in large part on the dynamical systems theory. One of the crucial features of systems in synergetics is self-organization, which was discussed above. According to Haken [42], the central question in synergetics is whether there are general principles which govern the self-organized formation of structures and/or functions. The main concepts of the theory are instability, order parameters, and slaving [42]. Instability is understood as the formation or collapse of structures (patterns) [65]. This is very common in fluid dynamics, lasers, chemistry and biology [42, 64, 65, 84]. A number of examples of instability can be found in the literature on morphogenesis [83], and pattern formation examples can be found in fluid dynamics. The phenomenon is called instability because a former state of fluid transforms into a new one, loses its ability to persist, and becomes unstable. One can view the formation of chaos in systems A$_{2}$, . . . , A$_{5}$ in our results as instability. Even though processes in finite dimensional spaces are considered, chaotic attractors are assumed to be not single trajectories, but collections of infinitely many trajectories with complex topologies. One might say that they are somehow in-between objects of ordinary differential equations and partial differential equations. This allows us to also talk about dissipative structures [65], due to the “density" of the chaotic trajectories in the space. Order parameters, when applied to differential equations theory, are those phase variables whose behavior produces the main properties of a macroscopic structure and which dominate all other variables in the formation, so that the latter can even depend on the order parameters functionally. The dependence that is proved (discovered) mathematically is what is called slaving. It is not difficult to see that the variables of system A$_{1}$ are order parameters, and they determine the chaotic behavior of the joined systems’ variables. We provide examples of models of aggregate economy where the main variables exhibit cycle-like mo- tion with chaotic elements. Thus, we obtain an irregular business cycle in a deterministic setting. This provides a modelling alternative to the business cycle literature relying on stochastic variation in the economy. Additionally, our investigation highlights the variety of ways of generating chaos in an eco- nomic model. Previous work has focused on generating chaos and, in particular, chaotic business cycles endogenously (see [19, 20, 58, 74, 88]). Our method of creating chaos has its own relevance for economics, since we show the role of exogenous shocks in the appearance of chaos in models that otherwise do not exhibit irregular behavior. It can also be said that our work provides a missing link in the research on the origins of irregularities in economic time series. While the literature on endogenous chaos was a response to the view that exogenous stochastic shocks are the source of fluctuations in the economy (see [15]), this paper is a response to the former, in that it provides a role for exogenous chaotic disturbances in producing these fluctuations, and thus completes the circle. 8 Conclusion 20