World Development Report 2015: Overview: Mind, Society, and Behavior. A World Bank Group Flagship Report. Available at https://openknowledge.worldbank.org/ or doi: 10.1596/978-1-4648-0342-0

[What follows are excerpts from a review forthcoming in the Journal of Economic Psychology; full version there or write me … ]

The World Development Report 2015 (henceforth, the Report) was launched in December 2014. Apart from a foreword of the president of The World Bank Group in which we are told “that, when it comes to understanding and changing human behavior, we can do better” (p. v), there are two full pages of acknowledgments and twenty pages of overview that introduce the three parts of the Report.

Part 1 sets the stage with a sketch of a conceptual framework. It builds on the well-established fact (a “principle” as it is called here also) that our cognitive resources are limited and hence much of our thinking is automatic (chapter 1, “Thinking automatically”) and that, furthermore, we are social animals and hence our actions tend to be moderated and influenced by our environment (chapter 2, “Thinking socially”). The automaticity and sociality of our thinking induces mental models and chapter 3 reflects on this principle: “When people think, they generally do not draw on concepts that they have invented themselves. Instead, they use concepts, categories, identities, prototypes, stereotypes, causal narratives, and worldviews drawn from their communities. These are all examples of mental models. Mental models affect what individuals perceive and how they interpret what they perceive, … “ (p. 11)

In Part 2 six thematically oriented reviews of the literature (chapter 4: Poverty, 5: Early childhood development, 6: Household finance, 7: Productivity, 8: Health, 9: Climate change) are offered, each with many references. Part 3 reflects on how the work of development professionals can be improved: In chapter 10 an attempt is made to assess the biases of development professionals and in chapter 11 adaptive design and adaptive interventions are discussed.

The Report is an enormous collaborative effort of more than a dozen direct contributors and many more indirect collaborators such as an advisory panel consisting of well-known academics. And, “[v]aluable inputs were received from all World Bank Group regions, the anchor networks, the research group, the global practices, the Independent Evaluation Group, and other units. The World Bank Chief Economist Council and the Chief Economist’s Council of Eminent Persons provided many helpful comments.” (vii) Two dozen organizations are also thanked for various forms of support and scores of individuals are thanked additionally for their feedback (see vii, viii). The Report draws on background papers and notes prepared by almost 30 people, and received expert advice from more than 40 people. The production and logistics team for the Report comprised a dozen people and there was both a principal editor and a principal designer of the Report.

The Report draws unapologetically on Behavioral Economics, whatever it is that this term denotes these days (Heukelom 2014; see Ortmann 2015).

An infographic usefully sketches out the conceptual framework: Economists, it is argued, typically assume people make rational choices, i.e., they carefully weigh choices, consider all readily available information, and make decisions individually. It is noted that that is not the way people actually make decisions. Behavioral economists – here understood to be economists enlightened by psychological insights – provide hence “a richer understanding of how people actually think and behave”: People think automatically (“We tend to think fast and rely on mental shortcuts”) and socially “We cooperate, as long as others do the same, and rely on social networks and norms”), and think with mental models that their automatic and social thinking made them pick up. Which, in turn, motivates the plea for numerous policy interventions from simplified information presentation, to application of social pressure, and derailing of mental models.

The Report provides scores of brief summaries of literally hundred of studies that document interesting and apparently successful interventions. Herein lies the major value of this Report.

