Examples of shocks of the form (4.12) and (4.13) are natural disasters and extreme events in general, such as market crashes. They take a finite number of values (an earthquake either happens or not), but their timing is irregular or regular. Equation A$_{1}$ is the logistic map, which will be used as the main source of chaos in system (4.11). The interval [0 , 1] is invariant under the iterations of the map for the parameter values µ ∈ (0 , 4] , and for µ = 3 . $_{8}$it is chaotic through period-doubling cascade [79]. The logistic map plays a very important role in many fields of science, particularly in economics. It can be used to describe economic variables. In [13] the logistic map emerges as the law of motion of the price of the non-numeraire good in a simple discrete-time model of an exchange economy with two goods under Walrasian tatonnement. Benhabib and Day [17] showed that a logistic map describes optimal consumption in a simple overlapping generations model with a quadratic utility function, and Mitra and Sorger [61] proved that the logistic map can be the optimal policy function of a regular dynamic optimisation problem, if and only if the discount factor does not exceed 1 / 16 . The logistic map A$_{1}$ is the generator of chaos for the global system (4.11) and as we mentioned above, a generator can be not only with continuous dynamics, but also with discrete, and even hybrid, i.e., combining both continuous and discrete. In fact the whole model (4.11) is an example of a hybrid system. System A$_{2}$ describes the aggregate economy of Country 1 . It is a perturbed Kaldor model ((3.6), obtained by setting α = 1 , s = 1 / 8 , δ = 1 / 16 and b = − 5 / 16 . In the absence of the perturbation function ν$_{1}$ ( t, θ $_{)}$, the model possesses an asymptotically stable equilibrium provided that the number a$_{1}$ is sufficiently small. One can verify that the associated linear system admits complex conjugate eigenvalues ( − 1 ± i ) / 8 . The function (4.12) describes a rainfall shock that impacts on the agricultural sector and through it on the total output. The higher value of ν$_{1}$ implies normal rainfall, while the lower value is drought, which leads to lower agricultural production and slower output growth. Using the results of [2, 5, 6], one can state that the chaoticity of the logistic map A$_{1}$ with µ = 3 . 8 makes the function ν$_{1}$ ( t, θ ) behave chaotically, and system A$_{2}$ is chaotic through period-doubling cascade for the same value of the parameter $_{µ}$. That is, it admits infinitely many unstable periodic solutions and exhibits sensitivity. For each natural number p, the system possesses an unstable periodic solution with period 2 p. Next, in its own turn system A$_{2}$ is the generator for the systems A$_{3}$ and A$_{4}$. System A$_{3}$ reflects the dynamics of Country 2 . It is obtained by using the coefficients α = 1 , s = 1 / 6 , δ = 1 / 4 , b = − 1 in the Kaldor model (3.6) and by perturbing it with the solutions of A$_{2}$ as well as with the periodic function (4.13). The associated linear system has the eigenvalues ( − 11 ± √$_{73)}$$_{/}$$_{24}$$_{.}$ In the absence of the perturbation terms 0 . 6 y$_{1}$ ( t ) and ν$_{2}$ ( t, ζ ) and if the number a$_{2}$ is sufficiently small, the 11 4.1 Description of the models A 1 to A 5