Technological Change in Israel: World-System (1960-2100)

 


Israel is a World-System leader in Technological Change. Google AI Notes:


However, the description has been challenged: The Myth of Israel Innovation. Using the IL_L20 Models, the hypothesis of Israel TECH dominance can be tested. The best short-term model, using AIC Statistics to make the selection, was the Business-As-Usual (BAU) Model. The best Attractor Path model was the Regional Input (MEA) model. Neither TECHP (Productivity) nor TECHE (Efficiency) models were strong competitors (see the graphic above).

 This post compares the models:

  • BAU Model In the Business-as-Usual model, technological change is measured by the coefficient on the Growth Component (the Learning by Doing coefficient (F[2,2] = 1.02477066 in the IL_SYS BAU Model). It is the primary driver of instability in the System. The BAU model is also cyclical with Eigenvalues = 1.053345+0.0000000i 0.941244+0.0579742i 0.941244-0.0579742i. To create unlimited, unstable exponential growth for the Middle-East (MEA), the BAU Model would be the best Geopolitical choice.
  • The MEA-Input Model Is stable and cyclical  Eigenvalues = (0.8499202+0.2355428i 0.8499202-0.2355428i 0.7872053+0.0000000i)--see the IL_SYS MEA-Input Model in the Notes below. The Israeli Economy would be an excellent Geopolitical driver of the Middle East (for many reason, this scenario is unlikely to happen).
  • The TECHE and TECHP Models Both technology-driven models (Efficiency and Productivity change) are unstable but do not provide the same level of unstable exponential growth as the BAU Model. The result suggests that Learning by Doing is the primary driver of Technological Change in Israel.
It should also be noted that the two Technology Indexes (TECHP and TECHE, see the Measurement Matrices in the Notes below) are strongly controlled by Environmental Components (Energy and CO2 Emissions, E/N, E/Q and CO2/N, CO2/Q, respectively). As with all the Middle Eastern Countries, Energy and Environmental Limits to Growth will eventually bend the curve of unstable, unending exponential growth.

Notes

Within Systems Theory there are three types of technology: Learning by Doing, Technical Productivity (TECHP) and Technical Efficiency (TECHE). Learning by Doing is measured by the coefficient on the first Growth State variable (usually F[1,1]). TECHP and TECHE are measured by indexes (see below). For more information, see the About page.

IL_TECHP Measurement Model


Technical Productivity (TECHP) in Israel is measured by three indexes that explain over 98% of the variation in the underlying indicators (CO2/N, E/N, GDP/N and L/N). TECHP1 measures overall growth in the indicators and explains over 88% of the variation. TECHP2 is an historical controller (E/N - L/N - Q/L), energy productivity compared to Employment and Labor productivity. TECHNP3 is an historical controller (L/N - Q/N - CO2/N) comparing Employment Productivity compared to GDP Productivity and CO2 productivity.


Over time, TECHP1 reaches a limit after 2000, TECHP2 is relatively constant (except for the period after WWII) and TECHP3 is cyclical.


IL_TECHE Measurement Model

Technical Efficiency is measured by the Intensive Coefficients of the Kaya Identity. In Israel, TECHE1 = (E/Q + Q/L - L/N - CO2/N), an historical Energy-Labor Productivity controller compared to Employment-Emissions that explains over 72% of the variation. TECHE2 = (CO2/E + Q/L - L/N - E/Q) an historical Emission-Employment controller compared to Employment-Energy Efficiency. TECHE3 = (Overall Growth).


Over time, TECHE1 has been decreasing, TECHE2 has been relatively stable and TECHE3 has been mildly cyclical.



IL_TECHP State Space Model


The IL TECHP-Input Model is cyclical and unstable.
 

IL_TECHE State Space Model

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The IL TECHE-Input Model is nonlinear, cyclical and unstable.

IL_SYS BAU Model


The IL Business-as-Usual (BAU) Model is cyclical and unstable. The  Learning by Doing coefficient is F[2,2] = 1.02477066 driving unstable growth.

IL_SYS MEA-Input Model


The IL MEA_Input Model is stable and cyclical. The F[3,3] (IL3) coefficient is close to a Random Walk.

IL_SYS Model AIC Statistics

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The AIC Statistics for the step-ahead models are presented above. There is a lot of overlap in the models.


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