Mental Models and Academic Models
Every year, the World Bank publishes a World Development Report, an analysis of a selected aspect of Economic Development and its status in the world at the time. In 2015, the selected theme was “Mind, Society, and Behavior.” In this report, the WB argues that there have been advances in our understanding of how people make decisions, and that this better understanding can be used to increase the effectiveness of development interventions.
They highlight three principles of human decision making:
Many of our decisions are done quickly, making use of an automatic and effortless system of thinking that contrasts with the slower and more deliberative and thoughtful process that we often identify with rational decision making processes. This argument builds on the work of psychologists such as Daniel Kahneman and Amos Tversky and I have discussed this in other blog posts on this site as well.
Our individual decision making is not really just individual, but influenced by the society around us: social preferences, norms, identities. We cannot assume that factors (preferences) taken in consideration in individual decision making are not shaped by the communities in which we are embedded.
The social influences that we receive are embedded in “mental models:” worldviews, stereotypes, simplifying concepts and categories that we use for decision making
The consequence of the three principles is that our decision making is influenced by “culture,” deeply rooted beliefs and practices that we often take for granted and may not even recognize. These beliefs and practices may favor or be detrimental to the achievement of desired development goals by any community. When they are detrimental, breaking the cultural patterns may require addressing social practices and institutions before individual incentives and decision-making can change.
The authors argue that “recognizing that individuals think automatically, think socially, and think with mental models expands the set of assumptions policy makers can use to analyze a given policy problem and suggests three main ways for improving the intervention cycle and development effectiveness:” (p. 192)
“First, concentrating more on the definition and diagnosis of problems, and expending more cognitive and financial investments at that stage, can lead to better-designed interventions. […]
Second, an experimental approach that incorporates testing during the implementation phase and tolerates failure can help identify cost-effective interventions […]
Third, since development practitioners themselves face cognitive constraints, abide by social norms, and use mental models in their work, development organizations may need to change their incentive structures, budget processes, and institutional culture to promote better diagnosis and experimentation so that evidence can feed back into midcourse adaptations and future intervention designs.” (p.192-193).
The recognition by the World Bank of the role that culture plays in development, through the functioning of mental models, came on the tails of increased attention paid to behavioral sciences. The report often cites, for example, the work of Nobel Prize laureates Esther Duflo and Abhijit Banerjee, that (among other things) call attention to the fact that there is evidence from randomized control trials that how foreign aid is designed and delivered often matters for their effectiveness. One of several members of the Advisory Panel to the World Bank report was Cass Sunstein, a legal scholar that, among other things, wrote a book called “Nudge” arguing that policy design and delivery can affect the choices that people make. As I write this post, he also happens to be the husband of the USAID administrator Samantha Power. When she took office in 2021, she seemed to bring the belief that the Agency could use more insights from behavioral science in its own design and delivery of foreign assistance activities and even brought her husband to speak to USAID staff.
Of particular interest to me is the role played by mental models as devices that seem inherent to our nature, to how our brains work, and necessary for our daily functioning and (often unconscious) decision making, but that simultaneously can be detrimental to our goals and hard to break from.
How far can a parallel be drawn with academic models?
Academic models would seem, at first, to be quite the opposite of mental models. They belong to the “thinking slow” realm, we are conscious of their assumptions, the connections between those and their implications, and are able to modify them, consciously, as needed to better explain what we observe in our reality. They would seem to only have in common with mental models, the fact that they are, umm… “models,” simplifications of reality used to allow us to deal with its complexities in a productive way. However, academic models too have a way of inserting themselves into our unconsciousness and biasing our thinking over time, to the point that we are no longer able to recognize this effect.
Hoping for some more insight on how academic models allow us to better understand reality, I found a 2008 paper by Mary S. Morgan and Tarja Knuuttila titled “Models and Modelling in Economics,” which I understand was later (in 2012) published in the “Handbook of Philosophy of Economics” edited by Uskali Mäki and published by Elsevier. I should state upfront that I do not know the extent to which the draft I found was edited before being published three years later. A quick internet search shows that Oxford published its own Handbook of Philosophy of Economics in 2009, as did Routledge in 2021. Philosophy of economics is the kind of subject that interests, annoys and troubles me, all at the same time. I do have a genuine interest in how we claim to know things, but my interest in economics always came from a practical standpoint of wanting to improve the conditions in which the populations I came from lived in. So having to spend too much time on these issues to be able to digest economic theory always struck me as simultaneously necessary but too time consuming, perhaps beyond my capacity to fully grasp, and potentially a waste of my time. In the end, my failure to overcome my methodological or philosophical discomfort with economic theory in general became a source of personal internal conflict and, hence, the troubling nature that these discussions have for me.
But Morgan and Knuuttila’s paper did seem promising to shed some light on these matters, so I dived into it and I will summarize my understanding and takeaways here.
