World-System (1950-2100+) What Can India Do About Tariffs?

 


The Trump II Administration has recently imposed 50% Tariffs on Indian imports trying to limit Russian Oil purchases. Whatever the rationale might be for punishing the Indian Economy in this way, the question now is what can India do about it? ChatGPT5 (recently released) reports:

Negotiating with the Trump II Administration seems pointless (although negotiating with other countries might be useful) so in this post I will focus on diversification and domestic adjustment (see the expanded ChatGPT5 output in the Notes below). Diversification, in the framework of my State Space Models (see the Boiler Plate) involves establishing linkages with countries and regions other than the US while domestic adjustment involves technological change.

The graphic at the beginning of this post shows future projects for various Geopolitical Alignments and structuring of the Indian economy from the WL20 IN Model. The graphic displays the dominant growth state variable (principal component) IN1 from the eight input models. On a year-to-year basis, the Random Walk (RW) is the best model. As an attractor path, the World System (W) and the Kaya Technical Efficiency model (TECHE) are good candidates. However, from the graphic display at the beginning of this post, all the models (except the BAU model) are closely lumped together. 

I interpret these results as mildly positive. As a year-to-year policy, the Random Walk (RW) allows India to search for an attractor path other than the US or RU. There are many options. India should be able to find Geopolitical Alignment with other countries and regions in the World-System.

In a future post, I will look more carefully at the BAU, TECHE and World System (W) models. The BAU model would essentially focus India on it's internal market, which is large (at 1.4 Billion+, India recently surpassed China as the largest population in the World-System). The World System model would require a careful selection of state variables to monitor. My best guess is that India will, through a Random Walk process, find elements of all the models presented above that would benefit the country. India already has a strong Technology sector  so expanding on the TECHE model will be compelling. Time will tell which Geopolitical Alignment would dominate.

You can experiment with the INL20 BAU model here. You can also experiment with the INL20W (World System Input) model here. You can run the INL20 RW model with code in each site (run the RW model multiple times to see how history changes).

Notes

Model Summary:
  • BAU (Business as Usual, no inputs) [99.73 < AIC=104.8 < 108.6] unstable, (lambda=1.023)**.
  • TECHE (Kaya Technical Efficiency) [71.63 < AIC=112.8 < 139.4] stable, (lambda=0.85).
  • EAP (East Asia Pacific Region) [73.29 < AIC=106.7 < 125] stable, (lambda=0.88).
  • LAC (Latin America Region) [104.1 < AIC=115.4 < 129.2] unstable, (lambda=1.01).
  • EU (European Union) [76.34 < AIC=112.3 < 133.7] stable, (lambda=0.85).
  • W (World System) [61.24 < AIC=95.86 < 118.4] stable, (lambda=0.88).
  • US (United States) [77.5 < AIC=99.11 < 114.4] stable, (lambda=0.88).
  • RW (Random Walk, no input) [31.92 < AIC=39.58 < 48.03] unstable.
  • RU (Russia) [88.14 < AIC=110.6 < 124.8] stable, (lambda=0.99). (not displayed above but covered in an earlier post here).
** AIC=Akaike Information Criterion, smaller is better. Lambda is the largest characteristic root of the Systems Matrix (see the Boiler Plate).


More detailed output from ChatGPT5:





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