Kulivets & Ushakov – 2016 – Modeling Relationship between Cognitive Abilities and Economic
We propose that problem solving is the mediator between human competencies and achievements. Creation of goods and services is based on problem solving in design, production and delivery. The quality of problem solving depends on human competencies and, in turn, determines economic achievements. More importantly, the choice of problems to be solved creates or does not create the possibility for application of highly qualified labor and, as a result, for full-fledged realization of human capital. We propose a mathematical model based on these assumptions. The simulation reproduces most important traits of Lynn and Vanhanen’s (2002) findings. The simulation shows a non-linear growth of economic achievements with national IQ growth as well as an increase of between countries variance. Thereby the proposed model can serve as a satisfactory explanation for empirical data on links between national IQs and economic achievements.
It’s well established that there is a very close correlation between average national IQ and GDP per capita, especially when corrected for resource windfalls and Communism.
(One such standard graph from Garett Jones).
However, there remain two additional results that correlational exercises cannot adequately explain:
- “First, the relationship between national IQs and income is not linear. As it was shown later this relationship can be well approximated by quadratic function (Whetzel & McDaniel, 2006). The mere assumption that more capable, competent and educated people produce better economic results is not sufficient to explain this specific finding.
- “Second, residuals of the regression of GDP on national IQ grow proportionally with the IQ. It means that in some high-IQ countries human potential leads to serious economic realizations while in others it is out of demand. So a comprehensive explanation of Lynn and Vanhanen’s data includes understanding of factors stimulating the use of highly qualified labor.”
So Sergey Kulivets, a mathematician at the Trapeznikov Institute, and Dmitry Ushakov, a psychologist at the Institute of Psychology RAN, created a model in which problem solving plays a central role to investigate these two puzzles.
They model a world composed of different countries, in which every resident has a “talent” with a bell curve distribution around different means. Each country has two types of people: Entrepreneurs and specialists. Entrepreneurs hire specialists to produce goods, the quality of which is determined by the talents of the specialists working on them. These goods are then sold on the international market, where any country can buy them. The “GDP” of each country is the sum of the income of its entrepreneurs, or the value of all the goods produced by the entrepreneurs within a country and sold in the international product market, during a set period.
Here is how the model works:
- Each entrepreur chooses a task for solving. There are two types of tasks: “Threshold” and “open type” ones. Threshold problems require a minimum competence level to complete, but additional competence beyond that threshold offers no further advantages beyond that minimal point; the value of the solutions to open problems increases with the talent of the specialists allocated to it.*
- The entrepreneur hires specialists from his own country to perform that task, attracting specialists by offering higher salaries for more competitive candidates.
- The entrepreneur produces goods. Quantity dependent on number of workers and money allocated to them; quality depends on the competence (talent) level of the hired specialists.
- The entrepreneur sells the good on an international market, competing with other enterpreneurs on price and quality.
- Income from this goes to entrepreneur, which in turn – after subtracting production costs and salaries – determines his budget for the next round of problem solving.
Consult the paper for the specific formulae used to describe task selection, the labor market, and the product market.
Towards the end, K&V compare their theoretical models against Lynn and Vanhanen’s. They match up near perfectly.
Competence: I; Development: D.
Left: Lynn & Vanhanen 2002; Right: Simulation results.
Also one can observe that K&V get a nicer fit than L&V, presumably because the Communist legacy (negative outliers) and resource windfalls (positive outliers) aren’t modeled.
Over time both consumers and entrepreneurs become much richer in competent countries relative to incompetent ones, as the “rise in entrepreneurs’ income influences the consumer income through salary rises.”
In this model, entrepreneurs choose tasks in a random way; unsuccessful ones are abandoned, while those that bring a return continue to be produced. As K&V note, if the quality of entrepreneur predictions as to the profitability of various tasks were to also depend on competence levels, then this cognitively-determined pattern of the wealth and poverty of nations can be expected to be even starker.
However, they do end with a cautionary note of some relevance to today’s political economy: Our model is based on the assumption that entrepreneurs’ income comes from organizing people to produce goods and services. This mechanismfunction is impaired if natural rent becomes the main source of profit.
* Incidentally, I would note that this division is justified by and reinforced by Garett Jones’ theory of the O-Ring sector: “I posit that there are two kinds of jobs: O-ring jobs where strategic complementarities to skill are large, and a diminishing-returns Foolproof sector, where two mediocre workers provide the same effective labor as one excellent worker… In a world where countries vary only slightly in the average skill of workers, these assumptions are sufficient to generate massive differences in cross-country income inequality while generating only small amounts of intra-country income inequality.“