Most professionals, from doctors to policy makers, are subject to biases that can prevent them from helping the people they are actually seeking to assist. Previous beliefs or personal culture can prevent them from objectively analyzing the information they have in front of them. This can be particularly serious in professions where data analysis plays a major role, like development professionals. Fortunately, the World Bank - an institution full of such people - decided that instead of pretending such issues were not present, they would release a report where they collected data examining how their staff behaved, testing if the biases were actually there.
Decisions can be very complex. Suppose you have a problem at hand, which is particularly messy. How do you compare alternatives in such situations? And what if alternatives are almost infinite? Even in simpler cases, going from two to three alternatives has been suggested to "irrationally" change professionals actions: doctors were outlined a situation where a patient had two alternatives: 1) Ibuprofen + Referral (to specialist); or 2) Just referral. In such a case 53% of doctors chose option 2. Another set of doctors was given a third alternative: 3) Piroxicam + Referral. Paradoxically, now many more doctors (72%) chose the previously available option of just Referral. Complexity modifies their behavior, leading them more to the simpler solution of just referral. Since the only difference between the two cases was that a new (possibly "irrelevant") alternative was added, we should expect less doctors choosing any of the previously available ones. But this did not happen. And this are highly educated and experienced professionals!
Framing (basically how something is described) is also unbelievably important: people seem to have much negative views of a policy that says 1/3 of people will die versus one that says 2/3 of them will survive. Obviously, the two are exactly the same. Moreover, when framed in terms of gains, people prefer certainty ("1/3 of people survive"). However, when framed in terms of losses ("2/3 of people die"), people are more willing to take a gamble and try to save more people (1/3 chance no one dies and 2/3 chance everyone dies"). Does this happen at the World Bank as well? Certainly.
Confirmation Bias means that people gather or value information selectively in order to support their previous beliefs. We all have cultural and ideological priors, which leaves us susceptible to analyze or interpret information with motivated reasoning, so as to arrive to the conclusions we like. A very nice experiment was held where professionals were given the same data to analyze. To some people they told it referred to the effectiveness of a skin cream (something for which we don't have priors or political beliefs) and others were told it was about the impact of the minimum wage laws on poverty. Figure 1 shows that World Bank professionals were more likely to identify the answer supported by the data (i.e. the "correct" one), when talking about skin cream. (I am also shocked by how low the percentage of right answers is when talking about skin cream, but I guess that's another issue...). When dealing with the minimum wage they were more likely to get the right answer when this matched their cultural views. And differences in seniority or cognitive ability did not improve the interpretation of the data. This was also done with people outside the World Bank and they actually found that skill helps only when the right answer matches your ideology...
Figure 1: Subjective interpretation of data.
We could take all this information in a negative way: some of the best people in charge of world development are not doing a good job. However, I believe that's not correct. This bias is present in all of us. And the positive thing is that the people at the World Bank now seem to be willing to recognize it and hopefully move forward to try to make progress. Identifying the problem is the first step, or as John Dewey said a problem well put is half solved.
Many major economic and social problems such as crime, teenage pregnancy, dropping out of high school and adverse health conditions can be traced to low levels of skill and ability in society. The figures below show that (measurable) ability is highly correlated with having been in jail or being single with children. Economists have always been interested in the way typical goods (say agricultural or industrial ones) are produced. But if these skills and abilities are that important in life, shouldn't we focus on better understanding their production process?
Ever been in Jail by 30 years old, by ability (males)
Probability of being single with children (females)
Would it be simplifying but relatively fair and innocuous to summarize all our skills into one word like ability or intelligence? Or is it important for us to recognize that there is more than one skill? For example, the No Child Left Behind Act concentrates attention on cognitive skills (math, reading) through achievement test scores, not evaluating a range of other factors. However, noncognitive (personality, social, emotional) skills seem to be very important as well. They contribute to performance in society at large. Gaps in skills seem to be present early in the lives of children, being family environments very good predictors of them. The chart below shows that Children's cognitive skills gaps are present as early as 3 years old and are strongly related related to mother's education.
