The United States recently imposed punishing tariffs on Switzerland. To understand how a trade war might affect the Economy of Switzerland we need to understand how the economy works. Socio-technical systems are complex systems that, in spite of claims to the contrary, no one can understand fully. What we can understand are mathematical models and I have one (a state space statistical model), the CH_LM model (see the Boiler Plate for a more detailed description of the models).
Not surprisingly, the bottom line is that the Swiss economy is an Export Controlled economy. Tariffs will trigger long-term adjustments to economic growth. What follows is a detailed explanation.
The five indicators variables are Q (Aggregate Production), N (Population), U (Urbanization), XREAL (Real Exports), X (Nominal Exports) and L (Labor). The first component, CH1, is overall growth (the variables are all similarly weighted). The second component, (CH2), is a historical feedback controller for (X-HOURS)--exports and employment have to stay in balance. Finally, the third component, (CH3), monitors the relationship between Urbanization and Export Employment. Together they explain approximately 100% of the variation in the indicators!
There are two important components to a Dynamic State Space Model: the Measurement Matrix and the Systems matrix. The Measurement Matrix (below) shows how the indicator variables are weighted in the state space, that is, how the state space is defined.
The five indicators variables are Q (Aggregate Production), N (Population), U (Urbanization), XREAL (Real Exports), X (Nominal Exports) and L (Labor). The first component, CH1, is overall growth (the variables are all similarly weighted). The second component, (CH2), is a historical feedback controller for (X-HOURS)--exports and employment have to stay in balance. Finally, the third component, (CH3), monitors the relationship between Urbanization and Export Employment. Together they explain approximately 100% of the variation in the indicators!
The time path of the three state variables is presented above. CH1 seem to be reaching a steady state after 2000. CH2 = (X-HOURS) reaches a low point (X < HOURS) around 1975. And, CH3 = (U-HOURS-X) reaches a low point (high Urban Export Employment) around 1995.
The important point to understand about the historical controllers (CH2 and CH3) is that they control the economy over decades, not from year to year, as in conventional economic models where price changes have relatively immediate effects.
The interaction between growth and the historical controllers is determined by the System Matrix, below.
Notice that one of the diagonal coefficients of F is greater than 1.0, meaning that CH2 = (X-HOURS) makes the system unstable. To understand the dynamics the model, we can look at a shock decomposition of the Systems matrix, below:
A shock to economic growth takes about 4 years to work it's way out of the system with the full shock not being felt by either CH2 or CH3 (CH3 peaks quickly and returns to equilibrium). A shock to the Export-Employment controller (second row) takes about 4 years to be corrected (middle graphic) and has a negative effect on CH1 and a negative effect on CH3 (which is over-corrected after about 7 years).
In other words, shocks such as the imposition of US Tariffs will have a multi-year effect on economic growth but will be met by historical feedback responses from the Export-employment controller and the Urban-Export-Employment controller.
If you would like to experiment with the CH_LM model, you can run the BAU code here. You can experiment by stabilizing CH2 = (X-HOURS) to see what effect stability will have on the Shock Decomposition. You can also look at the effect of going on a Random Walk (RW) for new trading relationships. The problem with the Random Walk (RW) is that it might product a period of declining economic growth while new trading partners are found; a new attractor path must eventually be found in a matter of years.
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