In their target article, Boyer & Petersen (B&P) draw a distinction between proximate and ultimate explanations for folk-economic beliefs. They argue that bias-based models explain only how such beliefs are forged (proximate cause), not why they arise (ultimate cause), nor do they explain the specific contents those beliefs contain. B&P argue that folk-economic beliefs emerge, ultimately, from the operation of specialized cognitive systems, crafted by evolution and “brought online” by the modern economic environment.
We applaud this approach but believe that it fails to seriously consider that many folk-economic misconceptions have no ultimate cause; they result from a “bug,” not a feature, of human cognition. In this sense, they are no different from folk-scientific or folk-medical beliefs, or those in any other complex domain (Shtulman Reference Shtulman2015).
The human cognitive system is severely constrained in both scope and depth. “Scope” refers to the range of elements brought to bear on a given issue, and it is mediated and constrained by long-term memory (LTM). The countless pieces of information in LTM are rarely harmonized (DiSessa Reference DiSessa2006; Leiser Reference Leiser2001), and retrieval from LTM is strongly biased by salience cues (Higgins Reference Higgins, Higgins and Kruglanski1996). Cognitive “depth” refers to the complexity and the number of reasoning steps of an argument, and it is bounded by the capacity of working memory (WM) (Halford et al. Reference Halford, Cowan and Andrews2007; Oberauer et al. Reference Oberauer, Süß, Wilhelm and Wittman2003; Reference Oberauer, Süß, Wilhelm, Sander, Conway, Jarrold, Kane, Miyake and Towse2007). The notorious exiguity of WM means that people struggle to follow the causal chains leading to and from the issues in question.
Economic theory relies on three interrelated key ideas not readily grasped without formal training: (1) It concerns itself with aggregated variables and treats them as causal factors; (2) it integrates indirect effects and feedback loops into a coherent system; and (3) it explains outcomes as equilibrium states. All three seriously challenge the limits of both the scope and depth of our reasoning.
To illustrate with an accessible example from an unrelated domain, consider the “fundamental law of traffic congestion” (Duranton & Turner Reference Duranton and Turner2011). Lay thinking assumes that increasing the number of lanes in a road will decrease congestion. In reality, congestion always rises back to maximum capacity. The optimistic assumption stems from a failure to consider feedback and to ignore equilibrium and aggregate effects.
The mismatch between our cognitive endowment and the assumptions of economics means that people often fail to grasp the proper economic explanations when presented, let alone identify them on their own. The resulting folk-economic beliefs are simply the best laypeople are able to come up with.
Whereas economists consider the aggregate, laypeople focus on individuals. Pitching explanations at the level of individual elements also impedes the understanding of other emergent processes such as heat flow, osmosis, natural selection, or indeed, traffic congestion. These are all processes where the complex interactions of a collection of elements jointly cause the observable outcome. Such processes are cognitively challenging and lead to robust misconceptions (see Chi et al. Reference Chi, Roscoe, Slotta, Roy and Chase2012). There is no need to refer to ancestral conditions to explain the difficulties experienced by laypeople in understanding such emergent processes. These misconceptions are not the output of some intuitive system, but rather arise from the absence thereof.
Elsewhere, we document many consequences of the mismatch between our cognitive makeup and economic theory (Leiser & Shemesh Reference Leiser and Shemesh2018). Here we will focus on two of the folk-economic beliefs discussed by B&P.
FEB 1 holds that international trade has negative consequences. According to B&P, trade activates a coalitional psychology evolved in the ancestral context, which assumes coalitionary interaction to be a zero-sum game. Applied to international trade, this principle leads people to believe that when one nation transfers resources to another, the latter is gaining something, which to them implies the former is losing.
But there is a more parsimonious explanation. The logic of comparative advantage states that nations are better at producing some things compared to others. Therefore, when a given nation buys from another, it is getting something at a lower price than it would cost itself to produce. Why do people see trade as a (zero-sum) transfer rather than a (non-zero-sum) exchange? The relational complexity (Halford et al. Reference Halford, Wilson and Phillips1998) of two-way exchange is overwhelming: Instead of focusing on Country A receiving payment from Country B for Product K, we now have to consider also A obtaining payment from B for Product L, and moreover realize that by obtaining K from B, and by doing so comparatively cheaply, A is able to shift production from K to L. We contend that the demands on working memory for the understanding of comparative advantage are so computationally taxing as to make this account inaccessible without considerable deliberation and effort.
Consider now FEB 8, which posits that regulations achieve their intended effects. B&P argue that this belief is based on the assumption that supply is stable, which itself results from the fact that the ancestral exchange environment included no changes in supply attendant on aggregate demand. As a result, humans never evolved the cognitive wherewithal to handle this specific aggregate dynamic.
We concur but would add that this FEB, and others, can be better understood once we consider the mechanisms underlying retrieval from long-term memory. As we noted, the failure to apprehend aggregate dynamics is widespread, and it does not depend on specific ancestral conditions. Because search in LTM is constrained by salience, when people contemplate economic problems, they tend to think of solutions stated in the same terms as the problem, but pushing in the opposite direction. If rent prices are too high, the popular preference will be to cap prices; if salaries are too low, the most intuitive policy is to raise the minimum wage. Similarly, if many people are unemployed, the “obvious” solution is to create more jobs rather than, say, increase competition. That is to say, people do not trawl their long-term memory for possible causes of the particular phenomenon but simply come up with the most direct solution and are satisfied to leave it at that.
