LateModernPeriod1950-2000+

  In prior blog postings, I have usually displayed only the first three state variables of a DCM ( Dynamic Components Model ).   There are three reasons: (1) Typically, the first three state variables explain at least 90% of the variation in the underlying indicators. For example, in Iran (see the Measurement Matrix below in the Notes) the first three components ( IR1 , IR2 , IR2 ) explain 98% of the variation in the underlying indicators. (2) Also, typically, the first state variable describes overall growth in the system and the next two state variables describe historical cycles and feedback controllers ( here and here ). And, (3) it is difficult to explain the dynamic path of state variables in more than three dimensions. However, interesting dynamics are observed in the lower-order state variables. In the graphic above, the state space IR4 , IR5 and IR6 is displayed. The graphic above shows the unstable, cyclical dynamic state-space interaction between IR4 =( a Popula...

  According to Google AI, the Economy of Iran is facing "significant challenges"   to include international sanctions, inflation, currency devaluation, economic stagnation, corruption/mismanagement, dependence on oil, and brain drain. My forecasts for the  Economy of Iran  are equally pessimistic ( here ). On the other hand, if the  Economy of Iran   were entirely cut out of the World-System (say for twenty years), the World-System would take a big hit ( here ). Before we make any conclusions about either qualitative or quantitative forecasts, it would be useful to understand how the  Economy of Iran   works ( HINT : It's an historically driven economy not a Neoclassical Economy ). From the perspective of   Systems Theory,  the first step is to estimate the state variables (the measurement matrix for the Dynamic Components  state space model is presented in the Notes below). There are three state variables (estimated by Pr...