LateModernPeriod1950-2000+

  Eastern Europe is a Export-Dominated region with an unstable cyclical historical pattern of development destabilized in the short-run by Russian historical events (the fall of the Soviet Union) and stabilized in the long-run by the World System attractor path. Notes The EE_LM model has three state variables explaining most of the variation in the indicators: EE1 = (Growth) , Export-Employment Controller EE2 = (L-X) and Export Price Controller EE3 = (X-XREAL) . From Google AI: Eastern European economies are experiencing a period of robust growth, particularly among EU member states, often outpacing the Eurozone .  This growth is fueled by factors like strong private consumption, rising real wages, and increased foreign direct investment.  However, they also face challenges like geopolitical risks, potential impacts from global trade tensions, and the need to effectively absorb EU funds.   Key Trends and Factors: Economic Growth: . Opens in new tab Many Eastern Euro...

It might seem paradoxical or even foolish to apply a Neoclassical Economic Model to Iran: Free markets for Products, Capital and Labor?  Exogenous Total Factor Productivity Growth (Technology)? Iran is generally considered  a  mixed ,  centrally planned economy  with a large  public sector  ( here ). But what is easy to forget is the long period of attempted US domination prior to the Iranian Revolution in 1978-1979 . The US, especially in the Kennedy administration , was trying to Modernize Iran and transform it into a model Capitalist System . They failed and brought on the  Iranian Revolution   and the current Anti-Modern Theocracy . In any event, I always test a  Neoclassical Economic Model   as one of the competitor models when I estimate the best State Space model for a particular country. The causal model is presented above as a directed graph  (see the Symbols defined in Notes below). The graphic is b...

  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...