had a 50 percent chance of making and didn’t pass to his teammate in a position to take a shot with a 60 percent chance? If he makes the basket the scoring is counted to his total even though his choice of shoot over pass had negative points for the team in expectation. Maybe Russell’s teammates look like better players on their individual statistics because his team play makes everyone better.
There are three separate questions a person or organization engaged in development could ask:
(Optimal Action) What do we think, based on our interpretation of the totality of the evidence, are the actions that we can take that would be the most effective in achieving development goals of improving our preferred measures human well-being?
(Rigor of Evidence) How reliable and rigorous is the evidence for the optimal action? How high is the risk the action has no impact or even is counter-productive?
(Attributable to Me) How rigorously and reliably can the improved outcome be directly and causally attributed to our (person or organization) actions?
Development is very much a team activity. In a team activity there can be a big difference between the answer to the “Optimal Action” question and the “Attributable to Me” question. There can also be a big trade-off between the “Optimal Action” question and the “Rigor of Evidence” question.
My father taught me “There is no end to what you can accomplish if you don’t care who gets the credit” (of course this is an old saying with many sources, but I learned it from my father).
Politically, team development has over the last decade been pushed in exactly the opposite direction. Development agencies, foundations, and philanthropists are being told: “If you cannot take direct credit (preferably with “rigorous evidence”) then it doesn’t matter what was accomplished.” Bill Russell is being encouraged to be less of a team player and to have better individual scoring statistics.
This is lamentable as development is fundamentally a process of social transformation—markets (and their supporting institutions and organizations (e.g. firms)) are social mechanisms that structure how people cooperate, governments (and their supporting institutions (e.g. agencies)) are social mechanisms. This social process of national development reliably produces higher human well-being in every dimension. However, no one can reliably and rigorously demonstrate exactly which actions best promote development (as, almost certainly they are contextual and complex) and certainly no one can reliably attribute development to specific organizations (and doing so may, in and of itself, cause less effectiveness).
One personal example. I first went to India right around the (incipient) macroeconomic crisis of 1991. A combination of political and policy circumstances had put India in a very precarious situation and on the brink of exactly the kind of macroeconomic crisis that occasioned the “lost decade” of growth in Latin America in the 1980s. The Indian government ultimately took a series of steps that most people regarded both as a good handling of the short run crisis and a decisive break with a past economic strategy and a new policy stance.
A study I did recently used common statistical procedures across all countries to estimate the dating of growth episodes and how much total Net Present Value (NPV) of GDP each episode created (or destroyed) relative to a “business as usual” counter-factual of growth during the episode period.
This procedure says that, rather than a growth slowdown, there was a growth acceleration in 1993 that created 1.1 trillion in additional GDP. Then, there was another growth acceleration in 2002 that created another 2.5 trillion in GDP (over and above the previous). Together, relative to the “business as usual” trajectory there has been 3.6 trillion dollars in gain (this cumulative additional GDP is larger than the annual total of the UK or France of about 2.8 trillion).
What caused this additional gain? Of course, no one is really sure exactly what it was and how to parse out the factors and simplistic (e.g. “trade reform”) explanations are almost certainly, well, simplistic. But something did happen and it almost certainly had to do with deft handling of the macro-economy plus a well-executed shift in strategy towards greater reliance on markets and more openness to the global economy (which is not saying that “laissez faire” was the answer or that India turned into a “neo-liberal” state).
Who caused this additional gain? In order to achieve a national policy shift there were of course hundreds, if not thousands of people who participated in producing evidence, disputing explanations of India’s past growth, examining alternatives for the future. But let me single out one group. The ICRIER (India Council on Research on International Economic Relations) was a think tank founded in 1981 that, according to its 20th anniversary document:
The Indian Council for Research on International Economic Relations (ICRIER) was established in August 1981 as an autonomous, policy-oriented, not-for-profit, research institution. This initiative was intended to foster improved understanding of policy choices for India in an era of growing international economic integration and interdependence.
The concept of ICRIER emerged from the Steering Committee for Research on International Economic Relations (SCRIER) to enable policy makers, civil society and academia in India to examine intended and unintended consequences of policy choices concerning globalisation, taking a more open and inclusive view of the world. The first advisory panel, chaired by K B Lall, included I G Patel, Jagdish Bhagwati, Malcolm Adiseshiah, Montek Singh Ahluwalia, C Rangarajan, Fredie Mehta, and Manu Shroff.
And, in the section of the 20th anniversary document discussing the funding of ICRIER:
The Ford Foundation deserves special mention for providing initial funding in 1982 and now, 20 years later, supporting a significant expansion of ICRIER’s endowment base
There is a narrative in which Ford Foundation, a global philanthropy provides some millions of dollars of funding that play some role in creating a think tank that itself then plays some role in providing the conditions in which good policy choices are made that then results in the creation of 3.6 trillion in additional output of Indians. Suppose the Ford Foundation gave 36 million dollars (I have no idea what it really was but I strongly suspect this was the right order of magnitude and I just make it divisible) to support ICRIER.
Optimistically, suppose this gift increased by 50 percent the chance ICRIER was created and became an effective think tank (perhaps other funding could have come along, perhaps not) and suppose the existence and actions of this think tank increased by 10 percent the odds India adopted growth accelerating policies (my read of the situation is that it was higher). Then the expected value of Ford Foundation’s 36 million of support was 180 billion dollars (bracketing discounting), a 5000-fold return per dollar of investment.
Pessimistically, suppose the Ford Foundation funding only increased the likelihood of an effective think tank by 10 percent (someone else almost certainly would have funded it) and the impact of ICRIER on the likelihood of a growth accelerating policy outcome was only 1 percent, the investment still returns 100-fold—3.6 billion on 36 million.
Suppose instead the Ford Foundation had given 36 million in what many regard as the highest return individualized investment: girl’s education. There are hundreds of studies showing a positive return both to wages and to other outcomes—fertility, child survival, empowerment, etc. Let’s suppose, super optimistically, the return on this investment was 20 percent. This means an additional 7.2 million dollars.
But, Ford Foundation can take direct causal credit for the outcomes for these specific girls. They have the names of the girls supported. They can take their pictures and put them in their brochures. They could do an RCT and prove rigorously the increased benefits were the direct result of their grant.
In a very strange turn of events the organizations and supporters of the wildly successful “team development” are under pressure to sacrifice actions that can produce trillions in gains (in the economy, in education, in health, etc.) through systemic transformation. Instead development actors are being pressured to do only actions for which “rigorous evidence” proves “what works” but that leads inevitably to a focus on individualized actions known to produce at best mere millions—but for which the donors and external development actors can take direct causal credit. But there are real dangers from the perils of partial attribution in which individual actors care more about what they can take credit for than whether there is team success.
This essay is based on a speech given to a retreat of DFID economists, September 14, 2017.
Rights & Permissions
You may use and disseminate CGD’s publications under these conditions.