What the Report does not do, unfortunately, is the kind of red teaming that it advocates as “one way to overcome the natural limitations on judgement among development professionals … In red teaming, an outside group has the role of challenging the plans, procedures, capabilities, and assumptions of an operational design, with the goal of taking the perspective of potential partners or adversaries. Red teaming is based on the insight, from social psychology, that group settings motivate individuals to argue vigorously. Group deliberation among people who disagree … increase the odds that the best design will come to light and mitigate the effects of ‘groupthink’” (p. 19)

It is hardly contestable that we are social animals and that our mental models take into account what good old Adam Smith has identified as the blame- and praise-worthiness of our actions (Meardon & Ortmann 1996). The incidence of corruption, for example, is in many cases positively correlated with its social acceptance. And “changing a social norm about corruption constitutes a collective action problem rather than simply the repression of deviant behavior” (p. 61). The challenge then is how to solve this collective action problem. In chapter 2 of the Report, we learn about pro-social motivations and group identification and that most people behave as conditional cooperators. Such cooperation depends on one’s expectation about others’ cooperation. Studies are being reviewed that show how expectations can be manipulated into desirable directions, through the possibility of punishment and/or opportunities to observe others’ behavior for example. The problem is that punishment prompts desirable behavior only in very specific circumstances (see Guala 2012 and Balafoukis & Nikoforakis 2012 and see also the literature on asset legitimacy and social distance such as Cherry et al. 2002, Bekkers 2007, and Smith 2010, to name a few). Also, the effects of social monitoring are by no means uncontested, surely highly contextual, and I am not aware of any study that investigates their robustness over time. I.e., how long will “watching eyes” prevent people from exercising constraint?

Overall, and notwithstanding the occasional claim of systematic reviewing (p. 155 fn 6), the sampling of the evidence seems often haphazard and partisan. Take as another example, in chapter 7, the discussion of reference points and daily income targeting that was started by Camerer et al. (1997) and brought about studies such as Fehr & Goette (2007). These studies suggested that taxi drivers and bike messengers in high-income settings have target earnings or target hours and do not intertemporally maximize allocation of labor and leisure. The problem with the argument is that several follow-up studies (prominently, the studies by Farber 2005, 2008) questioned the earlier results. Here no mention is made of these critical studies. Instead the authors argue that the failure to maximize intertemporally can also be found in low-income settings. They cite an unpublished working paper investigating bicycle taxi drivers in Kenya and another unpublished working paper citing fishermen in India. Tellingly, the authors (and the scores of commentators they gave them feedback) did not come across a paper, now forthcoming in Journal of Labor Economics, that has been circulating for a couple of years (see Stafford 2013) and that shows, and shows with an unusually rich data set for Florida lobster fishermen, that both participation decisions and hours spent on sea are consistent with a neoclassical model of labor supply. Stafford also shows that estimation issues, and not workers’ behavior, may be responsible for earlier findings. Methods that do not control for measurement error and endogeneity of the wage not only produce downward biased estimates of labor supply elasticities, but generate a spurious negative and significant elasticity of daily hours.

There are dozens of other examples of review of the literature that I find troublingly deficient on the basis of articles I know. Troubling because “[t]he body of evidence on decision making in developing country contexts is coming into view, and many of the emerging policy implications require further study.” (p. 3) But, as mentioned and as I have illustrated with examples above, there is little red teaming on display here. Not that that is a particularly new development. Behavioural Economics has since the beginning been oversold and much of that over-selling was done by ignoring the considerable controversies that have swirled around it for decades (Gigerenzer 1996 and Kahneman & Tversky 1996 anyone?; see also Hertwig & Ortmann 2004 and Gigerenzer et al. 2008; and specifically pertaining to the the kind of work reviewed in the Report, Harrison 2010, 2011, 2013, Andersen et al 2014; see also the hilarious Welch 2015)).

The troubling omission of contrarian evidence and critical voices on display in the Report is deplorable because there are important insights that have come out of these debates and the emerging policy implications would be based on less shifty ground if these insights would be taken into account in systematic ways. If you make the case for costly and policy interventions that might affect literally billions of people, you ought to make sure that the evidence on which you base your policy implications is robust.

In sum, it seems to me that the resources that went into the Report would have been better spent had there been adversarial collaborations (Mellers et al. 2001) and/or had reviews gone through a standard review process which hopefully would have forced some clear-cut and documented review criteria. A long list of people that gave feedback is not a good substitute for institutional quality control.