They distinguish between two major views of models in economics: as “idealized entities” or “purpose built constructions.”
As idealizations, they can be viewed as generalizing, abstracting, simplifying and/or isolating, for reasons such as facilitating deductive reasoning or for mathematical tractability. This can be done by identifying aspects of reality that are considered absent or negligible or that can be ignored because they remain unchanged over the time, place or scope of analysis. Often the idea is that, once used for its purpose of analysis, models can be “de-idealized,” or made more concrete, by adding back specificity. The practice of “idealizing” and “de-idealizing” is not simple or inconsequential, however. Deductions from an idealized model may not necessarily hold when more specificity is added back. In fact, the risk of distortion in each direction of the process is considerable.
A couple of traditional discussions around this view of models are, first, the traditional view that data without models reflecting theory can suggest spurious relationships and, therefore, data should follow models that should follow theory. A more recent discussion is on whether it is best to build models from the more general to specific or the other way around. Theory and data jointly feed model building under one or the other approach.
The second view of models, as purpose built constructions, sees them as “fictional entities,” “autonomous objects,” that are not constructed in relation to an observed reality, nor are they necessarily related to theory, or perhaps they are related to just one particular aspect of the observed reality or theory, but are simple tools for thought, perhaps creating a parallel, stylized reality that allows for understanding of the connecting between cause and effect, or “for a variety of purposes.”
My experience with economic theory in the past suggests a greater prevalence of the second view relative to the first, at least in the academic circles I was a part of. That is why I also came to see as a reasonable justification for economic theory that it can show that some results are possible to be observed, and it can show a set of conditions under which those results can be observed (sufficient conditions). This is useful often to demonstrate that what we observe does not necessarily mean that “a” or “b”is true, but could also mean that “c” is true. It helps dispel many myths that we create in our daily lives by not understanding the many circumstances that can lead to what we observe. However, being able to show all possible sufficient conditions for an observation to be true (i.e. the collection of scenarios that, seen as a whole, constitute the necessary conditions for an observation to be true), is much harder. A set of identified sufficient conditions may turn out to only be one of many sets of conditions under which the same result is observed. That is where the usefulness of these theoretical models ends. In other words, these constructed models tell us a lot of what reality is not necessarily, but very little about what reality is.
Morgan and Knuuttila then seem to suggest that, under either view of models, a more useful way to look at them could be one focused on their function: “instead of trying to define models in terms of what they are, a focus could be directed on what they are used to do (p28).”They go on to argue that this would be the focus less on the models themselves but on the process of modeling.
The parallel I was seeking with mental models is not in this paper, after all. The authors only very tangentially allude to it early on when they state that “economics shares an hermeneutic character with other social sciences […] individuals’ knowledge of economics feeds back into their economic behavior, and that of economic scientists feeds in turn into economic policy advice, giving economics a reflexive character quite unlike the natural sciences.” In my experience, no matter how rigorous academic economist may believe themselves to be in their views and uses of models, the moment they are asked to give their opinion about reality they will refer to them (irrespective of their constructive or simplified nature) and draw suggestions about reality that the models themselves to not allow them to. Academic models become academics’ mental models, and the myriad of assumptions, conditions, and circumstances under which they may inform reality get lost in the process.
I also found lacking in Morgan and Knuuttila’s paper a discussion of the possibility or not of actually “testing” models with data. Here too they tangentially allude to it when noting that econometric models are not just testing mathematical models built on theory (selection of variables and causal relationships) but are often simultaneously testing the data, assuming probabilistic distributions, functional forms, the nature of observed errors and stochastic behavior (p15).
The bottomline for me is that, as I found the World Bank’s effort to assess the role of mental models in development practice to be refreshing, I suspect I would find equally refreshing a critical look at the impact that academic modeling has had on our economic understanding as applied to our daily practice, the good and the bad of it. The discussion of “robustness” of academic models, touched in passing in Morgan and Knuuttila’s paper, makes some headway in this direction, as it recognizes the need to question whether models hold to changes in assumptions, place, time, circumstances. A step further would be to ask ourselves the extent to which we fall from academic rigor when we translate academic models to our daily view of the world and start confusing our models with reality. To be continued.
References
Morgan, Mary S. and Tarja Knuuttila. 2008. Models and Modelling in Economics. Forthcoming in U. Mäki (ed) Handbook of the Philosophy of Economics [one volume in Handbook of the Philosophy of Science, general editors: Dov Gabbay, Paul Thagard and John Woods]. Available: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://sites.pitt.edu/~jdnorton/teaching/Phil_Sci_Core/HPS_2501_2020/more_pdf/Knuuttila_Morgan_Models_2009.pdf/. Accessed: April 07, 2024.
World Bank. 2015. World Development Report 2015: Mind, Society, and Behavior. Available: https://www.worldbank.org/en/publication/wdr2015. Accessed: April 07, 2024