Mean Cognitive Score by Maternal Education
Can early intervention fix these differences? Economically speaking, are these skills better "produced" when children are one year old or can we later remediate them when they are older (through primary and high school)? These issues are essential when analyzing public policies to improve education or adult socioeconomic behavior. Current policies, like reducing pupil-teacher ratios, focus on later remediation. But shall we improve schools? Or is it better to focus in educating parents so that they can take better care of their children in the first three years of their lives?
Heckman has started a major project in order to be able to understand these important questions. But (good) economists like using data carefully in order to answer questions objectively. It's important to recognize that we don't have direct data on these skills. People don't carry a number with them saying "I have cognitive skills of level 2 and noncognitive ones of level 5". So Heckman and his coauthors are going to do some heroic econometric work to get around this.
They assume that these unobserved factors are related to children parents (through their also unobserved skills, income, education, etc) and their "investments" in their kids (reading them, taking them to museums, etc). But how can Heckman estimate the effects of things we don't observe? Basically they are going to assume that these (unobserved) skills are related to test results and later outcomes in life like education, crime, early pregnancy and many others. Taking into account how these multiple outcomes and investments correlate with each other, will allow them to estimate these two set of skills and give them the information they are after. Notice we need very large amounts of information on the same children and their parents at many periods of their lives. So where does the data come from? It may be hard to believe, but many countries have such data. For example, over 10 thousand American children (and their mothers) have been followed since they were born, which will let Heckman estimate what matters in child development and how we should distribute our efforts in order to improve it?*
Let me give you an idea of the amount and type of questions these families answered when they were interviewed, usually every two years. From these surveys, we know: children's gestation length weight at birth, memory for locations, picture vocabulary, standard test results (on reading and algebra), friendliness, sociability and behavior problems; whether their parents read them, how many books they have, how often the family eats together and whether they go to museums or concerts; their mother's arithmetic skills, self-esteem and their family income and savings. And many many more. A crazy large amount of information is collected in a regular manner from these same people. A by product of this study is that we can find out what seems to work best in improving children's skills. Interestingly, how often the mother reads to the child or if they eat together during the first year seems to be some of the most important factors. Similarly, once the children grow older (6+ years), going to museums or concerts seem to become very important for their development as well. (If you are thinking about applying this nowadays, you should take this with a grain of salt. Keep in mind these children grew up in the 1980s so they did not ask to go to Miley Cirus concerts. Music was probably better then.)
So what about the production process of these skills? Is it better to invest in the first years or we can achieve the same results by "fixing" children's bad initial years when they get older through better education systems? Heckman's results suggest we should focus on the first three years of their lives. Parental investment in these years has a much greater impact than later ones. Moreover, during these early years improving one set of skills seems to increase the quality of the other one. Skills beget skills.
And are the two skills equal? No. Children's cognitive skills tend to stabilize early in life (say around 6 years old) and are difficult to change later on. On the other hand, social skills seem to flourish when children are between 6 and 14 years old. In case you are wondering whether economics has gone mad, let me say that this seemingly crazy study suggests that what happens in these early years of life can explain over 50% of the years of education, criminality or teenage pregnancy. This is very relevant. Moreover, it suggests that if governments were interested in improving any of these outcomes, they should try to invest very early (before schooling years) in the disadvantaged. Possibly educating parents on the importance of reading to their children or taking them to social activities might help. How to approach this parental education is the next issue at hand.
* They are actually going to use only 2000 first-born white children in their estimates, in order to avoid issues related to my last week posts. They want children to be as similar as possible, in order to avoid capturing wrong effects in their estimates. They also allow for endogeneity and measurement error in their estimation process.
Follow me on twitter at @diedaruich
News and posts for an active mind.