We can indeed do better when it comes to understanding and changing human behavior but it ought to be done on a scientifically sound basis. The World Development Report 2015 seems wanting.

References

Andersen, S., Harrison, G.W., Lau, M.O., & E.E. Rutstroem (2014). Discounting behavior: A reconsideration. European Economic Review 71, 15 – 33.

Balafoukis, L. & Nikoforakis, N. (2012). Norm enforcement in the city: A natural field experiment, European Economic Review 56, 1773 – 1785.

Bekkers, R. (2007). Measuring Altruistic Behavior in Surveys: The All-or-Nothing Dictator Game. Survey Research Methods 1, 139-144.

Camerer, C., L. Babcock, G. Loewnstein, & R. Thaler (1997). Labor Supply of New York City Cab Drivers: One Day at a Time. Quarterly Journal of Economics 111, 407 – 441.

Cherry, T., Frykblom, P., & J. Shogren (2002). Hardnose the Dictator. American Economic Review 92, 1218-1221.

Farber, H.S. (2005). Is Tomorrow Another Day? The Labor Supply of New York City Cabdrivers. Journal of Political Economy 113, 46 – 82.

Farber, H.S. (2008). Reference-Dependent Preferences and Labor Supply: The Case of New York City Taxi Drivers. American Economic Review 98, 1069 – 82.

Fehr, E. & L. Goette (2007). Dow Workers Work More if Wages Are High? Evidence from a Randomized Field Experiment. American Economic Review 97, 298 – 317.

Gigerenzer, G. (1996). On narrow norms and vague heuristics. A reply to Kahneman and Tversky. Psychological Review 103, 592 – 596.

Gigerenzer, G., R. Hertwig, U. Hoffrage, & P. Sedlmeier (2008). Cognitive Illusions Reconsidered. Pp. 1018-1033 in Plott & Smith (eds.), Handbook of Experimental Economics Research. Vol. 1, Amsterdam: North-Holland.

Guala, F. (2012). Reciprocity: Weak or strong? What punishment experiments do (and do not) demonstrate. Behavioral and Brain Sciences 35, 1 – 59.

Harrison (2010). The behavioral counter-revolution. Journal of Economic Behavior & Organization 73, 49 – 57.

Harrison (2011), Randomisation and its Discontents. Journal of African Economics 20, 626 – 652.

Harrison (2013), Field Experiments and methodological intolerance. Journal of Economic Methodology 20, 103 – 117.

Hertwig, R. & Ortmann, A. (2004). The Cognitive Illusions Controversy: A Methodological Debate in Disguise That Matters To Economists. Pp. 113-130 in Zwick & Rapoport (eds.), Experimental Business Research III, Boston, MA: Kluwer.

Heukelom, F. (2014). Behavioral Economics. A History. New York: Cambridge University Press.

Kahneman, D. & A. Tversky (1996). On the reality of cognitive illusions: A reply to Gigerenzer’s critique. Psychological Review, 103, 582 – 591.

Meardon, S. & A. Ortmann (1996). Self-Command in Adam Smith’s Theory of Moral Sentiments. A Game-Theoretic Reinterpretation. Rationality and Society 8, 57 – 80.

Mellers, B., R. Hertwig, & D. Kahneman (2001). Do Frequency Representations Eliminate Conjunction Effects? An Exercise in Adversarial Collaboration. Psychological Science 12, 269-275

Ortmann, A. (2015), Review of Heukelom (2014). OEconomia, forthcoming.

Smith, V.L. (2010). What Are The Questions? Journal of Economic Behavior & Organization 73, 3–15.

Stafford, T. (2015). What Do Fishermen Tell Us That Taxi Drivers Don’t? An Empirical Investigation of Labor Supply. Journal of Labor Economics. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2262677

Welch, I. (2015). Plausibility. A Fair & Balanced View of 30 Years of Progress in Ecologics. Retrievable at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2570577