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ON CERTAIN IMPLICATIONS OF NON-LINEARITY IN KEYNESIANISM (O niektórych implikacjach nieliniowosci w keynesizmie)

100%
Jakimowicz A.
Ekonomista
|
2009
|
issue 1
15-48
EN
Following Kurt Gödel's incompleteness theorem, it should be observed that Keynesianism cannot be fully explained on economic grounds alone. A justified assessment of validity of any model requires that it should be referenced in a wider context. A natural framework for such assessments is provided by the general system's theory. When logical homologies that link separate bodies of science are identified, it is possible to apply concepts and methodology of a more advanced discipline into the approach of the less advanced one. At least nine logical homologies among Keynesianism and the ideas of contemporary natural sciences have been identified so far. The analysis of the non-linear model of business fluctuations (Keynes - Samuelson - Gabisch) indicates that the degree of complexity of any economy is subject to changes in relation to the contemplated control parameters.
2

Dynamika nieliniowa w badaniach ekonomicznych

100%
Jakimowicz A.
Didactics of Mathematics
|
2011
|
issue 8 (12)
39-54
EN
Nonlinear dynamics is a multidisciplinary branch of science which encompasses two major concepts of modern science: the deterministic chaos theory and the complexity theory. It also feeds on the rich achievements of cybernetics and the catastrophe theory. Over the recent years, nonlinear dynamics has contributed to considerable progress in system theories as a result of introduction of numerical methods on a broader scale. Initially, they were employed in natural sciences, however, as a result of interdisciplinary diffusion they quickly became common in social sciences, mainly in economics. It was possible thanks to isomorphisms that exist in science, which are based on logical homologies. The introduction of new methods into economics is necessary, since economic systems belong to the most complex dynamical systems that we know of. Moreover, we observe a steady increase in the degree of their complexity, which should be attributed to civilization progress. This is how studies on economic complexity become a central issue of contemporary economics. Numerical explorations of archetypal economic systems show that the increase in the degree of complexity beyond a certain upper limit destroys their adaptive capabilities. It serves as a guideline for societies, namely the prime goal of economic policy should be decreasing complexity of markets and economies. However, it turns out that it is not always possible, because a reduction of chaos can increase systems’ instability.
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