In their target article, Boyer & Petersen (B&P) draw a distinction between proximate and ultimate explanations for folk-economic beliefs. They argue that bias-based models explain only how such beliefs are forged (proximate cause), not why they arise (ultimate cause), nor do they explain the specific contents those beliefs contain. B&P argue that folk-economic beliefs emerge, ultimately, from the operation of specialized cognitive systems, crafted by evolution and “brought online” by the modern economic environment.
We applaud this approach but believe that it fails to seriously consider that many folk-economic misconceptions have no ultimate cause; they result from a “bug,” not a feature, of human cognition. In this sense, they are no different from folk-scientific or folk-medical beliefs, or those in any other complex domain (Shtulman Reference Shtulman2015).
The human cognitive system is severely constrained in both scope and depth. “Scope” refers to the range of elements brought to bear on a given issue, and it is mediated and constrained by long-term memory (LTM). The countless pieces of information in LTM are rarely harmonized (DiSessa Reference DiSessa2006; Leiser Reference Leiser2001), and retrieval from LTM is strongly biased by salience cues (Higgins Reference Higgins, Higgins and Kruglanski1996). Cognitive “depth” refers to the complexity and the number of reasoning steps of an argument, and it is bounded by the capacity of working memory (WM) (Halford et al. Reference Halford, Cowan and Andrews2007; Oberauer et al. Reference Oberauer, Süß, Wilhelm and Wittman2003; Reference Oberauer, Süß, Wilhelm, Sander, Conway, Jarrold, Kane, Miyake and Towse2007). The notorious exiguity of WM means that people struggle to follow the causal chains leading to and from the issues in question.
Economic theory relies on three interrelated key ideas not readily grasped without formal training: (1) It concerns itself with aggregated variables and treats them as causal factors; (2) it integrates indirect effects and feedback loops into a coherent system; and (3) it explains outcomes as equilibrium states. All three seriously challenge the limits of both the scope and depth of our reasoning.
To illustrate with an accessible example from an unrelated domain, consider the “fundamental law of traffic congestion” (Duranton & Turner Reference Duranton and Turner2011). Lay thinking assumes that increasing the number of lanes in a road will decrease congestion. In reality, congestion always rises back to maximum capacity. The optimistic assumption stems from a failure to consider feedback and to ignore equilibrium and aggregate effects.
The mismatch between our cognitive endowment and the assumptions of economics means that people often fail to grasp the proper economic explanations when presented, let alone identify them on their own. The resulting folk-economic beliefs are simply the best laypeople are able to come up with.
Whereas economists consider the aggregate, laypeople focus on individuals. Pitching explanations at the level of individual elements also impedes the understanding of other emergent processes such as heat flow, osmosis, natural selection, or indeed, traffic congestion. These are all processes where the complex interactions of a collection of elements jointly cause the observable outcome. Such processes are cognitively challenging and lead to robust misconceptions (see Chi et al. Reference Chi, Roscoe, Slotta, Roy and Chase2012). There is no need to refer to ancestral conditions to explain the difficulties experienced by laypeople in understanding such emergent processes. These misconceptions are not the output of some intuitive system, but rather arise from the absence thereof.
Elsewhere, we document many consequences of the mismatch between our cognitive makeup and economic theory (Leiser & Shemesh Reference Leiser and Shemesh2018). Here we will focus on two of the folk-economic beliefs discussed by B&P.
FEB 1 holds that international trade has negative consequences. According to B&P, trade activates a coalitional psychology evolved in the ancestral context, which assumes coalitionary interaction to be a zero-sum game. Applied to international trade, this principle leads people to believe that when one nation transfers resources to another, the latter is gaining something, which to them implies the former is losing.
But there is a more parsimonious explanation. The logic of comparative advantage states that nations are better at producing some things compared to others. Therefore, when a given nation buys from another, it is getting something at a lower price than it would cost itself to produce. Why do people see trade as a (zero-sum) transfer rather than a (non-zero-sum) exchange? The relational complexity (Halford et al. Reference Halford, Wilson and Phillips1998) of two-way exchange is overwhelming: Instead of focusing on Country A receiving payment from Country B for Product K, we now have to consider also A obtaining payment from B for Product L, and moreover realize that by obtaining K from B, and by doing so comparatively cheaply, A is able to shift production from K to L. We contend that the demands on working memory for the understanding of comparative advantage are so computationally taxing as to make this account inaccessible without considerable deliberation and effort.
Consider now FEB 8, which posits that regulations achieve their intended effects. B&P argue that this belief is based on the assumption that supply is stable, which itself results from the fact that the ancestral exchange environment included no changes in supply attendant on aggregate demand. As a result, humans never evolved the cognitive wherewithal to handle this specific aggregate dynamic.
We concur but would add that this FEB, and others, can be better understood once we consider the mechanisms underlying retrieval from long-term memory. As we noted, the failure to apprehend aggregate dynamics is widespread, and it does not depend on specific ancestral conditions. Because search in LTM is constrained by salience, when people contemplate economic problems, they tend to think of solutions stated in the same terms as the problem, but pushing in the opposite direction. If rent prices are too high, the popular preference will be to cap prices; if salaries are too low, the most intuitive policy is to raise the minimum wage. Similarly, if many people are unemployed, the “obvious” solution is to create more jobs rather than, say, increase competition. That is to say, people do not trawl their long-term memory for possible causes of the particular phenomenon but simply come up with the most direct solution and are satisfied to leave it at that.